blob_id stringlengths 40 40 | bodies listlengths 2 6 | bodies_text stringlengths 196 7.73k | class_docstring stringlengths 0 700 | class_name stringlengths 1 86 | detected_licenses listlengths 0 45 | format_version stringclasses 1
value | full_text stringlengths 378 8.64k | id stringlengths 44 44 | length_bytes int64 505 50k | license_type stringclasses 2
values | methods listlengths 2 6 | n_methods int64 2 6 | original_id stringlengths 38 40 ⌀ | prompt stringlengths 153 4.88k | prompted_full_text stringlengths 565 12.5k | revision_id stringlengths 40 40 | skeleton stringlengths 162 5.05k | snapshot_name stringclasses 1
value | snapshot_source_dir stringclasses 1
value | snapshot_total_rows int64 75.8k 75.8k | solution stringlengths 242 8.3k | source stringclasses 1
value | source_path stringlengths 4 177 | source_repo stringlengths 6 110 | split stringclasses 1
value | star_events_count int64 0 209k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
6a9d3b8a6494ffa42099fa4d6404c01fb3b9d87b | [
"dtype = dtypes.as_dtype(dtype).base_dtype\nif dtype not in (dtypes.uint8, dtypes.float32):\n raise TypeError('Invalid dtype %r, expected uint8 or float32' % dtype)\nassert data_X.shape[0] == data_Y.shape[0], 'data_X.shape: %s data_Y.shape: %s' % (data_X.shape, data_Y.shape)\nself.num_examples = data_X.shape[0]\... | <|body_start_0|>
dtype = dtypes.as_dtype(dtype).base_dtype
if dtype not in (dtypes.uint8, dtypes.float32):
raise TypeError('Invalid dtype %r, expected uint8 or float32' % dtype)
assert data_X.shape[0] == data_Y.shape[0], 'data_X.shape: %s data_Y.shape: %s' % (data_X.shape, data_Y.sha... | DataSet | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DataSet:
def __init__(self, data_X, data_Y, dtype=dtypes.float32):
"""Checks data and casts it into correct data type."""
<|body_0|>
def next_batch(self, batch_size, seed=None):
"""Return the next `batch_size` examples from this data set."""
<|body_1|>
<|end... | stack_v2_sparse_classes_75kplus_train_073400 | 19,030 | no_license | [
{
"docstring": "Checks data and casts it into correct data type.",
"name": "__init__",
"signature": "def __init__(self, data_X, data_Y, dtype=dtypes.float32)"
},
{
"docstring": "Return the next `batch_size` examples from this data set.",
"name": "next_batch",
"signature": "def next_batch... | 2 | stack_v2_sparse_classes_30k_train_010357 | Implement the Python class `DataSet` described below.
Class description:
Implement the DataSet class.
Method signatures and docstrings:
- def __init__(self, data_X, data_Y, dtype=dtypes.float32): Checks data and casts it into correct data type.
- def next_batch(self, batch_size, seed=None): Return the next `batch_siz... | Implement the Python class `DataSet` described below.
Class description:
Implement the DataSet class.
Method signatures and docstrings:
- def __init__(self, data_X, data_Y, dtype=dtypes.float32): Checks data and casts it into correct data type.
- def next_batch(self, batch_size, seed=None): Return the next `batch_siz... | 4514e7231ee36ad10030105db14333bd04ee7f72 | <|skeleton|>
class DataSet:
def __init__(self, data_X, data_Y, dtype=dtypes.float32):
"""Checks data and casts it into correct data type."""
<|body_0|>
def next_batch(self, batch_size, seed=None):
"""Return the next `batch_size` examples from this data set."""
<|body_1|>
<|end... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DataSet:
def __init__(self, data_X, data_Y, dtype=dtypes.float32):
"""Checks data and casts it into correct data type."""
dtype = dtypes.as_dtype(dtype).base_dtype
if dtype not in (dtypes.uint8, dtypes.float32):
raise TypeError('Invalid dtype %r, expected uint8 or float32' ... | the_stack_v2_python_sparse | statmech/ising2d.py | HussainAther/physics | train | 18 | |
c179f6185a227367bb957a4354ba34e1a24951b8 | [
"val = {'pay_now': operation_type == 'treasury' and 'pay_later' or 'pay_now', 'payment_option': operation_type == 'treasury' and 'with_writeoff' or 'without_writeoff'}\nif operation_type == 'treasury':\n val.update({'line_dr_ids': False})\n account = self.pool.get('res.partner').browse(cr, uid, partner_id, co... | <|body_start_0|>
val = {'pay_now': operation_type == 'treasury' and 'pay_later' or 'pay_now', 'payment_option': operation_type == 'treasury' and 'with_writeoff' or 'without_writeoff'}
if operation_type == 'treasury':
val.update({'line_dr_ids': False})
account = self.pool.get('res... | account_voucher | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class account_voucher:
def onchange_operation_type(self, cr, uid, ids, operation_type, partner_id, context=None):
"""Method that call when changing operation_type value, when operation is treasury feeding: * Reset line_dr_ids field * Make voucher with writeoff * Make voucher pay later @return:... | stack_v2_sparse_classes_75kplus_train_073401 | 3,763 | no_license | [
{
"docstring": "Method that call when changing operation_type value, when operation is treasury feeding: * Reset line_dr_ids field * Make voucher with writeoff * Make voucher pay later @return: dictionary of fields values",
"name": "onchange_operation_type",
"signature": "def onchange_operation_type(sel... | 5 | stack_v2_sparse_classes_30k_train_052022 | Implement the Python class `account_voucher` described below.
Class description:
Implement the account_voucher class.
Method signatures and docstrings:
- def onchange_operation_type(self, cr, uid, ids, operation_type, partner_id, context=None): Method that call when changing operation_type value, when operation is tr... | Implement the Python class `account_voucher` described below.
Class description:
Implement the account_voucher class.
Method signatures and docstrings:
- def onchange_operation_type(self, cr, uid, ids, operation_type, partner_id, context=None): Method that call when changing operation_type value, when operation is tr... | 0b997095c260d58b026440967fea3a202bef7efb | <|skeleton|>
class account_voucher:
def onchange_operation_type(self, cr, uid, ids, operation_type, partner_id, context=None):
"""Method that call when changing operation_type value, when operation is treasury feeding: * Reset line_dr_ids field * Make voucher with writeoff * Make voucher pay later @return:... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class account_voucher:
def onchange_operation_type(self, cr, uid, ids, operation_type, partner_id, context=None):
"""Method that call when changing operation_type value, when operation is treasury feeding: * Reset line_dr_ids field * Make voucher with writeoff * Make voucher pay later @return: dictionary of... | the_stack_v2_python_sparse | v_7/Dongola/wafi/account_indirect_treasury_feeding/account_custom.py | musabahmed/baba | train | 0 | |
63c56da208c8a3bfe9fe98d7679dd5cd0e400b18 | [
"if urlconf_modules is None:\n urlconf_modules = [settings.ROOT_URLCONF]\n if self.URLCONF_MODULES is not None:\n urlconf_modules.extend(self.URLCONF_MODULES)\nfor urlconf in urlconf_modules:\n if urlconf in sys.modules:\n reload(sys.modules[urlconf])\nclear_url_caches()\nresolve('/')",
"su... | <|body_start_0|>
if urlconf_modules is None:
urlconf_modules = [settings.ROOT_URLCONF]
if self.URLCONF_MODULES is not None:
urlconf_modules.extend(self.URLCONF_MODULES)
for urlconf in urlconf_modules:
if urlconf in sys.modules:
reload(s... | Mixin to reset urls.py before and after a test Django memoizes the function that reads the urls module (whatever module urlconf names). The module itself is also stored by python in sys.modules. To fully reload it, we need to reload the python module, and also clear django's cache of the parsed urls. However, the order... | UrlResetMixin | [
"MIT",
"AGPL-3.0-only",
"AGPL-3.0-or-later"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UrlResetMixin:
"""Mixin to reset urls.py before and after a test Django memoizes the function that reads the urls module (whatever module urlconf names). The module itself is also stored by python in sys.modules. To fully reload it, we need to reload the python module, and also clear django's cac... | stack_v2_sparse_classes_75kplus_train_073402 | 5,815 | permissive | [
{
"docstring": "Reset `urls.py` for a set of Django apps.",
"name": "reset_urls",
"signature": "def reset_urls(self, urlconf_modules=None)"
},
{
"docstring": "Reset Django urls before tests and after tests If you need to reset `urls.py` from a particular Django app (or apps), specify these modul... | 2 | stack_v2_sparse_classes_30k_train_035038 | Implement the Python class `UrlResetMixin` described below.
Class description:
Mixin to reset urls.py before and after a test Django memoizes the function that reads the urls module (whatever module urlconf names). The module itself is also stored by python in sys.modules. To fully reload it, we need to reload the pyt... | Implement the Python class `UrlResetMixin` described below.
Class description:
Mixin to reset urls.py before and after a test Django memoizes the function that reads the urls module (whatever module urlconf names). The module itself is also stored by python in sys.modules. To fully reload it, we need to reload the pyt... | 5809eaca7079a15ee56b0b7fcfea425337046c97 | <|skeleton|>
class UrlResetMixin:
"""Mixin to reset urls.py before and after a test Django memoizes the function that reads the urls module (whatever module urlconf names). The module itself is also stored by python in sys.modules. To fully reload it, we need to reload the python module, and also clear django's cac... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class UrlResetMixin:
"""Mixin to reset urls.py before and after a test Django memoizes the function that reads the urls module (whatever module urlconf names). The module itself is also stored by python in sys.modules. To fully reload it, we need to reload the python module, and also clear django's cache of the par... | the_stack_v2_python_sparse | Part-03-Understanding-Software-Crafting-Your-Own-Tools/models/edx-platform/common/djangoapps/util/testing.py | luque/better-ways-of-thinking-about-software | train | 3 |
b221d978994eee995013cf6ff6d17c730f16cdb8 | [
"if id is not None:\n self.id = id\nelse:\n Base.__nb_objects += 1\n self.id = Base.__nb_objects",
"if list_dictionaries is None:\n return '[]'\nelse:\n return json.dumps(list_dictionaries)",
"with open('{}.json'.format(cls.__name__), 'w', encoding='UTF8') as file:\n list = []\n if list_obj... | <|body_start_0|>
if id is not None:
self.id = id
else:
Base.__nb_objects += 1
self.id = Base.__nb_objects
<|end_body_0|>
<|body_start_1|>
if list_dictionaries is None:
return '[]'
else:
return json.dumps(list_dictionaries)
<|en... | This is the class Base. | Base | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Base:
"""This is the class Base."""
def __init__(self, id=None):
"""This init's the id."""
