blob_id stringlengths 40 40 | bodies listlengths 2 6 | bodies_text stringlengths 196 7.73k | class_docstring stringlengths 0 700 | class_name stringlengths 1 86 | detected_licenses listlengths 0 45 | format_version stringclasses 1
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value | snapshot_source_dir stringclasses 1
value | snapshot_total_rows int64 75.8k 75.8k | solution stringlengths 242 8.3k | source stringclasses 1
value | source_path stringlengths 4 177 | source_repo stringlengths 6 110 | split stringclasses 1
value | star_events_count int64 0 209k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
662423ab416d826e04f11ca0e33e718f6e0c9e1a | [
"self.sum = w[0:]\nif len(w) <= 0:\n return\nfor i in range(1, len(w)):\n self.sum[i] = self.sum[i - 1] + w[i]\nprint(self.sum)",
"import numpy as np\nrnd = np.random.randint(0, self.sum[-1])\nlow = 0\nhigh = len(self.sum) - 1\nwhile low < high:\n mid = low + (high - low) / 2\n if self.sum[mid] <= rnd... | <|body_start_0|>
self.sum = w[0:]
if len(w) <= 0:
return
for i in range(1, len(w)):
self.sum[i] = self.sum[i - 1] + w[i]
print(self.sum)
<|end_body_0|>
<|body_start_1|>
import numpy as np
rnd = np.random.randint(0, self.sum[-1])
low = 0
... | Solution1 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution1:
def __init__(self, w):
""":type w: List[int]"""
<|body_0|>
def pickIndex(self):
""":rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.sum = w[0:]
if len(w) <= 0:
return
for i in range(1, len(w)):
... | stack_v2_sparse_classes_75kplus_train_066900 | 1,927 | no_license | [
{
"docstring": ":type w: List[int]",
"name": "__init__",
"signature": "def __init__(self, w)"
},
{
"docstring": ":rtype: int",
"name": "pickIndex",
"signature": "def pickIndex(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_015571 | Implement the Python class `Solution1` described below.
Class description:
Implement the Solution1 class.
Method signatures and docstrings:
- def __init__(self, w): :type w: List[int]
- def pickIndex(self): :rtype: int | Implement the Python class `Solution1` described below.
Class description:
Implement the Solution1 class.
Method signatures and docstrings:
- def __init__(self, w): :type w: List[int]
- def pickIndex(self): :rtype: int
<|skeleton|>
class Solution1:
def __init__(self, w):
""":type w: List[int]"""
... | 176cc1db3291843fb068f06d0180766dd8c3122c | <|skeleton|>
class Solution1:
def __init__(self, w):
""":type w: List[int]"""
<|body_0|>
def pickIndex(self):
""":rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution1:
def __init__(self, w):
""":type w: List[int]"""
self.sum = w[0:]
if len(w) <= 0:
return
for i in range(1, len(w)):
self.sum[i] = self.sum[i - 1] + w[i]
print(self.sum)
def pickIndex(self):
""":rtype: int"""
import ... | the_stack_v2_python_sparse | 2019/sampling/random_pick_with_weight_528.py | yehongyu/acode | train | 0 | |
0bb290f4b07d6ed5a00eabd0551cc0df5ca722cd | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn WorkbookTableColumn()",
"from .entity import Entity\nfrom .json import Json\nfrom .workbook_filter import WorkbookFilter\nfrom .entity import Entity\nfrom .json import Json\nfrom .workbook_filter import WorkbookFilter\nfields: Dict[str... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return WorkbookTableColumn()
<|end_body_0|>
<|body_start_1|>
from .entity import Entity
from .json import Json
from .workbook_filter import WorkbookFilter
from .entity import En... | WorkbookTableColumn | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WorkbookTableColumn:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> WorkbookTableColumn:
"""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 ob... | stack_v2_sparse_classes_75kplus_train_066901 | 3,081 | 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: WorkbookTableColumn",
"name": "create_from_discriminator_value",
"signature": "def create_from_discriminator... | 3 | stack_v2_sparse_classes_30k_train_004455 | Implement the Python class `WorkbookTableColumn` described below.
Class description:
Implement the WorkbookTableColumn class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> WorkbookTableColumn: Creates a new instance of the appropriate class based on d... | Implement the Python class `WorkbookTableColumn` described below.
Class description:
Implement the WorkbookTableColumn class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> WorkbookTableColumn: Creates a new instance of the appropriate class based on d... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class WorkbookTableColumn:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> WorkbookTableColumn:
"""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 ob... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class WorkbookTableColumn:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> WorkbookTableColumn:
"""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: ... | the_stack_v2_python_sparse | msgraph/generated/models/workbook_table_column.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
e9433dda7638aade544bd5e12915d806c35cff27 | [
"error_messages = {'incomplete': _('Must fill all coordinates')}\ndimensions = kwargs.get('dimensions', self.DIMENSIONS)\nfields = [forms.FloatField() for i in range(dimensions)]\nfor field in fields:\n field.error_messages = {}\nkwargs['widget'] = VectorWidget(attrs={'dimensions': dimensions})\nif 'max_length' ... | <|body_start_0|>
error_messages = {'incomplete': _('Must fill all coordinates')}
dimensions = kwargs.get('dimensions', self.DIMENSIONS)
fields = [forms.FloatField() for i in range(dimensions)]
for field in fields:
field.error_messages = {}
kwargs['widget'] = VectorWid... | N dimensional vector field | VectorFormField | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VectorFormField:
"""N dimensional vector field"""
def __init__(self, *args, **kwargs):
"""Class initialization method"""
<|body_0|>
def compress(self, data_list):
"""Data compression method"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
error_m... | stack_v2_sparse_classes_75kplus_train_066902 | 6,288 | permissive | [
{
"docstring": "Class initialization method",
"name": "__init__",
"signature": "def __init__(self, *args, **kwargs)"
},
{
"docstring": "Data compression method",
"name": "compress",
"signature": "def compress(self, data_list)"
}
] | 2 | stack_v2_sparse_classes_30k_train_032112 | Implement the Python class `VectorFormField` described below.
Class description:
N dimensional vector field
Method signatures and docstrings:
- def __init__(self, *args, **kwargs): Class initialization method
- def compress(self, data_list): Data compression method | Implement the Python class `VectorFormField` described below.
Class description:
N dimensional vector field
Method signatures and docstrings:
- def __init__(self, *args, **kwargs): Class initialization method
- def compress(self, data_list): Data compression method
<|skeleton|>
class VectorFormField:
"""N dimens... | be9d747b8ca4c5d18f9725b2dad08dba6119d810 | <|skeleton|>
class VectorFormField:
"""N dimensional vector field"""
def __init__(self, *args, **kwargs):
"""Class initialization method"""
<|body_0|>
def compress(self, data_list):
"""Data compression method"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class VectorFormField:
"""N dimensional vector field"""
def __init__(self, *args, **kwargs):
"""Class initialization method"""
error_messages = {'incomplete': _('Must fill all coordinates')}
dimensions = kwargs.get('dimensions', self.DIMENSIONS)
fields = [forms.FloatField() for ... | the_stack_v2_python_sparse | sitetools/forms/fields.py | olivergs/django-sitetools | train | 0 |
d69c48471a57ac1f5cb05db09889aecda6a5ff9b | [
"self.input = fileInput\nself.output = fileOutput\nself.language = language\nself.minSilenceLen = 500\nself.silenceThresh = 14\nself.keepSilence = 500\nself.__check_files_valid()\nself.rec = sr.Recognizer()",
"self.__check_files_valid()\nsound = AudioSegment.from_file(self.input, format=pathlib.Path(self.input).s... | <|body_start_0|>
self.input = fileInput
self.output = fileOutput
self.language = language
self.minSilenceLen = 500
self.silenceThresh = 14
self.keepSilence = 500
self.__check_files_valid()
self.rec = sr.Recognizer()
<|end_body_0|>
<|body_start_1|>
... | Converts an audio file to text. | AudioToText | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AudioToText:
"""Converts an audio file to text."""
def __init__(self, fileInput, fileOutput, language):
"""Initialize."""
<|body_0|>
def get_text(self):
"""Returns the text recognized from the input file."""
<|body_1|>
def write_to_text_file(self, te... | stack_v2_sparse_classes_75kplus_train_066903 | 4,397 | permissive | [
{
"docstring": "Initialize.",
"name": "__init__",
"signature": "def __init__(self, fileInput, fileOutput, language)"
},
{
"docstring": "Returns the text recognized from the input file.",
"name": "get_text",
"signature": "def get_text(self)"
},
{
"docstring": "Write a text to a fi... | 4 | stack_v2_sparse_classes_30k_train_052952 | Implement the Python class `AudioToText` described below.
Class description:
Converts an audio file to text.
Method signatures and docstrings:
- def __init__(self, fileInput, fileOutput, language): Initialize.
- def get_text(self): Returns the text recognized from the input file.
- def write_to_text_file(self, text):... | Implement the Python class `AudioToText` described below.
Class description:
Converts an audio file to text.
Method signatures and docstrings:
- def __init__(self, fileInput, fileOutput, language): Initialize.
- def get_text(self): Returns the text recognized from the input file.
- def write_to_text_file(self, text):... | 2cb4b45dd14a230aa0e800042e893f8dfb23beda | <|skeleton|>
class AudioToText:
"""Converts an audio file to text."""
def __init__(self, fileInput, fileOutput, language):
"""Initialize."""
<|body_0|>
def get_text(self):
"""Returns the text recognized from the input file."""
<|body_1|>
def write_to_text_file(self, te... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AudioToText:
"""Converts an audio file to text."""
def __init__(self, fileInput, fileOutput, language):
"""Initialize."""
self.input = fileInput
self.output = fileOutput
self.language = language
self.minSilenceLen = 500
self.silenceThresh = 14
self.... | the_stack_v2_python_sparse | _RESOURCES/my-gists/__CONTAINER/825aa98d8f/825aa98d8fddbff215dadd41125cc487f503d563f1179583c1502bfebdb87cf8/audio-2-text.py | bgoonz/UsefulResourceRepo2.0 | train | 10 |
8ca51a317e94f584c2e4d2816f032db93a3332ba | [
"self.last_data_time: Optional[int] = None\nself.last_data_used_time_list: list = list()\nself.last_data_used_time_size = last_data_used_time_size",
"data_progress_display_str = self.draw_data_progress(current_value, total_value, data_progress_display_len)\ntime_progress_display_str = self.draw_time_progress(curr... | <|body_start_0|>
self.last_data_time: Optional[int] = None
self.last_data_used_time_list: list = list()
self.last_data_used_time_size = last_data_used_time_size
<|end_body_0|>
<|body_start_1|>
data_progress_display_str = self.draw_data_progress(current_value, total_value, data_progress_... | 数据进度 | DataProgress | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DataProgress:
"""数据进度"""
def __init__(self, last_data_used_time_size=50):
"""初始化"""
<|body_0|>
def print_data_progress(self, current_value: int, total_value: int, data_progress_display_len=50):
"""打印进度条 :param current_value: :param total_value: :param data_progre... | stack_v2_sparse_classes_75kplus_train_066904 | 6,281 | no_license | [
{
"docstring": "初始化",
"name": "__init__",
"signature": "def __init__(self, last_data_used_time_size=50)"
},
{
"docstring": "打印进度条 :param current_value: :param total_value: :param data_progress_display_len: :return:",
"name": "print_data_progress",
"signature": "def print_data_progress(se... | 4 | stack_v2_sparse_classes_30k_train_019473 | Implement the Python class `DataProgress` described below.
Class description:
数据进度
Method signatures and docstrings:
- def __init__(self, last_data_used_time_size=50): 初始化
- def print_data_progress(self, current_value: int, total_value: int, data_progress_display_len=50): 打印进度条 :param current_value: :param total_valu... | Implement the Python class `DataProgress` described below.
Class description:
数据进度
Method signatures and docstrings:
- def __init__(self, last_data_used_time_size=50): 初始化
- def print_data_progress(self, current_value: int, total_value: int, data_progress_display_len=50): 打印进度条 :param current_value: :param total_valu... | c447c94c367c029fc13af458c668eb1f87a7b67c | <|skeleton|>
class DataProgress:
"""数据进度"""
def __init__(self, last_data_used_time_size=50):
"""初始化"""
<|body_0|>
def print_data_progress(self, current_value: int, total_value: int, data_progress_display_len=50):
"""打印进度条 :param current_value: :param total_value: :param data_progre... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DataProgress:
"""数据进度"""
def __init__(self, last_data_used_time_size=50):
"""初始化"""
self.last_data_time: Optional[int] = None
self.last_data_used_time_list: list = list()
self.last_data_used_time_size = last_data_used_time_size
def print_data_progress(self, current_va... | the_stack_v2_python_sparse | base_spider.py | xiphodon/spider_hs_code | train | 4 |
2e1ca49fb763d986e1920e6b7dbce5a606c8bf1d | [
"contacts = CompanyContact.get_contacts(gets_email=True)\nemail_tuple = (self.email_contact(contact) for contact in contacts)\nsend_mass_mail(email_tuple)",
"if mig_alum:\n replace_text = self.mig_alum_text\nelif other_alum:\n replace_text = self.other_tbp_alum_text\nelif previous_contact:\n replace_text... | <|body_start_0|>
contacts = CompanyContact.get_contacts(gets_email=True)
email_tuple = (self.email_contact(contact) for contact in contacts)
send_mass_mail(email_tuple)
<|end_body_0|>
<|body_start_1|>
if mig_alum:
replace_text = self.mig_alum_text
elif other_alum:
... | Represents an email to be sent to the corporate contacts list. Provides an interface for creating and sending such emails. | CorporateEmail | [
"Apache-2.0",
"LicenseRef-scancode-warranty-disclaimer"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CorporateEmail:
"""Represents an email to be sent to the corporate contacts list. Provides an interface for creating and sending such emails."""
def send_corporate_email(self):
"""Sends the email to all company contacts who should receive it."""
<|body_0|>
def preview_em... | stack_v2_sparse_classes_75kplus_train_066905 | 18,793 | permissive | [
{
"docstring": "Sends the email to all company contacts who should receive it.",
"name": "send_corporate_email",
"signature": "def send_corporate_email(self)"
},
{
"docstring": "Returns an example email based on the flags provided. Used to spot check emails before sending.",
"name": "preview... | 3 | stack_v2_sparse_classes_30k_val_002097 | Implement the Python class `CorporateEmail` described below.
Class description:
Represents an email to be sent to the corporate contacts list. Provides an interface for creating and sending such emails.
Method signatures and docstrings:
- def send_corporate_email(self): Sends the email to all company contacts who sho... | Implement the Python class `CorporateEmail` described below.
Class description:
Represents an email to be sent to the corporate contacts list. Provides an interface for creating and sending such emails.
Method signatures and docstrings:
- def send_corporate_email(self): Sends the email to all company contacts who sho... | 527f9dd39a6b50caa24ea5d0d97b19a0c9b675d1 | <|skeleton|>
class CorporateEmail:
"""Represents an email to be sent to the corporate contacts list. Provides an interface for creating and sending such emails."""
def send_corporate_email(self):
"""Sends the email to all company contacts who should receive it."""
<|body_0|>
def preview_em... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CorporateEmail:
"""Represents an email to be sent to the corporate contacts list. Provides an interface for creating and sending such emails."""
def send_corporate_email(self):
"""Sends the email to all company contacts who should receive it."""
contacts = CompanyContact.get_contacts(gets... | the_stack_v2_python_sparse | corporate/models.py | tbpmig/mig-website | train | 7 |
b73f67c30a8632085dba56aff0e0ada7b3ee1a40 | [
"super(PromoTextRemover, self).__init__()\nself._language = language\nif flask.current_app:\n self._config = config_parser.get_config_contents(_PROMO_TEXT_REMOVAL_OPTIMIZER_CONFIG_OVERRIDE_KEY, _PROMO_TEXT_REMOVAL_OPTIMIZER_CONFIG_FILE_NAME.format(language))\nelse:\n self._config = PROMO_TEXT_REMOVER_CONFIG\n... | <|body_start_0|>
super(PromoTextRemover, self).__init__()
self._language = language
if flask.current_app:
self._config = config_parser.get_config_contents(_PROMO_TEXT_REMOVAL_OPTIMIZER_CONFIG_OVERRIDE_KEY, _PROMO_TEXT_REMOVAL_OPTIMIZER_CONFIG_FILE_NAME.format(language))
else:... | A class that removes text from a field of a product. | PromoTextRemover | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PromoTextRemover:
"""A class that removes text from a field of a product."""
def __init__(self, language: str) -> None:
"""Initializes PromoTextRemover. Args: language: The configured language code."""
<|body_0|>
def remove_text_from_field(self, product: Dict[str, Any], ... | stack_v2_sparse_classes_75kplus_train_066906 | 5,102 | permissive | [
{
"docstring": "Initializes PromoTextRemover. Args: language: The configured language code.",
"name": "__init__",
"signature": "def __init__(self, language: str) -> None"
},
{
"docstring": "Removes text and regex patterns in the config file from a product field. Args: product: A product data. fi... | 5 | stack_v2_sparse_classes_30k_train_044366 | Implement the Python class `PromoTextRemover` described below.
Class description:
A class that removes text from a field of a product.
Method signatures and docstrings:
- def __init__(self, language: str) -> None: Initializes PromoTextRemover. Args: language: The configured language code.
- def remove_text_from_field... | Implement the Python class `PromoTextRemover` described below.
Class description:
A class that removes text from a field of a product.
Method signatures and docstrings:
- def __init__(self, language: str) -> None: Initializes PromoTextRemover. Args: language: The configured language code.
- def remove_text_from_field... | 58588ce54f8ea065fdc7501398b1b2e10f8adc41 | <|skeleton|>
class PromoTextRemover:
"""A class that removes text from a field of a product."""
def __init__(self, language: str) -> None:
"""Initializes PromoTextRemover. Args: language: The configured language code."""
<|body_0|>
def remove_text_from_field(self, product: Dict[str, Any], ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PromoTextRemover:
"""A class that removes text from a field of a product."""
def __init__(self, language: str) -> None:
"""Initializes PromoTextRemover. Args: language: The configured language code."""
super(PromoTextRemover, self).__init__()
self._language = language
if f... | the_stack_v2_python_sparse | shoptimizer_api/util/promo_text_remover.py | google/shoptimizer | train | 43 |
022fb2f9a7f0f5aa9375428969e7cfdd0f387277 | [
"node = head\nwhile n and node:\n node = node.next\n n -= 1\nif n:\n return head\npp = None\np = head\nwhile node:\n node = node.next\n pp = p\n p = p.next\nif not pp:\n return p.next\npp.next = p.next\nreturn head",
"def length(node: ListNode):\n l = 0\n while node:\n l += 1\n ... | <|body_start_0|>
node = head
while n and node:
node = node.next
n -= 1
if n:
return head
pp = None
p = head
while node:
node = node.next
pp = p
p = p.next
if not pp:
return p.next
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def removeNthFromEnd(self, head: ListNode, n: int) -> ListNode:
"""One pass using two pointers Time complexity: O(n) Space complexity: O(1)"""
<|body_0|>
def removeNthFromEnd(self, head: Optional[ListNode], n: int) -> Optional[ListNode]:
"""10/16/2022 16:33... | stack_v2_sparse_classes_75kplus_train_066907 | 2,249 | no_license | [
{
"docstring": "One pass using two pointers Time complexity: O(n) Space complexity: O(1)",
"name": "removeNthFromEnd",
"signature": "def removeNthFromEnd(self, head: ListNode, n: int) -> ListNode"
},
{
"docstring": "10/16/2022 16:33",
"name": "removeNthFromEnd",
"signature": "def removeN... | 2 | stack_v2_sparse_classes_30k_train_015380 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def removeNthFromEnd(self, head: ListNode, n: int) -> ListNode: One pass using two pointers Time complexity: O(n) Space complexity: O(1)
- def removeNthFromEnd(self, head: Option... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def removeNthFromEnd(self, head: ListNode, n: int) -> ListNode: One pass using two pointers Time complexity: O(n) Space complexity: O(1)
- def removeNthFromEnd(self, head: Option... | 1389a009a02e90e8700a7a00e0b7f797c129cdf4 | <|skeleton|>
class Solution:
def removeNthFromEnd(self, head: ListNode, n: int) -> ListNode:
"""One pass using two pointers Time complexity: O(n) Space complexity: O(1)"""
<|body_0|>
def removeNthFromEnd(self, head: Optional[ListNode], n: int) -> Optional[ListNode]:
"""10/16/2022 16:33... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def removeNthFromEnd(self, head: ListNode, n: int) -> ListNode:
"""One pass using two pointers Time complexity: O(n) Space complexity: O(1)"""
node = head
while n and node:
node = node.next
n -= 1
if n:
return head
pp = None... | the_stack_v2_python_sparse | leetcode/solved/19_Remove_nth_Node_From_End_of_List/solution.py | sungminoh/algorithms | train | 0 | |
ffc0db7ee5b498a806685836c5fc25c4ab534c6d | [
"host = aggregate.hosts[0]\nnuma_count = 2\ncpus = get_cpu_distribition_per_numa_node(env)\nflavors[0].set_keys({'hw:numa_nodes': numa_count, 'hw:numa_cpus.0': self.cpu_numa0, 'hw:numa_cpus.1': self.cpu_numa1, 'hw:numa_mem.0': self.mem_numa0, 'hw:numa_mem.1': self.mem_numa1})\nexp_mem = {'0': self.mem_numa0, '1': s... | <|body_start_0|>
host = aggregate.hosts[0]
numa_count = 2
cpus = get_cpu_distribition_per_numa_node(env)
flavors[0].set_keys({'hw:numa_nodes': numa_count, 'hw:numa_cpus.0': self.cpu_numa0, 'hw:numa_cpus.1': self.cpu_numa1, 'hw:numa_mem.0': self.mem_numa0, 'hw:numa_mem.1': self.mem_numa1}... | TestResourceDistribution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestResourceDistribution:
def test_cpu_and_memory_distribution(self, env, os_conn, networks, flavors, security_group, aggregate, keypair):
"""This test checks distribution of cpu for vm with cpu pinning Steps: 1. Create flavor with custom numa_cpu and numa_mem distribution 2. Create net1... | stack_v2_sparse_classes_75kplus_train_066908 | 38,361 | no_license | [
{
"docstring": "This test checks distribution of cpu for vm with cpu pinning Steps: 1. Create flavor with custom numa_cpu and numa_mem distribution 2. Create net1 with subnet, net2 with subnet and router1 with interfaces to both nets 3. Launch vm using created flavor 4. Check memory allocation per numa node 5. ... | 2 | stack_v2_sparse_classes_30k_train_006877 | Implement the Python class `TestResourceDistribution` described below.
Class description:
Implement the TestResourceDistribution class.
Method signatures and docstrings:
- def test_cpu_and_memory_distribution(self, env, os_conn, networks, flavors, security_group, aggregate, keypair): This test checks distribution of ... | Implement the Python class `TestResourceDistribution` described below.
Class description:
Implement the TestResourceDistribution class.
Method signatures and docstrings:
- def test_cpu_and_memory_distribution(self, env, os_conn, networks, flavors, security_group, aggregate, keypair): This test checks distribution of ... | 8aced2855b78b5f123195d188c80e27b43888a2e | <|skeleton|>
class TestResourceDistribution:
def test_cpu_and_memory_distribution(self, env, os_conn, networks, flavors, security_group, aggregate, keypair):
"""This test checks distribution of cpu for vm with cpu pinning Steps: 1. Create flavor with custom numa_cpu and numa_mem distribution 2. Create net1... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TestResourceDistribution:
def test_cpu_and_memory_distribution(self, env, os_conn, networks, flavors, security_group, aggregate, keypair):
"""This test checks distribution of cpu for vm with cpu pinning Steps: 1. Create flavor with custom numa_cpu and numa_mem distribution 2. Create net1 with subnet, ... | the_stack_v2_python_sparse | mos_tests/nfv/test_cpu_pinning.py | Mirantis/mos-integration-tests | train | 16 | |
e3d85df34b0a5fedd9f2565fd3055c3174b890d0 | [
"try:\n self.sqlhandler = None\n if self.getTeaList():\n self.write(self.teaList)\n self.finish()\n else:\n raise RuntimeError\nexcept Exception:\n self.write('error')\n self.finish()\nfinally:\n if self.sqlhandler is not None:\n self.sqlhandler.closeMySql()\n tornad... | <|body_start_0|>
try:
self.sqlhandler = None
if self.getTeaList():
self.write(self.teaList)
self.finish()
else:
raise RuntimeError
except Exception:
self.write('error')
self.finish()
final... | AdmGetTeaListRequestHandler | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AdmGetTeaListRequestHandler:
def get(self):
"""从数据库获取老师列表返回给管理员"""
<|body_0|>
def getTeaList(self):
"""从数据库读取老师列表"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
try:
self.sqlhandler = None
if self.getTeaList():
... | stack_v2_sparse_classes_75kplus_train_066909 | 1,561 | no_license | [
{
"docstring": "从数据库获取老师列表返回给管理员",
"name": "get",
"signature": "def get(self)"
},
{
"docstring": "从数据库读取老师列表",
"name": "getTeaList",
"signature": "def getTeaList(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_023544 | Implement the Python class `AdmGetTeaListRequestHandler` described below.
Class description:
Implement the AdmGetTeaListRequestHandler class.
Method signatures and docstrings:
- def get(self): 从数据库获取老师列表返回给管理员
- def getTeaList(self): 从数据库读取老师列表 | Implement the Python class `AdmGetTeaListRequestHandler` described below.
Class description:
Implement the AdmGetTeaListRequestHandler class.
Method signatures and docstrings:
- def get(self): 从数据库获取老师列表返回给管理员
- def getTeaList(self): 从数据库读取老师列表
<|skeleton|>
class AdmGetTeaListRequestHandler:
def get(self):
... | b28eb4163b02bd0a931653b94851592f2654b199 | <|skeleton|>
class AdmGetTeaListRequestHandler:
def get(self):
"""从数据库获取老师列表返回给管理员"""
<|body_0|>
def getTeaList(self):
"""从数据库读取老师列表"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AdmGetTeaListRequestHandler:
def get(self):
"""从数据库获取老师列表返回给管理员"""
try:
self.sqlhandler = None
if self.getTeaList():
self.write(self.teaList)
self.finish()
else:
raise RuntimeError
except Exception:
... | the_stack_v2_python_sparse | app/src/main/pythonWork/AdmGetTeaListRequestHandler.py | lyh-ADT/edu-app | train | 1 | |
0eb46111eb08edbfa80309766168c1a44dc046b7 | [
"n = len(nums)\noutput = []\nfor i in range(2 ** n):\n bitmask = bin(i | 1 << n)[3:]\n output.append([nums[j] for j in range(n) if bitmask[j] == '1'])\nreturn output",
"n = len(nums)\noutput = []\nfor i in range(2 ** n, 2 ** (n + 1)):\n bitmask = bin(i)[3:]\n output.append([nums[j] for j in range(n) i... | <|body_start_0|>
n = len(nums)
output = []
for i in range(2 ** n):
bitmask = bin(i | 1 << n)[3:]
output.append([nums[j] for j in range(n) if bitmask[j] == '1'])
return output
<|end_body_0|>
<|body_start_1|>
n = len(nums)
output = []
for i ... | Subsets | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Subsets:
def generated(self, nums: List[int]) -> List[List[int]]:
"""Approach: Lexographic Binary Sorted Time Complexity: O(N * 2^N) Space Complexity: O(N * 2^N) :param nums: :return:"""
<|body_0|>
def generate(self, nums: List[int]) -> List[List[int]]:
"""Approach: ... | stack_v2_sparse_classes_75kplus_train_066910 | 2,118 | no_license | [
{
"docstring": "Approach: Lexographic Binary Sorted Time Complexity: O(N * 2^N) Space Complexity: O(N * 2^N) :param nums: :return:",
"name": "generated",
"signature": "def generated(self, nums: List[int]) -> List[List[int]]"
},
{
"docstring": "Approach: Lexographic Binary Sorted Time Complexity:... | 4 | null | Implement the Python class `Subsets` described below.
Class description:
Implement the Subsets class.
Method signatures and docstrings:
- def generated(self, nums: List[int]) -> List[List[int]]: Approach: Lexographic Binary Sorted Time Complexity: O(N * 2^N) Space Complexity: O(N * 2^N) :param nums: :return:
- def ge... | Implement the Python class `Subsets` described below.
Class description:
Implement the Subsets class.
Method signatures and docstrings:
- def generated(self, nums: List[int]) -> List[List[int]]: Approach: Lexographic Binary Sorted Time Complexity: O(N * 2^N) Space Complexity: O(N * 2^N) :param nums: :return:
- def ge... | 65cc78b5afa0db064f9fe8f06597e3e120f7363d | <|skeleton|>
class Subsets:
def generated(self, nums: List[int]) -> List[List[int]]:
"""Approach: Lexographic Binary Sorted Time Complexity: O(N * 2^N) Space Complexity: O(N * 2^N) :param nums: :return:"""
<|body_0|>
def generate(self, nums: List[int]) -> List[List[int]]:
"""Approach: ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Subsets:
def generated(self, nums: List[int]) -> List[List[int]]:
"""Approach: Lexographic Binary Sorted Time Complexity: O(N * 2^N) Space Complexity: O(N * 2^N) :param nums: :return:"""
n = len(nums)
output = []
for i in range(2 ** n):
bitmask = bin(i | 1 << n)[3:]... | the_stack_v2_python_sparse | revisited/permutations_combinations_subsets/subsets.py | Shiv2157k/leet_code | train | 1 | |
023776c9402f0f5915c2378c604e27879993da21 | [
"self.description = description\nself.domain = domain\nself.name = name\nself.nfs_access = nfs_access\nself.nfs_squash = nfs_squash",
"if dictionary is None:\n return None\ndescription = dictionary.get('description')\ndomain = dictionary.get('domain')\nname = dictionary.get('name')\nnfs_access = dictionary.get... | <|body_start_0|>
self.description = description
self.domain = domain
self.name = name
self.nfs_access = nfs_access
self.nfs_squash = nfs_squash
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
description = dictionary.get('descriptio... | Implementation of the 'NisNetgroup' model. Defines an NIS Netgroup. Attributes: description (string): Description of the netgroup. domain (string): Specifies the domain of the netgroup. name (string): Specifies the name of the netgroup. nfs_access (NfsAccessEnum): Specifies whether clients from this netgroup can mount ... | NisNetgroup | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NisNetgroup:
"""Implementation of the 'NisNetgroup' model. Defines an NIS Netgroup. Attributes: description (string): Description of the netgroup. domain (string): Specifies the domain of the netgroup. name (string): Specifies the name of the netgroup. nfs_access (NfsAccessEnum): Specifies whethe... | stack_v2_sparse_classes_75kplus_train_066911 | 2,471 | permissive | [
{
"docstring": "Constructor for the NisNetgroup class",
"name": "__init__",
"signature": "def __init__(self, description=None, domain=None, name=None, nfs_access=None, nfs_squash=None)"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: dictionary (dictionary): A dictio... | 2 | stack_v2_sparse_classes_30k_train_046607 | Implement the Python class `NisNetgroup` described below.
Class description:
Implementation of the 'NisNetgroup' model. Defines an NIS Netgroup. Attributes: description (string): Description of the netgroup. domain (string): Specifies the domain of the netgroup. name (string): Specifies the name of the netgroup. nfs_a... | Implement the Python class `NisNetgroup` described below.
Class description:
Implementation of the 'NisNetgroup' model. Defines an NIS Netgroup. Attributes: description (string): Description of the netgroup. domain (string): Specifies the domain of the netgroup. name (string): Specifies the name of the netgroup. nfs_a... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class NisNetgroup:
"""Implementation of the 'NisNetgroup' model. Defines an NIS Netgroup. Attributes: description (string): Description of the netgroup. domain (string): Specifies the domain of the netgroup. name (string): Specifies the name of the netgroup. nfs_access (NfsAccessEnum): Specifies whethe... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class NisNetgroup:
"""Implementation of the 'NisNetgroup' model. Defines an NIS Netgroup. Attributes: description (string): Description of the netgroup. domain (string): Specifies the domain of the netgroup. name (string): Specifies the name of the netgroup. nfs_access (NfsAccessEnum): Specifies whether clients fro... | the_stack_v2_python_sparse | cohesity_management_sdk/models/nis_netgroup.py | cohesity/management-sdk-python | train | 24 |
c1be3b6f21ccbf8fdf053412d3a910fc58fd8956 | [
"if create and extracted:\n for moira_list in extracted:\n self.admin_lists.add(moira_list)",
"if create and extracted:\n for moira_list in extracted:\n self.view_lists.add(moira_list)"
] | <|body_start_0|>
if create and extracted:
for moira_list in extracted:
self.admin_lists.add(moira_list)
<|end_body_0|>
<|body_start_1|>
if create and extracted:
for moira_list in extracted:
self.view_lists.add(moira_list)
<|end_body_1|>
| Factory for a Collection | CollectionFactory | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CollectionFactory:
"""Factory for a Collection"""
def admin_lists(self, create, extracted, **kwargs):
"""Post-generation hook to handle admin_lists (if provided)"""
<|body_0|>
def view_lists(self, create, extracted, **kwargs):
"""Post-generation hook to handle ad... | stack_v2_sparse_classes_75kplus_train_066912 | 5,608 | permissive | [
{
"docstring": "Post-generation hook to handle admin_lists (if provided)",
"name": "admin_lists",
"signature": "def admin_lists(self, create, extracted, **kwargs)"
},
{
"docstring": "Post-generation hook to handle admin_lists (if provided)",
"name": "view_lists",
"signature": "def view_l... | 2 | stack_v2_sparse_classes_30k_train_012589 | Implement the Python class `CollectionFactory` described below.
Class description:
Factory for a Collection
Method signatures and docstrings:
- def admin_lists(self, create, extracted, **kwargs): Post-generation hook to handle admin_lists (if provided)
- def view_lists(self, create, extracted, **kwargs): Post-generat... | Implement the Python class `CollectionFactory` described below.
Class description:
Factory for a Collection
Method signatures and docstrings:
- def admin_lists(self, create, extracted, **kwargs): Post-generation hook to handle admin_lists (if provided)
- def view_lists(self, create, extracted, **kwargs): Post-generat... | 7d731ce94b1fa4baba1c1b3752e2d03949a88ea0 | <|skeleton|>
class CollectionFactory:
"""Factory for a Collection"""
def admin_lists(self, create, extracted, **kwargs):
"""Post-generation hook to handle admin_lists (if provided)"""
<|body_0|>
def view_lists(self, create, extracted, **kwargs):
"""Post-generation hook to handle ad... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CollectionFactory:
"""Factory for a Collection"""
def admin_lists(self, create, extracted, **kwargs):
"""Post-generation hook to handle admin_lists (if provided)"""
if create and extracted:
for moira_list in extracted:
self.admin_lists.add(moira_list)
def ... | the_stack_v2_python_sparse | ui/factories.py | mitodl/odl-video-service | train | 4 |
192104c1630bf16a017743a7269bf8f5888ac02d | [
"if instance.channel:\n return instance.channel.name\nelse:\n return None",
"if instance.channel:\n return instance.channel.title\nelse:\n return None"
] | <|body_start_0|>
if instance.channel:
return instance.channel.name
else:
return None
<|end_body_0|>
<|body_start_1|>
if instance.channel:
return instance.channel.title
else:
return None
<|end_body_1|>
| Serializer for NotificationSettings | NotificationSettingsSerializer | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NotificationSettingsSerializer:
"""Serializer for NotificationSettings"""
def get_channel_name(self, instance):
"""get the channel name"""
<|body_0|>
def get_channel_title(self, instance):
"""get the channel title"""
<|body_1|>
<|end_skeleton|>
<|body_s... | stack_v2_sparse_classes_75kplus_train_066913 | 1,015 | permissive | [
{
"docstring": "get the channel name",
"name": "get_channel_name",
"signature": "def get_channel_name(self, instance)"
},
{
"docstring": "get the channel title",
"name": "get_channel_title",
"signature": "def get_channel_title(self, instance)"
}
] | 2 | stack_v2_sparse_classes_30k_train_007383 | Implement the Python class `NotificationSettingsSerializer` described below.
Class description:
Serializer for NotificationSettings
Method signatures and docstrings:
- def get_channel_name(self, instance): get the channel name
- def get_channel_title(self, instance): get the channel title | Implement the Python class `NotificationSettingsSerializer` described below.
Class description:
Serializer for NotificationSettings
Method signatures and docstrings:
- def get_channel_name(self, instance): get the channel name
- def get_channel_title(self, instance): get the channel title
<|skeleton|>
class Notifica... | ba7442482da97d463302658c0aac989567ee1241 | <|skeleton|>
class NotificationSettingsSerializer:
"""Serializer for NotificationSettings"""
def get_channel_name(self, instance):
"""get the channel name"""
<|body_0|>
def get_channel_title(self, instance):
"""get the channel title"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class NotificationSettingsSerializer:
"""Serializer for NotificationSettings"""
def get_channel_name(self, instance):
"""get the channel name"""
if instance.channel:
return instance.channel.name
else:
return None
def get_channel_title(self, instance):
... | the_stack_v2_python_sparse | notifications/serializers.py | mitodl/open-discussions | train | 13 |
3469d8599593f2db97cadec09075909c80df7baf | [
"QLabel.__init__(self, parent)\nself.start_animation(self.SLOW_DURATION)\nfont = QFont('Arial', 20)\nself.setFont(font)\nself.setText('Click to start')\nself.setFixedHeight(100)\nself.setAlignment(Qt.AlignCenter)\nself.setStyleSheet('color: ' + color)",
"self.effect = QGraphicsOpacityEffect()\nself.setGraphicsEff... | <|body_start_0|>
QLabel.__init__(self, parent)
self.start_animation(self.SLOW_DURATION)
font = QFont('Arial', 20)
self.setFont(font)
self.setText('Click to start')
self.setFixedHeight(100)
self.setAlignment(Qt.AlignCenter)
self.setStyleSheet('color: ' + co... | This class extends the functionality of the default QLabel to add a fadein-fadeout animation | AnimatedLabel | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AnimatedLabel:
"""This class extends the functionality of the default QLabel to add a fadein-fadeout animation"""
def __init__(self, parent=None, color='yellow'):
"""Constructor of the class Keyword Arguments: parent {ui.gui.views.title.TitleWindow} -- Parent of this widget (default:... | stack_v2_sparse_classes_75kplus_train_066914 | 5,803 | no_license | [
{
"docstring": "Constructor of the class Keyword Arguments: parent {ui.gui.views.title.TitleWindow} -- Parent of this widget (default: {None}) color {str} -- Color of the start text (default: {'yellow'})",
"name": "__init__",
"signature": "def __init__(self, parent=None, color='yellow')"
},
{
"d... | 2 | stack_v2_sparse_classes_30k_train_022049 | Implement the Python class `AnimatedLabel` described below.
Class description:
This class extends the functionality of the default QLabel to add a fadein-fadeout animation
Method signatures and docstrings:
- def __init__(self, parent=None, color='yellow'): Constructor of the class Keyword Arguments: parent {ui.gui.vi... | Implement the Python class `AnimatedLabel` described below.
Class description:
This class extends the functionality of the default QLabel to add a fadein-fadeout animation
Method signatures and docstrings:
- def __init__(self, parent=None, color='yellow'): Constructor of the class Keyword Arguments: parent {ui.gui.vi... | a6e40f9778284426a15c05ef362dde243e687888 | <|skeleton|>
class AnimatedLabel:
"""This class extends the functionality of the default QLabel to add a fadein-fadeout animation"""
def __init__(self, parent=None, color='yellow'):
"""Constructor of the class Keyword Arguments: parent {ui.gui.views.title.TitleWindow} -- Parent of this widget (default:... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AnimatedLabel:
"""This class extends the functionality of the default QLabel to add a fadein-fadeout animation"""
def __init__(self, parent=None, color='yellow'):
"""Constructor of the class Keyword Arguments: parent {ui.gui.views.title.TitleWindow} -- Parent of this widget (default: {None}) colo... | the_stack_v2_python_sparse | behavior_studio/ui/gui/views/title.py | dcharrezt/BehaviorStudio | train | 0 |
a9031d35c957a3509f566a19af661eee70e8d6e1 | [
"person = model.Person.get(self.repo, self.params.id)\nif not person:\n return self.error(400, 'No person with ID: %r' % self.params.id)\nself.render('enable_notes.html', person=person, view_url=self.get_url('/view', id=self.params.id), captcha_html=self.get_captcha_html())",
"person = model.Person.get(self.re... | <|body_start_0|>
person = model.Person.get(self.repo, self.params.id)
if not person:
return self.error(400, 'No person with ID: %r' % self.params.id)
self.render('enable_notes.html', person=person, view_url=self.get_url('/view', id=self.params.id), captcha_html=self.get_captcha_html(... | Handles an author request to disable comments to a person record. | Handler | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Handler:
"""Handles an author request to disable comments to a person record."""
def get(self):
"""Prompts the user with a CAPTCHA before proceeding the request."""
<|body_0|>
def post(self):
"""If the user passed the CAPTCHA, send the confirmation email."""
... | stack_v2_sparse_classes_75kplus_train_066915 | 3,055 | permissive | [
{
"docstring": "Prompts the user with a CAPTCHA before proceeding the request.",
"name": "get",
"signature": "def get(self)"
},
{
"docstring": "If the user passed the CAPTCHA, send the confirmation email.",
"name": "post",
"signature": "def post(self)"
}
] | 2 | null | Implement the Python class `Handler` described below.
Class description:
Handles an author request to disable comments to a person record.
Method signatures and docstrings:
- def get(self): Prompts the user with a CAPTCHA before proceeding the request.
- def post(self): If the user passed the CAPTCHA, send the confir... | Implement the Python class `Handler` described below.
Class description:
Handles an author request to disable comments to a person record.
Method signatures and docstrings:
- def get(self): Prompts the user with a CAPTCHA before proceeding the request.
- def post(self): If the user passed the CAPTCHA, send the confir... | 7e40f2783ac89b91efd1d8497f1acc5b006361fa | <|skeleton|>
class Handler:
"""Handles an author request to disable comments to a person record."""
def get(self):
"""Prompts the user with a CAPTCHA before proceeding the request."""
<|body_0|>
def post(self):
"""If the user passed the CAPTCHA, send the confirmation email."""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Handler:
"""Handles an author request to disable comments to a person record."""
def get(self):
"""Prompts the user with a CAPTCHA before proceeding the request."""
person = model.Person.get(self.repo, self.params.id)
if not person:
return self.error(400, 'No person wi... | the_stack_v2_python_sparse | app/enable_notes.py | ZhengC1/personfinder | train | 2 |
c87fe27c1723ac436172bcc6e911e7809e0d8363 | [
"super(Encoder, self).__init__(d_model, d_k, d_v, sequence_length, h, batch_size, num_layer=num_layer)\nself.Q = Q\nself.K_s = K_s\nself.mask = mask\nself.initializer = tf.random_normal_initializer(stddev=0.1)\nself.dropout_keep_prob = dropout_keep_prob\nself.use_residual_conn = use_residual_conn",
"start = time.... | <|body_start_0|>
super(Encoder, self).__init__(d_model, d_k, d_v, sequence_length, h, batch_size, num_layer=num_layer)
self.Q = Q
self.K_s = K_s
self.mask = mask
self.initializer = tf.random_normal_initializer(stddev=0.1)
self.dropout_keep_prob = dropout_keep_prob
... | Encoder | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Encoder:
def __init__(self, d_model, d_k, d_v, sequence_length, h, batch_size, num_layer, Q, K_s, mask=None, dropout_keep_prob=0.9, use_residual_conn=True):
""":param d_model: :param d_k: :param d_v: :param sequence_length: :param h: :param batch_size: :param embedded_words: shape:[batch... | stack_v2_sparse_classes_75kplus_train_066916 | 6,839 | permissive | [
{
"docstring": ":param d_model: :param d_k: :param d_v: :param sequence_length: :param h: :param batch_size: :param embedded_words: shape:[batch_size*sequence_length,embed_size]",
"name": "__init__",
"signature": "def __init__(self, d_model, d_k, d_v, sequence_length, h, batch_size, num_layer, Q, K_s, m... | 3 | stack_v2_sparse_classes_30k_train_049355 | Implement the Python class `Encoder` described below.
Class description:
Implement the Encoder class.
Method signatures and docstrings:
- def __init__(self, d_model, d_k, d_v, sequence_length, h, batch_size, num_layer, Q, K_s, mask=None, dropout_keep_prob=0.9, use_residual_conn=True): :param d_model: :param d_k: :par... | Implement the Python class `Encoder` described below.
Class description:
Implement the Encoder class.
Method signatures and docstrings:
- def __init__(self, d_model, d_k, d_v, sequence_length, h, batch_size, num_layer, Q, K_s, mask=None, dropout_keep_prob=0.9, use_residual_conn=True): :param d_model: :param d_k: :par... | 480c909e0835a455606e829310ff949c9dd23549 | <|skeleton|>
class Encoder:
def __init__(self, d_model, d_k, d_v, sequence_length, h, batch_size, num_layer, Q, K_s, mask=None, dropout_keep_prob=0.9, use_residual_conn=True):
""":param d_model: :param d_k: :param d_v: :param sequence_length: :param h: :param batch_size: :param embedded_words: shape:[batch... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Encoder:
def __init__(self, d_model, d_k, d_v, sequence_length, h, batch_size, num_layer, Q, K_s, mask=None, dropout_keep_prob=0.9, use_residual_conn=True):
""":param d_model: :param d_k: :param d_v: :param sequence_length: :param h: :param batch_size: :param embedded_words: shape:[batch_size*sequence... | the_stack_v2_python_sparse | bert_language_understanding-master/bert_language_understanding-master/model/encoder.py | yyht/BERT | train | 37 | |
308f5573477079878a37f4bf2f3b33606b41d745 | [
"self.output_image = output_image\nself.output = output\nself.width = 550\nself.height = 600\nself.image_format = '.png'\nif not path.exists(self.output):\n mkdir(self.output)",
"if self.output_image:\n fig.write_image('images//' + name + self.image_format, scale=3)\nelse:\n fig.write_html(name + '.html'... | <|body_start_0|>
self.output_image = output_image
self.output = output
self.width = 550
self.height = 600
self.image_format = '.png'
if not path.exists(self.output):
mkdir(self.output)
<|end_body_0|>
<|body_start_1|>
if self.output_image:
... | PlotChart | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PlotChart:
def __init__(self, output_image=True, output='image'):
""":param output_image: {Boolean} Ture: output image; False: output html :param output: {String} output path"""
<|body_0|>
def create_chart(self, fig, name):
""":param fig: (PLotlt) 生成的PLotlt对象 :param ... | stack_v2_sparse_classes_75kplus_train_066917 | 6,826 | no_license | [
{
"docstring": ":param output_image: {Boolean} Ture: output image; False: output html :param output: {String} output path",
"name": "__init__",
"signature": "def __init__(self, output_image=True, output='image')"
},
{
"docstring": ":param fig: (PLotlt) 生成的PLotlt对象 :param name: 名字 :return:",
... | 2 | stack_v2_sparse_classes_30k_train_019346 | Implement the Python class `PlotChart` described below.
Class description:
Implement the PlotChart class.
Method signatures and docstrings:
- def __init__(self, output_image=True, output='image'): :param output_image: {Boolean} Ture: output image; False: output html :param output: {String} output path
- def create_ch... | Implement the Python class `PlotChart` described below.
Class description:
Implement the PlotChart class.
Method signatures and docstrings:
- def __init__(self, output_image=True, output='image'): :param output_image: {Boolean} Ture: output image; False: output html :param output: {String} output path
- def create_ch... | dcbff7abe3300c1a4c668cf6a96370a53be99ac5 | <|skeleton|>
class PlotChart:
def __init__(self, output_image=True, output='image'):
""":param output_image: {Boolean} Ture: output image; False: output html :param output: {String} output path"""
<|body_0|>
def create_chart(self, fig, name):
""":param fig: (PLotlt) 生成的PLotlt对象 :param ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PlotChart:
def __init__(self, output_image=True, output='image'):
""":param output_image: {Boolean} Ture: output image; False: output html :param output: {String} output path"""
self.output_image = output_image
self.output = output
self.width = 550
self.height = 600
... | the_stack_v2_python_sparse | study_book/general_analysis.py | hygnic/boomboost | train | 0 | |
3400dbab0f9a3edb08d4b4528b4c878bc68bf906 | [
"out_file = open(file_path, 'w')\njson.dump(data, out_file, indent=4)\nout_file.close()",
"try:\n with open(file_path) as f:\n return json.load(f)\nexcept IOError as e:\n print('could not read ' + file_path)"
] | <|body_start_0|>
out_file = open(file_path, 'w')
json.dump(data, out_file, indent=4)
out_file.close()
<|end_body_0|>
<|body_start_1|>
try:
with open(file_path) as f:
return json.load(f)
except IOError as e:
print('could not read ' + file_p... | This class handles writing data objects to files and loading in data objects | MyJsonHandler | [
"BSD-3-Clause",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MyJsonHandler:
"""This class handles writing data objects to files and loading in data objects"""
def save_data_to_json_file(data, file_path):
"""Store data as json in designated file_path"""
<|body_0|>
def get_data_from_json_file(file_path):
"""get data as json ... | stack_v2_sparse_classes_75kplus_train_066918 | 704 | permissive | [
{
"docstring": "Store data as json in designated file_path",
"name": "save_data_to_json_file",
"signature": "def save_data_to_json_file(data, file_path)"
},
{
"docstring": "get data as json in designated file_path and returns the loaded json",
"name": "get_data_from_json_file",
"signatur... | 2 | stack_v2_sparse_classes_30k_train_013362 | Implement the Python class `MyJsonHandler` described below.
Class description:
This class handles writing data objects to files and loading in data objects
Method signatures and docstrings:
- def save_data_to_json_file(data, file_path): Store data as json in designated file_path
- def get_data_from_json_file(file_pat... | Implement the Python class `MyJsonHandler` described below.
Class description:
This class handles writing data objects to files and loading in data objects
Method signatures and docstrings:
- def save_data_to_json_file(data, file_path): Store data as json in designated file_path
- def get_data_from_json_file(file_pat... | 20d8df6172906337f81583dabb841d66b8f31857 | <|skeleton|>
class MyJsonHandler:
"""This class handles writing data objects to files and loading in data objects"""
def save_data_to_json_file(data, file_path):
"""Store data as json in designated file_path"""
<|body_0|>
def get_data_from_json_file(file_path):
"""get data as json ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MyJsonHandler:
"""This class handles writing data objects to files and loading in data objects"""
def save_data_to_json_file(data, file_path):
"""Store data as json in designated file_path"""
out_file = open(file_path, 'w')
json.dump(data, out_file, indent=4)
out_file.clos... | the_stack_v2_python_sparse | new_algs/Number+theoretic+algorithms/Euclidean+algorithm/myjsonhandler.py | coolsnake/JupyterNotebook | train | 0 |
9066e186cb56c17fcb07e3ee243f561a8c2b9024 | [
"self.first_name = first_name\nself.last_name = last_name\nself.salary = salary",
"bonus = 5000\nif new_raise:\n bonus = new_raise\n new_amount = self.salary + bonus\nelse:\n new_amount = self.salary + bonus\nreturn new_amount"
] | <|body_start_0|>
self.first_name = first_name
self.last_name = last_name
self.salary = salary
<|end_body_0|>
<|body_start_1|>
bonus = 5000
if new_raise:
bonus = new_raise
new_amount = self.salary + bonus
else:
new_amount = self.salary ... | Will store attributes of an employee Including first name, last name, and annual salary | Employee | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Employee:
"""Will store attributes of an employee Including first name, last name, and annual salary"""
def __init__(self, first_name, last_name, salary):
"""Stores the attributes of the employee"""
<|body_0|>
def give_raise(self, new_raise=''):
"""Increases the ... | stack_v2_sparse_classes_75kplus_train_066919 | 985 | no_license | [
{
"docstring": "Stores the attributes of the employee",
"name": "__init__",
"signature": "def __init__(self, first_name, last_name, salary)"
},
{
"docstring": "Increases the salary of the employee",
"name": "give_raise",
"signature": "def give_raise(self, new_raise='')"
}
] | 2 | null | Implement the Python class `Employee` described below.
Class description:
Will store attributes of an employee Including first name, last name, and annual salary
Method signatures and docstrings:
- def __init__(self, first_name, last_name, salary): Stores the attributes of the employee
- def give_raise(self, new_rais... | Implement the Python class `Employee` described below.
Class description:
Will store attributes of an employee Including first name, last name, and annual salary
Method signatures and docstrings:
- def __init__(self, first_name, last_name, salary): Stores the attributes of the employee
- def give_raise(self, new_rais... | 3d4a2405f37bb53860fa34ae1efc1aa4ef9b5bdc | <|skeleton|>
class Employee:
"""Will store attributes of an employee Including first name, last name, and annual salary"""
def __init__(self, first_name, last_name, salary):
"""Stores the attributes of the employee"""
<|body_0|>
def give_raise(self, new_raise=''):
"""Increases the ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Employee:
"""Will store attributes of an employee Including first name, last name, and annual salary"""
def __init__(self, first_name, last_name, salary):
"""Stores the attributes of the employee"""
self.first_name = first_name
self.last_name = last_name
self.salary = sala... | the_stack_v2_python_sparse | employees.py | Olelewe-PROHUB/Python-Projects | train | 0 |
84f2a9dd32dbe0a1b8b58f1709b1c232477458ad | [
"super(NeighborAggregator, self).__init__()\nassert aggr_method in ['mean', 'sum', 'max']\nself.use_bias = use_bias\nself.aggr_method = aggr_method\nself.weight = nn.Parameter(torch.Tensor(input_dim, output_dim))\nif self.use_bias:\n self.bias = nn.Parameter(torch.Tensor(output_dim))\nself.__init_parameters()\nr... | <|body_start_0|>
super(NeighborAggregator, self).__init__()
assert aggr_method in ['mean', 'sum', 'max']
self.use_bias = use_bias
self.aggr_method = aggr_method
self.weight = nn.Parameter(torch.Tensor(input_dim, output_dim))
if self.use_bias:
self.bias = nn.Pa... | 定义邻居特征聚合方式 | NeighborAggregator | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NeighborAggregator:
"""定义邻居特征聚合方式"""
def __init__(self, input_dim, output_dim, use_bias=True, aggr_method='mean'):
"""定义邻居特征聚合方式 Inputs: ------- input_dim: int, 输入特征维度 output_dim: int, 输出特征维度 use_bias: boolean, 是否使用偏置 aggr_method: string, 聚合方式, 可选'mean', 'sum', 'max'"""
<|bod... | stack_v2_sparse_classes_75kplus_train_066920 | 2,112 | permissive | [
{
"docstring": "定义邻居特征聚合方式 Inputs: ------- input_dim: int, 输入特征维度 output_dim: int, 输出特征维度 use_bias: boolean, 是否使用偏置 aggr_method: string, 聚合方式, 可选'mean', 'sum', 'max'",
"name": "__init__",
"signature": "def __init__(self, input_dim, output_dim, use_bias=True, aggr_method='mean')"
},
{
"docstring"... | 3 | null | Implement the Python class `NeighborAggregator` described below.
Class description:
定义邻居特征聚合方式
Method signatures and docstrings:
- def __init__(self, input_dim, output_dim, use_bias=True, aggr_method='mean'): 定义邻居特征聚合方式 Inputs: ------- input_dim: int, 输入特征维度 output_dim: int, 输出特征维度 use_bias: boolean, 是否使用偏置 aggr_meth... | Implement the Python class `NeighborAggregator` described below.
Class description:
定义邻居特征聚合方式
Method signatures and docstrings:
- def __init__(self, input_dim, output_dim, use_bias=True, aggr_method='mean'): 定义邻居特征聚合方式 Inputs: ------- input_dim: int, 输入特征维度 output_dim: int, 输出特征维度 use_bias: boolean, 是否使用偏置 aggr_meth... | ee16c37fd065ba4c732138096f715f04c0ad6fcf | <|skeleton|>
class NeighborAggregator:
"""定义邻居特征聚合方式"""
def __init__(self, input_dim, output_dim, use_bias=True, aggr_method='mean'):
"""定义邻居特征聚合方式 Inputs: ------- input_dim: int, 输入特征维度 output_dim: int, 输出特征维度 use_bias: boolean, 是否使用偏置 aggr_method: string, 聚合方式, 可选'mean', 'sum', 'max'"""
<|bod... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class NeighborAggregator:
"""定义邻居特征聚合方式"""
def __init__(self, input_dim, output_dim, use_bias=True, aggr_method='mean'):
"""定义邻居特征聚合方式 Inputs: ------- input_dim: int, 输入特征维度 output_dim: int, 输出特征维度 use_bias: boolean, 是否使用偏置 aggr_method: string, 聚合方式, 可选'mean', 'sum', 'max'"""
super(NeighborAggr... | the_stack_v2_python_sparse | Node/GraphSAGE/script/aggregate.py | robbinc91/GNN-Pytorch | train | 0 |
713b8427f8e6c60ab2470f8515a03ae8dd3eb73e | [
"if self.category:\n return models.Vendor.objects.filter(active=True, category_id__gte=self.category.gte, category_id__lt=self.category.lt)\nreturn models.Vendor.objects.filter(active=True)",
"context = super().get_context_data(*args, **kwargs)\ncontext.update(vendors_count=models.Vendor.objects.filter(active=... | <|body_start_0|>
if self.category:
return models.Vendor.objects.filter(active=True, category_id__gte=self.category.gte, category_id__lt=self.category.lt)
return models.Vendor.objects.filter(active=True)
<|end_body_0|>
<|body_start_1|>
context = super().get_context_data(*args, **kwar... | Show vendors according to categories. | Vendors | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Vendors:
"""Show vendors according to categories."""
def get_queryset(self):
"""Show vendors according to categories."""
<|body_0|>
def get_context_data(self, *args, **kwargs):
"""Add total vendors count."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_75kplus_train_066921 | 5,601 | permissive | [
{
"docstring": "Show vendors according to categories.",
"name": "get_queryset",
"signature": "def get_queryset(self)"
},
{
"docstring": "Add total vendors count.",
"name": "get_context_data",
"signature": "def get_context_data(self, *args, **kwargs)"
}
] | 2 | stack_v2_sparse_classes_30k_train_025644 | Implement the Python class `Vendors` described below.
Class description:
Show vendors according to categories.
Method signatures and docstrings:
- def get_queryset(self): Show vendors according to categories.
- def get_context_data(self, *args, **kwargs): Add total vendors count. | Implement the Python class `Vendors` described below.
Class description:
Show vendors according to categories.
Method signatures and docstrings:
- def get_queryset(self): Show vendors according to categories.
- def get_context_data(self, *args, **kwargs): Add total vendors count.
<|skeleton|>
class Vendors:
"""S... | 84c4fa10aefbd792a956cef3d727623ca78cb5fd | <|skeleton|>
class Vendors:
"""Show vendors according to categories."""
def get_queryset(self):
"""Show vendors according to categories."""
<|body_0|>
def get_context_data(self, *args, **kwargs):
"""Add total vendors count."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Vendors:
"""Show vendors according to categories."""
def get_queryset(self):
"""Show vendors according to categories."""
if self.category:
return models.Vendor.objects.filter(active=True, category_id__gte=self.category.gte, category_id__lt=self.category.lt)
return mode... | the_stack_v2_python_sparse | market/core/views/base.py | katomaso/django-market | train | 0 |
013edbd8447129b361126f345c19579d4e313d93 | [
"log.debug('Getting bee record with ID')\nengine = database.get_engine()\nbee = database.beerecord\nif id == -1:\n query = sql.select([bee.c.bee_dict_id, bee.c.bee_name, bee.c.loc_info, bee.c.time])\nelse:\n query = sql.select([bee.c.beerecord_id, bee.c.user_id, bee.c.bee_dict_id, bee.c.bee_name, bee.c.colora... | <|body_start_0|>
log.debug('Getting bee record with ID')
engine = database.get_engine()
bee = database.beerecord
if id == -1:
query = sql.select([bee.c.bee_dict_id, bee.c.bee_name, bee.c.loc_info, bee.c.time])
else:
query = sql.select([bee.c.beerecord_id, ... | BeeRecord | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BeeRecord:
def get(self, id: int, user=None):
"""Get a bee record by ID"""
<|body_0|>
def put(self, id: int, user=None):
"""Update a bee record by ID"""
<|body_1|>
def delete(self, id: int, user):
"""Delete a bee record by ID"""
<|body_2|... | stack_v2_sparse_classes_75kplus_train_066922 | 12,437 | no_license | [
{
"docstring": "Get a bee record by ID",
"name": "get",
"signature": "def get(self, id: int, user=None)"
},
{
"docstring": "Update a bee record by ID",
"name": "put",
"signature": "def put(self, id: int, user=None)"
},
{
"docstring": "Delete a bee record by ID",
"name": "dele... | 3 | stack_v2_sparse_classes_30k_train_028591 | Implement the Python class `BeeRecord` described below.
Class description:
Implement the BeeRecord class.
Method signatures and docstrings:
- def get(self, id: int, user=None): Get a bee record by ID
- def put(self, id: int, user=None): Update a bee record by ID
- def delete(self, id: int, user): Delete a bee record ... | Implement the Python class `BeeRecord` described below.
Class description:
Implement the BeeRecord class.
Method signatures and docstrings:
- def get(self, id: int, user=None): Get a bee record by ID
- def put(self, id: int, user=None): Update a bee record by ID
- def delete(self, id: int, user): Delete a bee record ... | ab45d78d207b957bb31381b0df12f4e318fb1e41 | <|skeleton|>
class BeeRecord:
def get(self, id: int, user=None):
"""Get a bee record by ID"""
<|body_0|>
def put(self, id: int, user=None):
"""Update a bee record by ID"""
<|body_1|>
def delete(self, id: int, user):
"""Delete a bee record by ID"""
<|body_2|... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class BeeRecord:
def get(self, id: int, user=None):
"""Get a bee record by ID"""
log.debug('Getting bee record with ID')
engine = database.get_engine()
bee = database.beerecord
if id == -1:
query = sql.select([bee.c.bee_dict_id, bee.c.bee_name, bee.c.loc_info, bee... | the_stack_v2_python_sparse | beecology_api/bee_data_api/endpoints/bee_record.py | C7C8/beecology-api-v7 | train | 0 | |
330c746b8fc75b8d698c83bbbbae41a9a077c913 | [
"if type(self) != type(other):\n return False\nreturn True",
"shape = x.shape\nparties = x.parties\nnr_parties = len(parties)\nkwargs = {'seed_id_locations': secrets.randbits(64)}\ndecomposed_shares = [share.bit_decomposition(share, ring_size, False, **kwargs) for share in x.child]\nres_shares: List[MPCTensor]... | <|body_start_0|>
if type(self) != type(other):
return False
return True
<|end_body_0|>
<|body_start_1|>
shape = x.shape
parties = x.parties
nr_parties = len(parties)
kwargs = {'seed_id_locations': secrets.randbits(64)}
decomposed_shares = [share.bit_d... | ABY3 Protocol Implementation. | ABY3 | [
"LicenseRef-scancode-warranty-disclaimer",
"Apache-2.0",
"Python-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ABY3:
"""ABY3 Protocol Implementation."""
def __eq__(self, other: Any) -> bool:
"""Check if "self" is equal with another object given a set of attributes to compare. Args: other (Any): Object to compare Returns: bool: True if equal False if not."""
<|body_0|>
def bit_inj... | stack_v2_sparse_classes_75kplus_train_066923 | 4,866 | permissive | [
{
"docstring": "Check if \"self\" is equal with another object given a set of attributes to compare. Args: other (Any): Object to compare Returns: bool: True if equal False if not.",
"name": "__eq__",
"signature": "def __eq__(self, other: Any) -> bool"
},
{
"docstring": "Perform ABY3 bit injecti... | 4 | stack_v2_sparse_classes_30k_train_027494 | Implement the Python class `ABY3` described below.
Class description:
ABY3 Protocol Implementation.
Method signatures and docstrings:
- def __eq__(self, other: Any) -> bool: Check if "self" is equal with another object given a set of attributes to compare. Args: other (Any): Object to compare Returns: bool: True if e... | Implement the Python class `ABY3` described below.
Class description:
ABY3 Protocol Implementation.
Method signatures and docstrings:
- def __eq__(self, other: Any) -> bool: Check if "self" is equal with another object given a set of attributes to compare. Args: other (Any): Object to compare Returns: bool: True if e... | 1d2c6928b95a2f8164167a8c53f350b188e4533c | <|skeleton|>
class ABY3:
"""ABY3 Protocol Implementation."""
def __eq__(self, other: Any) -> bool:
"""Check if "self" is equal with another object given a set of attributes to compare. Args: other (Any): Object to compare Returns: bool: True if equal False if not."""
<|body_0|>
def bit_inj... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ABY3:
"""ABY3 Protocol Implementation."""
def __eq__(self, other: Any) -> bool:
"""Check if "self" is equal with another object given a set of attributes to compare. Args: other (Any): Object to compare Returns: bool: True if equal False if not."""
if type(self) != type(other):
... | the_stack_v2_python_sparse | packages/syft/src/syft/core/smpc/protocol/aby3/aby3.py | aanurraj/PySyft | train | 0 |
d5b3d57a7ca5f8a5a5466c97d2966f91430abc00 | [
"filter_kwargs = {}\nregion_name = self.request.GET.get('region')\nif region_name is not None and region_name != '':\n filter_kwargs['region__name'] = region_name\nreturn self.model.awaiting_fulfillment.filter(**filter_kwargs).prefetch_related('region')",
"context = super().get_context_data(*args, **kwargs)\nc... | <|body_start_0|>
filter_kwargs = {}
region_name = self.request.GET.get('region')
if region_name is not None and region_name != '':
filter_kwargs['region__name'] = region_name
return self.model.awaiting_fulfillment.filter(**filter_kwargs).prefetch_related('region')
<|end_body_... | Display a filterable list of orders. | Awaitingfulfillment | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Awaitingfulfillment:
"""Display a filterable list of orders."""
def get_queryset(self):
"""Return a queryset of orders awaiting fulillment."""
<|body_0|>
def get_context_data(self, *args, **kwargs):
"""Return the template context."""
<|body_1|>
def g... | stack_v2_sparse_classes_75kplus_train_066924 | 25,252 | no_license | [
{
"docstring": "Return a queryset of orders awaiting fulillment.",
"name": "get_queryset",
"signature": "def get_queryset(self)"
},
{
"docstring": "Return the template context.",
"name": "get_context_data",
"signature": "def get_context_data(self, *args, **kwargs)"
},
{
"docstrin... | 3 | stack_v2_sparse_classes_30k_train_018982 | Implement the Python class `Awaitingfulfillment` described below.
Class description:
Display a filterable list of orders.
Method signatures and docstrings:
- def get_queryset(self): Return a queryset of orders awaiting fulillment.
- def get_context_data(self, *args, **kwargs): Return the template context.
- def get_p... | Implement the Python class `Awaitingfulfillment` described below.
Class description:
Display a filterable list of orders.
Method signatures and docstrings:
- def get_queryset(self): Return a queryset of orders awaiting fulillment.
- def get_context_data(self, *args, **kwargs): Return the template context.
- def get_p... | ba51d4e304b1aeb296fa2fe16611c892fcdbd471 | <|skeleton|>
class Awaitingfulfillment:
"""Display a filterable list of orders."""
def get_queryset(self):
"""Return a queryset of orders awaiting fulillment."""
<|body_0|>
def get_context_data(self, *args, **kwargs):
"""Return the template context."""
<|body_1|>
def g... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Awaitingfulfillment:
"""Display a filterable list of orders."""
def get_queryset(self):
"""Return a queryset of orders awaiting fulillment."""
filter_kwargs = {}
region_name = self.request.GET.get('region')
if region_name is not None and region_name != '':
filt... | the_stack_v2_python_sparse | fba/views/fba.py | stcstores/stcadmin | train | 0 |
fb10f6d6998c8c810fe9818015376f0b41ba7a02 | [
"if value is not None:\n assert value.tzinfo == timezone.utc, f\"Expected '{value}' to be UTC\"\nreturn value",
"if value is not None:\n assert value.tzinfo is None\n return value.replace(tzinfo=timezone.utc)\nreturn None"
] | <|body_start_0|>
if value is not None:
assert value.tzinfo == timezone.utc, f"Expected '{value}' to be UTC"
return value
<|end_body_0|>
<|body_start_1|>
if value is not None:
assert value.tzinfo is None
return value.replace(tzinfo=timezone.utc)
return... | A SQL column type to store UTC datetimes. Usage example: table = sqlalchemy.Table( ... sqlalchemy.Column("my_datetime_column", UTCDateTime) ) Opentrons robot-server code should always use this instead of SQLAlchemy's built-in DateTime type. Motivation: We generally want our datetimes to have a UTC timezone so they're u... | UTCDateTime | [
"LicenseRef-scancode-warranty-disclaimer",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UTCDateTime:
"""A SQL column type to store UTC datetimes. Usage example: table = sqlalchemy.Table( ... sqlalchemy.Column("my_datetime_column", UTCDateTime) ) Opentrons robot-server code should always use this instead of SQLAlchemy's built-in DateTime type. Motivation: We generally want our dateti... | stack_v2_sparse_classes_75kplus_train_066925 | 2,273 | permissive | [
{
"docstring": "Prepare a Python datetime object to inserted into SQL via SQLAlchemy.",
"name": "process_bind_param",
"signature": "def process_bind_param(self, value: Optional[datetime], dialect: object) -> Optional[datetime]"
},
{
"docstring": "Process a Python datetime object that SQLAlchemy ... | 2 | stack_v2_sparse_classes_30k_train_038152 | Implement the Python class `UTCDateTime` described below.