<|body_0|>
def to_json_string(list_dictionaries):
"""Returns the JSON string representation of list_dictionaries"""
<|body_1|>
def save_to_file(cls, list_objs)... | stack_v2_sparse_classes_75kplus_train_073403 | 2,151 | no_license | [
{
"docstring": "This init's the id.",
"name": "__init__",
"signature": "def __init__(self, id=None)"
},
{
"docstring": "Returns the JSON string representation of list_dictionaries",
"name": "to_json_string",
"signature": "def to_json_string(list_dictionaries)"
},
{
"docstring": "... | 6 | stack_v2_sparse_classes_30k_train_046457 | Implement the Python class `Base` described below.
Class description:
This is the class Base.
Method signatures and docstrings:
- def __init__(self, id=None): This init's the id.
- def to_json_string(list_dictionaries): Returns the JSON string representation of list_dictionaries
- def save_to_file(cls, list_objs): Wr... | Implement the Python class `Base` described below.
Class description:
This is the class Base.
Method signatures and docstrings:
- def __init__(self, id=None): This init's the id.
- def to_json_string(list_dictionaries): Returns the JSON string representation of list_dictionaries
- def save_to_file(cls, list_objs): Wr... | 5050902bc99d99cc779c5a31bf3bb767eb93521f | <|skeleton|>
class Base:
"""This is the class Base."""
def __init__(self, id=None):
"""This init's the id."""
<|body_0|>
def to_json_string(list_dictionaries):
"""Returns the JSON string representation of list_dictionaries"""
<|body_1|>
def save_to_file(cls, list_objs)... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Base:
"""This is the class Base."""
def __init__(self, id=None):
"""This init's the id."""
if id is not None:
self.id = id
else:
Base.__nb_objects += 1
self.id = Base.__nb_objects
def to_json_string(list_dictionaries):
"""Returns th... | the_stack_v2_python_sparse | 0x0C-python-almost_a_circle/models/base.py | koukijohn/holbertonschool-higher_level_programming | train | 0 |
64c205c66879ce9b153b5476d91bacf986692feb | [
"super().__init__()\nself.register_buffer('support', torch.linspace(vmin, vmax, n_atoms))\nself.fc1 = nn.Linear(state_size, 256)\nself.fc2 = nn.Linear(256 + action_size, 256)\nself.fc3 = nn.Linear(256, 128)\nself.fc4 = nn.Linear(128, n_atoms)",
"x = F.leaky_relu(self.fc1(state))\nx = torch.cat([x, action], dim=1)... | <|body_start_0|>
super().__init__()
self.register_buffer('support', torch.linspace(vmin, vmax, n_atoms))
self.fc1 = nn.Linear(state_size, 256)
self.fc2 = nn.Linear(256 + action_size, 256)
self.fc3 = nn.Linear(256, 128)
self.fc4 = nn.Linear(128, n_atoms)
<|end_body_0|>
<|... | Distributional Value Model | Critic | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Critic:
"""Distributional Value Model"""
def __init__(self, state_size, action_size, vmin, vmax, n_atoms=51):
"""Initialize parameters and build model. Parameters ---------- state_size : int Dimension of each state action_size : int Dimension of each action vmin, vmax : float Upper &... | stack_v2_sparse_classes_75kplus_train_073404 | 2,383 | no_license | [
{
"docstring": "Initialize parameters and build model. Parameters ---------- state_size : int Dimension of each state action_size : int Dimension of each action vmin, vmax : float Upper & Lower bounds of the support n_atoms : int Number of bins in the support",
"name": "__init__",
"signature": "def __in... | 2 | stack_v2_sparse_classes_30k_train_033084 | Implement the Python class `Critic` described below.
Class description:
Distributional Value Model
Method signatures and docstrings:
- def __init__(self, state_size, action_size, vmin, vmax, n_atoms=51): Initialize parameters and build model. Parameters ---------- state_size : int Dimension of each state action_size ... | Implement the Python class `Critic` described below.
Class description:
Distributional Value Model
Method signatures and docstrings:
- def __init__(self, state_size, action_size, vmin, vmax, n_atoms=51): Initialize parameters and build model. Parameters ---------- state_size : int Dimension of each state action_size ... | f6d450e0c68236bf493689bffef48a0f3723416d | <|skeleton|>
class Critic:
"""Distributional Value Model"""
def __init__(self, state_size, action_size, vmin, vmax, n_atoms=51):
"""Initialize parameters and build model. Parameters ---------- state_size : int Dimension of each state action_size : int Dimension of each action vmin, vmax : float Upper &... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Critic:
"""Distributional Value Model"""
def __init__(self, state_size, action_size, vmin, vmax, n_atoms=51):
"""Initialize parameters and build model. Parameters ---------- state_size : int Dimension of each state action_size : int Dimension of each action vmin, vmax : float Upper & Lower bounds... | the_stack_v2_python_sparse | drlnd/p2_continuous-control/control/model.py | jkorge/udacity | train | 0 |
4b129b03624e70565021613924dc3c291e73ae12 | [
"threading.Thread.__init__(self)\nself.daemon = True\nself.parent = parent\nself.commandsQueue = commandsQueue\nself.launcher = LauncherSingle()",
"self.launcher.bot._Print('Thread started')\nwhile not self.commandsQueue.empty():\n command = self.commandsQueue.get()\n argumentsList = shlex.split(command)\n ... | <|body_start_0|>
threading.Thread.__init__(self)
self.daemon = True
self.parent = parent
self.commandsQueue = commandsQueue
self.launcher = LauncherSingle()
<|end_body_0|>
<|body_start_1|>
self.launcher.bot._Print('Thread started')
while not self.commandsQueue.em... | Запускаем бота - одна команда в потоке | LauncherSingleThreaded | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LauncherSingleThreaded:
"""Запускаем бота - одна команда в потоке"""
def __init__(self, parent, commandsQueue):
"""Инициализация"""
<|body_0|>
def run(self):
"""Главный метод"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
threading.Thread.__ini... | stack_v2_sparse_classes_75kplus_train_073405 | 16,928 | no_license | [
{
"docstring": "Инициализация",
"name": "__init__",
"signature": "def __init__(self, parent, commandsQueue)"
},
{
"docstring": "Главный метод",
"name": "run",
"signature": "def run(self)"
}
] | 2 | null | Implement the Python class `LauncherSingleThreaded` described below.
Class description:
Запускаем бота - одна команда в потоке
Method signatures and docstrings:
- def __init__(self, parent, commandsQueue): Инициализация
- def run(self): Главный метод | Implement the Python class `LauncherSingleThreaded` described below.
Class description:
Запускаем бота - одна команда в потоке
Method signatures and docstrings:
- def __init__(self, parent, commandsQueue): Инициализация
- def run(self): Главный метод
<|skeleton|>
class LauncherSingleThreaded:
"""Запускаем бота -... | d2771bf04aa187dda6d468883a5a167237589369 | <|skeleton|>
class LauncherSingleThreaded:
"""Запускаем бота - одна команда в потоке"""
def __init__(self, parent, commandsQueue):
"""Инициализация"""
<|body_0|>
def run(self):
"""Главный метод"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class LauncherSingleThreaded:
"""Запускаем бота - одна команда в потоке"""
def __init__(self, parent, commandsQueue):
"""Инициализация"""
threading.Thread.__init__(self)
self.daemon = True
self.parent = parent
self.commandsQueue = commandsQueue
self.launcher = La... | the_stack_v2_python_sparse | pinterest/launcher.py | cash2one/doorscenter | train | 0 |
3554249ca6c1b9fcdfe14372cfed88d293e1424e | [
"if len(matrix) == 0 or len(matrix[0]) == 0:\n return False\nm, n = (len(matrix), len(matrix[0]))\nrow, col = (m - 1, 0)\ncount = 0\nwhile row >= 0 and col < n:\n if matrix[row][col] > target:\n row -= 1\n elif matrix[row][col] < target:\n col += 1\n else:\n return True\n print(r... | <|body_start_0|>
if len(matrix) == 0 or len(matrix[0]) == 0:
return False
m, n = (len(matrix), len(matrix[0]))
row, col = (m - 1, 0)
count = 0
while row >= 0 and col < n:
if matrix[row][col] > target:
row -= 1
elif matrix[row][c... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def searchMatrix(self, matrix, target):
""":type matrix: List[List[int]] :type target: int :rtype: bool"""
<|body_0|>
def searchMatrixCount(self, matrix, target):
"""return the occurrence number of 'target' in 'matrix' :type matrix: List[List[int]] :type ta... | stack_v2_sparse_classes_75kplus_train_073406 | 1,909 | no_license | [
{
"docstring": ":type matrix: List[List[int]] :type target: int :rtype: bool",
"name": "searchMatrix",
"signature": "def searchMatrix(self, matrix, target)"
},
{
"docstring": "return the occurrence number of 'target' in 'matrix' :type matrix: List[List[int]] :type target: int :rtype: bool",
... | 2 | stack_v2_sparse_classes_30k_train_025156 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def searchMatrix(self, matrix, target): :type matrix: List[List[int]] :type target: int :rtype: bool
- def searchMatrixCount(self, matrix, target): return the occurrence number o... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def searchMatrix(self, matrix, target): :type matrix: List[List[int]] :type target: int :rtype: bool
- def searchMatrixCount(self, matrix, target): return the occurrence number o... | e1a4c1bc5d01b4e2ba51a5255deed6426557dcb0 | <|skeleton|>
class Solution:
def searchMatrix(self, matrix, target):
""":type matrix: List[List[int]] :type target: int :rtype: bool"""
<|body_0|>
def searchMatrixCount(self, matrix, target):
"""return the occurrence number of 'target' in 'matrix' :type matrix: List[List[int]] :type ta... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def searchMatrix(self, matrix, target):
""":type matrix: List[List[int]] :type target: int :rtype: bool"""
if len(matrix) == 0 or len(matrix[0]) == 0:
return False
m, n = (len(matrix), len(matrix[0]))
row, col = (m - 1, 0)
count = 0
while r... | the_stack_v2_python_sparse | src/search2DMatrix2.py | xuetingandyang/leetcode | train | 3 | |
56d697ce3028da75a0d7691a5fab7f836962f271 | [
"super(HotstartEncoder, self).__init__(conf, constraint, name)\nconf.remove_section('encoder')\nconf.add_section('encoder')\nfor option, value in conf.items(self.conf['wrapped']):\n conf.set('encoder', option, value)\nconf.remove_section(self.conf['wrapped'])\nself.wrapped = ed_encoder_factory.factory(conf.get('... | <|body_start_0|>
super(HotstartEncoder, self).__init__(conf, constraint, name)
conf.remove_section('encoder')
conf.add_section('encoder')
for option, value in conf.items(self.conf['wrapped']):
conf.set('encoder', option, value)
conf.remove_section(self.conf['wrapped']... | a listener object transforms input features into a high level representation | HotstartEncoder | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HotstartEncoder:
"""a listener object transforms input features into a high level representation"""
def __init__(self, conf, constraint, name=None):
"""constructor Args: conf: the encoder configuration name: the encoder name constraint: the constraint for the variables"""
<|b... | stack_v2_sparse_classes_75kplus_train_073407 | 2,327 | permissive | [
{
"docstring": "constructor Args: conf: the encoder configuration name: the encoder name constraint: the constraint for the variables",
"name": "__init__",
"signature": "def __init__(self, conf, constraint, name=None)"
},
{
"docstring": "Create the variables and do the forward computation Args: ... | 2 | null | Implement the Python class `HotstartEncoder` described below.