Class description:
A SQL column type to store UTC datetimes. Usage example: table = sqlalchemy.Table( ... sqlalchemy.Column("my_datetime_column", UTCDateTime) ) Opentrons robot-server code should always use this instead of SQLAlchemy's built-in DateTime type. M... | Implement the Python class `UTCDateTime` described below.
Class description:
A SQL column type to store UTC datetimes. Usage example: table = sqlalchemy.Table( ... sqlalchemy.Column("my_datetime_column", UTCDateTime) ) Opentrons robot-server code should always use this instead of SQLAlchemy's built-in DateTime type. M... | 026b523c8c9e5d45910c490efb89194d72595be9 | <|skeleton|>
class UTCDateTime:
"""A SQL column type to store UTC datetimes. Usage example: table = sqlalchemy.Table( ... sqlalchemy.Column("my_datetime_column", UTCDateTime) ) Opentrons robot-server code should always use this instead of SQLAlchemy's built-in DateTime type. Motivation: We generally want our dateti... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class UTCDateTime:
"""A SQL column type to store UTC datetimes. Usage example: table = sqlalchemy.Table( ... sqlalchemy.Column("my_datetime_column", UTCDateTime) ) Opentrons robot-server code should always use this instead of SQLAlchemy's built-in DateTime type. Motivation: We generally want our datetimes to have a... | the_stack_v2_python_sparse | robot-server/robot_server/persistence/_utc_datetime.py | Opentrons/opentrons | train | 326 |
5c7dd48719ad1f842445bb763666cf8b956170d9 | [
"if len(S) == 0:\n return ['']\nqueue = []\nqueue.append(S)\nfor i in range(len(S)):\n if ord(S[i]) >= ord('0') and ord(S[i]) <= ord('9'):\n continue\n for j in range(len(queue)):\n cur = queue.pop(0)\n newStr = cur[:i] + cur[i].upper() + cur[i + 1:]\n queue.append(newStr)\n ... | <|body_start_0|>
if len(S) == 0:
return ['']
queue = []
queue.append(S)
for i in range(len(S)):
if ord(S[i]) >= ord('0') and ord(S[i]) <= ord('9'):
continue
for j in range(len(queue)):
cur = queue.pop(0)
... | https://leetcode.com/problems/letter-case-permutation/description/ | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
"""https://leetcode.com/problems/letter-case-permutation/description/"""
def letterCasePermutation(self, S):
""":type S: str :rtype: List[str] BFS solution"""
<|body_0|>
def letterCasePermutation2(self, S):
""":type S: str :rtype: List[str] DFS solution... | stack_v2_sparse_classes_75kplus_train_066926 | 2,798 | no_license | [
{
"docstring": ":type S: str :rtype: List[str] BFS solution",
"name": "letterCasePermutation",
"signature": "def letterCasePermutation(self, S)"
},
{
"docstring": ":type S: str :rtype: List[str] DFS solution",
"name": "letterCasePermutation2",
"signature": "def letterCasePermutation2(sel... | 4 | null | Implement the Python class `Solution` described below.
Class description:
https://leetcode.com/problems/letter-case-permutation/description/
Method signatures and docstrings:
- def letterCasePermutation(self, S): :type S: str :rtype: List[str] BFS solution
- def letterCasePermutation2(self, S): :type S: str :rtype: L... | Implement the Python class `Solution` described below.
Class description:
https://leetcode.com/problems/letter-case-permutation/description/
Method signatures and docstrings:
- def letterCasePermutation(self, S): :type S: str :rtype: List[str] BFS solution
- def letterCasePermutation2(self, S): :type S: str :rtype: L... | 54d3d9530b25272d4a2e5dc33e7035c44f506dc5 | <|skeleton|>
class Solution:
"""https://leetcode.com/problems/letter-case-permutation/description/"""
def letterCasePermutation(self, S):
""":type S: str :rtype: List[str] BFS solution"""
<|body_0|>
def letterCasePermutation2(self, S):
""":type S: str :rtype: List[str] DFS solution... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
"""https://leetcode.com/problems/letter-case-permutation/description/"""
def letterCasePermutation(self, S):
""":type S: str :rtype: List[str] BFS solution"""
if len(S) == 0:
return ['']
queue = []
queue.append(S)
for i in range(len(S)):
... | the_stack_v2_python_sparse | old/Session002/Backtracking/LetterCasePermutation.py | MaxIakovliev/algorithms | train | 0 |
20b019f7b14eb857bbc29b4770f5a8a382bfe157 | [
"count = 0\nfor s in range(len(A) - 2):\n d = A[s + 1] - A[s]\n for e in range(s + 2, len(A)):\n if A[e] - A[e - 1] == d:\n count += 1\n else:\n break\nreturn count",
"dp = [0] * len(A)\nsum = 0\nfor i in range(2, len(A)):\n if A[i] - A[i - 1] == A[i - 1] - A[i - 2]:\n... | <|body_start_0|>
count = 0
for s in range(len(A) - 2):
d = A[s + 1] - A[s]
for e in range(s + 2, len(A)):
if A[e] - A[e - 1] == d:
count += 1
else:
break
return count
<|end_body_0|>
<|body_start_1|>
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def numberOfArithmeticSlices_bruteforce(self, A):
"""time O(n^2) space O(1) :type A: List[int] :rtype: int"""
<|body_0|>
def numberOfArithmeticSlices_dp(self, A):
"""time O(n) space O(n) :param A: :return:"""
<|body_1|>
def numberOfArithmeticSl... | stack_v2_sparse_classes_75kplus_train_066927 | 1,251 | no_license | [
{
"docstring": "time O(n^2) space O(1) :type A: List[int] :rtype: int",
"name": "numberOfArithmeticSlices_bruteforce",
"signature": "def numberOfArithmeticSlices_bruteforce(self, A)"
},
{
"docstring": "time O(n) space O(n) :param A: :return:",
"name": "numberOfArithmeticSlices_dp",
"sign... | 3 | stack_v2_sparse_classes_30k_test_000112 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def numberOfArithmeticSlices_bruteforce(self, A): time O(n^2) space O(1) :type A: List[int] :rtype: int
- def numberOfArithmeticSlices_dp(self, A): time O(n) space O(n) :param A:... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def numberOfArithmeticSlices_bruteforce(self, A): time O(n^2) space O(1) :type A: List[int] :rtype: int
- def numberOfArithmeticSlices_dp(self, A): time O(n) space O(n) :param A:... | 85f71621c54f6b0029f3a2746f022f89dd7419d9 | <|skeleton|>
class Solution:
def numberOfArithmeticSlices_bruteforce(self, A):
"""time O(n^2) space O(1) :type A: List[int] :rtype: int"""
<|body_0|>
def numberOfArithmeticSlices_dp(self, A):
"""time O(n) space O(n) :param A: :return:"""
<|body_1|>
def numberOfArithmeticSl... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def numberOfArithmeticSlices_bruteforce(self, A):
"""time O(n^2) space O(1) :type A: List[int] :rtype: int"""
count = 0
for s in range(len(A) - 2):
d = A[s + 1] - A[s]
for e in range(s + 2, len(A)):
if A[e] - A[e - 1] == d:
... | the_stack_v2_python_sparse | LeetCode/DynamicProgramming/413_arithmetric_slices.py | XyK0907/for_work | train | 0 | |
90784e64bbeacfeb1a5014661fdb9ddbdae445cc | [
"res1 = SqlQuery('select * from \"Лицо\"')\nres2 = SqlQuery(query='select * from \"Лицо\"')\nself.assertEqual(res1.get().Size(), 15)\nself.assertEqual(res2.get().Size(), 15)",
"ans = SqlQuery('select * from \"Лицо\" where \"@Лицо\"=$1', 1)\nself.assertEqual(ans.get().Size(), 1)\nself.assertEqual(str(ans.get()[0][... | <|body_start_0|>
res1 = SqlQuery('select * from "Лицо"')
res2 = SqlQuery(query='select * from "Лицо"')
self.assertEqual(res1.get().Size(), 15)
self.assertEqual(res2.get().Size(), 15)
<|end_body_0|>
<|body_start_1|>
ans = SqlQuery('select * from "Лицо" where "@Лицо"=$1', 1)
... | TestSqlQuery | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestSqlQuery:
def test_clean(self):
"""Автор: Рыбаков М.А"""
<|body_0|>
def test_args(self):
"""Автор: Рыбаков М.А"""
<|body_1|>
def test_rec(self):
"""Автор: Рыбаков М.А"""
<|body_2|>
def test_format(self):
"""Автор: Рыбаков... | stack_v2_sparse_classes_75kplus_train_066928 | 3,928 | no_license | [
{
"docstring": "Автор: Рыбаков М.А",
"name": "test_clean",
"signature": "def test_clean(self)"
},
{
"docstring": "Автор: Рыбаков М.А",
"name": "test_args",
"signature": "def test_args(self)"
},
{
"docstring": "Автор: Рыбаков М.А",
"name": "test_rec",
"signature": "def tes... | 6 | null | Implement the Python class `TestSqlQuery` described below.
Class description:
Implement the TestSqlQuery class.
Method signatures and docstrings:
- def test_clean(self): Автор: Рыбаков М.А
- def test_args(self): Автор: Рыбаков М.А
- def test_rec(self): Автор: Рыбаков М.А
- def test_format(self): Автор: Рыбаков М.А
- ... | Implement the Python class `TestSqlQuery` described below.
Class description:
Implement the TestSqlQuery class.
Method signatures and docstrings:
- def test_clean(self): Автор: Рыбаков М.А
- def test_args(self): Автор: Рыбаков М.А
- def test_rec(self): Автор: Рыбаков М.А
- def test_format(self): Автор: Рыбаков М.А
- ... | 5559275accbfda0cb75c8c90d79090c10524e815 | <|skeleton|>
class TestSqlQuery:
def test_clean(self):
"""Автор: Рыбаков М.А"""
<|body_0|>
def test_args(self):
"""Автор: Рыбаков М.А"""
<|body_1|>
def test_rec(self):
"""Автор: Рыбаков М.А"""
<|body_2|>
def test_format(self):
"""Автор: Рыбаков... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TestSqlQuery:
def test_clean(self):
"""Автор: Рыбаков М.А"""
res1 = SqlQuery('select * from "Лицо"')
res2 = SqlQuery(query='select * from "Лицо"')
self.assertEqual(res1.get().Size(), 15)
self.assertEqual(res2.get().Size(), 15)
def test_args(self):
"""Автор:... | the_stack_v2_python_sparse | test_api/sqlquery.py | 4l1fe/miscellaneous | train | 0 | |
918ea9b37cf9ddc6b8bba942907fb87ed0c765ca | [
"super(FullyConnectedNNB, self).__init__(name=name)\nself._num_sites = num_sites\nself._num_layers = num_layers\nself._layer_sizes = layer_sizes\nnonlinearity = tf.nn.relu\nself._components = []\nwith self._enter_variable_scope():\n for _, layer_size in zip(range(num_layers), layer_sizes):\n self._compone... | <|body_start_0|>
super(FullyConnectedNNB, self).__init__(name=name)
self._num_sites = num_sites
self._num_layers = num_layers
self._layer_sizes = layer_sizes
nonlinearity = tf.nn.relu
self._components = []
with self._enter_variable_scope():
for _, laye... | BCS neural network backflow module. | FullyConnectedNNB | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FullyConnectedNNB:
"""BCS neural network backflow module."""
def __init__(self, num_sites: int, num_layers: int, layer_sizes: List[int], name: str='fully_connected_nnb'):
"""Constructs a neural net backflow module. Args: num_sites: Number of sites in the system. num_layers: Number of... | stack_v2_sparse_classes_75kplus_train_066929 | 40,960 | permissive | [
{
"docstring": "Constructs a neural net backflow module. Args: num_sites: Number of sites in the system. num_layers: Number of neural networks. layer_sizes: Sizes of fully connected networks. name: Name of the module.",
"name": "__init__",
"signature": "def __init__(self, num_sites: int, num_layers: int... | 3 | stack_v2_sparse_classes_30k_train_021455 | Implement the Python class `FullyConnectedNNB` described below.
Class description:
BCS neural network backflow module.
Method signatures and docstrings:
- def __init__(self, num_sites: int, num_layers: int, layer_sizes: List[int], name: str='fully_connected_nnb'): Constructs a neural net backflow module. Args: num_si... | Implement the Python class `FullyConnectedNNB` described below.
Class description:
BCS neural network backflow module.
Method signatures and docstrings:
- def __init__(self, num_sites: int, num_layers: int, layer_sizes: List[int], name: str='fully_connected_nnb'): Constructs a neural net backflow module. Args: num_si... | 3a298ceab53bf6403c1a4037cb22431499891d79 | <|skeleton|>
class FullyConnectedNNB:
"""BCS neural network backflow module."""
def __init__(self, num_sites: int, num_layers: int, layer_sizes: List[int], name: str='fully_connected_nnb'):
"""Constructs a neural net backflow module. Args: num_sites: Number of sites in the system. num_layers: Number of... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class FullyConnectedNNB:
"""BCS neural network backflow module."""
def __init__(self, num_sites: int, num_layers: int, layer_sizes: List[int], name: str='fully_connected_nnb'):
"""Constructs a neural net backflow module. Args: num_sites: Number of sites in the system. num_layers: Number of neural netwo... | the_stack_v2_python_sparse | cgs_vmc/wavefunctions.py | ClarkResearchGroup/cgs-vmc | train | 18 |
aa02375b03fe3920c23046f6fd00d9120c8304a8 | [
"rv = self.get(ident)\nif rv is None:\n abort(404)\nreturn rv",
"rv = self.first()\nif rv is None:\n abort(404)\nreturn rv",
"if error_out and page < 1:\n abort(404)\nitems = self.limit(per_page).offset((page - 1) * per_page).all()\nif not items and page != 1 and error_out:\n abort(404)\nreturn Pagi... | <|body_start_0|>
rv = self.get(ident)
if rv is None:
abort(404)
return rv
<|end_body_0|>
<|body_start_1|>
rv = self.first()
if rv is None:
abort(404)
return rv
<|end_body_1|>
<|body_start_2|>
if error_out and page < 1:
abort(4... | The default query object used for models, and exposed as :attr:`~SQLAlchemy.Query`. This can be subclassed and replaced for individual models by setting the :attr:`~Model.query_class` attribute. This is a subclass of a standard SQLAlchemy :class:`~sqlalchemy.orm.query.Query` class and has all the methods of a standard ... | BaseQuery | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BaseQuery:
"""The default query object used for models, and exposed as :attr:`~SQLAlchemy.Query`. This can be subclassed and replaced for individual models by setting the :attr:`~Model.query_class` attribute. This is a subclass of a standard SQLAlchemy :class:`~sqlalchemy.orm.query.Query` class a... | stack_v2_sparse_classes_75kplus_train_066930 | 30,678 | permissive | [
{
"docstring": "Like :meth:`get` but aborts with 404 if not found instead of returning `None`.",
"name": "get_or_404",
"signature": "def get_or_404(self, ident)"
},
{
"docstring": "Like :meth:`first` but aborts with 404 if not found instead of returning `None`.",
"name": "first_or_404",
... | 3 | stack_v2_sparse_classes_30k_test_002163 | Implement the Python class `BaseQuery` described below.
Class description:
The default query object used for models, and exposed as :attr:`~SQLAlchemy.Query`. This can be subclassed and replaced for individual models by setting the :attr:`~Model.query_class` attribute. This is a subclass of a standard SQLAlchemy :clas... | Implement the Python class `BaseQuery` described below.
Class description:
The default query object used for models, and exposed as :attr:`~SQLAlchemy.Query`. This can be subclassed and replaced for individual models by setting the :attr:`~Model.query_class` attribute. This is a subclass of a standard SQLAlchemy :clas... | 7053de769a3a7093f84cb6117a361ed394472ef0 | <|skeleton|>
class BaseQuery:
"""The default query object used for models, and exposed as :attr:`~SQLAlchemy.Query`. This can be subclassed and replaced for individual models by setting the :attr:`~Model.query_class` attribute. This is a subclass of a standard SQLAlchemy :class:`~sqlalchemy.orm.query.Query` class a... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class BaseQuery:
"""The default query object used for models, and exposed as :attr:`~SQLAlchemy.Query`. This can be subclassed and replaced for individual models by setting the :attr:`~Model.query_class` attribute. This is a subclass of a standard SQLAlchemy :class:`~sqlalchemy.orm.query.Query` class and has all th... | the_stack_v2_python_sparse | 1/chartnet/flask_sqlalchemy.py | catsky/rebang | train | 30 |
05d3c1e0dbc1523cd98da14d955a1e866336697c | [
"super().__init__(name=name)\npos_encoding = PositionalEmbedding.get_sinusoid_encoding(config['n_seq'], config['d_model'])\nself.embedding = new_embedding(config['n_seq'], config['d_model'], trainable=False, weights=[pos_encoding])",
"position = tf.cast(tf.math.cumsum(tf.ones_like(inputs), axis=1, exclusive=True)... | <|body_start_0|>
super().__init__(name=name)
pos_encoding = PositionalEmbedding.get_sinusoid_encoding(config['n_seq'], config['d_model'])
self.embedding = new_embedding(config['n_seq'], config['d_model'], trainable=False, weights=[pos_encoding])
<|end_body_0|>
<|body_start_1|>
position ... | Positional Embedding Class | PositionalEmbedding | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PositionalEmbedding:
"""Positional Embedding Class"""
def __init__(self, config, name='position_embedding'):
"""생성자 :param config: Config 객체 :param name: layer name"""
<|body_0|>
def call(self, inputs):
"""layer 실행 :param inputs: 입력 :return embed: positional embe... | stack_v2_sparse_classes_75kplus_train_066931 | 14,325 | permissive | [
{
"docstring": "생성자 :param config: Config 객체 :param name: layer name",
"name": "__init__",
"signature": "def __init__(self, config, name='position_embedding')"
},
{
"docstring": "layer 실행 :param inputs: 입력 :return embed: positional embedding lookup 결과",
"name": "call",
"signature": "def ... | 3 | null | Implement the Python class `PositionalEmbedding` described below.
Class description:
Positional Embedding Class
Method signatures and docstrings:
- def __init__(self, config, name='position_embedding'): 생성자 :param config: Config 객체 :param name: layer name
- def call(self, inputs): layer 실행 :param inputs: 입력 :return e... | Implement the Python class `PositionalEmbedding` described below.
Class description:
Positional Embedding Class
Method signatures and docstrings:
- def __init__(self, config, name='position_embedding'): 생성자 :param config: Config 객체 :param name: layer name
- def call(self, inputs): layer 실행 :param inputs: 입력 :return e... | cf8588ead07a098de9dd1e4f177374ba7ce08d74 | <|skeleton|>
class PositionalEmbedding:
"""Positional Embedding Class"""
def __init__(self, config, name='position_embedding'):
"""생성자 :param config: Config 객체 :param name: layer name"""
<|body_0|>
def call(self, inputs):
"""layer 실행 :param inputs: 입력 :return embed: positional embe... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PositionalEmbedding:
"""Positional Embedding Class"""
def __init__(self, config, name='position_embedding'):
"""생성자 :param config: Config 객체 :param name: layer name"""
super().__init__(name=name)
pos_encoding = PositionalEmbedding.get_sinusoid_encoding(config['n_seq'], config['d_m... | the_stack_v2_python_sparse | transformer/model.py | paul-hyun/tf_transformers | train | 10 |
71276ce46cf6055be31820b149f8d1edf19235a1 | [
"super().pre_trigger_run(trigger=trigger, **kwargs)\nrr_location = os.path.join(get_global_conf().getdir('utilities', 'install_directory'), 'rr')\ntrigger.cmd = '{} record {}'.format(os.path.join(rr_location, 'bin/rr'), trigger.cmd)",
"mozilla_rr = get_plugin_conf('base', 'rr')\ninstaller = Installer.factory(mozi... | <|body_start_0|>
super().pre_trigger_run(trigger=trigger, **kwargs)
rr_location = os.path.join(get_global_conf().getdir('utilities', 'install_directory'), 'rr')
trigger.cmd = '{} record {}'.format(os.path.join(rr_location, 'bin/rr'), trigger.cmd)
<|end_body_0|>
<|body_start_1|>
mozilla_... | Record Replay by Mozilla | RR | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RR:
"""Record Replay by Mozilla"""
def pre_trigger_run(self, trigger: RawTrigger, *args, **kwargs) -> None:
"""Updates the trigger command to run rr on top of the plugin's command :param trigger: the trigger that will run :param args: other arguments to pass to parents :param kwargs:... | stack_v2_sparse_classes_75kplus_train_066932 | 1,421 | no_license | [
{
"docstring": "Updates the trigger command to run rr on top of the plugin's command :param trigger: the trigger that will run :param args: other arguments to pass to parents :param kwargs: other keywords arguments to pass to parents",
"name": "pre_trigger_run",
"signature": "def pre_trigger_run(self, t... | 2 | null | Implement the Python class `RR` described below.
Class description:
Record Replay by Mozilla
Method signatures and docstrings:
- def pre_trigger_run(self, trigger: RawTrigger, *args, **kwargs) -> None: Updates the trigger command to run rr on top of the plugin's command :param trigger: the trigger that will run :para... | Implement the Python class `RR` described below.
Class description:
Record Replay by Mozilla
Method signatures and docstrings:
- def pre_trigger_run(self, trigger: RawTrigger, *args, **kwargs) -> None: Updates the trigger command to run rr on top of the plugin's command :param trigger: the trigger that will run :para... | e9f914fb6c4eb1bc97f7dfc665e8dd6c7e7ad068 | <|skeleton|>
class RR:
"""Record Replay by Mozilla"""
def pre_trigger_run(self, trigger: RawTrigger, *args, **kwargs) -> None:
"""Updates the trigger command to run rr on top of the plugin's command :param trigger: the trigger that will run :param args: other arguments to pass to parents :param kwargs:... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class RR:
"""Record Replay by Mozilla"""
def pre_trigger_run(self, trigger: RawTrigger, *args, **kwargs) -> None:
"""Updates the trigger command to run rr on top of the plugin's command :param trigger: the trigger that will run :param args: other arguments to pass to parents :param kwargs: other keywor... | the_stack_v2_python_sparse | plugins/base/rr.py | holaymzhang/bugbase | train | 0 |
c4db367989c2bc27f682738600241add92175873 | [
"global rsonline_CONN\ncursor = None\ntry:\n cursor = rsonline_CONN.cursor(buffered=True, dictionary=True)\n sql = 'insert into lie_brand(brand_name, brand_logo, brand_desc,site_url, web_url) values(%(brand_name)s,%(brand_logo)s,%(brand_desc)s,%(site_url)s, %(web_url)s)'\n cursor.execute(sql, lieBrand)\nex... | <|body_start_0|>
global rsonline_CONN
cursor = None
try:
cursor = rsonline_CONN.cursor(buffered=True, dictionary=True)
sql = 'insert into lie_brand(brand_name, brand_logo, brand_desc,site_url, web_url) values(%(brand_name)s,%(brand_logo)s,%(brand_desc)s,%(site_url)s, %(we... | LieBrand | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LieBrand:
def addLieBrand(cls, lieBrand):
"""method: addLieBrand params: lieBrand-type: LieBrand"""
<|body_0|>
def get_brand_id_by_brand_name(cls, brand_name):
"""method: get_brand_id_by_brand_name params: brand_name-type: str return: brand_id return-type: int"""
... | stack_v2_sparse_classes_75kplus_train_066933 | 18,849 | no_license | [
{
"docstring": "method: addLieBrand params: lieBrand-type: LieBrand",
"name": "addLieBrand",
"signature": "def addLieBrand(cls, lieBrand)"
},
{
"docstring": "method: get_brand_id_by_brand_name params: brand_name-type: str return: brand_id return-type: int",
"name": "get_brand_id_by_brand_nam... | 2 | stack_v2_sparse_classes_30k_train_042391 | Implement the Python class `LieBrand` described below.
Class description:
Implement the LieBrand class.
Method signatures and docstrings:
- def addLieBrand(cls, lieBrand): method: addLieBrand params: lieBrand-type: LieBrand
- def get_brand_id_by_brand_name(cls, brand_name): method: get_brand_id_by_brand_name params: ... | Implement the Python class `LieBrand` described below.
Class description:
Implement the LieBrand class.
Method signatures and docstrings:
- def addLieBrand(cls, lieBrand): method: addLieBrand params: lieBrand-type: LieBrand
- def get_brand_id_by_brand_name(cls, brand_name): method: get_brand_id_by_brand_name params: ... | 1e49a6e13ea4b11427f47999c13a609be9ae3ecf | <|skeleton|>
class LieBrand:
def addLieBrand(cls, lieBrand):
"""method: addLieBrand params: lieBrand-type: LieBrand"""
<|body_0|>
def get_brand_id_by_brand_name(cls, brand_name):
"""method: get_brand_id_by_brand_name params: brand_name-type: str return: brand_id return-type: int"""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class LieBrand:
def addLieBrand(cls, lieBrand):
"""method: addLieBrand params: lieBrand-type: LieBrand"""
global rsonline_CONN
cursor = None
try:
cursor = rsonline_CONN.cursor(buffered=True, dictionary=True)
sql = 'insert into lie_brand(brand_name, brand_logo,... | the_stack_v2_python_sparse | rsonline/server/db/rsonline/mysql_client.py | yunhao-qing/PythonScrapy | train | 0 | |
059bc78567a53d132a0850affd650fae82af9d97 | [
"if package:\n if not cls.load_module(package):\n return None\n if not mod_path.startswith('.'):\n mod_path = f'.{mod_path}'\nfull_path = resolve_name(mod_path, package)\nif full_path in sys.modules:\n return sys.modules[full_path]\nif '.' in mod_path:\n parent_mod_path, mod_name = mod_pat... | <|body_start_0|>
if package:
if not cls.load_module(package):
return None
if not mod_path.startswith('.'):
mod_path = f'.{mod_path}'
full_path = resolve_name(mod_path, package)
if full_path in sys.modules:
return sys.modules[ful... | Class used to load classes from modules dynamically. | ClassLoader | [
"LicenseRef-scancode-dco-1.1",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ClassLoader:
"""Class used to load classes from modules dynamically."""
def load_module(cls, mod_path: str, package: str=None) -> ModuleType:
"""Load a module by its absolute path. Args: mod_path: the absolute or relative module path package: the parent package to search for the modu... | stack_v2_sparse_classes_75kplus_train_066934 | 6,454 | permissive | [
{
"docstring": "Load a module by its absolute path. Args: mod_path: the absolute or relative module path package: the parent package to search for the module Returns: The resolved module or `None` if the module cannot be found Raises: ModuleLoadError: If there was an error loading the module",
"name": "load... | 4 | stack_v2_sparse_classes_30k_train_017157 | Implement the Python class `ClassLoader` described below.
Class description:
Class used to load classes from modules dynamically.
Method signatures and docstrings:
- def load_module(cls, mod_path: str, package: str=None) -> ModuleType: Load a module by its absolute path. Args: mod_path: the absolute or relative modul... | Implement the Python class `ClassLoader` described below.
Class description:
Class used to load classes from modules dynamically.
Method signatures and docstrings:
- def load_module(cls, mod_path: str, package: str=None) -> ModuleType: Load a module by its absolute path. Args: mod_path: the absolute or relative modul... | 39cac36d8937ce84a9307ce100aaefb8bc05ec04 | <|skeleton|>
class ClassLoader:
"""Class used to load classes from modules dynamically."""
def load_module(cls, mod_path: str, package: str=None) -> ModuleType:
"""Load a module by its absolute path. Args: mod_path: the absolute or relative module path package: the parent package to search for the modu... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ClassLoader:
"""Class used to load classes from modules dynamically."""
def load_module(cls, mod_path: str, package: str=None) -> ModuleType:
"""Load a module by its absolute path. Args: mod_path: the absolute or relative module path package: the parent package to search for the module Returns: T... | the_stack_v2_python_sparse | aries_cloudagent/utils/classloader.py | hyperledger/aries-cloudagent-python | train | 370 |
761f2361f030c896fb58b4cf4d8e99ad710b62a4 | [
"tmp = self.score_model.predict(x)\nif not pred is None:\n tmp = np.array([t[:, p:p + 1] for t, p in zip(tmp, pred)])\ntmp = [np.array([tmp[i][j] for j in range(tmp.shape[1]) if x[i][j] != 0]) for i in range(tmp.shape[0])]\nreturn tmp",
"assert self.score_model.output_shape == (None,) + self.orig.model.output_... | <|body_start_0|>
tmp = self.score_model.predict(x)
if not pred is None:
tmp = np.array([t[:, p:p + 1] for t, p in zip(tmp, pred)])
tmp = [np.array([tmp[i][j] for j in range(tmp.shape[1]) if x[i][j] != 0]) for i in range(tmp.shape[0])]
return tmp
<|end_body_0|>
<|body_start_1... | ScoreModel | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ScoreModel:
def score(self, x, pred):
"""Return relevance scores for x. pred: if none, return scores for all possible classes else, assume that pred is a list of target classes"""
<|body_0|>
def check(self):
"""Basic sanity check (e.g., output shapes ...)"""
... | stack_v2_sparse_classes_75kplus_train_066935 | 16,087 | no_license | [
{
"docstring": "Return relevance scores for x. pred: if none, return scores for all possible classes else, assume that pred is a list of target classes",
"name": "score",
"signature": "def score(self, x, pred)"
},
{
"docstring": "Basic sanity check (e.g., output shapes ...)",
"name": "check"... | 2 | stack_v2_sparse_classes_30k_train_012755 | Implement the Python class `ScoreModel` described below.
Class description:
Implement the ScoreModel class.
Method signatures and docstrings:
- def score(self, x, pred): Return relevance scores for x. pred: if none, return scores for all possible classes else, assume that pred is a list of target classes
- def check(... | Implement the Python class `ScoreModel` described below.
Class description:
Implement the ScoreModel class.
Method signatures and docstrings:
- def score(self, x, pred): Return relevance scores for x. pred: if none, return scores for all possible classes else, assume that pred is a list of target classes
- def check(... | 4f116264791a84655e2469cc274c0c7e0c478755 | <|skeleton|>
class ScoreModel:
def score(self, x, pred):
"""Return relevance scores for x. pred: if none, return scores for all possible classes else, assume that pred is a list of target classes"""
<|body_0|>
def check(self):
"""Basic sanity check (e.g., output shapes ...)"""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ScoreModel:
def score(self, x, pred):
"""Return relevance scores for x. pred: if none, return scores for all possible classes else, assume that pred is a list of target classes"""
tmp = self.score_model.predict(x)
if not pred is None:
tmp = np.array([t[:, p:p + 1] for t, p ... | the_stack_v2_python_sparse | HybridDocuments/SRC/explanation_methods.py | NPoe/neural-nlp-explanation-experiment | train | 14 | |
904d06c17a1b4784ca8c04cb77dea6b2a2998e80 | [
"def buildTree(nums, left, right):\n if left > right:\n return\n if left == right:\n root = Node(left, right)\n root.total = nums[left]\n return root\n mid = (left + right) // 2\n root = Node(left, right)\n root.left = buildTree(nums, left, mid)\n root.right = buildTree... | <|body_start_0|>
def buildTree(nums, left, right):
if left > right:
return
if left == right:
root = Node(left, right)
root.total = nums[left]
return root
mid = (left + right) // 2
root = Node(left, ri... | NumMatrix | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NumMatrix:
def __init__(self, matrix):
""":type matrix: List[List[int]]"""
<|body_0|>
def update(self, row, col, val):
""":type row: int :type col: int :type val: int :rtype: void"""
<|body_1|>
def sumRegion(self, row1, col1, row2, col2):
""":typ... | stack_v2_sparse_classes_75kplus_train_066936 | 2,584 | no_license | [
{
"docstring": ":type matrix: List[List[int]]",
"name": "__init__",
"signature": "def __init__(self, matrix)"
},
{
"docstring": ":type row: int :type col: int :type val: int :rtype: void",
"name": "update",
"signature": "def update(self, row, col, val)"
},
{
"docstring": ":type r... | 3 | stack_v2_sparse_classes_30k_train_051612 | Implement the Python class `NumMatrix` described below.
Class description:
Implement the NumMatrix class.
Method signatures and docstrings:
- def __init__(self, matrix): :type matrix: List[List[int]]
- def update(self, row, col, val): :type row: int :type col: int :type val: int :rtype: void
- def sumRegion(self, row... | Implement the Python class `NumMatrix` described below.
Class description:
Implement the NumMatrix class.
Method signatures and docstrings:
- def __init__(self, matrix): :type matrix: List[List[int]]
- def update(self, row, col, val): :type row: int :type col: int :type val: int :rtype: void
- def sumRegion(self, row... | 28219fbc5e2e96f59e9d2b9d1da18f05187898c8 | <|skeleton|>
class NumMatrix:
def __init__(self, matrix):
""":type matrix: List[List[int]]"""
<|body_0|>
def update(self, row, col, val):
""":type row: int :type col: int :type val: int :rtype: void"""
<|body_1|>
def sumRegion(self, row1, col1, row2, col2):
""":typ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class NumMatrix:
def __init__(self, matrix):
""":type matrix: List[List[int]]"""
def buildTree(nums, left, right):
if left > right:
return
if left == right:
root = Node(left, right)
root.total = nums[left]
return... | the_stack_v2_python_sparse | 2018/308-range-sum-query-2d.py | the-potato-man/lc | train | 0 | |
249e8426053c90f49b40b87972fdd531a8ef3597 | [
"ctrl = wx.TextCtrl(parent)\nself._bg = ctrl.GetBackgroundColour().GetRGB()\nbg = Color('red')\nbg.mix(Color.from_wxbgr(ctrl.GetBackgroundColour().GetRGBA()), 0.5, in_place=True)\nself._error_bg = wx.Colour(bg.to_wxbgr(alpha=False)).GetRGB()\nsuper().__init__(parent, *args, **kwargs)\nfont = ctrl.GetFont()\nself.Se... | <|body_start_0|>
ctrl = wx.TextCtrl(parent)
self._bg = ctrl.GetBackgroundColour().GetRGB()
bg = Color('red')
bg.mix(Color.from_wxbgr(ctrl.GetBackgroundColour().GetRGBA()), 0.5, in_place=True)
self._error_bg = wx.Colour(bg.to_wxbgr(alpha=False)).GetRGB()
super().__init__(p... | Time picker that we can force proper colors on. | TimePickerCtrl | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TimePickerCtrl:
"""Time picker that we can force proper colors on."""
def __init__(self, parent, *args, **kwargs):
"""Initialize. Create a temporary text control so we can get proper background and foreground colors."""