Class description:
a listener object transforms input features into a high level representation
Method signatures and docstrings:
- def __init__(self, conf, constraint, name=None): constructor Args: conf: the encoder configuration name: the encoder name co... | Implement the Python class `HotstartEncoder` described below.
Class description:
a listener object transforms input features into a high level representation
Method signatures and docstrings:
- def __init__(self, conf, constraint, name=None): constructor Args: conf: the encoder configuration name: the encoder name co... | 313018a46f68cec1d4a7eb15b8b1cf68111a959c | <|skeleton|>
class HotstartEncoder:
"""a listener object transforms input features into a high level representation"""
def __init__(self, conf, constraint, name=None):
"""constructor Args: conf: the encoder configuration name: the encoder name constraint: the constraint for the variables"""
<|b... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class HotstartEncoder:
"""a listener object transforms input features into a high level representation"""
def __init__(self, conf, constraint, name=None):
"""constructor Args: conf: the encoder configuration name: the encoder name constraint: the constraint for the variables"""
super(HotstartEn... | the_stack_v2_python_sparse | nabu/neuralnetworks/models/ed_encoders/hotstart_encoder.py | ishandutta2007/nabu | train | 0 |
db6b7eb3fcc16cf5bb81a8d4791acaf1751db37a | [
"if self.action in ['list']:\n permission_classes = [IsAuthenticated]\nelse:\n try:\n permission_classes = getattr(self, self.action).kwargs.get('permission_classes')\n except AttributeError:\n permission_classes = self.permission_classes\nreturn [permission() for permission in permission_cla... | <|body_start_0|>
if self.action in ['list']:
permission_classes = [IsAuthenticated]
else:
try:
permission_classes = getattr(self, self.action).kwargs.get('permission_classes')
except AttributeError:
permission_classes = self.permission_... | API endpoints for unit memberships. | UnitMembershipViewSet | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UnitMembershipViewSet:
"""API endpoints for unit memberships."""
def get_permissions(self):
"""Manage permissions for built-in DRF methods, defaulting to the actions self defined permissions if applicable or to the ViewSet's default permissions."""
<|body_0|>
def get_uni... | stack_v2_sparse_classes_75kplus_train_073408 | 2,178 | permissive | [
{
"docstring": "Manage permissions for built-in DRF methods, defaulting to the actions self defined permissions if applicable or to the ViewSet's default permissions.",
"name": "get_permissions",
"signature": "def get_permissions(self)"
},
{
"docstring": "Helper: get the related unit, return an ... | 3 | stack_v2_sparse_classes_30k_train_019516 | Implement the Python class `UnitMembershipViewSet` described below.
Class description:
API endpoints for unit memberships.
Method signatures and docstrings:
- def get_permissions(self): Manage permissions for built-in DRF methods, defaulting to the actions self defined permissions if applicable or to the ViewSet's de... | Implement the Python class `UnitMembershipViewSet` described below.
Class description:
API endpoints for unit memberships.
Method signatures and docstrings:
- def get_permissions(self): Manage permissions for built-in DRF methods, defaulting to the actions self defined permissions if applicable or to the ViewSet's de... | 22e4afa728a851bb4c2479fbb6f5944a75984b9b | <|skeleton|>
class UnitMembershipViewSet:
"""API endpoints for unit memberships."""
def get_permissions(self):
"""Manage permissions for built-in DRF methods, defaulting to the actions self defined permissions if applicable or to the ViewSet's default permissions."""
<|body_0|>
def get_uni... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class UnitMembershipViewSet:
"""API endpoints for unit memberships."""
def get_permissions(self):
"""Manage permissions for built-in DRF methods, defaulting to the actions self defined permissions if applicable or to the ViewSet's default permissions."""
if self.action in ['list']:
... | the_stack_v2_python_sparse | src/backend/partaj/core/api/unit_membership.py | MTES-MCT/partaj | train | 4 |
899c824a8382f9feb170f5138ae31660e3db922c | [
"cates = ctrl.cate.get_cates_ctl(self.current_user['store_id'])\ndata = {'list': []}\nif not cates:\n return self.send_json(data)\nFILTER = ({'id': 'cate_id'}, 'store_id', 'name', 'update_time')\ndata['list'] = [utils.dict_filter(cate, FILTER) for cate in cates]\nself.send_json(data)",
"try:\n args = json.l... | <|body_start_0|>
cates = ctrl.cate.get_cates_ctl(self.current_user['store_id'])
data = {'list': []}
if not cates:
return self.send_json(data)
FILTER = ({'id': 'cate_id'}, 'store_id', 'name', 'update_time')
data['list'] = [utils.dict_filter(cate, FILTER) for cate in ca... | CateHandler | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CateHandler:
def get(self):
"""获取所有的酒水分类"""
<|body_0|>
def post(self):
"""添加酒水分类"""
<|body_1|>
def delete(self):
"""删除酒水分类"""
<|body_2|>
def put(self):
"""修改某酒水分类"""
<|body_3|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_75kplus_train_073409 | 7,327 | no_license | [
{
"docstring": "获取所有的酒水分类",
"name": "get",
"signature": "def get(self)"
},
{
"docstring": "添加酒水分类",
"name": "post",
"signature": "def post(self)"
},
{
"docstring": "删除酒水分类",
"name": "delete",
"signature": "def delete(self)"
},
{
"docstring": "修改某酒水分类",
"name":... | 4 | null | Implement the Python class `CateHandler` described below.
Class description:
Implement the CateHandler class.
Method signatures and docstrings:
- def get(self): 获取所有的酒水分类
- def post(self): 添加酒水分类
- def delete(self): 删除酒水分类
- def put(self): 修改某酒水分类 | Implement the Python class `CateHandler` described below.
Class description:
Implement the CateHandler class.
Method signatures and docstrings:
- def get(self): 获取所有的酒水分类
- def post(self): 添加酒水分类
- def delete(self): 删除酒水分类
- def put(self): 修改某酒水分类
<|skeleton|>
class CateHandler:
def get(self):
"""获取所有的酒... | 3adc4347c942bd8378c13a026e30b0a30ee26919 | <|skeleton|>
class CateHandler:
def get(self):
"""获取所有的酒水分类"""
<|body_0|>
def post(self):
"""添加酒水分类"""
<|body_1|>
def delete(self):
"""删除酒水分类"""
<|body_2|>
def put(self):
"""修改某酒水分类"""
<|body_3|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CateHandler:
def get(self):
"""获取所有的酒水分类"""
cates = ctrl.cate.get_cates_ctl(self.current_user['store_id'])
data = {'list': []}
if not cates:
return self.send_json(data)
FILTER = ({'id': 'cate_id'}, 'store_id', 'name', 'update_time')
data['list'] = [u... | the_stack_v2_python_sparse | handler/cate.py | y00273676/O2O_ERP_Server | train | 0 | |
419e17a8ad7d54b6edab059bf1e0ed2e5557bcde | [
"self.sourcekind = 'MFC'\nself.win_length_ms = 25\nself.win_shift_ms = 10\nself.num_chans = 26\nself.num_lift_ceps = 22\nself.num_ceps = 12\nself.pre_em_coef = 0.97\nself.targetkindw = 'MFCC_0_D'\nself.targetkind = 'MFCC_0_D_N_Z'\nself.nbmv = 25\nself.configfile = ''\nself.mfcconfigfile = ''\nself.framerate = 16000... | <|body_start_0|>
self.sourcekind = 'MFC'
self.win_length_ms = 25
self.win_shift_ms = 10
self.num_chans = 26
self.num_lift_ceps = 22
self.num_ceps = 12
self.pre_em_coef = 0.97
self.targetkindw = 'MFCC_0_D'
self.targetkind = 'MFCC_0_D_N_Z'
se... | Acoustic model features. :organization: Laboratoire Parole et Langage, Aix-en-Provence, France :license: GPL, v3 :copyright: Copyright (C) 2011-2018 Brigitte Bigi :author: Brigitte Bigi :contact: develop@sppas.org | sppasAcFeatures | [
"GPL-3.0-only",
"MIT",
"GFDL-1.1-or-later",
"GPL-3.0-or-later"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class sppasAcFeatures:
"""Acoustic model features. :organization: Laboratoire Parole et Langage, Aix-en-Provence, France :license: GPL, v3 :copyright: Copyright (C) 2011-2018 Brigitte Bigi :author: Brigitte Bigi :contact: develop@sppas.org"""
def __init__(self):
"""Create a sppasAcFeatures... | stack_v2_sparse_classes_75kplus_train_073410 | 11,367 | permissive | [
{
"docstring": "Create a sppasAcFeatures instance.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Write all files at once. Write files with their default name, in the given directory. :param dirname: (str) a directory name (existing or to be created).",
"name": "w... | 4 | stack_v2_sparse_classes_30k_train_012624 | Implement the Python class `sppasAcFeatures` described below.
Class description:
Acoustic model features. :organization: Laboratoire Parole et Langage, Aix-en-Provence, France :license: GPL, v3 :copyright: Copyright (C) 2011-2018 Brigitte Bigi :author: Brigitte Bigi :contact: develop@sppas.org
Method signatures and d... | Implement the Python class `sppasAcFeatures` described below.
Class description:
Acoustic model features. :organization: Laboratoire Parole et Langage, Aix-en-Provence, France :license: GPL, v3 :copyright: Copyright (C) 2011-2018 Brigitte Bigi :author: Brigitte Bigi :contact: develop@sppas.org
Method signatures and d... | 3167b65f576abcc27a8767d24c274a04712bd948 | <|skeleton|>
class sppasAcFeatures:
"""Acoustic model features. :organization: Laboratoire Parole et Langage, Aix-en-Provence, France :license: GPL, v3 :copyright: Copyright (C) 2011-2018 Brigitte Bigi :author: Brigitte Bigi :contact: develop@sppas.org"""
def __init__(self):
"""Create a sppasAcFeatures... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class sppasAcFeatures:
"""Acoustic model features. :organization: Laboratoire Parole et Langage, Aix-en-Provence, France :license: GPL, v3 :copyright: Copyright (C) 2011-2018 Brigitte Bigi :author: Brigitte Bigi :contact: develop@sppas.org"""
def __init__(self):
"""Create a sppasAcFeatures instance."""... | the_stack_v2_python_sparse | sppas/sppas/src/models/acm/features.py | mirfan899/MTTS | train | 0 |
304281889024949fda88666d6129758adb98e5c3 | [
"self.__logger = State().getLogger('DetectionCore_Component_Logger')\nself.__logger.info('Starting __init__()', 'ImageResizer:__init__')\nself.__targetNumberOfRows = targetNumberOfRows\nself.__targetNumberOfColumns = targetNumberOfColumns\nself.__interpolation = interpolation\nself.__showImagesInWindow = showImages... | <|body_start_0|>
self.__logger = State().getLogger('DetectionCore_Component_Logger')
self.__logger.info('Starting __init__()', 'ImageResizer:__init__')
self.__targetNumberOfRows = targetNumberOfRows
self.__targetNumberOfColumns = targetNumberOfColumns
self.__interpolation = inter... | ImageResizer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ImageResizer:
def __init__(self, targetNumberOfRows=110, targetNumberOfColumns=32, interpolation=cv2.INTER_LINEAR, showImagesInWindow=False):
"""To-Do: Bitte Kommentar bzw. Dokumentaion erstellen!"""
<|body_0|>
def coreProcess(self, mats):
"""To-Do: Bitte Kommentar b... | stack_v2_sparse_classes_75kplus_train_073411 | 2,660 | no_license | [
{
"docstring": "To-Do: Bitte Kommentar bzw. Dokumentaion erstellen!",
"name": "__init__",
"signature": "def __init__(self, targetNumberOfRows=110, targetNumberOfColumns=32, interpolation=cv2.INTER_LINEAR, showImagesInWindow=False)"
},
{
"docstring": "To-Do: Bitte Kommentar bzw. Dokumentaion erst... | 2 | stack_v2_sparse_classes_30k_train_014026 | Implement the Python class `ImageResizer` described below.
Class description:
Implement the ImageResizer class.
Method signatures and docstrings:
- def __init__(self, targetNumberOfRows=110, targetNumberOfColumns=32, interpolation=cv2.INTER_LINEAR, showImagesInWindow=False): To-Do: Bitte Kommentar bzw. Dokumentaion e... | Implement the Python class `ImageResizer` described below.
Class description:
Implement the ImageResizer class.
Method signatures and docstrings:
- def __init__(self, targetNumberOfRows=110, targetNumberOfColumns=32, interpolation=cv2.INTER_LINEAR, showImagesInWindow=False): To-Do: Bitte Kommentar bzw. Dokumentaion e... | 3daaa72b193ebfb55894b47b6a752cdc2192bb6b | <|skeleton|>
class ImageResizer:
def __init__(self, targetNumberOfRows=110, targetNumberOfColumns=32, interpolation=cv2.INTER_LINEAR, showImagesInWindow=False):
"""To-Do: Bitte Kommentar bzw. Dokumentaion erstellen!"""
<|body_0|>
def coreProcess(self, mats):
"""To-Do: Bitte Kommentar b... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ImageResizer:
def __init__(self, targetNumberOfRows=110, targetNumberOfColumns=32, interpolation=cv2.INTER_LINEAR, showImagesInWindow=False):
"""To-Do: Bitte Kommentar bzw. Dokumentaion erstellen!"""
self.__logger = State().getLogger('DetectionCore_Component_Logger')
self.__logger.info... | the_stack_v2_python_sparse | SheetMusicScanner/DetectionCore_Component/ImageOptimizer/ImageResizer.py | jadeskon/score-scan | train | 0 | |
139bc12ad36a417dafb096b4d213836cbb068138 | [
"res = ApiFactory.get_order_api().order_list_api(1)\nlogging.info('请求地址:{}'.format(res.url))\nlogging.info('响应数据:{}'.format(res.json()))\nutils.common_assert_code(res)\nassert False not in [i in res.text for i in ['current_page', 'data', 'snap_name']]",
"product_id = 12\ncount = 7\nres = ApiFactory.get_order_api(... | <|body_start_0|>
res = ApiFactory.get_order_api().order_list_api(1)
logging.info('请求地址:{}'.format(res.url))
logging.info('响应数据:{}'.format(res.json()))
utils.common_assert_code(res)
assert False not in [i in res.text for i in ['current_page', 'data', 'snap_name']]
<|end_body_0|>
... | TestOrder | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestOrder:
def test_order_list(self):
"""订单列表"""
<|body_0|>
def test_create_order(self):
"""创建订单"""
<|body_1|>
def test_query_order(self):
"""查看订单"""
<|body_2|>
<|end_skeleton|>
<|body_start_0|>
res = ApiFactory.get_order_api().... | stack_v2_sparse_classes_75kplus_train_073412 | 1,694 | no_license | [
{
"docstring": "订单列表",
"name": "test_order_list",
"signature": "def test_order_list(self)"
},
{
"docstring": "创建订单",
"name": "test_create_order",
"signature": "def test_create_order(self)"
},
{
"docstring": "查看订单",
"name": "test_query_order",
"signature": "def test_query_... | 3 | stack_v2_sparse_classes_30k_train_023496 | Implement the Python class `TestOrder` described below.
Class description:
Implement the TestOrder class.
Method signatures and docstrings:
- def test_order_list(self): 订单列表
- def test_create_order(self): 创建订单
- def test_query_order(self): 查看订单 | Implement the Python class `TestOrder` described below.
Class description:
Implement the TestOrder class.
Method signatures and docstrings:
- def test_order_list(self): 订单列表
- def test_create_order(self): 创建订单
- def test_query_order(self): 查看订单
<|skeleton|>
class TestOrder:
def test_order_list(self):
""... | 8c0f3b3b499311f2dc0e2e5a1738476e0af77cac | <|skeleton|>
class TestOrder:
def test_order_list(self):
"""订单列表"""
<|body_0|>
def test_create_order(self):
"""创建订单"""
<|body_1|>
def test_query_order(self):
"""查看订单"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TestOrder:
def test_order_list(self):
"""订单列表"""
res = ApiFactory.get_order_api().order_list_api(1)
logging.info('请求地址:{}'.format(res.url))
logging.info('响应数据:{}'.format(res.json()))
utils.common_assert_code(res)
assert False not in [i in res.text for i in ['cur... | the_stack_v2_python_sparse | Scripts/testOrder.py | yang9801/ego | train | 1 | |
570abdf826968daea50cecc6d514f39001872008 | [
"n = len(init_val)\nself.segfunc = segfunc\nself.ide_ele = ide_ele\nself.num = 1 << (n - 1).bit_length()\nself.tree = [ide_ele] * 2 * self.num\nfor i in range(n):\n self.tree[self.num + i] = init_val[i]\nfor i in range(self.num - 1, 0, -1):\n self.tree[i] = segfunc(self.tree[2 * i], self.tree[2 * i + 1])",
... | <|body_start_0|>
n = len(init_val)
self.segfunc = segfunc
self.ide_ele = ide_ele
self.num = 1 << (n - 1).bit_length()
self.tree = [ide_ele] * 2 * self.num
for i in range(n):
self.tree[self.num + i] = init_val[i]
for i in range(self.num - 1, 0, -1):
... | Segment Tree | SegTree | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SegTree:
"""Segment Tree"""
def __init__(self, init_val, segfunc, ide_ele):
"""初期化 init_val: 配列の初期値 segfunc: 区間にしたい操作 ide_ele: 単位元 n: 要素数 num: n以上の最小の2のべき乗 tree: セグメント木(1-index)"""
<|body_0|>
def update(self, k, x):
"""k番目の値をxに更新 O(N) k: index(0-index) x: update ... | stack_v2_sparse_classes_75kplus_train_073413 | 4,134 | no_license | [
{
"docstring": "初期化 init_val: 配列の初期値 segfunc: 区間にしたい操作 ide_ele: 単位元 n: 要素数 num: n以上の最小の2のべき乗 tree: セグメント木(1-index)",
"name": "__init__",
"signature": "def __init__(self, init_val, segfunc, ide_ele)"
},
{
"docstring": "k番目の値をxに更新 O(N) k: index(0-index) x: update value",
"name": "update",
... | 3 | stack_v2_sparse_classes_30k_val_001672 | Implement the Python class `SegTree` described below.
Class description:
Segment Tree
Method signatures and docstrings:
- def __init__(self, init_val, segfunc, ide_ele): 初期化 init_val: 配列の初期値 segfunc: 区間にしたい操作 ide_ele: 単位元 n: 要素数 num: n以上の最小の2のべき乗 tree: セグメント木(1-index)
- def update(self, k, x): k番目の値をxに更新 O(N) k: inde... | Implement the Python class `SegTree` described below.
Class description:
Segment Tree
Method signatures and docstrings:
- def __init__(self, init_val, segfunc, ide_ele): 初期化 init_val: 配列の初期値 segfunc: 区間にしたい操作 ide_ele: 単位元 n: 要素数 num: n以上の最小の2のべき乗 tree: セグメント木(1-index)
- def update(self, k, x): k番目の値をxに更新 O(N) k: inde... | 07cb6dbbc32e98bb34427044cf3b4031a11c4367 | <|skeleton|>
class SegTree:
"""Segment Tree"""
def __init__(self, init_val, segfunc, ide_ele):
"""初期化 init_val: 配列の初期値 segfunc: 区間にしたい操作 ide_ele: 単位元 n: 要素数 num: n以上の最小の2のべき乗 tree: セグメント木(1-index)"""
<|body_0|>
def update(self, k, x):
"""k番目の値をxに更新 O(N) k: index(0-index) x: update ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SegTree:
"""Segment Tree"""
def __init__(self, init_val, segfunc, ide_ele):
"""初期化 init_val: 配列の初期値 segfunc: 区間にしたい操作 ide_ele: 単位元 n: 要素数 num: n以上の最小の2のべき乗 tree: セグメント木(1-index)"""
n = len(init_val)
self.segfunc = segfunc
self.ide_ele = ide_ele
self.num = 1 << (n -... | the_stack_v2_python_sparse | acl_b.py | inzm99/atcoder | train | 0 |
23f1b8647cce82f9a5b7fe535fc1eddb37fbf8b9 | [
"if allowed_classes is None:\n allowed_classes = []\nself._allowed_classes = set(allowed_classes)",
"if len(self._allowed_classes) > 0 and type(item) not in self._allowed_classes:\n raise ValueError(f'Cannot add {type(item)} to restricted set: {self._allowed_classes}')\nif item in self:\n super().discard... | <|body_start_0|>
if allowed_classes is None:
allowed_classes = []
self._allowed_classes = set(allowed_classes)
<|end_body_0|>
<|body_start_1|>
if len(self._allowed_classes) > 0 and type(item) not in self._allowed_classes:
raise ValueError(f'Cannot add {type(item)} to res... | a DSC set object. | dsc_set | [
"BSD-2-Clause-Patent"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class dsc_set:
"""a DSC set object."""
def __init__(self, allowed_classes=None):
"""Initializes an empty set."""