<|body_0|>
def on_color_change(self, event):
... | stack_v2_sparse_classes_75kplus_train_066937 | 2,245 | permissive | [
{
"docstring": "Initialize. Create a temporary text control so we can get proper background and foreground colors.",
"name": "__init__",
"signature": "def __init__(self, parent, *args, **kwargs)"
},
{
"docstring": "Handle color change.",
"name": "on_color_change",
"signature": "def on_co... | 4 | stack_v2_sparse_classes_30k_train_025571 | Implement the Python class `TimePickerCtrl` described below.
Class description:
Time picker that we can force proper colors on.
Method signatures and docstrings:
- def __init__(self, parent, *args, **kwargs): Initialize. Create a temporary text control so we can get proper background and foreground colors.
- def on_c... | Implement the Python class `TimePickerCtrl` described below.
Class description:
Time picker that we can force proper colors on.
Method signatures and docstrings:
- def __init__(self, parent, *args, **kwargs): Initialize. Create a temporary text control so we can get proper background and foreground colors.
- def on_c... | 95129ca054384a4c59a4effdb3fe32a7a66af6ff | <|skeleton|>
class TimePickerCtrl:
"""Time picker that we can force proper colors on."""
def __init__(self, parent, *args, **kwargs):
"""Initialize. Create a temporary text control so we can get proper background and foreground colors."""
<|body_0|>
def on_color_change(self, event):
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TimePickerCtrl:
"""Time picker that we can force proper colors on."""
def __init__(self, parent, *args, **kwargs):
"""Initialize. Create a temporary text control so we can get proper background and foreground colors."""
ctrl = wx.TextCtrl(parent)
self._bg = ctrl.GetBackgroundColou... | the_stack_v2_python_sparse | rummage/lib/gui/controls/time_picker.py | facelessuser/Rummage | train | 70 |
940509c4b44b76042893e9e9e08161c547052fab | [
"if kwargs.get('username') is None:\n kwargs['username'] = git.GetProjectUserEmail(os.path.dirname(__file__))\nif kwargs.get('host') is None:\n kwargs['host'] = cros_build_lib.GetHostName(fully_qualified=True)\nfor attr in ('cmd_args', 'cmd_base', 'cmd_line'):\n val = kwargs.get(attr)\n if isinstance(va... | <|body_start_0|>
if kwargs.get('username') is None:
kwargs['username'] = git.GetProjectUserEmail(os.path.dirname(__file__))
if kwargs.get('host') is None:
kwargs['host'] = cros_build_lib.GetHostName(fully_qualified=True)
for attr in ('cmd_args', 'cmd_base', 'cmd_line'):
... | Entity object for a stats entry. | Stats | [
"BSD-3-Clause",
"LicenseRef-scancode-unknown-license-reference",
"LGPL-2.0-or-later",
"GPL-1.0-or-later",
"MIT",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Stats:
"""Entity object for a stats entry."""
def __init__(self, **kwargs):
"""Initialize the record. **kwargs keys need to correspond to elements in __slots__. These arguments can be lists: - cmd_args - cmd_base - cmd_line If unset, the |username| and |host| attributes will be deter... | stack_v2_sparse_classes_75kplus_train_066938 | 6,553 | permissive | [
{
"docstring": "Initialize the record. **kwargs keys need to correspond to elements in __slots__. These arguments can be lists: - cmd_args - cmd_base - cmd_line If unset, the |username| and |host| attributes will be determined automatically.",
"name": "__init__",
"signature": "def __init__(self, **kwarg... | 3 | stack_v2_sparse_classes_30k_train_037010 | Implement the Python class `Stats` described below.
Class description:
Entity object for a stats entry.
Method signatures and docstrings:
- def __init__(self, **kwargs): Initialize the record. **kwargs keys need to correspond to elements in __slots__. These arguments can be lists: - cmd_args - cmd_base - cmd_line If ... | Implement the Python class `Stats` described below.
Class description:
Entity object for a stats entry.
Method signatures and docstrings:
- def __init__(self, **kwargs): Initialize the record. **kwargs keys need to correspond to elements in __slots__. These arguments can be lists: - cmd_args - cmd_base - cmd_line If ... | 72a05af97787001756bae2511b7985e61498c965 | <|skeleton|>
class Stats:
"""Entity object for a stats entry."""
def __init__(self, **kwargs):
"""Initialize the record. **kwargs keys need to correspond to elements in __slots__. These arguments can be lists: - cmd_args - cmd_base - cmd_line If unset, the |username| and |host| attributes will be deter... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Stats:
"""Entity object for a stats entry."""
def __init__(self, **kwargs):
"""Initialize the record. **kwargs keys need to correspond to elements in __slots__. These arguments can be lists: - cmd_args - cmd_base - cmd_line If unset, the |username| and |host| attributes will be determined automat... | the_stack_v2_python_sparse | third_party/chromite/lib/stats.py | metux/chromium-suckless | train | 5 |
949909c103bfbcd9b9b0f1250e66cc2695491108 | [
"if RedisPool.__pool == None:\n RedisPool()\nreturn RedisPool.__pool",
"if RedisPool.__pool != None:\n logger.info('Using redis pool singleton')\nelse:\n try:\n RedisPool.__pool = redis.ConnectionPool(host=REDIS_HOST, port=int(REDIS_PORT), db=0, decode_responses=True)\n except Exception as e:\n... | <|body_start_0|>
if RedisPool.__pool == None:
RedisPool()
return RedisPool.__pool
<|end_body_0|>
<|body_start_1|>
if RedisPool.__pool != None:
logger.info('Using redis pool singleton')
else:
try:
RedisPool.__pool = redis.ConnectionPool... | RedisPool | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RedisPool:
def getPool():
"""Static access method."""
<|body_0|>
def __init__(self):
"""Virtually private constructor."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if RedisPool.__pool == None:
RedisPool()
return RedisPool.__po... | stack_v2_sparse_classes_75kplus_train_066939 | 2,420 | permissive | [
{
"docstring": "Static access method.",
"name": "getPool",
"signature": "def getPool()"
},
{
"docstring": "Virtually private constructor.",
"name": "__init__",
"signature": "def __init__(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_037098 | Implement the Python class `RedisPool` described below.
Class description:
Implement the RedisPool class.
Method signatures and docstrings:
- def getPool(): Static access method.
- def __init__(self): Virtually private constructor. | Implement the Python class `RedisPool` described below.
Class description:
Implement the RedisPool class.
Method signatures and docstrings:
- def getPool(): Static access method.
- def __init__(self): Virtually private constructor.
<|skeleton|>
class RedisPool:
def getPool():
"""Static access method."""... | 7da0de453163130e116611f0ed750414d6d5c107 | <|skeleton|>
class RedisPool:
def getPool():
"""Static access method."""
<|body_0|>
def __init__(self):
"""Virtually private constructor."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class RedisPool:
def getPool():
"""Static access method."""
if RedisPool.__pool == None:
RedisPool()
return RedisPool.__pool
def __init__(self):
"""Virtually private constructor."""
if RedisPool.__pool != None:
logger.info('Using redis pool single... | the_stack_v2_python_sparse | gamechangerml/api/utils/redisdriver.py | iamjoshbinder/gamechanger-ml | train | 0 | |
cc15e2111cd96a422debe0d6bf491ae7cdd6723a | [
"self.x = kwargs.get('x')\nself.y = kwargs.get('y')\nself.z = kwargs.get('z')",
"self.x = kwargs['x']\nself.y = kwargs['y']\nself.z = kwargs['z']",
"ret = {}\nret['x'] = sockutil.dump(self.x)\nret['y'] = sockutil.dump(self.y)\nret['z'] = sockutil.dump(self.z)\nreturn ret"
] | <|body_start_0|>
self.x = kwargs.get('x')
self.y = kwargs.get('y')
self.z = kwargs.get('z')
<|end_body_0|>
<|body_start_1|>
self.x = kwargs['x']
self.y = kwargs['y']
self.z = kwargs['z']
<|end_body_1|>
<|body_start_2|>
ret = {}
ret['x'] = sockutil.dump(s... | Vector3 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Vector3:
def __init__(self, **kwargs):
"""Params: x: float y: float z: float"""
<|body_0|>
def load(self, **kwargs):
"""load from dict Exception: KeyError"""
<|body_1|>
def dump(self):
"""dump -> dict"""
<|body_2|>
<|end_skeleton|>
<|bo... | stack_v2_sparse_classes_75kplus_train_066940 | 26,590 | no_license | [
{
"docstring": "Params: x: float y: float z: float",
"name": "__init__",
"signature": "def __init__(self, **kwargs)"
},
{
"docstring": "load from dict Exception: KeyError",
"name": "load",
"signature": "def load(self, **kwargs)"
},
{
"docstring": "dump -> dict",
"name": "dump... | 3 | stack_v2_sparse_classes_30k_train_009414 | Implement the Python class `Vector3` described below.
Class description:
Implement the Vector3 class.
Method signatures and docstrings:
- def __init__(self, **kwargs): Params: x: float y: float z: float
- def load(self, **kwargs): load from dict Exception: KeyError
- def dump(self): dump -> dict | Implement the Python class `Vector3` described below.
Class description:
Implement the Vector3 class.
Method signatures and docstrings:
- def __init__(self, **kwargs): Params: x: float y: float z: float
- def load(self, **kwargs): load from dict Exception: KeyError
- def dump(self): dump -> dict
<|skeleton|>
class V... | aa0b2697e295889e8c23a7104889ea95f2a4b6b1 | <|skeleton|>
class Vector3:
def __init__(self, **kwargs):
"""Params: x: float y: float z: float"""
<|body_0|>
def load(self, **kwargs):
"""load from dict Exception: KeyError"""
<|body_1|>
def dump(self):
"""dump -> dict"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Vector3:
def __init__(self, **kwargs):
"""Params: x: float y: float z: float"""
self.x = kwargs.get('x')
self.y = kwargs.get('y')
self.z = kwargs.get('z')
def load(self, **kwargs):
"""load from dict Exception: KeyError"""
self.x = kwargs['x']
self.y... | the_stack_v2_python_sparse | message.py | songhui17/Server | train | 0 | |
82bb39dbb7391161dd61f37312a2e56b4923b0f9 | [
"is_cloud_admin = self.helper.is_user_cloud_admin()\napps_user_is_admin_on = self.helper.get_owned_apps()\napp_name = self.request.get('appid')\nif not is_cloud_admin and app_name not in apps_user_is_admin_on:\n response = json.dumps({'error': True, 'message': 'Not authorized'})\n self.response.out.write(resp... | <|body_start_0|>
is_cloud_admin = self.helper.is_user_cloud_admin()
apps_user_is_admin_on = self.helper.get_owned_apps()
app_name = self.request.get('appid')
if not is_cloud_admin and app_name not in apps_user_is_admin_on:
response = json.dumps({'error': True, 'message': 'Not... | Class that returns instance statistics in JSON relating to the number of AppServer processes running for a particular App Engine application. | InstanceStats | [
"Apache-2.0",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InstanceStats:
"""Class that returns instance statistics in JSON relating to the number of AppServer processes running for a particular App Engine application."""
def get(self):
"""Makes sure the user is allowed to see instance data for the named application, and if so, retrieves it ... | stack_v2_sparse_classes_75kplus_train_066941 | 37,207 | permissive | [
{
"docstring": "Makes sure the user is allowed to see instance data for the named application, and if so, retrieves it for them.",
"name": "get",
"signature": "def get(self)"
},
{
"docstring": "Adds information about one or more instances to the Datastore, for later viewing.",
"name": "post"... | 4 | stack_v2_sparse_classes_30k_train_051257 | Implement the Python class `InstanceStats` described below.
Class description:
Class that returns instance statistics in JSON relating to the number of AppServer processes running for a particular App Engine application.
Method signatures and docstrings:
- def get(self): Makes sure the user is allowed to see instance... | Implement the Python class `InstanceStats` described below.
Class description:
Class that returns instance statistics in JSON relating to the number of AppServer processes running for a particular App Engine application.
Method signatures and docstrings:
- def get(self): Makes sure the user is allowed to see instance... | aa36e8dfaa295d53bec616ed07f91ec8c02fa4e1 | <|skeleton|>
class InstanceStats:
"""Class that returns instance statistics in JSON relating to the number of AppServer processes running for a particular App Engine application."""
def get(self):
"""Makes sure the user is allowed to see instance data for the named application, and if so, retrieves it ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class InstanceStats:
"""Class that returns instance statistics in JSON relating to the number of AppServer processes running for a particular App Engine application."""
def get(self):
"""Makes sure the user is allowed to see instance data for the named application, and if so, retrieves it for them."""
... | the_stack_v2_python_sparse | AppDashboard/dashboard.py | shatterednirvana/appscale | train | 6 |
c5aebebcdb80e7bb2c9bfc9455db58b8cb505858 | [
"self.name = 'Alien Invasion'\nself.screen_width = 1200\nself.screen_height = 800\nself.bg_color = (230, 230, 230)\nself.ship_limit = 3\nself.bullet_width = 10\nself.bullet_height = 15\nself.bullet_color = (60, 60, 60)\nself.bullet_allowed = 10\nself.fleet_drop_speed = 20.0\nself.speedup_scale = 1.1\nself.score_sca... | <|body_start_0|>
self.name = 'Alien Invasion'
self.screen_width = 1200
self.screen_height = 800
self.bg_color = (230, 230, 230)
self.ship_limit = 3
self.bullet_width = 10
self.bullet_height = 15
self.bullet_color = (60, 60, 60)
self.bullet_allowed ... | 存储《外星人入侵》所有设置的类 | Settings | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Settings:
"""存储《外星人入侵》所有设置的类"""
def __init__(self):
"""初始化游戏设置"""
<|body_0|>
def initialize_dyanmic_settings(self):
"""初始化随游戏进行而变化的设置"""
<|body_1|>
def increase_speed(self):
"""提高速度设置和外星人点数"""
<|body_2|>
<|end_skeleton|>
<|body_star... | stack_v2_sparse_classes_75kplus_train_066942 | 1,683 | no_license | [
{
"docstring": "初始化游戏设置",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "初始化随游戏进行而变化的设置",
"name": "initialize_dyanmic_settings",
"signature": "def initialize_dyanmic_settings(self)"
},
{
"docstring": "提高速度设置和外星人点数",
"name": "increase_speed",
"sig... | 3 | stack_v2_sparse_classes_30k_train_051296 | Implement the Python class `Settings` described below.
Class description:
存储《外星人入侵》所有设置的类
Method signatures and docstrings:
- def __init__(self): 初始化游戏设置
- def initialize_dyanmic_settings(self): 初始化随游戏进行而变化的设置
- def increase_speed(self): 提高速度设置和外星人点数 | Implement the Python class `Settings` described below.
Class description:
存储《外星人入侵》所有设置的类
Method signatures and docstrings:
- def __init__(self): 初始化游戏设置
- def initialize_dyanmic_settings(self): 初始化随游戏进行而变化的设置
- def increase_speed(self): 提高速度设置和外星人点数
<|skeleton|>
class Settings:
"""存储《外星人入侵》所有设置的类"""
def __... | 11145f9fe4d9b0d5a9cb351c75dd673004b8f30d | <|skeleton|>
class Settings:
"""存储《外星人入侵》所有设置的类"""
def __init__(self):
"""初始化游戏设置"""
<|body_0|>
def initialize_dyanmic_settings(self):
"""初始化随游戏进行而变化的设置"""
<|body_1|>
def increase_speed(self):
"""提高速度设置和外星人点数"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Settings:
"""存储《外星人入侵》所有设置的类"""
def __init__(self):
"""初始化游戏设置"""
self.name = 'Alien Invasion'
self.screen_width = 1200
self.screen_height = 800
self.bg_color = (230, 230, 230)
self.ship_limit = 3
self.bullet_width = 10
self.bullet_height = ... | the_stack_v2_python_sparse | alien_invasion/settings.py | shijiegong123/myPythonProject | train | 0 |
a6a81615763395e47f8090e701dc97339f80e756 | [
"if data.ndim != 2:\n print('Data must be a 2d array')\n return None\nn, m = data.shape\nself.num = n\nself.semean = [np.mean(data[:, i]) for i in range(m)]\nself.semedian = [np.median(data[:, i]) for i in range(m)]\nself.lowerquart = np.zeros(m)\nself.upperquart = np.zeros(m)\nfor i in range(m):\n dum = n... | <|body_start_0|>
if data.ndim != 2:
print('Data must be a 2d array')
return None
n, m = data.shape
self.num = n
self.semean = [np.mean(data[:, i]) for i in range(m)]
self.semedian = [np.median(data[:, i]) for i in range(m)]
self.lowerquart = np.zer... | Class to conduct a superposed epoch analysis on dataset returning the mean,median, and quartile information | sea | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class sea:
"""Class to conduct a superposed epoch analysis on dataset returning the mean,median, and quartile information"""
def __init__(self, data):
"""User provides a (n,m) data array with n being the number of epochs and m being the length of the analysis window Returns the mean,median... | stack_v2_sparse_classes_75kplus_train_066943 | 1,538 | no_license | [
{
"docstring": "User provides a (n,m) data array with n being the number of epochs and m being the length of the analysis window Returns the mean,median, lower quartile, and upper quartile as numpy arrays of size m",
"name": "__init__",
"signature": "def __init__(self, data)"
},
{
"docstring": "... | 2 | null | Implement the Python class `sea` described below.
Class description:
Class to conduct a superposed epoch analysis on dataset returning the mean,median, and quartile information
Method signatures and docstrings:
- def __init__(self, data): User provides a (n,m) data array with n being the number of epochs and m being ... | Implement the Python class `sea` described below.
Class description:
Class to conduct a superposed epoch analysis on dataset returning the mean,median, and quartile information
Method signatures and docstrings:
- def __init__(self, data): User provides a (n,m) data array with n being the number of epochs and m being ... | bb00b8292bf5f3e191cb48b981c25453a3615b65 | <|skeleton|>
class sea:
"""Class to conduct a superposed epoch analysis on dataset returning the mean,median, and quartile information"""
def __init__(self, data):
"""User provides a (n,m) data array with n being the number of epochs and m being the length of the analysis window Returns the mean,median... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class sea:
"""Class to conduct a superposed epoch analysis on dataset returning the mean,median, and quartile information"""
def __init__(self, data):
"""User provides a (n,m) data array with n being the number of epochs and m being the length of the analysis window Returns the mean,median, lower quart... | the_stack_v2_python_sparse | pyLTR/Tools/sea.py | erigler-usgs/pyLTR | train | 0 |
ad6a05892e617584bcbda7ad6b4e46120f97f57a | [
"n = len(nums)\ndp = [[[]] for _ in range(n + 1)]\nfor i in range(1, n + 1):\n dp[i] = dp[i - 1] + [x + [nums[i - 1]] for x in dp[i - 1]]\nreturn dp[-1]",
"res = [[]]\nfor i in nums:\n res += [t + [i] for t in res]\nreturn res"
] | <|body_start_0|>
n = len(nums)
dp = [[[]] for _ in range(n + 1)]
for i in range(1, n + 1):
dp[i] = dp[i - 1] + [x + [nums[i - 1]] for x in dp[i - 1]]
return dp[-1]
<|end_body_0|>
<|body_start_1|>
res = [[]]
for i in nums:
res += [t + [i] for t in ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def subsets(self, nums):
"""从前往后遍历,遇到一个数则就把上一个的所有子集 加上该数组成新的子集 [1]的子集: [[],[1]] [1,2]的子集: [[],[1]] + [[]+[2],[1]+[2]] dp[i] 前i个数的所有子集 :param nums: :return:"""
<|body_0|>
def subsets2(self, nums):
"""节省空间 dp[i]只与dp[i-1]有关 所以只需要记录最后一个res就行了"""
<|body_... | stack_v2_sparse_classes_75kplus_train_066944 | 1,185 | no_license | [
{
"docstring": "从前往后遍历,遇到一个数则就把上一个的所有子集 加上该数组成新的子集 [1]的子集: [[],[1]] [1,2]的子集: [[],[1]] + [[]+[2],[1]+[2]] dp[i] 前i个数的所有子集 :param nums: :return:",
"name": "subsets",
"signature": "def subsets(self, nums)"
},
{
"docstring": "节省空间 dp[i]只与dp[i-1]有关 所以只需要记录最后一个res就行了",
"name": "subsets2",
"si... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def subsets(self, nums): 从前往后遍历,遇到一个数则就把上一个的所有子集 加上该数组成新的子集 [1]的子集: [[],[1]] [1,2]的子集: [[],[1]] + [[]+[2],[1]+[2]] dp[i] 前i个数的所有子集 :param nums: :return:
- def subsets2(self, nums... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def subsets(self, nums): 从前往后遍历,遇到一个数则就把上一个的所有子集 加上该数组成新的子集 [1]的子集: [[],[1]] [1,2]的子集: [[],[1]] + [[]+[2],[1]+[2]] dp[i] 前i个数的所有子集 :param nums: :return:
- def subsets2(self, nums... | 5d3574ccd282d0146c83c286ae28d8baaabd4910 | <|skeleton|>
class Solution:
def subsets(self, nums):
"""从前往后遍历,遇到一个数则就把上一个的所有子集 加上该数组成新的子集 [1]的子集: [[],[1]] [1,2]的子集: [[],[1]] + [[]+[2],[1]+[2]] dp[i] 前i个数的所有子集 :param nums: :return:"""
<|body_0|>
def subsets2(self, nums):
"""节省空间 dp[i]只与dp[i-1]有关 所以只需要记录最后一个res就行了"""
<|body_... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def subsets(self, nums):
"""从前往后遍历,遇到一个数则就把上一个的所有子集 加上该数组成新的子集 [1]的子集: [[],[1]] [1,2]的子集: [[],[1]] + [[]+[2],[1]+[2]] dp[i] 前i个数的所有子集 :param nums: :return:"""
n = len(nums)
dp = [[[]] for _ in range(n + 1)]
for i in range(1, n + 1):
dp[i] = dp[i - 1] + [x ... | the_stack_v2_python_sparse | 78_子集.py | lovehhf/LeetCode | train | 0 | |
e767234d860b04d844ab98d7e41aa068f97f0efb | [
"if dispatch in self.poll_answers and (not self.voted):\n temp_poll_answers = self.poll_answers\n temp_poll_answers[dispatch] += 1\n self.poll_answers = temp_poll_answers\n self.voted = True\n self.poll_answer = dispatch\n return json.dumps({'poll_answers': self.poll_answers, 'total': sum(self.pol... | <|body_start_0|>
if dispatch in self.poll_answers and (not self.voted):
temp_poll_answers = self.poll_answers
temp_poll_answers[dispatch] += 1
self.poll_answers = temp_poll_answers
self.voted = True
self.poll_answer = dispatch
return json.d... | Poll Module | PollBlock | [
"AGPL-3.0-only",
"AGPL-3.0-or-later",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PollBlock:
"""Poll Module"""
def handle_ajax(self, dispatch, data):
"""Ajax handler. Args: dispatch: string request slug data: dict request data parameters Returns: json string"""
<|body_0|>
def student_view(self, _context):
"""Renders the student view."""
... | stack_v2_sparse_classes_75kplus_train_066945 | 9,113 | permissive | [
{
"docstring": "Ajax handler. Args: dispatch: string request slug data: dict request data parameters Returns: json string",
"name": "handle_ajax",
"signature": "def handle_ajax(self, dispatch, data)"
},
{
"docstring": "Renders the student view.",
"name": "student_view",
"signature": "def... | 5 | stack_v2_sparse_classes_30k_val_000605 | Implement the Python class `PollBlock` described below.
Class description:
Poll Module
Method signatures and docstrings:
- def handle_ajax(self, dispatch, data): Ajax handler. Args: dispatch: string request slug data: dict request data parameters Returns: json string
- def student_view(self, _context): Renders the st... | Implement the Python class `PollBlock` described below.
Class description:
Poll Module
Method signatures and docstrings:
- def handle_ajax(self, dispatch, data): Ajax handler. Args: dispatch: string request slug data: dict request data parameters Returns: json string
- def student_view(self, _context): Renders the st... | 5809eaca7079a15ee56b0b7fcfea425337046c97 | <|skeleton|>
class PollBlock:
"""Poll Module"""
def handle_ajax(self, dispatch, data):
"""Ajax handler. Args: dispatch: string request slug data: dict request data parameters Returns: json string"""
<|body_0|>
def student_view(self, _context):
"""Renders the student view."""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PollBlock:
"""Poll Module"""
def handle_ajax(self, dispatch, data):
"""Ajax handler. Args: dispatch: string request slug data: dict request data parameters Returns: json string"""
if dispatch in self.poll_answers and (not self.voted):
temp_poll_answers = self.poll_answers
... | the_stack_v2_python_sparse | Part-03-Understanding-Software-Crafting-Your-Own-Tools/models/edx-platform/common/lib/xmodule/xmodule/poll_module.py | luque/better-ways-of-thinking-about-software | train | 3 |
cc4a92e6c57e061dde4c4601695171de66c6e4dc | [
"ratio_product = 1\nfor i in ratio:\n ratio_product *= i\naddress_space_size = int(math.log(ratio_product, 2))\nword_size = Vector(*word_size)\nsuper(MemoryAccessUnit, self).__init__(address_space_size)\nself.input_address = self.add_input(input_address)\nself.ratio = Vector(*ratio)\nself.word_size = word_size\n... | <|body_start_0|>
ratio_product = 1
for i in ratio:
ratio_product *= i
address_space_size = int(math.log(ratio_product, 2))
word_size = Vector(*word_size)
super(MemoryAccessUnit, self).__init__(address_space_size)
self.input_address = self.add_input(input_addre... | This unit provides basic functionality for accessing memory and preforming some user-defined action. See example of use in the ReadUnit. | MemoryAccessUnit | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MemoryAccessUnit:
"""This unit provides basic functionality for accessing memory and preforming some user-defined action. See example of use in the ReadUnit."""
def __init__(self, ratio=(1, 16, 16), word_size=(8, 1, 1), raw_memory=None, input_address=std_logic.InputRegister):
""":par... | stack_v2_sparse_classes_75kplus_train_066946 | 6,650 | no_license | [
{
"docstring": ":param ratio: The ration of words distributed in 3D space. :param word_size: the size of a word. by default it is a 8 bits facing east. :param raw_memory: This is the actual \"raw\" memory on which this access unit is operating. If no is specified, Memory block will be generated from the ratios ... | 2 | stack_v2_sparse_classes_30k_train_044225 | Implement the Python class `MemoryAccessUnit` described below.
Class description:
This unit provides basic functionality for accessing memory and preforming some user-defined action. See example of use in the ReadUnit.
Method signatures and docstrings:
- def __init__(self, ratio=(1, 16, 16), word_size=(8, 1, 1), raw_... | Implement the Python class `MemoryAccessUnit` described below.
Class description:
This unit provides basic functionality for accessing memory and preforming some user-defined action. See example of use in the ReadUnit.
Method signatures and docstrings:
- def __init__(self, ratio=(1, 16, 16), word_size=(8, 1, 1), raw_... | 8bbb26b2c3bbaa0712b5321d85b9f3834a0016fb | <|skeleton|>
class MemoryAccessUnit:
"""This unit provides basic functionality for accessing memory and preforming some user-defined action. See example of use in the ReadUnit."""
def __init__(self, ratio=(1, 16, 16), word_size=(8, 1, 1), raw_memory=None, input_address=std_logic.InputRegister):
""":par... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MemoryAccessUnit:
"""This unit provides basic functionality for accessing memory and preforming some user-defined action. See example of use in the ReadUnit."""
def __init__(self, ratio=(1, 16, 16), word_size=(8, 1, 1), raw_memory=None, input_address=std_logic.InputRegister):
""":param ratio: The... | the_stack_v2_python_sparse | cbac/std_unit/ram_unit.py | bowiz2/cbac | train | 1 |
97c8f9bf93a7fb14a83ce34d692cfce38d97cca4 | [
"self.entry_id = entry_id\nself.entry_markers = entry_markers\nself._idgen = IDGenerator('LX')\nself._idset = set()\nself.entries = sfm.SFM()",
"new_entry, rest = split_by_pred(lambda pair: pair[0] in self.entry_markers, entry, constructor=sfm.Entry)\nif not new_entry:\n return False\noriginal_id = entry.get(s... | <|body_start_0|>
self.entry_id = entry_id
self.entry_markers = entry_markers
self._idgen = IDGenerator('LX')
self._idset = set()
self.entries = sfm.SFM()
<|end_body_0|>
<|body_start_1|>
new_entry, rest = split_by_pred(lambda pair: pair[0] in self.entry_markers, entry, co... | Visitor for extracting Entry information from an SFM entry. | EntryExtractor | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EntryExtractor:
"""Visitor for extracting Entry information from an SFM entry."""
def __init__(self, entry_id, entry_markers):
"""Create an entry extractor. :arg entry_id: marker, which contains the entry's original ID :arg entry_markers: collection of markers, which make up an entry... | stack_v2_sparse_classes_75kplus_train_066947 | 44,273 | permissive | [
{
"docstring": "Create an entry extractor. :arg entry_id: marker, which contains the entry's original ID :arg entry_markers: collection of markers, which make up an entry (as opposed to a sense or an example)",
"name": "__init__",
"signature": "def __init__(self, entry_id, entry_markers)"
},
{
"... | 2 | stack_v2_sparse_classes_30k_train_051417 | Implement the Python class `EntryExtractor` described below.
Class description:
Visitor for extracting Entry information from an SFM entry.
Method signatures and docstrings:
- def __init__(self, entry_id, entry_markers): Create an entry extractor. :arg entry_id: marker, which contains the entry's original ID :arg ent... | Implement the Python class `EntryExtractor` described below.
Class description:
Visitor for extracting Entry information from an SFM entry.
Method signatures and docstrings:
- def __init__(self, entry_id, entry_markers): Create an entry extractor. :arg entry_id: marker, which contains the entry's original ID :arg ent... | 9fcb35608ab7ce0df3f02a88aba893ce3920e48a | <|skeleton|>
class EntryExtractor:
"""Visitor for extracting Entry information from an SFM entry."""
def __init__(self, entry_id, entry_markers):
"""Create an entry extractor. :arg entry_id: marker, which contains the entry's original ID :arg entry_markers: collection of markers, which make up an entry... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class EntryExtractor:
"""Visitor for extracting Entry information from an SFM entry."""
def __init__(self, entry_id, entry_markers):
"""Create an entry extractor. :arg entry_id: marker, which contains the entry's original ID :arg entry_markers: collection of markers, which make up an entry (as opposed ... | the_stack_v2_python_sparse | src/pydictionaria/sfm2cldf.py | dictionaria/pydictionaria | train | 1 |
9dd7e373e2490f0bffea69098130256586d35efb | [
"assert type(var_scope) == str\nassert type(config) == dict\nassert X.shape == (config['n_batches'], config['n_input'])\nwith tf.variable_scope(var_scope):\n W = tf.get_variable('W', shape=(config['n_input'], config['n_classes']))\n b = tf.get_variable('bias', shape=config['n_classes'])\n prediction = tf.n... | <|body_start_0|>
assert type(var_scope) == str
assert type(config) == dict
assert X.shape == (config['n_batches'], config['n_input'])
with tf.variable_scope(var_scope):
W = tf.get_variable('W', shape=(config['n_input'], config['n_classes']))
b = tf.get_variable('b... | Standard TF components. | StandardLayers | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StandardLayers:
"""Standard TF components."""
def _prediction_layer(self, X, var_scope, config):
"""Predicts end result Args: - X: input data of shape (batch, features) - var_scope: string name of tf variable scope. - config { 'n_batches': number of batches, 'n_input': number of inpu... | stack_v2_sparse_classes_75kplus_train_066948 | 4,722 | permissive | [
{
"docstring": "Predicts end result Args: - X: input data of shape (batch, features) - var_scope: string name of tf variable scope. - config { 'n_batches': number of batches, 'n_input': number of input features, 'n_classes': number of potential output classes }",
"name": "_prediction_layer",
"signature"... | 4 | stack_v2_sparse_classes_30k_train_002826 | Implement the Python class `StandardLayers` described below.
Class description:
Standard TF components.
Method signatures and docstrings:
- def _prediction_layer(self, X, var_scope, config): Predicts end result Args: - X: input data of shape (batch, features) - var_scope: string name of tf variable scope. - config { ... | Implement the Python class `StandardLayers` described below.
Class description:
Standard TF components.
Method signatures and docstrings:
- def _prediction_layer(self, X, var_scope, config): Predicts end result Args: - X: input data of shape (batch, features) - var_scope: string name of tf variable scope. - config { ... | 6bf608d61722d86e8fab4087b2e725df1cd236ab | <|skeleton|>
class StandardLayers:
"""Standard TF components."""
def _prediction_layer(self, X, var_scope, config):
"""Predicts end result Args: - X: input data of shape (batch, features) - var_scope: string name of tf variable scope. - config { 'n_batches': number of batches, 'n_input': number of inpu... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class StandardLayers:
"""Standard TF components."""
def _prediction_layer(self, X, var_scope, config):
"""Predicts end result Args: - X: input data of shape (batch, features) - var_scope: string name of tf variable scope. - config { 'n_batches': number of batches, 'n_input': number of input features, '... | the_stack_v2_python_sparse | NetDetect/src/model_base/standard_layers.py | joaoceron/NetDetect | train | 0 |
a0a268d7fedd1574c3913652b0e3749cbf222223 | [
"test_dictionary = {'donor': 'ME', 'amount': round(float(100), 2)}\nexpected = '\\nDear ME,\\n\\nThank you for your generous donation of $100.00\\n\\nSincerely,\\nThe Charity\\n'\nactual = mailroom4.letter(test_dictionary)\nself.assertEqual(expected, actual)",
"expected = [['William Gates, III', '$', 653784.49, 2... | <|body_start_0|>
test_dictionary = {'donor': 'ME', 'amount': round(float(100), 2)}
expected = '\nDear ME,\n\nThank you for your generous donation of $100.00\n\nSincerely,\nThe Charity\n'
actual = mailroom4.letter(test_dictionary)
self.assertEqual(expected, actual)
<|end_body_0|>
<|body_... | Write a class containing a full suite of tests | TestMailroom | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestMailroom:
"""Write a class containing a full suite of tests"""
def test_letter(self):
"""Test letter output"""
<|body_0|>
def test_calculation(self):
"""Test average and donation count calculations"""
<|body_1|>
def test_table(self):
"""T... | stack_v2_sparse_classes_75kplus_train_066949 | 2,174 | no_license | [
{
"docstring": "Test letter output",
"name": "test_letter",
"signature": "def test_letter(self)"
},
{
"docstring": "Test average and donation count calculations",
"name": "test_calculation",
"signature": "def test_calculation(self)"
},
{
"docstring": "Test table output format",
... | 4 | stack_v2_sparse_classes_30k_train_020865 | Implement the Python class `TestMailroom` described below.