<|body_0|>
def add(self, item):
"""Adds the item to the set. Raises: (ValueError): if the type is not allowed to be added."""
<|body_1|>
<|end_skel... | stack_v2_sparse_classes_75kplus_train_073414 | 25,923 | permissive | [
{
"docstring": "Initializes an empty set.",
"name": "__init__",
"signature": "def __init__(self, allowed_classes=None)"
},
{
"docstring": "Adds the item to the set. Raises: (ValueError): if the type is not allowed to be added.",
"name": "add",
"signature": "def add(self, item)"
}
] | 2 | null | Implement the Python class `dsc_set` described below.
Class description:
a DSC set object.
Method signatures and docstrings:
- def __init__(self, allowed_classes=None): Initializes an empty set.
- def add(self, item): Adds the item to the set. Raises: (ValueError): if the type is not allowed to be added. | Implement the Python class `dsc_set` described below.
Class description:
a DSC set object.
Method signatures and docstrings:
- def __init__(self, allowed_classes=None): Initializes an empty set.
- def add(self, item): Adds the item to the set. Raises: (ValueError): if the type is not allowed to be added.
<|skeleton|... | 78295929b37af62a8cfc4c28eab72ed0c468f350 | <|skeleton|>
class dsc_set:
"""a DSC set object."""
def __init__(self, allowed_classes=None):
"""Initializes an empty set."""
<|body_0|>
def add(self, item):
"""Adds the item to the set. Raises: (ValueError): if the type is not allowed to be added."""
<|body_1|>
<|end_skel... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class dsc_set:
"""a DSC set object."""
def __init__(self, allowed_classes=None):
"""Initializes an empty set."""
if allowed_classes is None:
allowed_classes = []
self._allowed_classes = set(allowed_classes)
def add(self, item):
"""Adds the item to the set. Raise... | the_stack_v2_python_sparse | edk2toollib/uefi/edk2/build_objects/dsc.py | tianocore/edk2-pytool-library | train | 47 |
a045ade5528c7dd52b83167a2633e5d4d1ef2ea6 | [
"self.tokenlabel = tokenlabel\nif tokenlabel is not None:\n self.token_xpath = '[@{:s}]'.format(tokenlabel)\nelse:\n self.token_xpath = ''\nself.token_xpath = './/tok' + self.token_xpath\nif doc_sel == 'DOCUMENT':\n self.doc_xpath = './/doc'\nelif doc_sel == 'SENTENCE':\n self.doc_xpath = './/doc//sent'... | <|body_start_0|>
self.tokenlabel = tokenlabel
if tokenlabel is not None:
self.token_xpath = '[@{:s}]'.format(tokenlabel)
else:
self.token_xpath = ''
self.token_xpath = './/tok' + self.token_xpath
if doc_sel == 'DOCUMENT':
self.doc_xpath = './/d... | BagOfWords | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BagOfWords:
def __init__(self, tokenlabel='label', doc_sel='DOCUMENT'):
"""Specifies the element of a corpus to treat as a document. Can be one of "DOCUMENT" or "SENTENCE". Specifies the attribute of the token to treat as a word. If None, extracts the text of the token to treat as a word... | stack_v2_sparse_classes_75kplus_train_073415 | 2,683 | no_license | [
{
"docstring": "Specifies the element of a corpus to treat as a document. Can be one of \"DOCUMENT\" or \"SENTENCE\". Specifies the attribute of the token to treat as a word. If None, extracts the text of the token to treat as a word.",
"name": "__init__",
"signature": "def __init__(self, tokenlabel='la... | 2 | stack_v2_sparse_classes_30k_train_002246 | Implement the Python class `BagOfWords` described below.
Class description:
Implement the BagOfWords class.
Method signatures and docstrings:
- def __init__(self, tokenlabel='label', doc_sel='DOCUMENT'): Specifies the element of a corpus to treat as a document. Can be one of "DOCUMENT" or "SENTENCE". Specifies the at... | Implement the Python class `BagOfWords` described below.
Class description:
Implement the BagOfWords class.
Method signatures and docstrings:
- def __init__(self, tokenlabel='label', doc_sel='DOCUMENT'): Specifies the element of a corpus to treat as a document. Can be one of "DOCUMENT" or "SENTENCE". Specifies the at... | affe6a5c64697d38081d0d2581212c2f2fdd304a | <|skeleton|>
class BagOfWords:
def __init__(self, tokenlabel='label', doc_sel='DOCUMENT'):
"""Specifies the element of a corpus to treat as a document. Can be one of "DOCUMENT" or "SENTENCE". Specifies the attribute of the token to treat as a word. If None, extracts the text of the token to treat as a word... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class BagOfWords:
def __init__(self, tokenlabel='label', doc_sel='DOCUMENT'):
"""Specifies the element of a corpus to treat as a document. Can be one of "DOCUMENT" or "SENTENCE". Specifies the attribute of the token to treat as a word. If None, extracts the text of the token to treat as a word."""
s... | the_stack_v2_python_sparse | themecrafter/preprocessing/words.py | joesdesk/themecrafter | train | 1 | |
c8c26f5c37a8f07031365282c3d7b7aff23d96c0 | [
"private_key_path = Path(path)\ninstance = SshKey(private_key=private_key_path.read_text(), label=private_key_path.name)\nself.validate_ssh_key(instance, storage)\nreturn instance",
"with_same_label = storage.filter(SshKey, **{'label': instance.label, 'id.ne': instance.id})\nif with_same_label:\n raise Invalid... | <|body_start_0|>
private_key_path = Path(path)
instance = SshKey(private_key=private_key_path.read_text(), label=private_key_path.name)
self.validate_ssh_key(instance, storage)
return instance
<|end_body_0|>
<|body_start_1|>
with_same_label = storage.filter(SshKey, **{'label': i... | Mixin for create new ssh key from file. | SshKeyGeneratorMixin | [
"BSD-3-Clause",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SshKeyGeneratorMixin:
"""Mixin for create new ssh key from file."""
def generate_ssh_key_instance(self, path, storage):
"""Generate ssh key from file."""
<|body_0|>
def validate_ssh_key(self, instance, storage):
"""Raise an error when any instances exist with sam... | stack_v2_sparse_classes_75kplus_train_073416 | 2,354 | permissive | [
{
"docstring": "Generate ssh key from file.",
"name": "generate_ssh_key_instance",
"signature": "def generate_ssh_key_instance(self, path, storage)"
},
{
"docstring": "Raise an error when any instances exist with same label.",
"name": "validate_ssh_key",
"signature": "def validate_ssh_ke... | 2 | stack_v2_sparse_classes_30k_train_037576 | Implement the Python class `SshKeyGeneratorMixin` described below.
Class description:
Mixin for create new ssh key from file.
Method signatures and docstrings:
- def generate_ssh_key_instance(self, path, storage): Generate ssh key from file.
- def validate_ssh_key(self, instance, storage): Raise an error when any ins... | Implement the Python class `SshKeyGeneratorMixin` described below.
Class description:
Mixin for create new ssh key from file.
Method signatures and docstrings:
- def generate_ssh_key_instance(self, path, storage): Generate ssh key from file.
- def validate_ssh_key(self, instance, storage): Raise an error when any ins... | 2664d0c70d3d682ad931b885b4965447b156c280 | <|skeleton|>
class SshKeyGeneratorMixin:
"""Mixin for create new ssh key from file."""
def generate_ssh_key_instance(self, path, storage):
"""Generate ssh key from file."""
<|body_0|>
def validate_ssh_key(self, instance, storage):
"""Raise an error when any instances exist with sam... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SshKeyGeneratorMixin:
"""Mixin for create new ssh key from file."""
def generate_ssh_key_instance(self, path, storage):
"""Generate ssh key from file."""
private_key_path = Path(path)
instance = SshKey(private_key=private_key_path.read_text(), label=private_key_path.name)
... | the_stack_v2_python_sparse | termius/handlers/ssh_key.py | termius/termius-cli | train | 262 |
44fedd5f108a10694d4a9a0880751ea0533a54de | [
"super().__init__()\nself.pending_q = data_q\nself.done_q = batch_q\nself.stop_event = stop_event\nself.batch_size = batch_size\nself.batch = []\nif n_in_queue is None:\n self.n_in_queue = Counter()\nelse:\n self.n_in_queue = n_in_queue\nself.nsaved = 0\nself.postprocess_fun = postprocess_fun",
"while not s... | <|body_start_0|>
super().__init__()
self.pending_q = data_q
self.done_q = batch_q
self.stop_event = stop_event
self.batch_size = batch_size
self.batch = []
if n_in_queue is None:
self.n_in_queue = Counter()
else:
self.n_in_queue = n... | Create a new process that will aggregate examples created by DataGenerator processes into a batch of examples | DataAggregator | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DataAggregator:
"""Create a new process that will aggregate examples created by DataGenerator processes into a batch of examples"""
def __init__(self, data_q: Queue, batch_q: Queue, stop_event: Event, batch_size: int, n_in_queue: Counter=None, postprocess_fun=None):
"""This is the co... | stack_v2_sparse_classes_75kplus_train_073417 | 7,565 | permissive | [
{
"docstring": "This is the constructor for the class. @params: data_q (Queue): A Queue in which to get new examples batch_q (Queue): A Queue in which to put new batches of examples stop_event (Event): An Event to kill the DataAggregator process batch_size (int): The number of examples in a batch n_in_queue (Co... | 2 | null | Implement the Python class `DataAggregator` described below.
Class description:
Create a new process that will aggregate examples created by DataGenerator processes into a batch of examples
Method signatures and docstrings:
- def __init__(self, data_q: Queue, batch_q: Queue, stop_event: Event, batch_size: int, n_in_q... | Implement the Python class `DataAggregator` described below.