Class description:
Write a class containing a full suite of tests
Method signatures and docstrings:
- def test_letter(self): Test letter output
- def test_calculation(self): Test average and donation count calculations
- def test_table(self): Test table outpu... | Implement the Python class `TestMailroom` described below.
Class description:
Write a class containing a full suite of tests
Method signatures and docstrings:
- def test_letter(self): Test letter output
- def test_calculation(self): Test average and donation count calculations
- def test_table(self): Test table outpu... | e298b1151dab639659d8dfa56f47bcb43dd3438f | <|skeleton|>
class TestMailroom:
"""Write a class containing a full suite of tests"""
def test_letter(self):
"""Test letter output"""
<|body_0|>
def test_calculation(self):
"""Test average and donation count calculations"""
<|body_1|>
def test_table(self):
"""T... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TestMailroom:
"""Write a class containing a full suite of tests"""
def test_letter(self):
"""Test letter output"""
test_dictionary = {'donor': 'ME', 'amount': round(float(100), 2)}
expected = '\nDear ME,\n\nThank you for your generous donation of $100.00\n\nSincerely,\nThe Charity... | the_stack_v2_python_sparse | students/Daniel_Spray/Lesson06/test_mailroom4.py | UWPCE-PythonCert-ClassRepos/Self_Paced-Online | train | 13 |
63be88ee34c7a7c99cee6fb3528d4ecf9bfd7578 | [
"self._with_bkg_par = bool(with_bkg_par)\nself._t_start = float(t_start)\nself._exposure = float(exposure)\nself._seed = int(seed)\nself._simput = simput\nself._data_dir = data_dir\nself._ra_cen = ra_cen\nself._dec_cen = dec_cen",
"try:\n os.makedirs(self._data_dir)\nexcept OSError as e:\n print('already ex... | <|body_start_0|>
self._with_bkg_par = bool(with_bkg_par)
self._t_start = float(t_start)
self._exposure = float(exposure)
self._seed = int(seed)
self._simput = simput
self._data_dir = data_dir
self._ra_cen = ra_cen
self._dec_cen = dec_cen
<|end_body_0|>
<|... | SIXTE simulator for eROSITA observations. 1. Compute GTI file for given simput 2. Simulate eROSITA observations of simput, using GTI to speed things up. | Simulator | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Simulator:
"""SIXTE simulator for eROSITA observations. 1. Compute GTI file for given simput 2. Simulate eROSITA observations of simput, using GTI to speed things up."""
def __init__(self, with_bkg_par, t_start, exposure, seed, simput, data_dir, ra_cen, dec_cen):
""":param with_bkg_p... | stack_v2_sparse_classes_75kplus_train_066950 | 5,418 | no_license | [
{
"docstring": ":param with_bkg_par: Simulate with particle background. :param t_start: Start time of simulation. Input units of [s] :param exposure: Length of time to simulate for after t_start :param seed: Seed for random number generator. :param simput: Simput file (ie. the sky model)",
"name": "__init__... | 5 | stack_v2_sparse_classes_30k_train_039203 | Implement the Python class `Simulator` described below.
Class description:
SIXTE simulator for eROSITA observations. 1. Compute GTI file for given simput 2. Simulate eROSITA observations of simput, using GTI to speed things up.
Method signatures and docstrings:
- def __init__(self, with_bkg_par, t_start, exposure, se... | Implement the Python class `Simulator` described below.
Class description:
SIXTE simulator for eROSITA observations. 1. Compute GTI file for given simput 2. Simulate eROSITA observations of simput, using GTI to speed things up.
Method signatures and docstrings:
- def __init__(self, with_bkg_par, t_start, exposure, se... | 2b8ac686b1d445a39fcd28dbe07ef467c0b14c7e | <|skeleton|>
class Simulator:
"""SIXTE simulator for eROSITA observations. 1. Compute GTI file for given simput 2. Simulate eROSITA observations of simput, using GTI to speed things up."""
def __init__(self, with_bkg_par, t_start, exposure, seed, simput, data_dir, ra_cen, dec_cen):
""":param with_bkg_p... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Simulator:
"""SIXTE simulator for eROSITA observations. 1. Compute GTI file for given simput 2. Simulate eROSITA observations of simput, using GTI to speed things up."""
def __init__(self, with_bkg_par, t_start, exposure, seed, simput, data_dir, ra_cen, dec_cen):
""":param with_bkg_par: Simulate ... | the_stack_v2_python_sparse | python/sixte/simulate_agn_only.py | HuiboZhou/mocks_high_fidelity | train | 0 |
0a57c5a3170437619a128837257a2b49a44eddab | [
"super(PingCommand, self).__init__()\nself.target = target\nself.connection = connection\nself.operating_system = operating_system\nself._arguments = None\nself._expression = None\nreturn",
"if self._arguments is None:\n try:\n self._arguments = PingArguments.arguments[self.operating_system] + self.targ... | <|body_start_0|>
super(PingCommand, self).__init__()
self.target = target
self.connection = connection
self.operating_system = operating_system
self._arguments = None
self._expression = None
return
<|end_body_0|>
<|body_start_1|>
if self._arguments is Non... | A ping is a simple ping-command. | PingCommand | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PingCommand:
"""A ping is a simple ping-command."""
def __init__(self, target=None, connection=None, operating_system=None):
"""PingCommand constructor :param: - `target`: An IP Address to ping. - `connection`: A Connection to the device - `operating_system`: The operating system of ... | stack_v2_sparse_classes_75kplus_train_066951 | 4,487 | permissive | [
{
"docstring": "PingCommand constructor :param: - `target`: An IP Address to ping. - `connection`: A Connection to the device - `operating_system`: The operating system of the device",
"name": "__init__",
"signature": "def __init__(self, target=None, connection=None, operating_system=None)"
},
{
... | 5 | stack_v2_sparse_classes_30k_train_051355 | Implement the Python class `PingCommand` described below.
Class description:
A ping is a simple ping-command.
Method signatures and docstrings:
- def __init__(self, target=None, connection=None, operating_system=None): PingCommand constructor :param: - `target`: An IP Address to ping. - `connection`: A Connection to ... | Implement the Python class `PingCommand` described below.
Class description:
A ping is a simple ping-command.
Method signatures and docstrings:
- def __init__(self, target=None, connection=None, operating_system=None): PingCommand constructor :param: - `target`: An IP Address to ping. - `connection`: A Connection to ... | b4d1c77e1d611fe2b30768b42bdc7493afb0ea95 | <|skeleton|>
class PingCommand:
"""A ping is a simple ping-command."""
def __init__(self, target=None, connection=None, operating_system=None):
"""PingCommand constructor :param: - `target`: An IP Address to ping. - `connection`: A Connection to the device - `operating_system`: The operating system of ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PingCommand:
"""A ping is a simple ping-command."""
def __init__(self, target=None, connection=None, operating_system=None):
"""PingCommand constructor :param: - `target`: An IP Address to ping. - `connection`: A Connection to the device - `operating_system`: The operating system of the device"""... | the_stack_v2_python_sparse | apetools/commands/ping.py | russell-n/oldape | train | 0 |
763c7d589872762f7d6902eaf1f32c03aab70192 | [
"eobjreader = ExtObjReader.ExtObjReader()\ndatlist = [['1'], ['1', '2'], ['1', '2', '3'], ['1', '', '3'], ['1', '2', ''], ['1', '', '']]\nanslist = [[True, False, False], [True, True, False], [True, True, True], [True, False, True], [True, True, False], [True, False, False]]\nn = len(datlist)\ni = 0\nwhile i < n:\n... | <|body_start_0|>
eobjreader = ExtObjReader.ExtObjReader()
datlist = [['1'], ['1', '2'], ['1', '2', '3'], ['1', '', '3'], ['1', '2', ''], ['1', '', '']]
anslist = [[True, False, False], [True, True, False], [True, True, True], [True, False, True], [True, True, False], [True, False, False]]
... | test for extended obj file reader | TestExtObjReader | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestExtObjReader:
"""test for extended obj file reader"""
def test_extobjreader_unit0(self):
"""extended objreader test 0"""
<|body_0|>
def test_extobjreader_sample0(self):
"""extended objreader sample0"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_75kplus_train_066952 | 2,184 | no_license | [
{
"docstring": "extended objreader test 0",
"name": "test_extobjreader_unit0",
"signature": "def test_extobjreader_unit0(self)"
},
{
"docstring": "extended objreader sample0",
"name": "test_extobjreader_sample0",
"signature": "def test_extobjreader_sample0(self)"
}
] | 2 | null | Implement the Python class `TestExtObjReader` described below.
Class description:
test for extended obj file reader
Method signatures and docstrings:
- def test_extobjreader_unit0(self): extended objreader test 0
- def test_extobjreader_sample0(self): extended objreader sample0 | Implement the Python class `TestExtObjReader` described below.
Class description:
test for extended obj file reader
Method signatures and docstrings:
- def test_extobjreader_unit0(self): extended objreader test 0
- def test_extobjreader_sample0(self): extended objreader sample0
<|skeleton|>
class TestExtObjReader:
... | f163b6b9e15100d223ddf4e180727a2b63fbae2d | <|skeleton|>
class TestExtObjReader:
"""test for extended obj file reader"""
def test_extobjreader_unit0(self):
"""extended objreader test 0"""
<|body_0|>
def test_extobjreader_sample0(self):
"""extended objreader sample0"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TestExtObjReader:
"""test for extended obj file reader"""
def test_extobjreader_unit0(self):
"""extended objreader test 0"""
eobjreader = ExtObjReader.ExtObjReader()
datlist = [['1'], ['1', '2'], ['1', '2', '3'], ['1', '', '3'], ['1', '2', ''], ['1', '', '']]
anslist = [[T... | the_stack_v2_python_sparse | obsolete/test_ExtObjReader.py | yamauchih/ifgi-path-tracer | train | 0 |
e8ef54e7460905bdb5b9d2ebc0dc9e7dfa41b1fc | [
"self.output_path = Path(output_path)\nself.games_list = games_list\nself.should_append_to_file = append",
"headers = self.games_list[0].keys()\nfile_exists = self.output_path.exists()\nif file_exists and (not self.should_append_to_file):\n os.remove(self.output_path)\nwith self.output_path.open('a') as games_... | <|body_start_0|>
self.output_path = Path(output_path)
self.games_list = games_list
self.should_append_to_file = append
<|end_body_0|>
<|body_start_1|>
headers = self.games_list[0].keys()
file_exists = self.output_path.exists()
if file_exists and (not self.should_append_t... | Writes data for games to output csv as series of features | GameWriter | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GameWriter:
"""Writes data for games to output csv as series of features"""
def __init__(self, output_path, games_list, append=False):
""":param output_path: specify the output path for the csv file :param games_list: list of games to write (each game gets its own row) :param append:... | stack_v2_sparse_classes_75kplus_train_066953 | 1,346 | no_license | [
{
"docstring": ":param output_path: specify the output path for the csv file :param games_list: list of games to write (each game gets its own row) :param append: open in append mode",
"name": "__init__",
"signature": "def __init__(self, output_path, games_list, append=False)"
},
{
"docstring": ... | 2 | stack_v2_sparse_classes_30k_train_023464 | Implement the Python class `GameWriter` described below.
Class description:
Writes data for games to output csv as series of features
Method signatures and docstrings:
- def __init__(self, output_path, games_list, append=False): :param output_path: specify the output path for the csv file :param games_list: list of g... | Implement the Python class `GameWriter` described below.
Class description:
Writes data for games to output csv as series of features
Method signatures and docstrings:
- def __init__(self, output_path, games_list, append=False): :param output_path: specify the output path for the csv file :param games_list: list of g... | c2c833a7de6a63cbd058929fb992f28740851e4a | <|skeleton|>
class GameWriter:
"""Writes data for games to output csv as series of features"""
def __init__(self, output_path, games_list, append=False):
""":param output_path: specify the output path for the csv file :param games_list: list of games to write (each game gets its own row) :param append:... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class GameWriter:
"""Writes data for games to output csv as series of features"""
def __init__(self, output_path, games_list, append=False):
""":param output_path: specify the output path for the csv file :param games_list: list of games to write (each game gets its own row) :param append: open in appe... | the_stack_v2_python_sparse | score_writer/game_writer.py | CHeffernan087/NBA_Machine_Learning_Model | train | 0 |
42e276dba5736f372e79251e55eb095fa8cd7a88 | [
"super(BayesianLinearRegression, self).__init__(basis_function, mu, s, deg)\nself.S = None\nself.M = None\nself.N = 0\nself.alpha = alpha\nself.beta = beta",
"self.N = X.shape[0]\nif optimize_evidence:\n self._optimize_evidence(X, y, max_iter, threshold)\ndesign_mat = self.make_design_mat(X)\nself.M = design_m... | <|body_start_0|>
super(BayesianLinearRegression, self).__init__(basis_function, mu, s, deg)
self.S = None
self.M = None
self.N = 0
self.alpha = alpha
self.beta = beta
<|end_body_0|>
<|body_start_1|>
self.N = X.shape[0]
if optimize_evidence:
se... | BayesianLinearRegression | BayesianLinearRegression | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BayesianLinearRegression:
"""BayesianLinearRegression"""
def __init__(self, alpha=0.1, beta=0.1, basis_function='gauss', mu=None, s=None, deg=None):
"""Args: alpha (float) : regularization parameter beta (float) : precision parameter basis_funtion (str) : "gauss" or "sigmoid" or "pol... | stack_v2_sparse_classes_75kplus_train_066954 | 8,340 | permissive | [
{
"docstring": "Args: alpha (float) : regularization parameter beta (float) : precision parameter basis_funtion (str) : \"gauss\" or \"sigmoid\" or \"polynomial\" mu (1-D array) : mean parameter s (1-D array) : standard deviation parameter deg (int) : max degree of polynomial features Node: alpha/beta performs ... | 6 | stack_v2_sparse_classes_30k_train_006889 | Implement the Python class `BayesianLinearRegression` described below.
Class description:
BayesianLinearRegression
Method signatures and docstrings:
- def __init__(self, alpha=0.1, beta=0.1, basis_function='gauss', mu=None, s=None, deg=None): Args: alpha (float) : regularization parameter beta (float) : precision par... | Implement the Python class `BayesianLinearRegression` described below.
Class description:
BayesianLinearRegression
Method signatures and docstrings:
- def __init__(self, alpha=0.1, beta=0.1, basis_function='gauss', mu=None, s=None, deg=None): Args: alpha (float) : regularization parameter beta (float) : precision par... | 992f2c07e88b2bad331e08303bdba84684f04d40 | <|skeleton|>
class BayesianLinearRegression:
"""BayesianLinearRegression"""
def __init__(self, alpha=0.1, beta=0.1, basis_function='gauss', mu=None, s=None, deg=None):
"""Args: alpha (float) : regularization parameter beta (float) : precision parameter basis_funtion (str) : "gauss" or "sigmoid" or "pol... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class BayesianLinearRegression:
"""BayesianLinearRegression"""
def __init__(self, alpha=0.1, beta=0.1, basis_function='gauss', mu=None, s=None, deg=None):
"""Args: alpha (float) : regularization parameter beta (float) : precision parameter basis_funtion (str) : "gauss" or "sigmoid" or "polynomial" mu (... | the_stack_v2_python_sparse | prml/linear_regression.py | hedwig100/PRML | train | 1 |
166d255aab158dab1c97c2b8db277b8e6a76c206 | [
"n = len(nums)\nresult = []\n\ndef backtrack(first=0):\n if first == n:\n result.append(nums[:])\n for i in range(first, n):\n nums[first], nums[i] = (nums[i], nums[first])\n backtrack(first + 1)\n nums[first], nums[i] = (nums[i], nums[first])\nbacktrack()\nreturn result",
"def b... | <|body_start_0|>
n = len(nums)
result = []
def backtrack(first=0):
if first == n:
result.append(nums[:])
for i in range(first, n):
nums[first], nums[i] = (nums[i], nums[first])
backtrack(first + 1)
nums[firs... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def permute(self, nums: List[int]) -> List[List[int]]:
"""46. 全排列 给定一个 没有重复 数字的序列，返回其所有可能的全排列。"""
<|body_0|>
def permuteUnique(self, nums: List[int]) -> List[List[int]]:
"""47. 全排列 II 给定一个可包含重复数字的序列，返回所有不重复的全排列。"""
<|body_1|>
<|end_skeleton|>
<|bo... | stack_v2_sparse_classes_75kplus_train_066955 | 1,593 | no_license | [
{
"docstring": "46. 全排列 给定一个 没有重复 数字的序列，返回其所有可能的全排列。",
"name": "permute",
"signature": "def permute(self, nums: List[int]) -> List[List[int]]"
},
{
"docstring": "47. 全排列 II 给定一个可包含重复数字的序列，返回所有不重复的全排列。",
"name": "permuteUnique",
"signature": "def permuteUnique(self, nums: List[int]) -> Li... | 2 | stack_v2_sparse_classes_30k_train_029500 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def permute(self, nums: List[int]) -> List[List[int]]: 46. 全排列 给定一个 没有重复 数字的序列，返回其所有可能的全排列。
- def permuteUnique(self, nums: List[int]) -> List[List[int]]: 47. 全排列 II 给定一个可包含重复数字的... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def permute(self, nums: List[int]) -> List[List[int]]: 46. 全排列 给定一个 没有重复 数字的序列，返回其所有可能的全排列。
- def permuteUnique(self, nums: List[int]) -> List[List[int]]: 47. 全排列 II 给定一个可包含重复数字的... | 6580c7fd9a62494f82cedf69edda793865b5bd2d | <|skeleton|>
class Solution:
def permute(self, nums: List[int]) -> List[List[int]]:
"""46. 全排列 给定一个 没有重复 数字的序列，返回其所有可能的全排列。"""
<|body_0|>
def permuteUnique(self, nums: List[int]) -> List[List[int]]:
"""47. 全排列 II 给定一个可包含重复数字的序列，返回所有不重复的全排列。"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def permute(self, nums: List[int]) -> List[List[int]]:
"""46. 全排列 给定一个 没有重复 数字的序列，返回其所有可能的全排列。"""
n = len(nums)
result = []
def backtrack(first=0):
if first == n:
result.append(nums[:])
for i in range(first, n):
... | the_stack_v2_python_sparse | Week_03/permutations.py | ZGingko/algorithm008-class02 | train | 0 | |
83bbcf4648a55d6e84c5f8ee27b27ce040b290e1 | [
"extra_data = {}\nif instance.profile:\n extra_data.update(SocialAuthProfileSerializer(instance.profile).data)\nreturn extra_data",
"if 'next' in data:\n backend = self.context['backend']\n redirect_uri = data['next']\n if backend.setting('SANITIZE_REDIRECTS', True):\n allowed_hosts = backend.s... | <|body_start_0|>
extra_data = {}
if instance.profile:
extra_data.update(SocialAuthProfileSerializer(instance.profile).data)
return extra_data
<|end_body_0|>
<|body_start_1|>
if 'next' in data:
backend = self.context['backend']
redirect_uri = data['nex... | Serializer for social auth | SocialAuthSerializer | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SocialAuthSerializer:
"""Serializer for social auth"""
def get_extra_data(self, instance):
"""Serialize extra_data"""
<|body_0|>
def _save_next(self, data):
"""Persists the next url to the session"""
<|body_1|>
def _authenticate(self, flow):
... | stack_v2_sparse_classes_75kplus_train_066956 | 11,156 | permissive | [
{
"docstring": "Serialize extra_data",
"name": "get_extra_data",
"signature": "def get_extra_data(self, instance)"
},
{
"docstring": "Persists the next url to the session",
"name": "_save_next",
"signature": "def _save_next(self, data)"
},
{
"docstring": "Authenticate the current... | 4 | stack_v2_sparse_classes_30k_train_027605 | Implement the Python class `SocialAuthSerializer` described below.
Class description:
Serializer for social auth
Method signatures and docstrings:
- def get_extra_data(self, instance): Serialize extra_data
- def _save_next(self, data): Persists the next url to the session
- def _authenticate(self, flow): Authenticate... | Implement the Python class `SocialAuthSerializer` described below.
Class description:
Serializer for social auth
Method signatures and docstrings:
- def get_extra_data(self, instance): Serialize extra_data
- def _save_next(self, data): Persists the next url to the session
- def _authenticate(self, flow): Authenticate... | ba7442482da97d463302658c0aac989567ee1241 | <|skeleton|>
class SocialAuthSerializer:
"""Serializer for social auth"""
def get_extra_data(self, instance):
"""Serialize extra_data"""
<|body_0|>
def _save_next(self, data):
"""Persists the next url to the session"""
<|body_1|>
def _authenticate(self, flow):
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SocialAuthSerializer:
"""Serializer for social auth"""
def get_extra_data(self, instance):
"""Serialize extra_data"""
extra_data = {}
if instance.profile:
extra_data.update(SocialAuthProfileSerializer(instance.profile).data)
return extra_data
def _save_nex... | the_stack_v2_python_sparse | authentication/serializers.py | mitodl/open-discussions | train | 13 |
4656602306d83d8f4bffb11f375f730a7639a065 | [
"odooclient = odoo_client.get_odoo_client()\nproject_id = request.keystone_user['project_id']\nproject_search = [('tenant_id', '=', project_id)]\ntry:\n odoo_project_id = odooclient.projects.list(project_search, read=True)[0]['id']\nexcept IndexError:\n return Response({'errors': ['Project not found']}, statu... | <|body_start_0|>
odooclient = odoo_client.get_odoo_client()
project_id = request.keystone_user['project_id']
project_search = [('tenant_id', '=', project_id)]
try:
odoo_project_id = odooclient.projects.list(project_search, read=True)[0]['id']
except IndexError:
... | AccountDetailsManagement | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AccountDetailsManagement:
def get(self, request):
"""View Account Details"""
<|body_0|>
def post(self, request):
"""Update Account Details"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
odooclient = odoo_client.get_odoo_client()
project_id ... | stack_v2_sparse_classes_75kplus_train_066957 | 7,915 | permissive | [
{
"docstring": "View Account Details",
"name": "get",
"signature": "def get(self, request)"
},
{
"docstring": "Update Account Details",
"name": "post",
"signature": "def post(self, request)"
}
] | 2 | stack_v2_sparse_classes_30k_train_020014 | Implement the Python class `AccountDetailsManagement` described below.
Class description:
Implement the AccountDetailsManagement class.
Method signatures and docstrings:
- def get(self, request): View Account Details
- def post(self, request): Update Account Details | Implement the Python class `AccountDetailsManagement` described below.
Class description:
Implement the AccountDetailsManagement class.
Method signatures and docstrings:
- def get(self, request): View Account Details
- def post(self, request): Update Account Details
<|skeleton|>
class AccountDetailsManagement:
... | 6d1e473710e1757b92b4344d65d5bd106677fe36 | <|skeleton|>
class AccountDetailsManagement:
def get(self, request):
"""View Account Details"""
<|body_0|>
def post(self, request):
"""Update Account Details"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AccountDetailsManagement:
def get(self, request):
"""View Account Details"""
odooclient = odoo_client.get_odoo_client()
project_id = request.keystone_user['project_id']
project_search = [('tenant_id', '=', project_id)]
try:
odoo_project_id = odooclient.proje... | the_stack_v2_python_sparse | odoo_views/views.py | catalyst-cloud/adjutant-odoo | train | 1 | |
39b2110306ffbf176b3fc00fee4e37696b58f44c | [
"group1, group2 = data\ntest_stat = abs(group1.mean() - group2.mean())\nreturn test_stat",
"group1, group2 = self.data\nself.n, self.m = (len(group1), len(group2))\nself.pool = np.hstack((group1, group2))",
"np.random.shuffle(self.pool)\ndata = (self.pool[:self.n], self.pool[self.n:])\nreturn data"
] | <|body_start_0|>
group1, group2 = data
test_stat = abs(group1.mean() - group2.mean())
return test_stat
<|end_body_0|>
<|body_start_1|>
group1, group2 = self.data
self.n, self.m = (len(group1), len(group2))
self.pool = np.hstack((group1, group2))
<|end_body_1|>
<|body_st... | Tests a difference in means by permutation. | DiffMeansPermute | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DiffMeansPermute:
"""Tests a difference in means by permutation."""
def TestStatistic(self, data):
"""Computes the test statistic. data: data in whatever form is relevant"""
<|body_0|>
def MakeModel(self):
"""Build a model of the null hypothesis."""
<|bod... | stack_v2_sparse_classes_75kplus_train_066958 | 10,162 | permissive | [
{
"docstring": "Computes the test statistic. data: data in whatever form is relevant",
"name": "TestStatistic",
"signature": "def TestStatistic(self, data)"
},
{
"docstring": "Build a model of the null hypothesis.",
"name": "MakeModel",
"signature": "def MakeModel(self)"
},
{
"do... | 3 | stack_v2_sparse_classes_30k_train_043665 | Implement the Python class `DiffMeansPermute` described below.
Class description:
Tests a difference in means by permutation.
Method signatures and docstrings:
- def TestStatistic(self, data): Computes the test statistic. data: data in whatever form is relevant
- def MakeModel(self): Build a model of the null hypothe... | Implement the Python class `DiffMeansPermute` described below.
Class description:
Tests a difference in means by permutation.
Method signatures and docstrings:
- def TestStatistic(self, data): Computes the test statistic. data: data in whatever form is relevant
- def MakeModel(self): Build a model of the null hypothe... | 30a85d5137db95e01461ad21519bc1bdf294044b | <|skeleton|>
class DiffMeansPermute:
"""Tests a difference in means by permutation."""
def TestStatistic(self, data):
"""Computes the test statistic. data: data in whatever form is relevant"""
<|body_0|>
def MakeModel(self):
"""Build a model of the null hypothesis."""
<|bod... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DiffMeansPermute:
"""Tests a difference in means by permutation."""
def TestStatistic(self, data):
"""Computes the test statistic. data: data in whatever form is relevant"""
group1, group2 = data
test_stat = abs(group1.mean() - group2.mean())
return test_stat
def Make... | the_stack_v2_python_sparse | CompStats/hypothesis.py | sunny2309/scipy_conf_notebooks | train | 2 |
c2744166669b99c6e32a885d92505d613db28787 | [
"point_cloud_1 = [[[1.0, 1.0, 1.0], [2.0, 2.0, 2.0], [3.0, 3.0, 3.0]]]\npoint_cloud_2 = [[[1.0, 1.0, 1.0], [2.0, 2.0, 2.0], [3.0, 3.0, 3.0]]]\ntf_point_cloud_1 = tf.constant(point_cloud_1)\ntf_point_cloud_2 = tf.constant(point_cloud_2)\ndist1, idx1, dist2, idx2 = tf_nndistance.nn_distance(tf_point_cloud_1, tf_point... | <|body_start_0|>
point_cloud_1 = [[[1.0, 1.0, 1.0], [2.0, 2.0, 2.0], [3.0, 3.0, 3.0]]]
point_cloud_2 = [[[1.0, 1.0, 1.0], [2.0, 2.0, 2.0], [3.0, 3.0, 3.0]]]
tf_point_cloud_1 = tf.constant(point_cloud_1)
tf_point_cloud_2 = tf.constant(point_cloud_2)
dist1, idx1, dist2, idx2 = tf_n... | NearestNeighborTest | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NearestNeighborTest:
def test_nn_distance(self):
"""Test for nearest neighbor algorithm where distance should be 0."""
<|body_0|>
def test_nn_distance_2(self):
"""Test for nearest neighbor algorithm where distance is non-zero."""
<|body_1|>
def test_nn_d... | stack_v2_sparse_classes_75kplus_train_066959 | 4,084 | permissive | [
{
"docstring": "Test for nearest neighbor algorithm where distance should be 0.",
"name": "test_nn_distance",
"signature": "def test_nn_distance(self)"
},
{
"docstring": "Test for nearest neighbor algorithm where distance is non-zero.",
"name": "test_nn_distance_2",
"signature": "def tes... | 5 | stack_v2_sparse_classes_30k_train_007708 | Implement the Python class `NearestNeighborTest` described below.
Class description:
Implement the NearestNeighborTest class.
Method signatures and docstrings:
- def test_nn_distance(self): Test for nearest neighbor algorithm where distance should be 0.
- def test_nn_distance_2(self): Test for nearest neighbor algori... | Implement the Python class `NearestNeighborTest` described below.
Class description:
Implement the NearestNeighborTest class.
Method signatures and docstrings:
- def test_nn_distance(self): Test for nearest neighbor algorithm where distance should be 0.
- def test_nn_distance_2(self): Test for nearest neighbor algori... | f3cb31909666012dfcf38e5fe0b0f6feb3801560 | <|skeleton|>
class NearestNeighborTest:
def test_nn_distance(self):
"""Test for nearest neighbor algorithm where distance should be 0."""
<|body_0|>
def test_nn_distance_2(self):
"""Test for nearest neighbor algorithm where distance is non-zero."""
<|body_1|>
def test_nn_d... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class NearestNeighborTest:
def test_nn_distance(self):
"""Test for nearest neighbor algorithm where distance should be 0."""
point_cloud_1 = [[[1.0, 1.0, 1.0], [2.0, 2.0, 2.0], [3.0, 3.0, 3.0]]]
point_cloud_2 = [[[1.0, 1.0, 1.0], [2.0, 2.0, 2.0], [3.0, 3.0, 3.0]]]
tf_point_cloud_1 = ... | the_stack_v2_python_sparse | src/tf_ops/nn_distance/tf_nndistance_test.py | minghanz/monopsr | train | 0 | |
1396cb1b6303a56eddc253b2ebd7b84bc20bae4f | [
"xo = x[:-dt]\nxt = x[dt:]\nmuo = np.mean(xo, axis=0)\nmut = np.mean(xt, axis=0)\ncoo = (xo - muo).T @ (xo - muo) + (xt - mut).T @ (xt - mut)\ncot = (xo - muo).T @ (xt - mut) + (xt - mut).T @ (xo - muo)\neigvals, eigvecs = eig(cot.astype(np.double), coo.astype(np.double))\nself.kinetic_map_scaling = kinetic_map_sca... | <|body_start_0|>
xo = x[:-dt]
xt = x[dt:]
muo = np.mean(xo, axis=0)
mut = np.mean(xt, axis=0)
coo = (xo - muo).T @ (xo - muo) + (xt - mut).T @ (xt - mut)
cot = (xo - muo).T @ (xt - mut) + (xt - mut).T @ (xo - muo)
eigvals, eigvecs = eig(cot.astype(np.double), coo.... | Implemented based on description in Frank Noé, Machine Learning for Molecular Dynamics on Long Timescales, 2018 (https://arxiv.org/abs/1812.07669) | TICA | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TICA:
"""Implemented based on description in Frank Noé, Machine Learning for Molecular Dynamics on Long Timescales, 2018 (https://arxiv.org/abs/1812.07669)"""
def __init__(self, x, dt, kinetic_map_scaling=True):
"""Takes time series data"""
<|body_0|>
def transform(self,... | stack_v2_sparse_classes_75kplus_train_066960 | 2,287 | no_license | [
{
"docstring": "Takes time series data",
"name": "__init__",
"signature": "def __init__(self, x, dt, kinetic_map_scaling=True)"
},
{
"docstring": "Transforms to tIC space",
"name": "transform",
"signature": "def transform(self, xx)"
},
{
"docstring": "Transforms from tIC space to... | 3 | stack_v2_sparse_classes_30k_train_049375 | Implement the Python class `TICA` described below.
Class description:
Implemented based on description in Frank Noé, Machine Learning for Molecular Dynamics on Long Timescales, 2018 (https://arxiv.org/abs/1812.07669)
Method signatures and docstrings:
- def __init__(self, x, dt, kinetic_map_scaling=True): Takes time s... | Implement the Python class `TICA` described below.
Class description:
Implemented based on description in Frank Noé, Machine Learning for Molecular Dynamics on Long Timescales, 2018 (https://arxiv.org/abs/1812.07669)
Method signatures and docstrings:
- def __init__(self, x, dt, kinetic_map_scaling=True): Takes time s... | 7961815a329c5643f3fc740feeb776c71965a383 | <|skeleton|>
class TICA:
"""Implemented based on description in Frank Noé, Machine Learning for Molecular Dynamics on Long Timescales, 2018 (https://arxiv.org/abs/1812.07669)"""
def __init__(self, x, dt, kinetic_map_scaling=True):
"""Takes time series data"""
<|body_0|>
def transform(self,... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TICA:
"""Implemented based on description in Frank Noé, Machine Learning for Molecular Dynamics on Long Timescales, 2018 (https://arxiv.org/abs/1812.07669)"""
def __init__(self, x, dt, kinetic_map_scaling=True):
"""Takes time series data"""
xo = x[:-dt]
xt = x[dt:]
muo = n... | the_stack_v2_python_sparse | BarstarBarnase/tica.py | oortsang/BiophysLearning | train | 0 |
dea3f0798ae58931974ad967d03a7035f185d213 | [
"if not self:\n return []\nlen_vector = []\nstatus_vector = []\nfor i in range(0, len(self)):\n status_vector.append(0)\n if type(self[i]) == list:\n len_vector.append(len(self[i]))\n else:\n len_vector.append(1)\nsolution = []\nwhile 1:\n solution.append(self.extract_vector(status_vect... | <|body_start_0|>
if not self:
return []
len_vector = []
status_vector = []
for i in range(0, len(self)):
status_vector.append(0)
if type(self[i]) == list:
len_vector.append(len(self[i]))
else:
len_vector.appe... | a list of list | Multi_list | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Multi_list:
"""a list of list"""
def give_combinaison(self):
"""return all the combinatory possibility in a list"""
<|body_0|>
def extract_vector(self, pos_list):
"""return the list of element corresponding at position in pos_list"""
<|body_1|>
def g... | stack_v2_sparse_classes_75kplus_train_066961 | 7,736 | no_license | [
{
"docstring": "return all the combinatory possibility in a list",
"name": "give_combinaison",
"signature": "def give_combinaison(self)"
},
{
"docstring": "return the list of element corresponding at position in pos_list",
"name": "extract_vector",
"signature": "def extract_vector(self, ... | 3 | stack_v2_sparse_classes_30k_train_038206 | Implement the Python class `Multi_list` described below.
Class description:
a list of list
Method signatures and docstrings:
- def give_combinaison(self): return all the combinatory possibility in a list
- def extract_vector(self, pos_list): return the list of element corresponding at position in pos_list
- def give_... | Implement the Python class `Multi_list` described below.