Class description:
Create a new process that will aggregate examples created by DataGenerator processes into a batch of examples
Method signatures and docstrings:
- def __init__(self, data_q: Queue, batch_q: Queue, stop_event: Event, batch_size: int, n_in_q... | 3c0c12b06b01175e0f0ab0a60383cfc7da8fb402 | <|skeleton|>
class DataAggregator:
"""Create a new process that will aggregate examples created by DataGenerator processes into a batch of examples"""
def __init__(self, data_q: Queue, batch_q: Queue, stop_event: Event, batch_size: int, n_in_queue: Counter=None, postprocess_fun=None):
"""This is the co... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DataAggregator:
"""Create a new process that will aggregate examples created by DataGenerator processes into a batch of examples"""
def __init__(self, data_q: Queue, batch_q: Queue, stop_event: Event, batch_size: int, n_in_queue: Counter=None, postprocess_fun=None):
"""This is the constructor for... | the_stack_v2_python_sparse | vrmslearn/Inputqueue.py | GeoCode-polymtl/Deep_1D_velocity | train | 16 |
27b9deaa7481efb6f3041665dbb30fa4fc107915 | [
"labels, label_ids = self.get_labels()\nself.save_field_to_hdf5(set_name=self.set_name, field='labels', data=labels, dtype=np.uint8, fillvalue=0)\nreturn label_ids",
"labels = self.data['labels']\nlabel_ids = list(range(len(labels)))\nreturn (labels, label_ids)"
] | <|body_start_0|>
labels, label_ids = self.get_labels()
self.save_field_to_hdf5(set_name=self.set_name, field='labels', data=labels, dtype=np.uint8, fillvalue=0)
return label_ids
<|end_body_0|>
<|body_start_1|>
labels = self.data['labels']
label_ids = list(range(len(labels)))
... | Label id field metadata process/save class. | LabelIdField | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LabelIdField:
"""Label id field metadata process/save class."""
def process(self):
"""Processes and saves the labels metadata to hdf5."""
<|body_0|>
def get_labels(self):
"""Returns a np.ndarray of labels and a list of label ids for each row of 'object_ids' field... | stack_v2_sparse_classes_75kplus_train_073418 | 9,235 | permissive | [
{
"docstring": "Processes and saves the labels metadata to hdf5.",
"name": "process",
"signature": "def process(self)"
},
{
"docstring": "Returns a np.ndarray of labels and a list of label ids for each row of 'object_ids' field.",
"name": "get_labels",
"signature": "def get_labels(self)"... | 2 | stack_v2_sparse_classes_30k_train_036010 | Implement the Python class `LabelIdField` described below.
Class description:
Label id field metadata process/save class.
Method signatures and docstrings:
- def process(self): Processes and saves the labels metadata to hdf5.
- def get_labels(self): Returns a np.ndarray of labels and a list of label ids for each row ... | Implement the Python class `LabelIdField` described below.
Class description:
Label id field metadata process/save class.
Method signatures and docstrings:
- def process(self): Processes and saves the labels metadata to hdf5.
- def get_labels(self): Returns a np.ndarray of labels and a list of label ids for each row ... | e0be95d941b50a5b2e27ffa1c5be20dc6aa2d6a1 | <|skeleton|>
class LabelIdField:
"""Label id field metadata process/save class."""
def process(self):
"""Processes and saves the labels metadata to hdf5."""
<|body_0|>
def get_labels(self):
"""Returns a np.ndarray of labels and a list of label ids for each row of 'object_ids' field... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class LabelIdField:
"""Label id field metadata process/save class."""
def process(self):
"""Processes and saves the labels metadata to hdf5."""
labels, label_ids = self.get_labels()
self.save_field_to_hdf5(set_name=self.set_name, field='labels', data=labels, dtype=np.uint8, fillvalue=0)... | the_stack_v2_python_sparse | dbcollection/datasets/mnist/classification.py | dbcollection/dbcollection | train | 25 |
df42bb737f4a84506114f08a24aa01ae322ecc8c | [
"super(Decoder, self).__init__()\nself.deEmb = nn.Embedding(deVocabSize, embSize)\nself.dePos = Position(deVocabSize, embSize, dropout).to(device)\nself.layers = nn.ModuleList([DecoderLayer(embSize, qSize, kSize, vSize, hiddenSize, numHeads=numHeads, bias=bias) for _ in range(numLayers)]).to(device)",
"deInputs =... | <|body_start_0|>
super(Decoder, self).__init__()
self.deEmb = nn.Embedding(deVocabSize, embSize)
self.dePos = Position(deVocabSize, embSize, dropout).to(device)
self.layers = nn.ModuleList([DecoderLayer(embSize, qSize, kSize, vSize, hiddenSize, numHeads=numHeads, bias=bias) for _ in rang... | Decoder | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Decoder:
def __init__(self, deVocabSize, embSize, qSize, kSize, vSize, hiddenSize, numHeads=numHeads, bias=bias, numLayers=numLayers, dropout=dropout):
"""@doc: Decoder @author: Alpaca-Man @date: 2021/2/22 @param: { deVocabSize: Decoder 单词表长度 embSize: 词向量维度 qSize: Q 的维度 kSize: K 的维度(需要与 ... | stack_v2_sparse_classes_75kplus_train_073419 | 9,438 | no_license | [
{
"docstring": "@doc: Decoder @author: Alpaca-Man @date: 2021/2/22 @param: { deVocabSize: Decoder 单词表长度 embSize: 词向量维度 qSize: Q 的维度 kSize: K 的维度(需要与 Q 的维度相等) vSize: V 的维度 hiddenSize: 两层全连接层中间的维度 numHeads: 头数 default 8 bias: 偏置 default False numLayers: Encoder 层数 default 8 } @return: { }",
"name": "__init__"... | 2 | null | Implement the Python class `Decoder` described below.
Class description:
Implement the Decoder class.
Method signatures and docstrings:
- def __init__(self, deVocabSize, embSize, qSize, kSize, vSize, hiddenSize, numHeads=numHeads, bias=bias, numLayers=numLayers, dropout=dropout): @doc: Decoder @author: Alpaca-Man @da... | Implement the Python class `Decoder` described below.
Class description:
Implement the Decoder class.
Method signatures and docstrings:
- def __init__(self, deVocabSize, embSize, qSize, kSize, vSize, hiddenSize, numHeads=numHeads, bias=bias, numLayers=numLayers, dropout=dropout): @doc: Decoder @author: Alpaca-Man @da... | 49824925970f0439634dc66a7f19edc512f18a5f | <|skeleton|>
class Decoder:
def __init__(self, deVocabSize, embSize, qSize, kSize, vSize, hiddenSize, numHeads=numHeads, bias=bias, numLayers=numLayers, dropout=dropout):
"""@doc: Decoder @author: Alpaca-Man @date: 2021/2/22 @param: { deVocabSize: Decoder 单词表长度 embSize: 词向量维度 qSize: Q 的维度 kSize: K 的维度(需要与 ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Decoder:
def __init__(self, deVocabSize, embSize, qSize, kSize, vSize, hiddenSize, numHeads=numHeads, bias=bias, numLayers=numLayers, dropout=dropout):
"""@doc: Decoder @author: Alpaca-Man @date: 2021/2/22 @param: { deVocabSize: Decoder 单词表长度 embSize: 词向量维度 qSize: Q 的维度 kSize: K 的维度(需要与 Q 的维度相等) vSize... | the_stack_v2_python_sparse | Transformer/standard/Transformer.py | Alpaca-Man/NLP-Newcomer | train | 1 | |
269834b1313970654ee77467a6237c292e52caa7 | [
"self.start_time = datetime.now()\nself.master_db = get_master_mongo_conn()\nself.clean_ingredients()",
"query_params = {}\nrecipes = self.master_db['cleansed_ingredients'].find(query_params, no_cursor_timeout=True)\ntotal_records_count = recipes.count()\nspecial_cases = []\nsand_cases = []\nerror_cases = []\nfor... | <|body_start_0|>
self.start_time = datetime.now()
self.master_db = get_master_mongo_conn()
self.clean_ingredients()
<|end_body_0|>
<|body_start_1|>
query_params = {}
recipes = self.master_db['cleansed_ingredients'].find(query_params, no_cursor_timeout=True)
total_records... | Tokenizes ingredient text | TokenizeIngredients | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TokenizeIngredients:
"""Tokenizes ingredient text"""
def __init__(self):
"""Creating mongo connection and calling main method directly from initialization method"""
<|body_0|>
def clean_ingredients(self):
"""This is the main function where the tokenization starts... | stack_v2_sparse_classes_75kplus_train_073420 | 2,209 | no_license | [
{
"docstring": "Creating mongo connection and calling main method directly from initialization method",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "This is the main function where the tokenization starts",
"name": "clean_ingredients",
"signature": "def clean_... | 2 | stack_v2_sparse_classes_30k_train_002192 | Implement the Python class `TokenizeIngredients` described below.
Class description:
Tokenizes ingredient text
Method signatures and docstrings:
- def __init__(self): Creating mongo connection and calling main method directly from initialization method
- def clean_ingredients(self): This is the main function where th... | Implement the Python class `TokenizeIngredients` described below.
Class description:
Tokenizes ingredient text
Method signatures and docstrings:
- def __init__(self): Creating mongo connection and calling main method directly from initialization method
- def clean_ingredients(self): This is the main function where th... | 495bfd49f245b1a6b7bc1d336745813a30c898ab | <|skeleton|>
class TokenizeIngredients:
"""Tokenizes ingredient text"""
def __init__(self):
"""Creating mongo connection and calling main method directly from initialization method"""
<|body_0|>
def clean_ingredients(self):
"""This is the main function where the tokenization starts... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TokenizeIngredients:
"""Tokenizes ingredient text"""
def __init__(self):
"""Creating mongo connection and calling main method directly from initialization method"""
self.start_time = datetime.now()
self.master_db = get_master_mongo_conn()
self.clean_ingredients()
def ... | the_stack_v2_python_sparse | cleansing_ingredients/get_error_cases.py | nireeshach/Groceryappstore | train | 0 |
9ea1c2746cd676d8a16df87e9b920ae9f6c52dd6 | [
"seq_length = 4\nnum_predictions = 2\nxlnet_base = _get_xlnet_base()\nxlnet_trainer_model = xlnet.XLNetPretrainer(network=xlnet_base)\ninputs = dict(input_word_ids=tf.keras.layers.Input(shape=(seq_length,), dtype=tf.int32, name='input_word_ids'), input_type_ids=tf.keras.layers.Input(shape=(seq_length,), dtype=tf.in... | <|body_start_0|>
seq_length = 4
num_predictions = 2
xlnet_base = _get_xlnet_base()
xlnet_trainer_model = xlnet.XLNetPretrainer(network=xlnet_base)
inputs = dict(input_word_ids=tf.keras.layers.Input(shape=(seq_length,), dtype=tf.int32, name='input_word_ids'), input_type_ids=tf.ker... | XLNetPretrainerTest | [
"Apache-2.0",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class XLNetPretrainerTest:
def test_xlnet_trainer(self):
"""Validates that the Keras object can be created."""