Class description:
a list of list
Method signatures and docstrings:
- def give_combinaison(self): return all the combinatory possibility in a list
- def extract_vector(self, pos_list): return the list of element corresponding at position in pos_list
- def give_... | c77b09fda48877ef6f1d2db85237b220f696e512 | <|skeleton|>
class Multi_list:
"""a list of list"""
def give_combinaison(self):
"""return all the combinatory possibility in a list"""
<|body_0|>
def extract_vector(self, pos_list):
"""return the list of element corresponding at position in pos_list"""
<|body_1|>
def g... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Multi_list:
"""a list of list"""
def give_combinaison(self):
"""return all the combinatory possibility in a list"""
if not self:
return []
len_vector = []
status_vector = []
for i in range(0, len(self)):
status_vector.append(0)
i... | the_stack_v2_python_sparse | AprimeAlAlpha1/Source/MadWeight_File/Python/MW_fct.py | JeffersonLab/BDXEventGenerator | train | 1 |
048fda669d0a9d79d22253633f0437b2406081c7 | [
"cache_dir = os.getenv('GREENFLOW_CACHE_DIR', self.cache_dir)\nif filename is None:\n filename = cache_dir + '/' + self.uid + '.hdf5'\noutput_df = {}\nwith pd.HDFStore(filename, mode='r') as hf:\n for oport, pspec in self._get_output_ports(full_port_spec=True).items():\n ptype = pspec.get(PortsSpecSche... | <|body_start_0|>
cache_dir = os.getenv('GREENFLOW_CACHE_DIR', self.cache_dir)
if filename is None:
filename = cache_dir + '/' + self.uid + '.hdf5'
output_df = {}
with pd.HDFStore(filename, mode='r') as hf:
for oport, pspec in self._get_output_ports(full_port_spec=... | NodeHDFCacheMixin | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NodeHDFCacheMixin:
def load_cache(self, filename=None) -> dict:
"""Defines the behavior of how to load the cache file from the `filename`. Node can override this method. Default implementation assumes cudf dataframes. Arguments ------- filename: str filename of the cache file. Leave as n... | stack_v2_sparse_classes_75kplus_train_066962 | 3,546 | permissive | [
{
"docstring": "Defines the behavior of how to load the cache file from the `filename`. Node can override this method. Default implementation assumes cudf dataframes. Arguments ------- filename: str filename of the cache file. Leave as none to use default. returns: dict dictionary of the output from this node",... | 2 | null | Implement the Python class `NodeHDFCacheMixin` described below.
Class description:
Implement the NodeHDFCacheMixin class.
Method signatures and docstrings:
- def load_cache(self, filename=None) -> dict: Defines the behavior of how to load the cache file from the `filename`. Node can override this method. Default impl... | Implement the Python class `NodeHDFCacheMixin` described below.
Class description:
Implement the NodeHDFCacheMixin class.
Method signatures and docstrings:
- def load_cache(self, filename=None) -> dict: Defines the behavior of how to load the cache file from the `filename`. Node can override this method. Default impl... | 94ac1d1ca7b0f04660edd2a773f76c752610b2bd | <|skeleton|>
class NodeHDFCacheMixin:
def load_cache(self, filename=None) -> dict:
"""Defines the behavior of how to load the cache file from the `filename`. Node can override this method. Default implementation assumes cudf dataframes. Arguments ------- filename: str filename of the cache file. Leave as n... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class NodeHDFCacheMixin:
def load_cache(self, filename=None) -> dict:
"""Defines the behavior of how to load the cache file from the `filename`. Node can override this method. Default implementation assumes cudf dataframes. Arguments ------- filename: str filename of the cache file. Leave as none to use def... | the_stack_v2_python_sparse | gQuant/plugins/gquant_plugin/greenflow_gquant_plugin/node_hdf_cache.py | Anhmike/gQuant | train | 0 | |
5e2285e371fddee1e6fb7f840be35fa0b3d943ec | [
"self.ident = ident\nself.func = func\nself.forceKeepArgsCasing = forceKeepArgsCasing\nself.forceKeepCommandCasing = forceKeepCommandCasing\nself.allowDM = allowDM\nself.allowHelp = allowHelp\nself.aliases = aliases\nself.signatureStr = signatureStr\nself.shortHelp = shortHelp\nself.longHelp = longHelp\nself.helpSe... | <|body_start_0|>
self.ident = ident
self.func = func
self.forceKeepArgsCasing = forceKeepArgsCasing
self.forceKeepCommandCasing = forceKeepCommandCasing
self.allowDM = allowDM
self.allowHelp = allowHelp
self.aliases = aliases
self.signatureStr = signatureS... | Represents a registration of a command in a HeirarchicalCommandsDB. TODO: Make allowDM so we dont have to make two HeirarchicalCommandsDBs to handle DM commands :var ident: The string command name by which this command is identified and called :vartype ident: str :var func: A reference to the function to call upon call... | CommandRegistry | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CommandRegistry:
"""Represents a registration of a command in a HeirarchicalCommandsDB. TODO: Make allowDM so we dont have to make two HeirarchicalCommandsDBs to handle DM commands :var ident: The string command name by which this command is identified and called :vartype ident: str :var func: A ... | stack_v2_sparse_classes_75kplus_train_066963 | 15,557 | permissive | [
{
"docstring": ":param str ident: The string command name by which this command is identified and called :param FunctionType func: A reference to the function to call upon calling this CommandRegistry :param bool forceKeepArgsCasing: Whether to pass arguments to the function with their original casing. If False... | 2 | stack_v2_sparse_classes_30k_train_028272 | Implement the Python class `CommandRegistry` described below.
Class description:
Represents a registration of a command in a HeirarchicalCommandsDB. TODO: Make allowDM so we dont have to make two HeirarchicalCommandsDBs to handle DM commands :var ident: The string command name by which this command is identified and c... | Implement the Python class `CommandRegistry` described below.
Class description:
Represents a registration of a command in a HeirarchicalCommandsDB. TODO: Make allowDM so we dont have to make two HeirarchicalCommandsDBs to handle DM commands :var ident: The string command name by which this command is identified and c... | b4fe3d765b764ab169284ce0869a810825013389 | <|skeleton|>
class CommandRegistry:
"""Represents a registration of a command in a HeirarchicalCommandsDB. TODO: Make allowDM so we dont have to make two HeirarchicalCommandsDBs to handle DM commands :var ident: The string command name by which this command is identified and called :vartype ident: str :var func: A ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CommandRegistry:
"""Represents a registration of a command in a HeirarchicalCommandsDB. TODO: Make allowDM so we dont have to make two HeirarchicalCommandsDBs to handle DM commands :var ident: The string command name by which this command is identified and called :vartype ident: str :var func: A reference to ... | the_stack_v2_python_sparse | BB/bbDatabases/HeirarchicalCommandsDB.py | Trimatix/GOF2BountyBot | train | 7 |
80961b4353ea6e194afb9ba47c2780dabccd9865 | [
"super(FasterRCNN, self).__init__()\nself.backbone = self.define_props('backbone', backbone, dtype=ClassType.NETWORK)\nself.neck = self.define_props('neck', neck, dtype=ClassType.NETWORK)\nbackbone_neck = Sequential(self.backbone, self.neck)\nself.head = ClassFactory.get_cls(ClassType.NETWORK, network_name)(backbon... | <|body_start_0|>
super(FasterRCNN, self).__init__()
self.backbone = self.define_props('backbone', backbone, dtype=ClassType.NETWORK)
self.neck = self.define_props('neck', neck, dtype=ClassType.NETWORK)
backbone_neck = Sequential(self.backbone, self.neck)
self.head = ClassFactory.... | Create ResNet Network. | FasterRCNN | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FasterRCNN:
"""Create ResNet Network."""
def __init__(self, num_classes, backbone='ResNetDet', neck='FPN', network_name='torchvision_FasterRCNN', **kwargs):
"""Create layers. :param num_class: number of class :type num_class: int"""
<|body_0|>
def call(self, inputs, targ... | stack_v2_sparse_classes_75kplus_train_066964 | 1,588 | permissive | [
{
"docstring": "Create layers. :param num_class: number of class :type num_class: int",
"name": "__init__",
"signature": "def __init__(self, num_classes, backbone='ResNetDet', neck='FPN', network_name='torchvision_FasterRCNN', **kwargs)"
},
{
"docstring": "Call inputs.",
"name": "call",
... | 2 | null | Implement the Python class `FasterRCNN` described below.
Class description:
Create ResNet Network.
Method signatures and docstrings:
- def __init__(self, num_classes, backbone='ResNetDet', neck='FPN', network_name='torchvision_FasterRCNN', **kwargs): Create layers. :param num_class: number of class :type num_class: i... | Implement the Python class `FasterRCNN` described below.
Class description:
Create ResNet Network.
Method signatures and docstrings:
- def __init__(self, num_classes, backbone='ResNetDet', neck='FPN', network_name='torchvision_FasterRCNN', **kwargs): Create layers. :param num_class: number of class :type num_class: i... | e4ef3a1c92d19d1d08c3ef0e2156b6fecefdbe04 | <|skeleton|>
class FasterRCNN:
"""Create ResNet Network."""
def __init__(self, num_classes, backbone='ResNetDet', neck='FPN', network_name='torchvision_FasterRCNN', **kwargs):
"""Create layers. :param num_class: number of class :type num_class: int"""
<|body_0|>
def call(self, inputs, targ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class FasterRCNN:
"""Create ResNet Network."""
def __init__(self, num_classes, backbone='ResNetDet', neck='FPN', network_name='torchvision_FasterRCNN', **kwargs):
"""Create layers. :param num_class: number of class :type num_class: int"""
super(FasterRCNN, self).__init__()
self.backbone... | the_stack_v2_python_sparse | zeus/networks/faster_rcnn.py | huawei-noah/xingtian | train | 308 |
ca01656d31d6477a77b67a888efa91bbe24cc9ae | [
"super(MVAEdecoder, self).__init__()\nself.experts = []\nself.num_experts = FLAGS.num_experts\nfor _ in range(self.num_experts):\n self.experts.append(nn.ModuleList([nn.Linear(FLAGS.input_dim * 3 + FLAGS.latent_dim + FLAGS.c_dim, FLAGS.dec_hidden_units), nn.Linear(FLAGS.dec_hidden_units + FLAGS.latent_dim, FLAGS... | <|body_start_0|>
super(MVAEdecoder, self).__init__()
self.experts = []
self.num_experts = FLAGS.num_experts
for _ in range(self.num_experts):
self.experts.append(nn.ModuleList([nn.Linear(FLAGS.input_dim * 3 + FLAGS.latent_dim + FLAGS.c_dim, FLAGS.dec_hidden_units), nn.Linear(... | MVAEdecoder | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MVAEdecoder:
def __init__(self, FLAGS):
"""Decoder module for the char motion decoder :param FLAGS: abseil flags"""
<|body_0|>
def forward(self, x, z):
"""forward pass through the module :param x: input to the module :param z: random variable :return: output"""
... | stack_v2_sparse_classes_75kplus_train_066965 | 2,731 | no_license | [
{
"docstring": "Decoder module for the char motion decoder :param FLAGS: abseil flags",
"name": "__init__",
"signature": "def __init__(self, FLAGS)"
},
{
"docstring": "forward pass through the module :param x: input to the module :param z: random variable :return: output",
"name": "forward",... | 2 | stack_v2_sparse_classes_30k_train_035841 | Implement the Python class `MVAEdecoder` described below.
Class description:
Implement the MVAEdecoder class.
Method signatures and docstrings:
- def __init__(self, FLAGS): Decoder module for the char motion decoder :param FLAGS: abseil flags
- def forward(self, x, z): forward pass through the module :param x: input ... | Implement the Python class `MVAEdecoder` described below.
Class description:
Implement the MVAEdecoder class.
Method signatures and docstrings:
- def __init__(self, FLAGS): Decoder module for the char motion decoder :param FLAGS: abseil flags
- def forward(self, x, z): forward pass through the module :param x: input ... | 87e8b0554ba979d0e409235de728c01edb0a48a6 | <|skeleton|>
class MVAEdecoder:
def __init__(self, FLAGS):
"""Decoder module for the char motion decoder :param FLAGS: abseil flags"""
<|body_0|>
def forward(self, x, z):
"""forward pass through the module :param x: input to the module :param z: random variable :return: output"""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MVAEdecoder:
def __init__(self, FLAGS):
"""Decoder module for the char motion decoder :param FLAGS: abseil flags"""
super(MVAEdecoder, self).__init__()
self.experts = []
self.num_experts = FLAGS.num_experts
for _ in range(self.num_experts):
self.experts.appe... | the_stack_v2_python_sparse | net/basemodel/MVAEdecoder.py | peacekurella/sell-it | train | 4 | |
075e296054c81222723d21f76aa52c0d6eec0c9b | [
"if model._meta.app_label in self.route_app_labels:\n return 'data_db'\nreturn None",
"if model._meta.app_label in self.route_app_labels:\n return 'data_db'\nreturn None",
"if obj1._meta.app_label in self.route_app_labels or obj2._meta.app_label in self.route_app_labels:\n return True\nreturn None",
... | <|body_start_0|>
if model._meta.app_label in self.route_app_labels:
return 'data_db'
return None
<|end_body_0|>
<|body_start_1|>
if model._meta.app_label in self.route_app_labels:
return 'data_db'
return None
<|end_body_1|>
<|body_start_2|>
if obj1._meta... | A router to control all database operations on models in the certain applications. | DataRouter | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DataRouter:
"""A router to control all database operations on models in the certain applications."""
def db_for_read(self, model, **hints):
"""Attempts to read certain models go to data_db."""
<|body_0|>
def db_for_write(self, model, **hints):
"""Attempts to writ... | stack_v2_sparse_classes_75kplus_train_066966 | 1,292 | permissive | [
{
"docstring": "Attempts to read certain models go to data_db.",
"name": "db_for_read",
"signature": "def db_for_read(self, model, **hints)"
},
{
"docstring": "Attempts to write certain models go to data_db.",
"name": "db_for_write",
"signature": "def db_for_write(self, model, **hints)"
... | 4 | stack_v2_sparse_classes_30k_train_016182 | Implement the Python class `DataRouter` described below.
Class description:
A router to control all database operations on models in the certain applications.
Method signatures and docstrings:
- def db_for_read(self, model, **hints): Attempts to read certain models go to data_db.
- def db_for_write(self, model, **hin... | Implement the Python class `DataRouter` described below.
Class description:
A router to control all database operations on models in the certain applications.
Method signatures and docstrings:
- def db_for_read(self, model, **hints): Attempts to read certain models go to data_db.
- def db_for_write(self, model, **hin... | dfe0533d4359806ff8f90bd7aa1c679b4a016d09 | <|skeleton|>
class DataRouter:
"""A router to control all database operations on models in the certain applications."""
def db_for_read(self, model, **hints):
"""Attempts to read certain models go to data_db."""
<|body_0|>
def db_for_write(self, model, **hints):
"""Attempts to writ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DataRouter:
"""A router to control all database operations on models in the certain applications."""
def db_for_read(self, model, **hints):
"""Attempts to read certain models go to data_db."""
if model._meta.app_label in self.route_app_labels:
return 'data_db'
return N... | the_stack_v2_python_sparse | volebni_kalkulacka/utils/dataRouter.py | tmajerech/volebni_kalkulacka | train | 0 |
1556d0bf24457c169b637de4ca77be4c6916e18f | [
"self.total_count = total_count\nself.page_info = page_info\nself.messages = messages",
"if dictionary is None:\n return None\ntotal_count = dictionary.get('totalCount')\npage_info = PageInfo.from_dictionary(dictionary.get('pageInfo')) if dictionary.get('pageInfo') else None\nmessages = None\nif dictionary.get... | <|body_start_0|>
self.total_count = total_count
self.page_info = page_info
self.messages = messages
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
total_count = dictionary.get('totalCount')
page_info = PageInfo.from_dictionary(dictionary.g... | Implementation of the 'BandwidthMessagesList' model. TODO: type model description here. Attributes: total_count (int): Total number of messages matched by the search page_info (PageInfo): TODO: type description here. messages (list of BandwidthMessageItem): TODO: type description here. | BandwidthMessagesList | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BandwidthMessagesList:
"""Implementation of the 'BandwidthMessagesList' model. TODO: type model description here. Attributes: total_count (int): Total number of messages matched by the search page_info (PageInfo): TODO: type description here. messages (list of BandwidthMessageItem): TODO: type de... | stack_v2_sparse_classes_75kplus_train_066967 | 2,301 | permissive | [
{
"docstring": "Constructor for the BandwidthMessagesList class",
"name": "__init__",
"signature": "def __init__(self, total_count=None, page_info=None, messages=None)"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: dictionary (dictionary): A dictionary representati... | 2 | null | Implement the Python class `BandwidthMessagesList` described below.
Class description:
Implementation of the 'BandwidthMessagesList' model. TODO: type model description here. Attributes: total_count (int): Total number of messages matched by the search page_info (PageInfo): TODO: type description here. messages (list ... | Implement the Python class `BandwidthMessagesList` described below.
Class description:
Implementation of the 'BandwidthMessagesList' model. TODO: type model description here. Attributes: total_count (int): Total number of messages matched by the search page_info (PageInfo): TODO: type description here. messages (list ... | 447df3cc8cb7acaf3361d842630c432a9c31ce6e | <|skeleton|>
class BandwidthMessagesList:
"""Implementation of the 'BandwidthMessagesList' model. TODO: type model description here. Attributes: total_count (int): Total number of messages matched by the search page_info (PageInfo): TODO: type description here. messages (list of BandwidthMessageItem): TODO: type de... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class BandwidthMessagesList:
"""Implementation of the 'BandwidthMessagesList' model. TODO: type model description here. Attributes: total_count (int): Total number of messages matched by the search page_info (PageInfo): TODO: type description here. messages (list of BandwidthMessageItem): TODO: type description her... | the_stack_v2_python_sparse | bandwidth/messaging/models/bandwidth_messages_list.py | Bandwidth/python-sdk | train | 10 |
76d61f95b2f041bdddabff067593ee2c7547499a | [
"from torch.nn import AvgPool2d, LeakyReLU\nfrom torch.nn import Conv2d\nsuper().__init__()\nself.conv_1 = Conv2d(in_channels, in_channels, (3, 3), dilation=dilation, padding=dilation, bias=True)\nself.conv_2 = Conv2d(in_channels, out_channels, (3, 3), dilation=dilation, padding=dilation, bias=True)\nself.downSampl... | <|body_start_0|>
from torch.nn import AvgPool2d, LeakyReLU
from torch.nn import Conv2d
super().__init__()
self.conv_1 = Conv2d(in_channels, in_channels, (3, 3), dilation=dilation, padding=dilation, bias=True)
self.conv_2 = Conv2d(in_channels, out_channels, (3, 3), dilation=dilati... | General block in the discriminator | DisGeneralConvBlock | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DisGeneralConvBlock:
"""General block in the discriminator"""
def __init__(self, in_channels, out_channels, dilation=1):
"""constructor of the class :param in_channels: number of input channels :param out_channels: number of output channels"""
<|body_0|>
def forward(self... | stack_v2_sparse_classes_75kplus_train_066968 | 14,685 | no_license | [
{
"docstring": "constructor of the class :param in_channels: number of input channels :param out_channels: number of output channels",
"name": "__init__",
"signature": "def __init__(self, in_channels, out_channels, dilation=1)"
},
{
"docstring": "forward pass of the module :param x: input :retur... | 2 | stack_v2_sparse_classes_30k_train_040487 | Implement the Python class `DisGeneralConvBlock` described below.
Class description:
General block in the discriminator
Method signatures and docstrings:
- def __init__(self, in_channels, out_channels, dilation=1): constructor of the class :param in_channels: number of input channels :param out_channels: number of ou... | Implement the Python class `DisGeneralConvBlock` described below.
Class description:
General block in the discriminator
Method signatures and docstrings:
- def __init__(self, in_channels, out_channels, dilation=1): constructor of the class :param in_channels: number of input channels :param out_channels: number of ou... | 428abe1fefe5ea4ef00290155e7e59657bc83444 | <|skeleton|>
class DisGeneralConvBlock:
"""General block in the discriminator"""
def __init__(self, in_channels, out_channels, dilation=1):
"""constructor of the class :param in_channels: number of input channels :param out_channels: number of output channels"""
<|body_0|>
def forward(self... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DisGeneralConvBlock:
"""General block in the discriminator"""
def __init__(self, in_channels, out_channels, dilation=1):
"""constructor of the class :param in_channels: number of input channels :param out_channels: number of output channels"""
from torch.nn import AvgPool2d, LeakyReLU
... | the_stack_v2_python_sparse | src/msg_stylegan2.py | blakecheng/lafin | train | 0 |
f71043721417d00212bc58287a844aacdc4aca5b | [
"if not self.instance:\n raise RuntimeError('Manager method should be called: instance.images.get_or_download()')\nimage = Image.objects.get_image_from_url(url=url)\nif image.id:\n image_link = self.get_or_create(image=image, object_id=self.instance.id, content_type=ContentType.objects.get_for_model(self.inst... | <|body_start_0|>
if not self.instance:
raise RuntimeError('Manager method should be called: instance.images.get_or_download()')
image = Image.objects.get_image_from_url(url=url)
if image.id:
image_link = self.get_or_create(image=image, object_id=self.instance.id, content_... | ImageLinkManager | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ImageLinkManager:
def get_or_download(self, url, **kwargs):
"""Try to get already downloaded or download image using self.download() method Return tuple with image_link instance and boolean flag equal True if image was downloaded"""
<|body_0|>
def download(self, url, **kwarg... | stack_v2_sparse_classes_75kplus_train_066969 | 5,904 | permissive | [
{
"docstring": "Try to get already downloaded or download image using self.download() method Return tuple with image_link instance and boolean flag equal True if image was downloaded",
"name": "get_or_download",
"signature": "def get_or_download(self, url, **kwargs)"
},
{
"docstring": "Download ... | 2 | stack_v2_sparse_classes_30k_train_041961 | Implement the Python class `ImageLinkManager` described below.
Class description:
Implement the ImageLinkManager class.
Method signatures and docstrings:
- def get_or_download(self, url, **kwargs): Try to get already downloaded or download image using self.download() method Return tuple with image_link instance and b... | Implement the Python class `ImageLinkManager` described below.
Class description:
Implement the ImageLinkManager class.
Method signatures and docstrings:
- def get_or_download(self, url, **kwargs): Try to get already downloaded or download image using self.download() method Return tuple with image_link instance and b... | c393dc8c2d59dc99aa2c3314d3372b6e2bf5497f | <|skeleton|>
class ImageLinkManager:
def get_or_download(self, url, **kwargs):
"""Try to get already downloaded or download image using self.download() method Return tuple with image_link instance and boolean flag equal True if image was downloaded"""
<|body_0|>
def download(self, url, **kwarg... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ImageLinkManager:
def get_or_download(self, url, **kwargs):
"""Try to get already downloaded or download image using self.download() method Return tuple with image_link instance and boolean flag equal True if image was downloaded"""
if not self.instance:
raise RuntimeError('Manager... | the_stack_v2_python_sparse | cinemanio/images/models.py | cinemanio/backend | train | 4 | |
2df4ccc94811bbbea5d5bc9ef22f5f56b0c66963 | [
"running_instances = session.query(FtaSolutionsAppAlarminstance).filter_by(status=status)\nrunning_instance_ids = [a.id for a in running_instances]\nlogger.info('running alarm[%s](%s): %s', status, running_instances.count(), running_instance_ids)\nredis_key = 'QOS_RUNNING_%s' % status\nhis_data = redis_cache.get(re... | <|body_start_0|>
running_instances = session.query(FtaSolutionsAppAlarminstance).filter_by(status=status)
running_instance_ids = [a.id for a in running_instances]
logger.info('running alarm[%s](%s): %s', status, running_instances.count(), running_instance_ids)
redis_key = 'QOS_RUNNING_%s... | Qos | [
"MIT",
"BSD-3-Clause",
"LicenseRef-scancode-unknown-license-reference",
"BSL-1.0",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Qos:
def check_blocked(self, status):
"""get block whether happened in sqecial topic by alarm_instance's status :param status: which status"""
<|body_0|>
def _mark_alarm_to_notice(self, status, tot_count, blocked_instance_ids):
"""mark alarm_instance status to 'for_n... | stack_v2_sparse_classes_75kplus_train_066970 | 7,722 | permissive | [
{
"docstring": "get block whether happened in sqecial topic by alarm_instance's status :param status: which status",
"name": "check_blocked",
"signature": "def check_blocked(self, status)"
},
{
"docstring": "mark alarm_instance status to 'for_notice' and pass solution :param status: which status... | 4 | stack_v2_sparse_classes_30k_train_004501 | Implement the Python class `Qos` described below.
Class description:
Implement the Qos class.
Method signatures and docstrings:
- def check_blocked(self, status): get block whether happened in sqecial topic by alarm_instance's status :param status: which status
- def _mark_alarm_to_notice(self, status, tot_count, blo... | Implement the Python class `Qos` described below.
Class description:
Implement the Qos class.
Method signatures and docstrings:
- def check_blocked(self, status): get block whether happened in sqecial topic by alarm_instance's status :param status: which status
- def _mark_alarm_to_notice(self, status, tot_count, blo... | a50a3c498c39b14e7df4a0a960c2a1499b1ec6bb | <|skeleton|>
class Qos:
def check_blocked(self, status):
"""get block whether happened in sqecial topic by alarm_instance's status :param status: which status"""
<|body_0|>
def _mark_alarm_to_notice(self, status, tot_count, blocked_instance_ids):
"""mark alarm_instance status to 'for_n... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Qos:
def check_blocked(self, status):
"""get block whether happened in sqecial topic by alarm_instance's status :param status: which status"""
running_instances = session.query(FtaSolutionsAppAlarminstance).filter_by(status=status)
running_instance_ids = [a.id for a in running_instance... | the_stack_v2_python_sparse | server/fta/qos/process.py | huang1125677925/fta | train | 0 | |
f556af0554511ed6caea20ed6d3fabec1fb4d79a | [
"super(Decoder, self).__init__()\nself.upscale = UpscaleBlockBlock(input_dim, 256, num_convblocks)\nresulting_channels = 256 // 2 ** (num_convblocks - 1)\nself.conv = nn.Conv2d(resulting_channels, 3, kernel_size=5, padding=2)\nself.sigmoid = nn.Sigmoid()",
"x = self.upscale(x)\nx = self.conv(x)\nx = self.sigmoid(... | <|body_start_0|>
super(Decoder, self).__init__()
self.upscale = UpscaleBlockBlock(input_dim, 256, num_convblocks)
resulting_channels = 256 // 2 ** (num_convblocks - 1)
self.conv = nn.Conv2d(resulting_channels, 3, kernel_size=5, padding=2)
self.sigmoid = nn.Sigmoid()
<|end_body_0|... | This is just a simple decoder with some upscaling convolutions. The last layer ends with a sigmoid to compress the output between 0 and 1 for a RGB image. | Decoder | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Decoder:
"""This is just a simple decoder with some upscaling convolutions. The last layer ends with a sigmoid to compress the output between 0 and 1 for a RGB image."""
def __init__(self, input_dim, num_convblocks=3):
"""Initialize a new decoder network. Inputs: - latent_dim: dimens... | stack_v2_sparse_classes_75kplus_train_066971 | 1,116 | no_license | [
{
"docstring": "Initialize a new decoder network. Inputs: - latent_dim: dimension of the latent space.",
"name": "__init__",
"signature": "def __init__(self, input_dim, num_convblocks=3)"
},
{
"docstring": "Forward pass of the encoder network. Should not be called manually but by calling a model... | 2 | stack_v2_sparse_classes_30k_train_019119 | Implement the Python class `Decoder` described below.
Class description:
This is just a simple decoder with some upscaling convolutions. The last layer ends with a sigmoid to compress the output between 0 and 1 for a RGB image.
Method signatures and docstrings:
- def __init__(self, input_dim, num_convblocks=3): Initi... | Implement the Python class `Decoder` described below.
Class description:
This is just a simple decoder with some upscaling convolutions. The last layer ends with a sigmoid to compress the output between 0 and 1 for a RGB image.
Method signatures and docstrings:
- def __init__(self, input_dim, num_convblocks=3): Initi... | 05d959c9c41c9e4bff7ec12a69afd98dba14da00 | <|skeleton|>
class Decoder:
"""This is just a simple decoder with some upscaling convolutions. The last layer ends with a sigmoid to compress the output between 0 and 1 for a RGB image."""
def __init__(self, input_dim, num_convblocks=3):
"""Initialize a new decoder network. Inputs: - latent_dim: dimens... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Decoder:
"""This is just a simple decoder with some upscaling convolutions. The last layer ends with a sigmoid to compress the output between 0 and 1 for a RGB image."""
def __init__(self, input_dim, num_convblocks=3):
"""Initialize a new decoder network. Inputs: - latent_dim: dimension of the la... | the_stack_v2_python_sparse | implementation/Models/DeepFake/Decoder.py | JanFschr/FaceSwap-1 | train | 0 |
fb42951a51294cfff88ca441eb07fc9529dc8ddd | [
"self.msg_id = msg_id\nif failure_info is not None:\n ex_class = failure_info[0]\n ex = failure_info[1]\n tb = traceback.format_exception(*failure_info)\n if issubclass(ex_class, RemoteExceptionMixin):\n failure_data = {'c': ex.clazz, 'm': ex.module, 's': ex.message, 't': tb}\n else:\n ... | <|body_start_0|>
self.msg_id = msg_id
if failure_info is not None:
ex_class = failure_info[0]
ex = failure_info[1]
tb = traceback.format_exception(*failure_info)
if issubclass(ex_class, RemoteExceptionMixin):
failure_data = {'c': ex.clazz, ... | PikaOutgoingMessage implementation for RPC reply messages. It sets correlation_id AMQP property to link this reply with response | RpcReplyPikaOutgoingMessage | [
"Python-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RpcReplyPikaOutgoingMessage:
"""PikaOutgoingMessage implementation for RPC reply messages. It sets correlation_id AMQP property to link this reply with response"""
def __init__(self, pika_engine, msg_id, reply=None, failure_info=None, content_type=None):
"""Initialize with reply info... | stack_v2_sparse_classes_75kplus_train_066972 | 24,684 | permissive | [
{
"docstring": "Initialize with reply information for sending :param pika_engine: PikaEngine, shared object with configuration and shared driver functionality :param msg_id: String, msg_id of RPC request, which waits for reply :param reply: Dictionary, reply. In case of exception should be None :param failure_i... | 2 | stack_v2_sparse_classes_30k_train_037144 | Implement the Python class `RpcReplyPikaOutgoingMessage` described below.
Class description:
PikaOutgoingMessage implementation for RPC reply messages. It sets correlation_id AMQP property to link this reply with response
Method signatures and docstrings:
- def __init__(self, pika_engine, msg_id, reply=None, failure_... | Implement the Python class `RpcReplyPikaOutgoingMessage` described below.
Class description:
PikaOutgoingMessage implementation for RPC reply messages. It sets correlation_id AMQP property to link this reply with response
Method signatures and docstrings:
- def __init__(self, pika_engine, msg_id, reply=None, failure_... | c01951b33e278de9e769c2d0609c0be61d2cb26b | <|skeleton|>
class RpcReplyPikaOutgoingMessage:
"""PikaOutgoingMessage implementation for RPC reply messages. It sets correlation_id AMQP property to link this reply with response"""
def __init__(self, pika_engine, msg_id, reply=None, failure_info=None, content_type=None):
"""Initialize with reply info... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class RpcReplyPikaOutgoingMessage:
"""PikaOutgoingMessage implementation for RPC reply messages. It sets correlation_id AMQP property to link this reply with response"""
def __init__(self, pika_engine, msg_id, reply=None, failure_info=None, content_type=None):
"""Initialize with reply information for s... | the_stack_v2_python_sparse | filesystems/vnx_rootfs_lxc_ubuntu64-16.04-v025-openstack-compute/rootfs/usr/lib/python2.7/dist-packages/oslo_messaging/_drivers/pika_driver/pika_message.py | juancarlosdiaztorres/Ansible-OpenStack | train | 0 |
cbd0ef0ecb4c751f9bcaad01ca19239cb985318c | [
"id_asignacion = request.data['primary_key']\nasignacion = Asignacion.objects.get(id=id_asignacion)\nasignacion.delete()\nreturn Response({'mensaje': 'Cambio Aceptado'}, status=status.HTTP_200_OK)",
"participante_id = request.data['participante']\ngrupo_id = request.data['grupo']\ngrupos = Grupo.objects.get(id=gr... | <|body_start_0|>
id_asignacion = request.data['primary_key']
asignacion = Asignacion.objects.get(id=id_asignacion)
asignacion.delete()
return Response({'mensaje': 'Cambio Aceptado'}, status=status.HTTP_200_OK)
<|end_body_0|>
<|body_start_1|>
participante_id = request.data['parti... | AsignacionViewSet | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AsignacionViewSet:
def desactivar_asignacion(self, request, pk=None):
"""Método que elimina una asignación"""
<|body_0|>
def verificar_duplicidad(self, request, pk=None):
"""Metodo para ver si el participante esta asignado en otro grupo"""
<|body_1|>
<|end_s... | stack_v2_sparse_classes_75kplus_train_066973 | 13,765 | no_license | [
{
"docstring": "Método que elimina una asignación",
"name": "desactivar_asignacion",
"signature": "def desactivar_asignacion(self, request, pk=None)"
},
{
"docstring": "Metodo para ver si el participante esta asignado en otro grupo",
"name": "verificar_duplicidad",
"signature": "def veri... | 2 | stack_v2_sparse_classes_30k_train_019323 | Implement the Python class `AsignacionViewSet` described below.
Class description:
Implement the AsignacionViewSet class.
Method signatures and docstrings:
- def desactivar_asignacion(self, request, pk=None): Método que elimina una asignación
- def verificar_duplicidad(self, request, pk=None): Metodo para ver si el p... | Implement the Python class `AsignacionViewSet` described below.
Class description:
Implement the AsignacionViewSet class.
Method signatures and docstrings:
- def desactivar_asignacion(self, request, pk=None): Método que elimina una asignación
- def verificar_duplicidad(self, request, pk=None): Metodo para ver si el p... | 0e37786d7173abe820fd10b094ffcc2db9593a9c | <|skeleton|>
class AsignacionViewSet:
def desactivar_asignacion(self, request, pk=None):
"""Método que elimina una asignación"""
<|body_0|>
def verificar_duplicidad(self, request, pk=None):
"""Metodo para ver si el participante esta asignado en otro grupo"""
<|body_1|>
<|end_s... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AsignacionViewSet:
def desactivar_asignacion(self, request, pk=None):
"""Método que elimina una asignación"""
id_asignacion = request.data['primary_key']
asignacion = Asignacion.objects.get(id=id_asignacion)
asignacion.delete()
return Response({'mensaje': 'Cambio Acepta... | the_stack_v2_python_sparse | src/apps/cyd/api_views.py | jinchuika/app-suni | train | 7 | |
a0c114483329b253162e84fc8b70f93bd9eaa3e2 | [
"value = None\ncache = None\nprefix = None\nif self.should_cache():\n prefix = '%s:%s:string' % (self.get_cache_version(), self.get_cache_prefix())\n cache = router.router.get_cache(prefix)\n value = cache.get(prefix)\nif not value:\n value = super(CacheView, self).get_as_string(request, *args, **kwargs... | <|body_start_0|>
value = None
cache = None
prefix = None
if self.should_cache():
prefix = '%s:%s:string' % (self.get_cache_version(), self.get_cache_prefix())
cache = router.router.get_cache(prefix)
value = cache.get(prefix)
if not value:
... | A class based view that overrides the default dispatch method to determine the cache_prefix. If the cms view is available this class will inherit from there otherwise it will inherit from django's generic class View. :param cache_time: How long should we cache this attribute. This gets passed to django middleware and d... | CacheView | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CacheView:
"""A class based view that overrides the default dispatch method to determine the cache_prefix. If the cms view is available this class will inherit from there otherwise it will inherit from django's generic class View. :param cache_time: How long should we cache this attribute. This g... | stack_v2_sparse_classes_75kplus_train_066974 | 7,096 | permissive | [
{
"docstring": "Should only be used when inheriting from cms View. Gets the response as a string and caches it with a separate prefix",
"name": "get_as_string",
"signature": "def get_as_string(self, request, *args, **kwargs)"
},
{
"docstring": "Overrides Django's default dispatch to provide cach... | 2 | stack_v2_sparse_classes_30k_test_001934 | Implement the Python class `CacheView` described below.
Class description:
A class based view that overrides the default dispatch method to determine the cache_prefix. If the cms view is available this class will inherit from there otherwise it will inherit from django's generic class View. :param cache_time: How long... | Implement the Python class `CacheView` described below.
Class description:
A class based view that overrides the default dispatch method to determine the cache_prefix. If the cms view is available this class will inherit from there otherwise it will inherit from django's generic class View. :param cache_time: How long... | 9f5ac28618059eef99152214c7a90ad78151629e | <|skeleton|>
class CacheView:
"""A class based view that overrides the default dispatch method to determine the cache_prefix. If the cms view is available this class will inherit from there otherwise it will inherit from django's generic class View. :param cache_time: How long should we cache this attribute. This g... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CacheView:
"""A class based view that overrides the default dispatch method to determine the cache_prefix. If the cms view is available this class will inherit from there otherwise it will inherit from django's generic class View. :param cache_time: How long should we cache this attribute. This gets passed to... | the_stack_v2_python_sparse | scarlet/cache/views.py | markmiscavage/scarlet | train | 1 |
28539162ad213c238aa4d68bfe1f299cbb3069e9 | [
"self.global_weight = 1\nself.prevention_reductions = prevention_reductions\nself.env_scalars = env_type_scalars",
"weight = self.global_weight * self.env_scalars[environment.quality]\nif environment.preventions != None:\n n_masks = environment.mask_status[personA] + environment.mask_status[personB]\n weigh... | <|body_start_0|>
self.global_weight = 1
self.prevention_reductions = prevention_reductions
self.env_scalars = env_type_scalars
<|end_body_0|>
<|body_start_1|>
weight = self.global_weight * self.env_scalars[environment.quality]
if environment.preventions != None:
n_ma... | a transmission weighter object carries all parameters and functions that involve calculating weight for edges in the graph | TransmissionWeighter | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TransmissionWeighter:
"""a transmission weighter object carries all parameters and functions that involve calculating weight for edges in the graph"""
def __init__(self, env_type_scalars, prevention_reductions):
""":param env_type_scalars: dict must map to a scalar for each environme... | stack_v2_sparse_classes_75kplus_train_066975 | 45,926 | no_license | [
{
"docstring": ":param env_type_scalars: dict must map to a scalar for each environment type, for scaling weights :param prevention_reductions: dict must map prevention names, currently either 'masking' or 'distancing' to scalars",
"name": "__init__",
"signature": "def __init__(self, env_type_scalars, p... | 2 | null | Implement the Python class `TransmissionWeighter` described below.
Class description:
a transmission weighter object carries all parameters and functions that involve calculating weight for edges in the graph
Method signatures and docstrings:
- def __init__(self, env_type_scalars, prevention_reductions): :param env_t... | Implement the Python class `TransmissionWeighter` described below.
Class description:
a transmission weighter object carries all parameters and functions that involve calculating weight for edges in the graph
Method signatures and docstrings:
- def __init__(self, env_type_scalars, prevention_reductions): :param env_t... | 666dea33ca22347e9c0656b15cd80cc5cb42eae7 | <|skeleton|>
class TransmissionWeighter:
"""a transmission weighter object carries all parameters and functions that involve calculating weight for edges in the graph"""
def __init__(self, env_type_scalars, prevention_reductions):
""":param env_type_scalars: dict must map to a scalar for each environme... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TransmissionWeighter:
"""a transmission weighter object carries all parameters and functions that involve calculating weight for edges in the graph"""
def __init__(self, env_type_scalars, prevention_reductions):
""":param env_type_scalars: dict must map to a scalar for each environment type, for ... | the_stack_v2_python_sparse | PopulaceGraphModel/ge_simResults_good/2020-10-19_21-50-18/src/ModelToolkit_bak.py | FiveCrows/SIRsims | train | 0 |
b8352ef22b3ff5ab3435bfae9ae27192c503ac9f | [
"self.token = {'access_token': Mytest.access_token}\ntag_name = {'tag': {'name': '545656'}}\nhost = 'https://api.weixin.qq.com/cgi-bin/tags/create'\nr6 = ApiDefine().creatertagname(self.session, host, params=self.token, data=json.dumps(tag_name))\ntime.sleep(2)\nprint('创建标签', r6.text)",
"self.token = {'assess_tok... | <|body_start_0|>
self.token = {'access_token': Mytest.access_token}
tag_name = {'tag': {'name': '545656'}}
host = 'https://api.weixin.qq.com/cgi-bin/tags/create'
r6 = ApiDefine().creatertagname(self.session, host, params=self.token, data=json.dumps(tag_name))
time.sleep(2)
... | Mytest | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Mytest:
def test_createtag(self):
"""创建标签"""
<|body_0|>
def test_createtag30(self):
"""超过30个字符"""
<|body_1|>
def test_gettag(self):
"""获取标签列表"""
<|body_2|>
<|end_skeleton|>
<|body_start_0|>
self.token = {'access_token': Mytest.a... | stack_v2_sparse_classes_75kplus_train_066976 | 1,828 | no_license | [
{
"docstring": "创建标签",
"name": "test_createtag",
"signature": "def test_createtag(self)"
},
{
"docstring": "超过30个字符",
"name": "test_createtag30",
"signature": "def test_createtag30(self)"
},
{
"docstring": "获取标签列表",
"name": "test_gettag",
"signature": "def test_gettag(sel... | 3 | stack_v2_sparse_classes_30k_train_028692 | Implement the Python class `Mytest` described below.
Class description:
Implement the Mytest class.
Method signatures and docstrings:
- def test_createtag(self): 创建标签
- def test_createtag30(self): 超过30个字符
- def test_gettag(self): 获取标签列表 | Implement the Python class `Mytest` described below.
Class description:
Implement the Mytest class.
Method signatures and docstrings:
- def test_createtag(self): 创建标签
- def test_createtag30(self): 超过30个字符
- def test_gettag(self): 获取标签列表
<|skeleton|>
class Mytest:
def test_createtag(self):
"""创建标签"""
... | 7b790f675419224bfdbe1542eddc5a638982e68a | <|skeleton|>
class Mytest:
def test_createtag(self):
"""创建标签"""
<|body_0|>
def test_createtag30(self):
"""超过30个字符"""
<|body_1|>
def test_gettag(self):
"""获取标签列表"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Mytest:
def test_createtag(self):
"""创建标签"""
self.token = {'access_token': Mytest.access_token}
tag_name = {'tag': {'name': '545656'}}
host = 'https://api.weixin.qq.com/cgi-bin/tags/create'
r6 = ApiDefine().creatertagname(self.session, host, params=self.token, data=json... | the_stack_v2_python_sparse | P9/weixin_apitest/testcases/weixin_createtag.py | liousAlready/NewDream_learning | train | 0 | |
689aaed9359e63811b14a442acac827911ed8811 | [
"super().__init__()\nself.subsections = []\nself.create(pars)",
"self.heading = pars[0].title().replace('\\t', '')\nself.paragraphs = [self.parse_paragraph(p) for p in pars[1:]]\nself.create_subsections()\nself.strip_pars()",
"split_indices = [i for i in range(len(self.paragraphs)) if self.paragraphs[i] == '']\... | <|body_start_0|>
super().__init__()
self.subsections = []
self.create(pars)
<|end_body_0|>
<|body_start_1|>
self.heading = pars[0].title().replace('\t', '')
self.paragraphs = [self.parse_paragraph(p) for p in pars[1:]]
self.create_subsections()
self.strip_pars()
... | TODO Docs | Section | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Section:
"""TODO Docs"""
def __init__(self, pars):
"""TODO Docs"""
<|body_0|>
def create(self, pars):
"""TODO Docs"""
<|body_1|>
def create_subsections(self):
"""TODO Docs"""
<|body_2|>
def parse_paragraph(par: str):
"""T... | stack_v2_sparse_classes_75kplus_train_066977 | 6,946 | permissive | [
{
"docstring": "TODO Docs",
"name": "__init__",
"signature": "def __init__(self, pars)"
},
{
"docstring": "TODO Docs",
"name": "create",
"signature": "def create(self, pars)"
},
{
"docstring": "TODO Docs",
"name": "create_subsections",
"signature": "def create_subsections... | 5 | stack_v2_sparse_classes_30k_train_038905 | Implement the Python class `Section` described below.
Class description:
TODO Docs
Method signatures and docstrings:
- def __init__(self, pars): TODO Docs
- def create(self, pars): TODO Docs
- def create_subsections(self): TODO Docs
- def parse_paragraph(par: str): TODO Docs
- def __str__(self): TODO Docs | Implement the Python class `Section` described below.
Class description:
TODO Docs
Method signatures and docstrings:
- def __init__(self, pars): TODO Docs
- def create(self, pars): TODO Docs
- def create_subsections(self): TODO Docs
- def parse_paragraph(par: str): TODO Docs
- def __str__(self): TODO Docs
<|skeleton... | 6090f7b1c82e36625939edaa47a846abc10e70a0 | <|skeleton|>
class Section:
"""TODO Docs"""
def __init__(self, pars):
"""TODO Docs"""
<|body_0|>
def create(self, pars):
"""TODO Docs"""
<|body_1|>
def create_subsections(self):
"""TODO Docs"""
<|body_2|>
def parse_paragraph(par: str):
"""T... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Section:
"""TODO Docs"""
def __init__(self, pars):
"""TODO Docs"""
super().__init__()
self.subsections = []
self.create(pars)
def create(self, pars):
"""TODO Docs"""
self.heading = pars[0].title().replace('\t', '')
self.paragraphs = [self.parse... | the_stack_v2_python_sparse | backend/backend/resume/scripts.py | epm0dev/personal-website | train | 1 |
cdd6d3f86cb6b835fb751b5260be3eaa29ee6a31 | [
"response = await self.response\nif not response.code.is_successful():\n raise error.ResponseWrappingError(response)\nreturn response",
"try:\n return await self.response\nexcept error.RenderableError as e:\n return e.to_message()\nexcept Exception:\n return Message(code=INTERNAL_SERVER_ERROR)"
] | <|body_start_0|>
response = await self.response
if not response.code.is_successful():
raise error.ResponseWrappingError(response)
return response
<|end_body_0|>
<|body_start_1|>
try:
return await self.response
except error.RenderableError as e:
... | A utility class that offers the :attr:`response_raising` and :attr:`response_nonraising` alternatives to waiting for the :attr:`response` future whose error states can be presented either as an unsuccessful response (eg. 4.04) or an exception. It also provides some internal tools for handling anything that has a :attr:... | BaseUnicastRequest | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BaseUnicastRequest:
"""A utility class that offers the :attr:`response_raising` and :attr:`response_nonraising` alternatives to waiting for the :attr:`response` future whose error states can be presented either as an unsuccessful response (eg. 4.04) or an exception. It also provides some internal... | stack_v2_sparse_classes_75kplus_train_066978 | 43,955 | permissive | [
{
"docstring": "An awaitable that returns if a response comes in and is successful, otherwise raises generic network exception or a :class:`.error.ResponseWrappingError` for unsuccessful responses. Experimental Interface.",
"name": "response_raising",
"signature": "async def response_raising(self)"
},... | 2 | stack_v2_sparse_classes_30k_train_018966 | Implement the Python class `BaseUnicastRequest` described below.
Class description:
A utility class that offers the :attr:`response_raising` and :attr:`response_nonraising` alternatives to waiting for the :attr:`response` future whose error states can be presented either as an unsuccessful response (eg. 4.04) or an ex... | Implement the Python class `BaseUnicastRequest` described below.
Class description:
A utility class that offers the :attr:`response_raising` and :attr:`response_nonraising` alternatives to waiting for the :attr:`response` future whose error states can be presented either as an unsuccessful response (eg. 4.04) or an ex... | 66bd6f66b5ba9f17c5c688dfae51a3aace7e0070 | <|skeleton|>
class BaseUnicastRequest:
"""A utility class that offers the :attr:`response_raising` and :attr:`response_nonraising` alternatives to waiting for the :attr:`response` future whose error states can be presented either as an unsuccessful response (eg. 4.04) or an exception. It also provides some internal... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class BaseUnicastRequest:
"""A utility class that offers the :attr:`response_raising` and :attr:`response_nonraising` alternatives to waiting for the :attr:`response` future whose error states can be presented either as an unsuccessful response (eg. 4.04) or an exception. It also provides some internal tools for ha... | the_stack_v2_python_sparse | aiocoap/protocol.py | chrysn/aiocoap | train | 258 |
942f7e2ac06f33815a91e6f04e0527deb23a6d66 | [
"expected_result = np.array([[0.0125, 0.03125, 0.196875, 0.03125, 0.0125], [0.025, 0.0625, 0.29375, 0.0625, 0.025], [0.05, 0.125, 0.3375, 0.125, 0.05], [0.0, 0.0, 0.175, 0.0, 0.0], [0.0, 0.0, 0.1, 0.0, 0.0]])\nresult = RecursiveFilter(edge_width=1)._recurse_backward(self.cube.data[0, :], self.smoothing_coefficients... | <|body_start_0|>
expected_result = np.array([[0.0125, 0.03125, 0.196875, 0.03125, 0.0125], [0.025, 0.0625, 0.29375, 0.0625, 0.025], [0.05, 0.125, 0.3375, 0.125, 0.05], [0.0, 0.0, 0.175, 0.0, 0.0], [0.0, 0.0, 0.1, 0.0, 0.0]])
result = RecursiveFilter(edge_width=1)._recurse_backward(self.cube.data[0, :], ... | Test the _recurse_backward method | Test__recurse_backward | [
"BSD-3-Clause",
"LicenseRef-scancode-proprietary-license"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Test__recurse_backward:
"""Test the _recurse_backward method"""
def test_first_axis(self):
"""Test that the returned _recurse_backward array has the expected type and result."""
<|body_0|>
def test_second_axis(self):
"""Test that the returned _recurse_backward ar... | stack_v2_sparse_classes_75kplus_train_066979 | 22,857 | permissive | [
{
"docstring": "Test that the returned _recurse_backward array has the expected type and result.",
"name": "test_first_axis",
"signature": "def test_first_axis(self)"
},
{
"docstring": "Test that the returned _recurse_backward array has the expected type and result.",
"name": "test_second_ax... | 2 | stack_v2_sparse_classes_30k_train_041409 | Implement the Python class `Test__recurse_backward` described below.
Class description:
Test the _recurse_backward method
Method signatures and docstrings:
- def test_first_axis(self): Test that the returned _recurse_backward array has the expected type and result.
- def test_second_axis(self): Test that the returned... | Implement the Python class `Test__recurse_backward` described below.
Class description:
Test the _recurse_backward method
Method signatures and docstrings:
- def test_first_axis(self): Test that the returned _recurse_backward array has the expected type and result.
- def test_second_axis(self): Test that the returned... | cd2c9019944345df1e703bf8f625db537ad9f559 | <|skeleton|>
class Test__recurse_backward:
"""Test the _recurse_backward method"""
def test_first_axis(self):
"""Test that the returned _recurse_backward array has the expected type and result."""
<|body_0|>
def test_second_axis(self):
"""Test that the returned _recurse_backward ar... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Test__recurse_backward:
"""Test the _recurse_backward method"""
def test_first_axis(self):
"""Test that the returned _recurse_backward array has the expected type and result."""
expected_result = np.array([[0.0125, 0.03125, 0.196875, 0.03125, 0.0125], [0.025, 0.0625, 0.29375, 0.0625, 0.02... | the_stack_v2_python_sparse | improver_tests/nbhood/recursive_filter/test_RecursiveFilter.py | metoppv/improver | train | 101 |
204837e6365227f2b5c9259cee61720831530093 | [
"f = self.RequiredForm()\np = f.as_p()\nself.assert_('<input type=\"file\" name=\"files[]\" id=\"id_files0\" />' in p)",
"f = self.MultiForm()\np = f.as_p()\nself.assert_('<input type=\"file\" name=\"files[]\" id=\"id_files0\" />' in p)\nself.assert_('<input type=\"file\" name=\"files[]\" id=\"id_files1\" />' in ... | <|body_start_0|>
f = self.RequiredForm()
p = f.as_p()
self.assert_('<input type="file" name="files[]" id="id_files0" />' in p)
<|end_body_0|>
<|body_start_1|>
f = self.MultiForm()
p = f.as_p()
self.assert_('<input type="file" name="files[]" id="id_files0" />' in p)
... | Tests that MultiFileField field. | MultiFileFieldTest | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MultiFileFieldTest:
"""Tests that MultiFileField field."""
def testOneRender(self):
"""Test the rendering of a MultiFileField with 1 input box."""
<|body_0|>
def testTwoRender(self):
"""Test the rendering of a MultiFileField with 2 input boxes."""
<|body_... | stack_v2_sparse_classes_75kplus_train_066980 | 3,598 | no_license | [
{
"docstring": "Test the rendering of a MultiFileField with 1 input box.",
"name": "testOneRender",
"signature": "def testOneRender(self)"
},
{
"docstring": "Test the rendering of a MultiFileField with 2 input boxes.",
"name": "testTwoRender",
"signature": "def testTwoRender(self)"
},
... | 4 | stack_v2_sparse_classes_30k_test_002566 | Implement the Python class `MultiFileFieldTest` described below.
Class description:
Tests that MultiFileField field.
Method signatures and docstrings:
- def testOneRender(self): Test the rendering of a MultiFileField with 1 input box.
- def testTwoRender(self): Test the rendering of a MultiFileField with 2 input boxe... | Implement the Python class `MultiFileFieldTest` described below.
Class description:
Tests that MultiFileField field.
Method signatures and docstrings:
- def testOneRender(self): Test the rendering of a MultiFileField with 1 input box.
- def testTwoRender(self): Test the rendering of a MultiFileField with 2 input boxe... | 2791145f62a7e296be859a400499812b394249e9 | <|skeleton|>
class MultiFileFieldTest:
"""Tests that MultiFileField field."""
def testOneRender(self):
"""Test the rendering of a MultiFileField with 1 input box."""
<|body_0|>
def testTwoRender(self):
"""Test the rendering of a MultiFileField with 2 input boxes."""
<|body_... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MultiFileFieldTest:
"""Tests that MultiFileField field."""
def testOneRender(self):
"""Test the rendering of a MultiFileField with 1 input box."""
f = self.RequiredForm()
p = f.as_p()
self.assert_('<input type="file" name="files[]" id="id_files0" />' in p)
def testTwo... | the_stack_v2_python_sparse | combaragi/ccboard/tests.py | yonseics/yonseics | train | 1 |
951d03847e11ef5a80a9a7becd95a904fac31a6f | [
"try:\n self.wait(5).until(EC.presence_of_element_located(self.login_locator))\n user_is_loggedin = False\nexcept:\n user_is_loggedin = True\nreturn user_is_loggedin",
"if self.is_user_loggedin() != True:\n user_name_element = self.wait().until(EC.visibility_of_element_located(self.user_name_locator),... | <|body_start_0|>
try:
self.wait(5).until(EC.presence_of_element_located(self.login_locator))
user_is_loggedin = False
except:
user_is_loggedin = True
return user_is_loggedin
<|end_body_0|>
<|body_start_1|>
if self.is_user_loggedin() != True:
... | Contains Login UI page locators Login function | LoginPage | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LoginPage:
"""Contains Login UI page locators Login function"""
def is_user_loggedin(self):
"""Check if the user is already logged in or not :return: True/False"""
<|body_0|>
def perform_login(self, user_name, password):
"""Implementing Login functionality :param... | stack_v2_sparse_classes_75kplus_train_066981 | 1,890 | no_license | [
{
"docstring": "Check if the user is already logged in or not :return: True/False",
"name": "is_user_loggedin",
"signature": "def is_user_loggedin(self)"
},
{
"docstring": "Implementing Login functionality :param user_name: :param password: :return:",
"name": "perform_login",
"signature"... | 2 | stack_v2_sparse_classes_30k_train_001204 | Implement the Python class `LoginPage` described below.
Class description:
Contains Login UI page locators Login function
Method signatures and docstrings:
- def is_user_loggedin(self): Check if the user is already logged in or not :return: True/False
- def perform_login(self, user_name, password): Implementing Login... | Implement the Python class `LoginPage` described below.
Class description:
Contains Login UI page locators Login function
Method signatures and docstrings:
- def is_user_loggedin(self): Check if the user is already logged in or not :return: True/False
- def perform_login(self, user_name, password): Implementing Login... | 6b8830b702e41b73d3b55b9db957635890453414 | <|skeleton|>
class LoginPage:
"""Contains Login UI page locators Login function"""
def is_user_loggedin(self):
"""Check if the user is already logged in or not :return: True/False"""
<|body_0|>
def perform_login(self, user_name, password):
"""Implementing Login functionality :param... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class LoginPage:
"""Contains Login UI page locators Login function"""
def is_user_loggedin(self):
"""Check if the user is already logged in or not :return: True/False"""
try:
self.wait(5).until(EC.presence_of_element_located(self.login_locator))
user_is_loggedin = False
... | the_stack_v2_python_sparse | Test_Automation/TestFramework/Libraries/Pages/login_page.py | praveenreddynarala/RobotFramework | train | 0 |
1b8966dab0538a1e9b8ed464c26ff46fe285eed0 | [
"if not intervals:\n return 0\nintervals.sort()\nroom_num = 1\nrooms = [[] for _ in intervals]\nrooms[0].append(intervals[0])\nfor i in range(1, len(intervals)):\n for j in range(len(rooms)):\n if rooms[j] != []:\n last_int = rooms[j][-1]\n if intervals[i][0] >= last_int[1]:\n ... | <|body_start_0|>
if not intervals:
return 0
intervals.sort()
room_num = 1
rooms = [[] for _ in intervals]
rooms[0].append(intervals[0])
for i in range(1, len(intervals)):
for j in range(len(rooms)):
if rooms[j] != []:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def minMeetingRooms(self, intervals):
"""Algorithm: go through all the intervals, and see if current interval can be added to a existing room, if not, create a new room for current interval return the final number of rooms created"""
<|body_0|>
def minMeetingRoomsH... | stack_v2_sparse_classes_75kplus_train_066982 | 2,318 | no_license | [
{
"docstring": "Algorithm: go through all the intervals, and see if current interval can be added to a existing room, if not, create a new room for current interval return the final number of rooms created",
"name": "minMeetingRooms",
"signature": "def minMeetingRooms(self, intervals)"
},
{
"doc... | 2 | stack_v2_sparse_classes_30k_train_051814 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def minMeetingRooms(self, intervals): Algorithm: go through all the intervals, and see if current interval can be added to a existing room, if not, create a new room for current ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def minMeetingRooms(self, intervals): Algorithm: go through all the intervals, and see if current interval can be added to a existing room, if not, create a new room for current ... | 7eddbc93a237d1d5cabcdc67806b01ff55ea8562 | <|skeleton|>
class Solution:
def minMeetingRooms(self, intervals):
"""Algorithm: go through all the intervals, and see if current interval can be added to a existing room, if not, create a new room for current interval return the final number of rooms created"""
<|body_0|>
def minMeetingRoomsH... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def minMeetingRooms(self, intervals):
"""Algorithm: go through all the intervals, and see if current interval can be added to a existing room, if not, create a new room for current interval return the final number of rooms created"""
if not intervals:
return 0
int... | the_stack_v2_python_sparse | LeetCode Problems/Array/Meeting Rooms II.py | GZHOUW/Algorithm | train | 0 | |
63ecff1f4c873a82cf948bd1b905c127a90cbd43 | [
"in0 = np.random.rand(1, 1)\nin1 = np.random.rand(4000, 4000)\ncheck0 = sps.medfilt2d(in0, 5)\ncheck1 = sps.medfilt2d(in1, 5)\nself.assertTrue(np.allclose(check0, mf.MedianFilter(kernel_size=5, input=[in0])[0]))\nself.assertTrue(np.allclose(check1, mf.MedianFilter(kernel_size=5, input=[in1])[0]))",
"in0 = np.rand... | <|body_start_0|>
in0 = np.random.rand(1, 1)
in1 = np.random.rand(4000, 4000)
check0 = sps.medfilt2d(in0, 5)
check1 = sps.medfilt2d(in1, 5)
self.assertTrue(np.allclose(check0, mf.MedianFilter(kernel_size=5, input=[in0])[0]))
self.assertTrue(np.allclose(check1, mf.MedianFil... | BigTest | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BigTest:
def testFivebyFive(self):
"""Test using a 5x5 window"""
<|body_0|>
def testNinebyNine(self):
"""Test using a 9x9 window"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
in0 = np.random.rand(1, 1)
in1 = np.random.rand(4000, 4000)
... | stack_v2_sparse_classes_75kplus_train_066983 | 902 | no_license | [
{
"docstring": "Test using a 5x5 window",
"name": "testFivebyFive",
"signature": "def testFivebyFive(self)"
},
{
"docstring": "Test using a 9x9 window",
"name": "testNinebyNine",
"signature": "def testNinebyNine(self)"
}
] | 2 | null | Implement the Python class `BigTest` described below.
Class description:
Implement the BigTest class.
Method signatures and docstrings:
- def testFivebyFive(self): Test using a 5x5 window
- def testNinebyNine(self): Test using a 9x9 window | Implement the Python class `BigTest` described below.
Class description:
Implement the BigTest class.
Method signatures and docstrings:
- def testFivebyFive(self): Test using a 5x5 window
- def testNinebyNine(self): Test using a 9x9 window
<|skeleton|>
class BigTest:
def testFivebyFive(self):
"""Test us... | c02e4d3bb3b3959e1be43e46cbc0fa38c900ee7d | <|skeleton|>
class BigTest:
def testFivebyFive(self):
"""Test using a 5x5 window"""
<|body_0|>
def testNinebyNine(self):
"""Test using a 9x9 window"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class BigTest:
def testFivebyFive(self):
"""Test using a 5x5 window"""
in0 = np.random.rand(1, 1)
in1 = np.random.rand(4000, 4000)
check0 = sps.medfilt2d(in0, 5)
check1 = sps.medfilt2d(in1, 5)
self.assertTrue(np.allclose(check0, mf.MedianFilter(kernel_size=5, input=[i... | the_stack_v2_python_sparse | mf/test_big.py | Jackmastr/cuda_sandbox | train | 0 | |
d3cf85de89fc4da88cb6c583465f2d232ee3017d | [
"engine = db_connect()\ncreate_table(engine)\nself.Session = sessionmaker(bind=engine)",
"session = self.Session()\nyoutube_db = YoutubeCelebrityInfoDB()\nyoutube_db.keyword = item['keyword']\nyoutube_db.name = item['name']\nyoutube_db.homepage_link = item['homepage_link']\nyoutube_db.description = item['descript... | <|body_start_0|>
engine = db_connect()
create_table(engine)
self.Session = sessionmaker(bind=engine)
<|end_body_0|>
<|body_start_1|>
session = self.Session()
youtube_db = YoutubeCelebrityInfoDB()
youtube_db.keyword = item['keyword']
youtube_db.name = item['name']... | YoutubeCelebrityInfoPipeline | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class YoutubeCelebrityInfoPipeline:
def __init__(self):
"""Initializes database connection and sessionmaker. Creates deals table."""
<|body_0|>
def process_item(self, item, spider):
"""Save deals in the database. This method is called for every item pipeline component."""
... | stack_v2_sparse_classes_75kplus_train_066984 | 2,658 | no_license | [
{
"docstring": "Initializes database connection and sessionmaker. Creates deals table.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Save deals in the database. This method is called for every item pipeline component.",
"name": "process_item",
"signature": "d... | 2 | null | Implement the Python class `YoutubeCelebrityInfoPipeline` described below.
Class description:
Implement the YoutubeCelebrityInfoPipeline class.
Method signatures and docstrings:
- def __init__(self): Initializes database connection and sessionmaker. Creates deals table.
- def process_item(self, item, spider): Save de... | Implement the Python class `YoutubeCelebrityInfoPipeline` described below.
Class description:
Implement the YoutubeCelebrityInfoPipeline class.
Method signatures and docstrings:
- def __init__(self): Initializes database connection and sessionmaker. Creates deals table.
- def process_item(self, item, spider): Save de... | 2af304f7971a60569ed51a1fb157299426919b08 | <|skeleton|>
class YoutubeCelebrityInfoPipeline:
def __init__(self):
"""Initializes database connection and sessionmaker. Creates deals table."""
<|body_0|>
def process_item(self, item, spider):
"""Save deals in the database. This method is called for every item pipeline component."""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class YoutubeCelebrityInfoPipeline:
def __init__(self):
"""Initializes database connection and sessionmaker. Creates deals table."""
engine = db_connect()
create_table(engine)
self.Session = sessionmaker(bind=engine)
def process_item(self, item, spider):
"""Save deals in... | the_stack_v2_python_sparse | scrapy_spider/pipelines_.py | windshallow/youtube_scraper | train | 1 | |
a57776d7e32d4849b590e837cbcf4b5fd735f187 | [
"cmd = 'sound = ' + self._val(reg)\nself.exc.execs(cmd)\nreturn f'{self.i}: ' + cmd",
"if int(self._val(reg)) != 0:\n m = '{}: sound = {}'.format(self.i, self.exc.sbox_locals['sound'])\n raise StopIteration(m)"
] | <|body_start_0|>
cmd = 'sound = ' + self._val(reg)
self.exc.execs(cmd)
return f'{self.i}: ' + cmd
<|end_body_0|>
<|body_start_1|>
if int(self._val(reg)) != 0:
m = '{}: sound = {}'.format(self.i, self.exc.sbox_locals['sound'])
raise StopIteration(m)
<|end_body_1|>... | Part1Program | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Part1Program:
def _snd(self, reg: str) -> str:
"""An implementation of Interpreter.snd() for Part 1 of the puzzle"""
<|body_0|>
def _rcv(self, reg: str):
"""An implementation of Interpreter.rcv() for Part 1 of the puzzle"""
<|body_1|>
<|end_skeleton|>
<|bod... | stack_v2_sparse_classes_75kplus_train_066985 | 6,238 | no_license | [
{
"docstring": "An implementation of Interpreter.snd() for Part 1 of the puzzle",
"name": "_snd",
"signature": "def _snd(self, reg: str) -> str"
},
{
"docstring": "An implementation of Interpreter.rcv() for Part 1 of the puzzle",
"name": "_rcv",
"signature": "def _rcv(self, reg: str)"
... | 2 | stack_v2_sparse_classes_30k_train_016555 | Implement the Python class `Part1Program` described below.
Class description:
Implement the Part1Program class.
Method signatures and docstrings:
- def _snd(self, reg: str) -> str: An implementation of Interpreter.snd() for Part 1 of the puzzle
- def _rcv(self, reg: str): An implementation of Interpreter.rcv() for Pa... | Implement the Python class `Part1Program` described below.
Class description:
Implement the Part1Program class.
Method signatures and docstrings:
- def _snd(self, reg: str) -> str: An implementation of Interpreter.snd() for Part 1 of the puzzle
- def _rcv(self, reg: str): An implementation of Interpreter.rcv() for Pa... | 60d33ddbc138e265e1248259fb6777fc02407f0f | <|skeleton|>
class Part1Program:
def _snd(self, reg: str) -> str:
"""An implementation of Interpreter.snd() for Part 1 of the puzzle"""
<|body_0|>
def _rcv(self, reg: str):
"""An implementation of Interpreter.rcv() for Part 1 of the puzzle"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Part1Program:
def _snd(self, reg: str) -> str:
"""An implementation of Interpreter.snd() for Part 1 of the puzzle"""
cmd = 'sound = ' + self._val(reg)
self.exc.execs(cmd)
return f'{self.i}: ' + cmd
def _rcv(self, reg: str):
"""An implementation of Interpreter.rcv()... | the_stack_v2_python_sparse | 18_duet.py | davidstaab/AOC17 | train | 0 | |
5b82728ecdb8af261742df9cdf47c4237b1d2a6e | [
"osh = ObjectStateHolder('mscsresource')\nosh.setAttribute('data_name', resource.name)\nif resource.details:\n details = resource.details\n if details.description:\n osh.setStringAttribute('data_description', details.description)\n if details.type is not None:\n osh.setStringAttribute('type',... | <|body_start_0|>
osh = ObjectStateHolder('mscsresource')
osh.setAttribute('data_name', resource.name)
if resource.details:
details = resource.details
if details.description:
osh.setStringAttribute('data_description', details.description)
if det... | ResourceBuilder | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ResourceBuilder:
def buildResource(self, resource):
"""@types: Resource -> ObjectStateHolder"""
<|body_0|>
def buildResourcePdo(self, pdo):
"""@types: Builder.Pdo -> ObjectStateHolder"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
osh = ObjectState... | stack_v2_sparse_classes_75kplus_train_066986 | 15,554 | no_license | [
{
"docstring": "@types: Resource -> ObjectStateHolder",
"name": "buildResource",
"signature": "def buildResource(self, resource)"
},
{
"docstring": "@types: Builder.Pdo -> ObjectStateHolder",
"name": "buildResourcePdo",
"signature": "def buildResourcePdo(self, pdo)"
}
] | 2 | stack_v2_sparse_classes_30k_train_047844 | Implement the Python class `ResourceBuilder` described below.
Class description:
Implement the ResourceBuilder class.
Method signatures and docstrings:
- def buildResource(self, resource): @types: Resource -> ObjectStateHolder
- def buildResourcePdo(self, pdo): @types: Builder.Pdo -> ObjectStateHolder | Implement the Python class `ResourceBuilder` described below.
Class description:
Implement the ResourceBuilder class.