<|body_0|>
def test_xlnet_tensor_call(self):
"""Validates that the Keras object can be invoked."""
<|body_1|>
def test_serialize_deserialize(self):
... | stack_v2_sparse_classes_75kplus_train_073421 | 13,124 | permissive | [
{
"docstring": "Validates that the Keras object can be created.",
"name": "test_xlnet_trainer",
"signature": "def test_xlnet_trainer(self)"
},
{
"docstring": "Validates that the Keras object can be invoked.",
"name": "test_xlnet_tensor_call",
"signature": "def test_xlnet_tensor_call(self... | 3 | stack_v2_sparse_classes_30k_train_001553 | Implement the Python class `XLNetPretrainerTest` described below.
Class description:
Implement the XLNetPretrainerTest class.
Method signatures and docstrings:
- def test_xlnet_trainer(self): Validates that the Keras object can be created.
- def test_xlnet_tensor_call(self): Validates that the Keras object can be inv... | Implement the Python class `XLNetPretrainerTest` described below.
Class description:
Implement the XLNetPretrainerTest class.
Method signatures and docstrings:
- def test_xlnet_trainer(self): Validates that the Keras object can be created.
- def test_xlnet_tensor_call(self): Validates that the Keras object can be inv... | 6fc53292b1d3ce3c0340ce724c2c11c77e663d27 | <|skeleton|>
class XLNetPretrainerTest:
def test_xlnet_trainer(self):
"""Validates that the Keras object can be created."""
<|body_0|>
def test_xlnet_tensor_call(self):
"""Validates that the Keras object can be invoked."""
<|body_1|>
def test_serialize_deserialize(self):
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class XLNetPretrainerTest:
def test_xlnet_trainer(self):
"""Validates that the Keras object can be created."""
seq_length = 4
num_predictions = 2
xlnet_base = _get_xlnet_base()
xlnet_trainer_model = xlnet.XLNetPretrainer(network=xlnet_base)
inputs = dict(input_word_id... | the_stack_v2_python_sparse | models/official/nlp/modeling/models/xlnet_test.py | aboerzel/German_License_Plate_Recognition | train | 34 | |
0145583c62075cd4d4baaa61a746f33d0397f943 | [
"orders = []\n\ndef inorder(node):\n if node:\n inorder(node.left)\n orders.append(node.val)\n inorder(node.right)\ninorder(root)\nreturn orders",
"res, stack = ([], [])\ncur = root\nwhile cur or len(stack) != 0:\n while cur:\n '\\n 对一节点执行左根右的遍历，其实就是不断地去寻找节点的左子... | <|body_start_0|>
orders = []
def inorder(node):
if node:
inorder(node.left)
orders.append(node.val)
inorder(node.right)
inorder(root)
return orders
<|end_body_0|>
<|body_start_1|>
res, stack = ([], [])
cur = ro... | 94. 给定一个二叉树，返回它的中序 遍历。 示例: 输入: [1,null,2,3] 1 2 / 3 输出: [1,3,2] 分析： 树的中序遍历的顺序为：左根右 | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
"""94. 给定一个二叉树，返回它的中序 遍历。 示例: 输入: [1,null,2,3] 1 2 / 3 输出: [1,3,2] 分析： 树的中序遍历的顺序为：左根右"""
def inorder_traversal(self, root):
""":type root: TreeNode :rtype: List[int] 直接使用递归，从根节点开始遍历的顺序为左根右，假定当前层左子树、右子树均完成遍历， 则此时对于根节点来说遍历的顺序就为左节点、根节点、右节点。左子树、右子树中任意节点均与根节点具有相同的遍历规律 因为树种每个节点都要... | stack_v2_sparse_classes_75kplus_train_073422 | 2,703 | no_license | [
{
"docstring": ":type root: TreeNode :rtype: List[int] 直接使用递归，从根节点开始遍历的顺序为左根右，假定当前层左子树、右子树均完成遍历， 则此时对于根节点来说遍历的顺序就为左节点、根节点、右节点。左子树、右子树中任意节点均与根节点具有相同的遍历规律 因为树种每个节点都要被访问两遍，因此时间复杂度为O(n)，空间上如果除了子节点外所有结点都具有左、右子节点，则空间复杂度为 O(n)，平均下来为O(logn) 时间复杂度：O(n) 空间复杂度：O(logn)",
"name": "inorder_traversal",
"signature": "d... | 2 | stack_v2_sparse_classes_30k_train_053914 | Implement the Python class `Solution` described below.
Class description:
94. 给定一个二叉树，返回它的中序 遍历。 示例: 输入: [1,null,2,3] 1 2 / 3 输出: [1,3,2] 分析： 树的中序遍历的顺序为：左根右
Method signatures and docstrings:
- def inorder_traversal(self, root): :type root: TreeNode :rtype: List[int] 直接使用递归，从根节点开始遍历的顺序为左根右，假定当前层左子树、右子树均完成遍历， 则此时对于根节点来... | Implement the Python class `Solution` described below.
Class description:
94. 给定一个二叉树，返回它的中序 遍历。 示例: 输入: [1,null,2,3] 1 2 / 3 输出: [1,3,2] 分析： 树的中序遍历的顺序为：左根右
Method signatures and docstrings:
- def inorder_traversal(self, root): :type root: TreeNode :rtype: List[int] 直接使用递归，从根节点开始遍历的顺序为左根右，假定当前层左子树、右子树均完成遍历， 则此时对于根节点来... | 2c534185854c1a6f5ffdb2698f9db9989f30a25b | <|skeleton|>
class Solution:
"""94. 给定一个二叉树，返回它的中序 遍历。 示例: 输入: [1,null,2,3] 1 2 / 3 输出: [1,3,2] 分析： 树的中序遍历的顺序为：左根右"""
def inorder_traversal(self, root):
""":type root: TreeNode :rtype: List[int] 直接使用递归，从根节点开始遍历的顺序为左根右，假定当前层左子树、右子树均完成遍历， 则此时对于根节点来说遍历的顺序就为左节点、根节点、右节点。左子树、右子树中任意节点均与根节点具有相同的遍历规律 因为树种每个节点都要... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
"""94. 给定一个二叉树，返回它的中序 遍历。 示例: 输入: [1,null,2,3] 1 2 / 3 输出: [1,3,2] 分析： 树的中序遍历的顺序为：左根右"""
def inorder_traversal(self, root):
""":type root: TreeNode :rtype: List[int] 直接使用递归，从根节点开始遍历的顺序为左根右，假定当前层左子树、右子树均完成遍历， 则此时对于根节点来说遍历的顺序就为左节点、根节点、右节点。左子树、右子树中任意节点均与根节点具有相同的遍历规律 因为树种每个节点都要被访问两遍，因此时间复杂度... | the_stack_v2_python_sparse | Week 02/id_668/leetcode_94_668.py | Carryours/algorithm004-03 | train | 2 |
9b394f830b91a7ca0074dd44e3fb9f58f04b2d3e | [
"binding_ids = self.session.search(self.model._name, [('civicrm_id', '=', external_id), ('backend_id', '=', self.backend_record.id)])\nif not binding_ids:\n return None\nassert len(binding_ids) == 1, 'Several records found: %s' % binding_ids\nbinding_id = binding_ids[0]\nif unwrap:\n return self.session.read(... | <|body_start_0|>
binding_ids = self.session.search(self.model._name, [('civicrm_id', '=', external_id), ('backend_id', '=', self.backend_record.id)])
if not binding_ids:
return None
assert len(binding_ids) == 1, 'Several records found: %s' % binding_ids
binding_id = binding_i... | CivicrmBinder | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CivicrmBinder:
def to_openerp(self, external_id, unwrap=False):
"""Give the OpenERP ID for an external ID :param external_id: external ID for which we want the OpenERP ID :param unwrap: if True, returns the openerp_id of the icops_xxxx record, else return the id (binding id) of that reco... | stack_v2_sparse_classes_75kplus_train_073423 | 2,576 | no_license | [
{
"docstring": "Give the OpenERP ID for an external ID :param external_id: external ID for which we want the OpenERP ID :param unwrap: if True, returns the openerp_id of the icops_xxxx record, else return the id (binding id) of that record :return: a record ID, depending on the value of unwrap, or None if the e... | 3 | null | Implement the Python class `CivicrmBinder` described below.
Class description:
Implement the CivicrmBinder class.
Method signatures and docstrings:
- def to_openerp(self, external_id, unwrap=False): Give the OpenERP ID for an external ID :param external_id: external ID for which we want the OpenERP ID :param unwrap: ... | Implement the Python class `CivicrmBinder` described below.
Class description:
Implement the CivicrmBinder class.
Method signatures and docstrings:
- def to_openerp(self, external_id, unwrap=False): Give the OpenERP ID for an external ID :param external_id: external ID for which we want the OpenERP ID :param unwrap: ... | a359060d67d3049ffad0946b65691a73738f0ebf | <|skeleton|>
class CivicrmBinder:
def to_openerp(self, external_id, unwrap=False):
"""Give the OpenERP ID for an external ID :param external_id: external ID for which we want the OpenERP ID :param unwrap: if True, returns the openerp_id of the icops_xxxx record, else return the id (binding id) of that reco... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CivicrmBinder:
def to_openerp(self, external_id, unwrap=False):
"""Give the OpenERP ID for an external ID :param external_id: external ID for which we want the OpenERP ID :param unwrap: if True, returns the openerp_id of the icops_xxxx record, else return the id (binding id) of that record :return: a ... | the_stack_v2_python_sparse | sp_civicrmconnector/binder.py | shouyejing/civicrm_connector | train | 0 | |
5e76fab39bf8811971226f2a15ef2bb2432703c3 | [
"self.params = {}\nself.reg = reg\nself.dtype = dtype\nC, H, W = input_dim\npooled_height = 1 + (H - 2) / 2\npooled_width = 1 + (W - 2) / 2\nself.params['W1'] = np.random.randn(num_filters, C, filter_size, filter_size) * weight_scale\nself.params['b1'] = np.zeros(num_filters)\nself.params['W2'] = np.random.randn(nu... | <|body_start_0|>
self.params = {}
self.reg = reg
self.dtype = dtype
C, H, W = input_dim
pooled_height = 1 + (H - 2) / 2
pooled_width = 1 + (W - 2) / 2
self.params['W1'] = np.random.randn(num_filters, C, filter_size, filter_size) * weight_scale
self.params[... | A three-layer convolutional network with the following architecture: conv - relu - 2x2 max pool - affine - relu - affine - softmax The network operates on minibatches of data that have shape (N, C, H, W) consisting of N images, each with height H and width W and with C input channels. | ThreeLayerConvNet | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ThreeLayerConvNet:
"""A three-layer convolutional network with the following architecture: conv - relu - 2x2 max pool - affine - relu - affine - softmax The network operates on minibatches of data that have shape (N, C, H, W) consisting of N images, each with height H and width W and with C input... | stack_v2_sparse_classes_75kplus_train_073424 | 9,082 | no_license | [
{
"docstring": "Initialize a new network. Inputs: - input_dim: Tuple (C, H, W) giving size of input data - num_filters: Number of filters to use in the convolutional layer - filter_size: Size of filters to use in the convolutional layer - hidden_dim: Number of units to use in the fully-connected hidden layer - ... | 2 | null | Implement the Python class `ThreeLayerConvNet` described below.