Method signatures and docstrings:
- def buildResource(self, resource): @types: Resource -> ObjectStateHolder
- def buildResourcePdo(self, pdo): @types: Builder.Pdo -> ObjectStateHolder
<|skeleton|>
c... | c431e809e8d0f82e1bca7e3429dd0245560b5680 | <|skeleton|>
class ResourceBuilder:
def buildResource(self, resource):
"""@types: Resource -> ObjectStateHolder"""
<|body_0|>
def buildResourcePdo(self, pdo):
"""@types: Builder.Pdo -> ObjectStateHolder"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ResourceBuilder:
def buildResource(self, resource):
"""@types: Resource -> ObjectStateHolder"""
osh = ObjectStateHolder('mscsresource')
osh.setAttribute('data_name', resource.name)
if resource.details:
details = resource.details
if details.description:
... | the_stack_v2_python_sparse | reference/ucmdb/discovery/ms_cluster.py | madmonkyang/cda-record | train | 0 | |
5c85b8021c67cf302622c215b1e7b4d784c0cb2d | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn IntelligenceProfile()",
"from ..entity import Entity\nfrom .formatted_content import FormattedContent\nfrom .intelligence_profile_country_or_region_of_origin import IntelligenceProfileCountryOrRegionOfOrigin\nfrom .intelligence_profile... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return IntelligenceProfile()
<|end_body_0|>
<|body_start_1|>
from ..entity import Entity
from .formatted_content import FormattedContent
from .intelligence_profile_country_or_region_of_... | IntelligenceProfile | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IntelligenceProfile:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> IntelligenceProfile:
"""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 ob... | stack_v2_sparse_classes_75kplus_train_066987 | 6,060 | 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: IntelligenceProfile",
"name": "create_from_discriminator_value",
"signature": "def create_from_discriminator... | 3 | stack_v2_sparse_classes_30k_train_041896 | Implement the Python class `IntelligenceProfile` described below.
Class description:
Implement the IntelligenceProfile class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> IntelligenceProfile: Creates a new instance of the appropriate class based on d... | Implement the Python class `IntelligenceProfile` described below.
Class description:
Implement the IntelligenceProfile class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> IntelligenceProfile: Creates a new instance of the appropriate class based on d... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class IntelligenceProfile:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> IntelligenceProfile:
"""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 ob... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class IntelligenceProfile:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> IntelligenceProfile:
"""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: ... | the_stack_v2_python_sparse | msgraph/generated/models/security/intelligence_profile.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
0fc1fb19b44468dcc64c18ab486eba23e4edf1a4 | [
"if not txt:\n raise error.BadArgument('Empty Object ID')\nobjid_s = string.split(txt, '.')\nobjid_s = filter(lambda x: len(x), objid_s)\ntry:\n objid_n = map(lambda x: string.atol(x), objid_s)\nexcept:\n raise error.BadArgument('Malformed Object ID: ' + str(txt))\nif not len(objid_n):\n raise error.Bad... | <|body_start_0|>
if not txt:
raise error.BadArgument('Empty Object ID')
objid_s = string.split(txt, '.')
objid_s = filter(lambda x: len(x), objid_s)
try:
objid_n = map(lambda x: string.atol(x), objid_s)
except:
raise error.BadArgument('Malforme... | Implement various convertions of ASN1 Object ID's value | objid | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class objid:
"""Implement various convertions of ASN1 Object ID's value"""
def str2nums(self, txt):
"""str2nums(obj_id) -> object id Convert Object ID (given as string) into a list of integer sub IDs."""
<|body_0|>
def nums2str(self, objid_n):
"""nums2str(obj_id) -> ob... | stack_v2_sparse_classes_75kplus_train_066988 | 1,815 | no_license | [
{
"docstring": "str2nums(obj_id) -> object id Convert Object ID (given as string) into a list of integer sub IDs.",
"name": "str2nums",
"signature": "def str2nums(self, txt)"
},
{
"docstring": "nums2str(obj_id) -> object id Convert Object ID (given as a list of integer sub Object IDs) into strin... | 2 | stack_v2_sparse_classes_30k_val_000771 | Implement the Python class `objid` described below.
Class description:
Implement various convertions of ASN1 Object ID's value
Method signatures and docstrings:
- def str2nums(self, txt): str2nums(obj_id) -> object id Convert Object ID (given as string) into a list of integer sub IDs.
- def nums2str(self, objid_n): n... | Implement the Python class `objid` described below.
Class description:
Implement various convertions of ASN1 Object ID's value
Method signatures and docstrings:
- def str2nums(self, txt): str2nums(obj_id) -> object id Convert Object ID (given as string) into a list of integer sub IDs.
- def nums2str(self, objid_n): n... | f7f5edd58527a3ad98497b994f5d1b6d4c2c8b25 | <|skeleton|>
class objid:
"""Implement various convertions of ASN1 Object ID's value"""
def str2nums(self, txt):
"""str2nums(obj_id) -> object id Convert Object ID (given as string) into a list of integer sub IDs."""
<|body_0|>
def nums2str(self, objid_n):
"""nums2str(obj_id) -> ob... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class objid:
"""Implement various convertions of ASN1 Object ID's value"""
def str2nums(self, txt):
"""str2nums(obj_id) -> object id Convert Object ID (given as string) into a list of integer sub IDs."""
if not txt:
raise error.BadArgument('Empty Object ID')
objid_s = string... | the_stack_v2_python_sparse | eddie/eddietool/common/Extra/pysnmp/objid.py | dimasajipangestu/belajarpostgres2 | train | 0 |
79197e702409d13ab78abb8bb7dec1b13ca98275 | [
"if not root:\n return ''\nqueue = deque([root])\nret = []\nwhile queue:\n n = queue.popleft()\n if n is not None:\n ret.append(str(n.val))\n queue.append(n.left)\n queue.append(n.right)\n else:\n ret.append('.')\nwhile ret[-1] == '.':\n ret.pop()\nreturn '_'.join(ret)",
... | <|body_start_0|>
if not root:
return ''
queue = deque([root])
ret = []
while queue:
n = queue.popleft()
if n is not None:
ret.append(str(n.val))
queue.append(n.left)
queue.append(n.right)
else... | 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_75kplus_train_066989 | 3,577 | no_license | [
{
"docstring": "Encodes a tree to a single string. :type root: TreeNode :rtype: str",
"name": "serialize",
"signature": "def serialize(self, root)"
},
{
"docstring": "Decodes your encoded data to tree. :type data: str :rtype: TreeNode",
"name": "deserialize",
"signature": "def deserializ... | 2 | stack_v2_sparse_classes_30k_train_050875 | 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:... | 1389a009a02e90e8700a7a00e0b7f797c129cdf4 | <|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_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
if not root:
return ''
queue = deque([root])
ret = []
while queue:
n = queue.popleft()
if n is not None:
ret.a... | the_stack_v2_python_sparse | leetcode/solved/297_Serialize_and_Deserialize_Binary_Tree/solution.py | sungminoh/algorithms | train | 0 | |
00a16404f30a7f2e6baa4e684ec4435e5ae5287a | [
"self.corpora = self.process_corpora(corporaList, stopwords_f)\nprint('loading pre-trained w2v model...')\ntic = time.time()\nif pretrained_w2v:\n self.w2v_model = pretrained_w2v\nelif w2v_f.endswith('.bin'):\n self.w2v_model = gensim.models.KeyedVectors.load_word2vec_format(w2v_f, binary=True)\nelse:\n se... | <|body_start_0|>
self.corpora = self.process_corpora(corporaList, stopwords_f)
print('loading pre-trained w2v model...')
tic = time.time()
if pretrained_w2v:
self.w2v_model = pretrained_w2v
elif w2v_f.endswith('.bin'):
self.w2v_model = gensim.models.KeyedV... | W2VModel | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class W2VModel:
def __init__(self, corporaList, w2v_f, stopwords_f, pretrained_w2v=None, saved_corpora_vec_M=None):
"""实现使用语言模型对句子和句子, 词语对句子的匹配. 初始化模型: StatisticModel(corpora) Args: corporaList: 多个语料组成的列表, 应该是一个嵌套Python列表. For example: [["There", "is", "a", "cat"], ["There", "is", "a", "dog"],... | stack_v2_sparse_classes_75kplus_train_066990 | 8,398 | no_license | [
{
"docstring": "实现使用语言模型对句子和句子, 词语对句子的匹配. 初始化模型: StatisticModel(corpora) Args: corporaList: 多个语料组成的列表, 应该是一个嵌套Python列表. For example: [[\"There\", \"is\", \"a\", \"cat\"], [\"There\", \"is\", \"a\", \"dog\"], [\"There\", \"is\", \"a\", \"wolf\"]] w2v_f: str, 预训练的词向量文件路径 stopwords_f: str, 停用词文件 pretrained_w2v: ge... | 6 | stack_v2_sparse_classes_30k_train_024885 | Implement the Python class `W2VModel` described below.
Class description:
Implement the W2VModel class.
Method signatures and docstrings:
- def __init__(self, corporaList, w2v_f, stopwords_f, pretrained_w2v=None, saved_corpora_vec_M=None): 实现使用语言模型对句子和句子, 词语对句子的匹配. 初始化模型: StatisticModel(corpora) Args: corporaList: 多个... | Implement the Python class `W2VModel` described below.
Class description:
Implement the W2VModel class.
Method signatures and docstrings:
- def __init__(self, corporaList, w2v_f, stopwords_f, pretrained_w2v=None, saved_corpora_vec_M=None): 实现使用语言模型对句子和句子, 词语对句子的匹配. 初始化模型: StatisticModel(corpora) Args: corporaList: 多个... | c2a20a430de197d06dca5ada96160388730a5db5 | <|skeleton|>
class W2VModel:
def __init__(self, corporaList, w2v_f, stopwords_f, pretrained_w2v=None, saved_corpora_vec_M=None):
"""实现使用语言模型对句子和句子, 词语对句子的匹配. 初始化模型: StatisticModel(corpora) Args: corporaList: 多个语料组成的列表, 应该是一个嵌套Python列表. For example: [["There", "is", "a", "cat"], ["There", "is", "a", "dog"],... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class W2VModel:
def __init__(self, corporaList, w2v_f, stopwords_f, pretrained_w2v=None, saved_corpora_vec_M=None):
"""实现使用语言模型对句子和句子, 词语对句子的匹配. 初始化模型: StatisticModel(corpora) Args: corporaList: 多个语料组成的列表, 应该是一个嵌套Python列表. For example: [["There", "is", "a", "cat"], ["There", "is", "a", "dog"], ["There", "is... | the_stack_v2_python_sparse | Models/Word2Vec/API/Word2VecModel.py | JaMesLiMers/Image_Retrieval_Framework_FYP | train | 2 | |
56183902770fadcf1e11ffbfda8ff0b569ab8b12 | [
"self._buff = ''\nself._termDeferred = termDeferred\nself._escalation = 0\nself._stopCall = None",
"self._buff += data\nlines = [line for line in self._buff.split('\\n')]\nself._buff = lines[-1]\nfor line in lines[:-1]:\n log.msg(line)",
"if reason.value.exitCode != 0:\n log.msg(reason)\nself._escalation ... | <|body_start_0|>
self._buff = ''
self._termDeferred = termDeferred
self._escalation = 0
self._stopCall = None
<|end_body_0|>
<|body_start_1|>
self._buff += data
lines = [line for line in self._buff.split('\n')]
self._buff = lines[-1]
for line in lines[:-1... | Simple ProcessProtocol which forwards the stdout of the subprocesses to the stdout of this process in a orderly fashion. | LoggerProtocol | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LoggerProtocol:
"""Simple ProcessProtocol which forwards the stdout of the subprocesses to the stdout of this process in a orderly fashion."""
def __init__(self, termDeferred):
"""Initialize the LoggerProtocol."""
<|body_0|>
def outReceived(self, data):
"""Callba... | stack_v2_sparse_classes_75kplus_train_066991 | 6,407 | permissive | [
{
"docstring": "Initialize the LoggerProtocol.",
"name": "__init__",
"signature": "def __init__(self, termDeferred)"
},
{
"docstring": "Callback which is called by twisted when new data has arrived from subprocess.",
"name": "outReceived",
"signature": "def outReceived(self, data)"
},
... | 4 | stack_v2_sparse_classes_30k_train_008111 | Implement the Python class `LoggerProtocol` described below.
Class description:
Simple ProcessProtocol which forwards the stdout of the subprocesses to the stdout of this process in a orderly fashion.
Method signatures and docstrings:
- def __init__(self, termDeferred): Initialize the LoggerProtocol.
- def outReceive... | Implement the Python class `LoggerProtocol` described below.
Class description:
Simple ProcessProtocol which forwards the stdout of the subprocesses to the stdout of this process in a orderly fashion.
Method signatures and docstrings:
- def __init__(self, termDeferred): Initialize the LoggerProtocol.
- def outReceive... | c277efd809fce8f0f18b009fb3b9c7f785cc3739 | <|skeleton|>
class LoggerProtocol:
"""Simple ProcessProtocol which forwards the stdout of the subprocesses to the stdout of this process in a orderly fashion."""
def __init__(self, termDeferred):
"""Initialize the LoggerProtocol."""
<|body_0|>
def outReceived(self, data):
"""Callba... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class LoggerProtocol:
"""Simple ProcessProtocol which forwards the stdout of the subprocesses to the stdout of this process in a orderly fashion."""
def __init__(self, termDeferred):
"""Initialize the LoggerProtocol."""
self._buff = ''
self._termDeferred = termDeferred
self._esc... | the_stack_v2_python_sparse | framework/initMachine.py | LCROBOT/rce | train | 0 |
16e2ed0a28c699ed0b8a52e24fd15417c9207ada | [
"if measurement.fingerprint == 'type=elasticsearch, operation=search, search_type=aggs':\n agg_dsl = measurement.cfg.get('dsl') if measurement.cfg.get('dsl') else None\n if 'size' not in agg_dsl:\n agg_dsl['size'] = 0\n es_msearch_body.extend(({'index': es_index_info['index']}, measurement.cfg.get('... | <|body_start_0|>
if measurement.fingerprint == 'type=elasticsearch, operation=search, search_type=aggs':
agg_dsl = measurement.cfg.get('dsl') if measurement.cfg.get('dsl') else None
if 'size' not in agg_dsl:
agg_dsl['size'] = 0
es_msearch_body.extend(({'index'... | ES aggregation 采集器, 已经废弃，统一使用EsSearchCollector | EsAggregationCollector | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EsAggregationCollector:
"""ES aggregation 采集器, 已经废弃，统一使用EsSearchCollector"""
def _get_es_msearch_dsl(self, es_index_info, measurement, es_msearch_body):
"""获取ES msearch dsl :param es_index_info: :param measurement: :param es_msearch_body: :return:"""
<|body_0|>
def _pars... | stack_v2_sparse_classes_75kplus_train_066992 | 12,040 | permissive | [
{
"docstring": "获取ES msearch dsl :param es_index_info: :param measurement: :param es_msearch_body: :return:",
"name": "_get_es_msearch_dsl",
"signature": "def _get_es_msearch_dsl(self, es_index_info, measurement, es_msearch_body)"
},
{
"docstring": "解析ES msearch aggs result :param es_index_list:... | 2 | null | Implement the Python class `EsAggregationCollector` described below.
Class description:
ES aggregation 采集器, 已经废弃，统一使用EsSearchCollector
Method signatures and docstrings:
- def _get_es_msearch_dsl(self, es_index_info, measurement, es_msearch_body): 获取ES msearch dsl :param es_index_info: :param measurement: :param es_ms... | Implement the Python class `EsAggregationCollector` described below.
Class description:
ES aggregation 采集器, 已经废弃，统一使用EsSearchCollector
Method signatures and docstrings:
- def _get_es_msearch_dsl(self, es_index_info, measurement, es_msearch_body): 获取ES msearch dsl :param es_index_info: :param measurement: :param es_ms... | a72b4e4d78b4375f69887e75abcc1e6a6782c551 | <|skeleton|>
class EsAggregationCollector:
"""ES aggregation 采集器, 已经废弃，统一使用EsSearchCollector"""
def _get_es_msearch_dsl(self, es_index_info, measurement, es_msearch_body):
"""获取ES msearch dsl :param es_index_info: :param measurement: :param es_msearch_body: :return:"""
<|body_0|>
def _pars... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class EsAggregationCollector:
"""ES aggregation 采集器, 已经废弃，统一使用EsSearchCollector"""
def _get_es_msearch_dsl(self, es_index_info, measurement, es_msearch_body):
"""获取ES msearch dsl :param es_index_info: :param measurement: :param es_msearch_body: :return:"""
if measurement.fingerprint == 'type=el... | the_stack_v2_python_sparse | measure/collectors.py | RitterHou/search_platform | train | 0 |
655dbf220ed4a0350fcfe145acc66a8ee0df94ae | [
"ndim = len(shape)\nassert ndim in [2, 3]\nheight, width = shape[:2]\ndepth = 1 if ndim == 2 else shape[2]\nreturn cls(shape, ndim, height, width, depth)",
"if self.ndim != data.ndim:\n return False\nif self.ndim == 3 and self.depth != data.shape[2]:\n return False\nif data.shape[0] > self.height or data.sh... | <|body_start_0|>
ndim = len(shape)
assert ndim in [2, 3]
height, width = shape[:2]
depth = 1 if ndim == 2 else shape[2]
return cls(shape, ndim, height, width, depth)
<|end_body_0|>
<|body_start_1|>
if self.ndim != data.ndim:
return False
if self.ndim ... | Specification for the tiles in the atlas. Parameters ---------- shape : np.darray The shape of single tile. ndim : int The number of dimension in the shape of the tile. height : int The height of a tile. width : int The width of a tile. depth : int The depth of a tile, 1 for grayscale or RGB/RGBA. | TileSpec | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TileSpec:
"""Specification for the tiles in the atlas. Parameters ---------- shape : np.darray The shape of single tile. ndim : int The number of dimension in the shape of the tile. height : int The height of a tile. width : int The width of a tile. depth : int The depth of a tile, 1 for grayscal... | stack_v2_sparse_classes_75kplus_train_066993 | 11,936 | permissive | [
{
"docstring": "Create a TileSpec from just the shape. Parameters ---------- shape : np.darray Create a TileSpec based on this shape.",
"name": "from_shape",
"signature": "def from_shape(cls, shape: np.ndarray)"
},
{
"docstring": "Return True if the given data is compatible with our tiles. Param... | 2 | stack_v2_sparse_classes_30k_train_000220 | Implement the Python class `TileSpec` described below.
Class description:
Specification for the tiles in the atlas. Parameters ---------- shape : np.darray The shape of single tile. ndim : int The number of dimension in the shape of the tile. height : int The height of a tile. width : int The width of a tile. depth : ... | Implement the Python class `TileSpec` described below.
Class description:
Specification for the tiles in the atlas. Parameters ---------- shape : np.darray The shape of single tile. ndim : int The number of dimension in the shape of the tile. height : int The height of a tile. width : int The width of a tile. depth : ... | 19867df427b1eb1e503618a1ab109e7210ae8a83 | <|skeleton|>
class TileSpec:
"""Specification for the tiles in the atlas. Parameters ---------- shape : np.darray The shape of single tile. ndim : int The number of dimension in the shape of the tile. height : int The height of a tile. width : int The width of a tile. depth : int The depth of a tile, 1 for grayscal... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TileSpec:
"""Specification for the tiles in the atlas. Parameters ---------- shape : np.darray The shape of single tile. ndim : int The number of dimension in the shape of the tile. height : int The height of a tile. width : int The width of a tile. depth : int The depth of a tile, 1 for grayscale or RGB/RGBA... | the_stack_v2_python_sparse | napari/_vispy/experimental/texture_atlas.py | tlambert03/napari | train | 5 |
63b20e14c2da68189f08d842fa9a0fab436892f6 | [
"meta = self.model._meta\nif self.field_names:\n field_names = self.field_names\nelse:\n field_names = [field.name for field in meta.fields]\nresponse = HttpResponse(content_type='text/csv')\nresponse['Content-Disposition'] = 'attachment; filename={}.csv'.format(meta)\nwriter = csv.writer(response)\nwriter.wr... | <|body_start_0|>
meta = self.model._meta
if self.field_names:
field_names = self.field_names
else:
field_names = [field.name for field in meta.fields]
response = HttpResponse(content_type='text/csv')
response['Content-Disposition'] = 'attachment; filename=... | CSV Export 기능 제공용 Mixin. | ExportCsvMixin | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ExportCsvMixin:
"""CSV Export 기능 제공용 Mixin."""
def export_as_csv(self, request, queryset):
"""CSV으로 Export."""
<|body_0|>
def get_urls(self):
"""Get urls."""
<|body_1|>
def import_csv(self, request):
"""Import CSV File."""
<|body_2|>
... | stack_v2_sparse_classes_75kplus_train_066994 | 4,479 | no_license | [
{
"docstring": "CSV으로 Export.",
"name": "export_as_csv",
"signature": "def export_as_csv(self, request, queryset)"
},
{
"docstring": "Get urls.",
"name": "get_urls",
"signature": "def get_urls(self)"
},
{
"docstring": "Import CSV File.",
"name": "import_csv",
"signature":... | 3 | null | Implement the Python class `ExportCsvMixin` described below.
Class description:
CSV Export 기능 제공용 Mixin.
Method signatures and docstrings:
- def export_as_csv(self, request, queryset): CSV으로 Export.
- def get_urls(self): Get urls.
- def import_csv(self, request): Import CSV File. | Implement the Python class `ExportCsvMixin` described below.
Class description:
CSV Export 기능 제공용 Mixin.
Method signatures and docstrings:
- def export_as_csv(self, request, queryset): CSV으로 Export.
- def get_urls(self): Get urls.
- def import_csv(self, request): Import CSV File.
<|skeleton|>
class ExportCsvMixin:
... | f6688ca670d983ee683df4032e61c86fd56be74b | <|skeleton|>
class ExportCsvMixin:
"""CSV Export 기능 제공용 Mixin."""
def export_as_csv(self, request, queryset):
"""CSV으로 Export."""
<|body_0|>
def get_urls(self):
"""Get urls."""
<|body_1|>
def import_csv(self, request):
"""Import CSV File."""
<|body_2|>
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ExportCsvMixin:
"""CSV Export 기능 제공용 Mixin."""
def export_as_csv(self, request, queryset):
"""CSV으로 Export."""
meta = self.model._meta
if self.field_names:
field_names = self.field_names
else:
field_names = [field.name for field in meta.fields]
... | the_stack_v2_python_sparse | dashboard/book/utils.py | paryoja/dashboard | train | 1 |
5013b22e1ed34dbb63ec0d1962aea665a67c5e8f | [
"self.prefix_sums = []\nprefix_sum = 0\nfor weight in w:\n prefix_sum += weight\n self.prefix_sums.append(prefix_sum)\nself.total_sum = prefix_sum",
"target = self.total_sum * random.random()\nprint(f'target is {target}')\nfor i, prefix_sum in enumerate(self.prefix_sums):\n if target < prefix_sum:\n ... | <|body_start_0|>
self.prefix_sums = []
prefix_sum = 0
for weight in w:
prefix_sum += weight
self.prefix_sums.append(prefix_sum)
self.total_sum = prefix_sum
<|end_body_0|>
<|body_start_1|>
target = self.total_sum * random.random()
print(f'target is... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def __init__(self, w: [int]):
""":type w: List[int]"""
<|body_0|>
def pickIndex(self) -> int:
""":rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.prefix_sums = []
prefix_sum = 0
for weight in w:
... | stack_v2_sparse_classes_75kplus_train_066995 | 714 | no_license | [
{
"docstring": ":type w: List[int]",
"name": "__init__",
"signature": "def __init__(self, w: [int])"
},
{
"docstring": ":rtype: int",
"name": "pickIndex",
"signature": "def pickIndex(self) -> int"
}
] | 2 | stack_v2_sparse_classes_30k_train_041074 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def __init__(self, w: [int]): :type w: List[int]
- def pickIndex(self) -> int: :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def __init__(self, w: [int]): :type w: List[int]
- def pickIndex(self) -> int: :rtype: int
<|skeleton|>
class Solution:
def __init__(self, w: [int]):
""":type w: Li... | a09bd0105c0ac9e76e9b4ef1946faa2fb8797660 | <|skeleton|>
class Solution:
def __init__(self, w: [int]):
""":type w: List[int]"""
<|body_0|>
def pickIndex(self) -> int:
""":rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def __init__(self, w: [int]):
""":type w: List[int]"""
self.prefix_sums = []
prefix_sum = 0
for weight in w:
prefix_sum += weight
self.prefix_sums.append(prefix_sum)
self.total_sum = prefix_sum
def pickIndex(self) -> int:
"... | the_stack_v2_python_sparse | 528. Random Pick with Weight.py | yaoyu2001/LeetCode_Practice_Python | train | 1 | |
b3ac2504aa8a11a80ff4d33d2fb3bd8f509571d9 | [
"test_args = list(kwargs.get('test_args') or [])\ntest_args.append('--enable-run-ios-unittests-with-xctest')\nkwargs['test_args'] = test_args\nsuper(SimulatorXCTestUnitTestsApp, self).__init__(tests_app, **kwargs)",
"plugins_dir = os.path.join(self.test_app_path, 'PlugIns')\nif not os.path.exists(plugins_dir):\n ... | <|body_start_0|>
test_args = list(kwargs.get('test_args') or [])
test_args.append('--enable-run-ios-unittests-with-xctest')
kwargs['test_args'] = test_args
super(SimulatorXCTestUnitTestsApp, self).__init__(tests_app, **kwargs)
<|end_body_0|>
<|body_start_1|>
plugins_dir = os.pat... | XCTest hosted unit tests to run on simulators. This is for the XCTest framework hosted unit tests running on simulators. Stores data about tests: tests_app: full path to tests app. project_path: root project folder. module_name: egtests module name. included_tests: List of tests to run. excluded_tests: List of tests no... | SimulatorXCTestUnitTestsApp | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SimulatorXCTestUnitTestsApp:
"""XCTest hosted unit tests to run on simulators. This is for the XCTest framework hosted unit tests running on simulators. Stores data about tests: tests_app: full path to tests app. project_path: root project folder. module_name: egtests module name. included_tests:... | stack_v2_sparse_classes_75kplus_train_066996 | 24,623 | permissive | [
{
"docstring": "Initialize the class. Args: tests_app: (str) full path to tests app. (Following are potential args in **kwargs) included_tests: (list) Specific tests to run E.g. [ 'TestCaseClass1/testMethod1', 'TestCaseClass2/testMethod2'] excluded_tests: (list) Specific tests not to run E.g. [ 'TestCaseClass1'... | 3 | stack_v2_sparse_classes_30k_train_016700 | Implement the Python class `SimulatorXCTestUnitTestsApp` described below.
Class description:
XCTest hosted unit tests to run on simulators. This is for the XCTest framework hosted unit tests running on simulators. Stores data about tests: tests_app: full path to tests app. project_path: root project folder. module_nam... | Implement the Python class `SimulatorXCTestUnitTestsApp` described below.
Class description:
XCTest hosted unit tests to run on simulators. This is for the XCTest framework hosted unit tests running on simulators. Stores data about tests: tests_app: full path to tests app. project_path: root project folder. module_nam... | a401d6cf4f7bf0e2d2e964c512ebb923c3d8832c | <|skeleton|>
class SimulatorXCTestUnitTestsApp:
"""XCTest hosted unit tests to run on simulators. This is for the XCTest framework hosted unit tests running on simulators. Stores data about tests: tests_app: full path to tests app. project_path: root project folder. module_name: egtests module name. included_tests:... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SimulatorXCTestUnitTestsApp:
"""XCTest hosted unit tests to run on simulators. This is for the XCTest framework hosted unit tests running on simulators. Stores data about tests: tests_app: full path to tests app. project_path: root project folder. module_name: egtests module name. included_tests: List of test... | the_stack_v2_python_sparse | ios/build/bots/scripts/test_apps.py | chromium/chromium | train | 17,408 |
de44cd149c7525e8f4a255a66461ad19f5b4f823 | [
"logger.info('Compressing sky')\nif image.data.shape[1] % blocksize != 0 or image.data.shape[0] % blocksize != 0:\n raise skyinfo.SkyError('blocksize {:d} does not evenly divide image ({:d}x{:d})'.format(blocksize, image.data.shape[0], image.data.shape[1]))\n exit(1)\nnx = int(image.data.shape[1] / blocksize)... | <|body_start_0|>
logger.info('Compressing sky')
if image.data.shape[1] % blocksize != 0 or image.data.shape[0] % blocksize != 0:
raise skyinfo.SkyError('blocksize {:d} does not evenly divide image ({:d}x{:d})'.format(blocksize, image.data.shape[0], image.data.shape[1]))
exit(1)
... | SkyCompress | [
"NCSA"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SkyCompress:
def __call__(cls, image, skyfilename, blocksize, bitmask):
"""Produce compressed image of sky background :Parameters: - `image`: the DESImage to be compressed. - `skyfilename`: filename for the output compressed sky image - `blocksize`: side length of squares in which median... | stack_v2_sparse_classes_75kplus_train_066997 | 5,208 | permissive | [
{
"docstring": "Produce compressed image of sky background :Parameters: - `image`: the DESImage to be compressed. - `skyfilename`: filename for the output compressed sky image - `blocksize`: side length of squares in which medians are taken - `bitmask`: Bitmask that will be or'ed with mask plane of image (if an... | 4 | null | Implement the Python class `SkyCompress` described below.
Class description:
Implement the SkyCompress class.
Method signatures and docstrings:
- def __call__(cls, image, skyfilename, blocksize, bitmask): Produce compressed image of sky background :Parameters: - `image`: the DESImage to be compressed. - `skyfilename`... | Implement the Python class `SkyCompress` described below.
Class description:
Implement the SkyCompress class.
Method signatures and docstrings:
- def __call__(cls, image, skyfilename, blocksize, bitmask): Produce compressed image of sky background :Parameters: - `image`: the DESImage to be compressed. - `skyfilename`... | 8a299e9368d01cac51f53af6e4937e797f378d7a | <|skeleton|>
class SkyCompress:
def __call__(cls, image, skyfilename, blocksize, bitmask):
"""Produce compressed image of sky background :Parameters: - `image`: the DESImage to be compressed. - `skyfilename`: filename for the output compressed sky image - `blocksize`: side length of squares in which median... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SkyCompress:
def __call__(cls, image, skyfilename, blocksize, bitmask):
"""Produce compressed image of sky background :Parameters: - `image`: the DESImage to be compressed. - `skyfilename`: filename for the output compressed sky image - `blocksize`: side length of squares in which medians are taken - ... | the_stack_v2_python_sparse | python/pixcorrect/sky_compress.py | DarkEnergySurvey/pixcorrect | train | 1 | |
e3bc578e03846f97d1463077d8a11d9321e84435 | [
"length = longest = 0\nfor num in nums:\n if num == 1:\n length += 1\n else:\n longest = longest if longest > length else length\n length = 0\nreturn longest if longest > length else length",
"length = longest = 0\nfor num in nums:\n if num == 1:\n length += 1\n else:\n ... | <|body_start_0|>
length = longest = 0
for num in nums:
if num == 1:
length += 1
else:
longest = longest if longest > length else length
length = 0
return longest if longest > length else length
<|end_body_0|>
<|body_start_1... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def _findMaxConsecutiveOnes(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def findMaxConsecutiveOnes(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
length = longest = 0
... | stack_v2_sparse_classes_75kplus_train_066998 | 1,591 | permissive | [
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "_findMaxConsecutiveOnes",
"signature": "def _findMaxConsecutiveOnes(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "findMaxConsecutiveOnes",
"signature": "def findMaxConsecutiveOnes(self, nums)"
}... | 2 | stack_v2_sparse_classes_30k_train_015218 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def _findMaxConsecutiveOnes(self, nums): :type nums: List[int] :rtype: int
- def findMaxConsecutiveOnes(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 _findMaxConsecutiveOnes(self, nums): :type nums: List[int] :rtype: int
- def findMaxConsecutiveOnes(self, nums): :type nums: List[int] :rtype: int
<|skeleton|>
class Solutio... | 0dd67edca4e0b0323cb5a7239f02ea46383cd15a | <|skeleton|>
class Solution:
def _findMaxConsecutiveOnes(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def findMaxConsecutiveOnes(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def _findMaxConsecutiveOnes(self, nums):
""":type nums: List[int] :rtype: int"""
length = longest = 0
for num in nums:
if num == 1:
length += 1
else:
longest = longest if longest > length else length
leng... | the_stack_v2_python_sparse | 485.max-consecutive-ones.py | windard/leeeeee | train | 0 | |
31ea009c064d8563d71e44c719094fbb9f03f610 | [
"data['uuid'] = self.context['kwargs']['uuid']\ndata = FavoriteModelSerializer(data).data\nself.context['data'] = data\nreturn data",
"request = self.context['request']\nif not request.user.is_authenticated:\n return status_code(status=status.HTTP_401_UNAUTHORIZED)\nreturn create_item(get_authentication(reques... | <|body_start_0|>
data['uuid'] = self.context['kwargs']['uuid']
data = FavoriteModelSerializer(data).data
self.context['data'] = data
return data
<|end_body_0|>
<|body_start_1|>
request = self.context['request']
if not request.user.is_authenticated:
return sta... | Favorite delete serializer. | FavoriteCreateSerializer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FavoriteCreateSerializer:
"""Favorite delete serializer."""
def validate(self, data):
"""Validate data to the model."""
<|body_0|>
def create(self):
"""It will create an favorite item only if the user is authenticated."""
<|body_1|>
<|end_skeleton|>
<|b... | stack_v2_sparse_classes_75kplus_train_066999 | 10,323 | no_license | [
{
"docstring": "Validate data to the model.",
"name": "validate",
"signature": "def validate(self, data)"
},
{
"docstring": "It will create an favorite item only if the user is authenticated.",
"name": "create",
"signature": "def create(self)"
}
] | 2 | null | Implement the Python class `FavoriteCreateSerializer` described below.
Class description:
Favorite delete serializer.
Method signatures and docstrings:
- def validate(self, data): Validate data to the model.
- def create(self): It will create an favorite item only if the user is authenticated. | Implement the Python class `FavoriteCreateSerializer` described below.
Class description:
Favorite delete serializer.
Method signatures and docstrings:
- def validate(self, data): Validate data to the model.
- def create(self): It will create an favorite item only if the user is authenticated.
<|skeleton|>
class Fav... | cd8767b5eeaef3a09d77c936781b4126fd8591de | <|skeleton|>
class FavoriteCreateSerializer:
"""Favorite delete serializer."""
def validate(self, data):
"""Validate data to the model."""
<|body_0|>
def create(self):
"""It will create an favorite item only if the user is authenticated."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class FavoriteCreateSerializer:
"""Favorite delete serializer."""
def validate(self, data):
"""Validate data to the model."""
data['uuid'] = self.context['kwargs']['uuid']
data = FavoriteModelSerializer(data).data
self.context['data'] = data
return data
def create(s... | the_stack_v2_python_sparse | api/services/serializers.py | ignite7/backproject | train | 0 |
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