Class description:
A three-layer convolutional network with the following architecture: conv - relu - 2x2 max pool - affine - relu - affine - softmax The network operates on minibatches of data that have shape (N, C, H, W) consisting of N images, each wit... | Implement the Python class `ThreeLayerConvNet` described below.
Class description:
A three-layer convolutional network with the following architecture: conv - relu - 2x2 max pool - affine - relu - affine - softmax The network operates on minibatches of data that have shape (N, C, H, W) consisting of N images, each wit... | 49a1992ef1559030287cd1090ad410936f2125fd | <|skeleton|>
class ThreeLayerConvNet:
"""A three-layer convolutional network with the following architecture: conv - relu - 2x2 max pool - affine - relu - affine - softmax The network operates on minibatches of data that have shape (N, C, H, W) consisting of N images, each with height H and width W and with C input... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ThreeLayerConvNet:
"""A three-layer convolutional network with the following architecture: conv - relu - 2x2 max pool - affine - relu - affine - softmax The network operates on minibatches of data that have shape (N, C, H, W) consisting of N images, each with height H and width W and with C input channels."""... | the_stack_v2_python_sparse | cs231n-convnets-2016/assignment-2/assignment2/cs231n/classifiers/cnn.py | fagan2888/original-machine-learning | train | 0 |
da2c3febebe42f269d2b0802d4378863d8d970ee | [
"this_user = self.context['request'].user\nworkflow = validated_data['workflow']\nif workflow.user != this_user:\n raise APIException(_('Incorrect permission to manipulate workflow.'))\naction = validated_data['action']\nif action is not None and action.workflow != workflow:\n raise APIException(_('Incorrect ... | <|body_start_0|>
this_user = self.context['request'].user
workflow = validated_data['workflow']
if workflow.user != this_user:
raise APIException(_('Incorrect permission to manipulate workflow.'))
action = validated_data['action']
if action is not None and action.work... | Serializer to take care of a few fields and the item column. | ScheduledOperationSerializer | [
"LGPL-2.0-or-later",
"BSD-3-Clause",
"MIT",
"Apache-2.0",
"LGPL-2.1-only",
"Python-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ScheduledOperationSerializer:
"""Serializer to take care of a few fields and the item column."""
def extra_validation(self, validated_data: Dict):
"""Check for extra properties. Checking for extra properties in the information contained in the validated data. Namely: - The action nam... | stack_v2_sparse_classes_75kplus_train_073425 | 8,568 | permissive | [
{
"docstring": "Check for extra properties. Checking for extra properties in the information contained in the validated data. Namely: - The action name corresponds with a valid action for the user. - The execution time must be in the future - The received object has a payload - The item_column, if present, must... | 3 | stack_v2_sparse_classes_30k_train_000866 | Implement the Python class `ScheduledOperationSerializer` described below.
Class description:
Serializer to take care of a few fields and the item column.
Method signatures and docstrings:
- def extra_validation(self, validated_data: Dict): Check for extra properties. Checking for extra properties in the information ... | Implement the Python class `ScheduledOperationSerializer` described below.
Class description:
Serializer to take care of a few fields and the item column.
Method signatures and docstrings:
- def extra_validation(self, validated_data: Dict): Check for extra properties. Checking for extra properties in the information ... | c432745dfff932cbe7397100422d49df78f0a882 | <|skeleton|>
class ScheduledOperationSerializer:
"""Serializer to take care of a few fields and the item column."""
def extra_validation(self, validated_data: Dict):
"""Check for extra properties. Checking for extra properties in the information contained in the validated data. Namely: - The action nam... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ScheduledOperationSerializer:
"""Serializer to take care of a few fields and the item column."""
def extra_validation(self, validated_data: Dict):
"""Check for extra properties. Checking for extra properties in the information contained in the validated data. Namely: - The action name corresponds... | the_stack_v2_python_sparse | ontask/scheduler/serializers.py | abelardopardo/ontask_b | train | 43 |
9dd439a6460486272b6c8148cee620a926b5507a | [
"for i in xrange(1, len(nums)):\n if i % 2 == 0 and nums[i] > nums[i - 1] or (i % 2 == 1 and nums[i] < nums[i - 1]):\n nums[i], nums[i - 1] = (nums[i - 1], nums[i])",
"nums.sort()\nfor i in xrange((len(nums) - 1) / 2):\n nums[2 * i + 1], nums[2 * i + 2] = (nums[2 * i + 2], nums[2 * i + 1])"
] | <|body_start_0|>
for i in xrange(1, len(nums)):
if i % 2 == 0 and nums[i] > nums[i - 1] or (i % 2 == 1 and nums[i] < nums[i - 1]):
nums[i], nums[i - 1] = (nums[i - 1], nums[i])
<|end_body_0|>
<|body_start_1|>
nums.sort()
for i in xrange((len(nums) - 1) / 2):
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def wiggleSort(self, nums):
""":type nums: List[int] :rtype: void Do not return anything, modify nums in-place instead."""
<|body_0|>
def wiggleSort_nlogn(self, nums):
""":type nums: List[int] :rtype: void Do not return anything, modify nums in-place instea... | stack_v2_sparse_classes_75kplus_train_073426 | 718 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: void Do not return anything, modify nums in-place instead.",
"name": "wiggleSort",
"signature": "def wiggleSort(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: void Do not return anything, modify nums in-place instead.",
"name": "wi... | 2 | stack_v2_sparse_classes_30k_train_002061 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def wiggleSort(self, nums): :type nums: List[int] :rtype: void Do not return anything, modify nums in-place instead.
- def wiggleSort_nlogn(self, nums): :type nums: List[int] :rt... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def wiggleSort(self, nums): :type nums: List[int] :rtype: void Do not return anything, modify nums in-place instead.
- def wiggleSort_nlogn(self, nums): :type nums: List[int] :rt... | ed15eb27936b39980d4cb5fb61cd937ec7ddcb6a | <|skeleton|>
class Solution:
def wiggleSort(self, nums):
""":type nums: List[int] :rtype: void Do not return anything, modify nums in-place instead."""
<|body_0|>
def wiggleSort_nlogn(self, nums):
""":type nums: List[int] :rtype: void Do not return anything, modify nums in-place instea... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def wiggleSort(self, nums):
""":type nums: List[int] :rtype: void Do not return anything, modify nums in-place instead."""
for i in xrange(1, len(nums)):
if i % 2 == 0 and nums[i] > nums[i - 1] or (i % 2 == 1 and nums[i] < nums[i - 1]):
nums[i], nums[i - 1... | the_stack_v2_python_sparse | alice/LC280.py | AliceTTXu/LeetCode | train | 0 | |
6953bdcd9eacadc9f273a711cbc22ada826d51ce | [
"elems = self.find_elements_by_css_selector(css_selector)\nfound = len(elems)\nif found == 1:\n return elems[0]\nelif not elems:\n raise NoSuchElementException(css_selector)\nreturn elems",
"try:\n return WebDriverWait(self, timeout).until(lambda driver: driver.find_css(css_selector))\nexcept:\n self.... | <|body_start_0|>
elems = self.find_elements_by_css_selector(css_selector)
found = len(elems)
if found == 1:
return elems[0]
elif not elems:
raise NoSuchElementException(css_selector)
return elems
<|end_body_0|>
<|body_start_1|>
try:
re... | Our own WebDriver with some helpers added | CustomWebDriver | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CustomWebDriver:
"""Our own WebDriver with some helpers added"""
def find_css(self, css_selector):
"""Shortcut to find elements by CSS. Returns either a list or singleton"""
<|body_0|>
def wait_for_css(self, css_selector, timeout=7):
"""Shortcut for WebDriverWait... | stack_v2_sparse_classes_75kplus_train_073427 | 7,802 | no_license | [
{
"docstring": "Shortcut to find elements by CSS. Returns either a list or singleton",
"name": "find_css",
"signature": "def find_css(self, css_selector)"
},
{
"docstring": "Shortcut for WebDriverWait",
"name": "wait_for_css",
"signature": "def wait_for_css(self, css_selector, timeout=7)... | 2 | null | Implement the Python class `CustomWebDriver` described below.
Class description:
Our own WebDriver with some helpers added
Method signatures and docstrings:
- def find_css(self, css_selector): Shortcut to find elements by CSS. Returns either a list or singleton
- def wait_for_css(self, css_selector, timeout=7): Short... | Implement the Python class `CustomWebDriver` described below.
Class description:
Our own WebDriver with some helpers added
Method signatures and docstrings:
- def find_css(self, css_selector): Shortcut to find elements by CSS. Returns either a list or singleton
- def wait_for_css(self, css_selector, timeout=7): Short... | 27a1bfb342c0e533ba99d197db3b47dc4443b170 | <|skeleton|>
class CustomWebDriver:
"""Our own WebDriver with some helpers added"""
def find_css(self, css_selector):
"""Shortcut to find elements by CSS. Returns either a list or singleton"""
<|body_0|>
def wait_for_css(self, css_selector, timeout=7):
"""Shortcut for WebDriverWait... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CustomWebDriver:
"""Our own WebDriver with some helpers added"""
def find_css(self, css_selector):
"""Shortcut to find elements by CSS. Returns either a list or singleton"""
elems = self.find_elements_by_css_selector(css_selector)
found = len(elems)
if found == 1:
... | the_stack_v2_python_sparse | webcdi/cdi_forms/tests.py | langcog/web-cdi | train | 9 |
ba168de0b51e4c0c6ba4db85c47c6e4c4136e23b | [
"super(AutoEncoder, self).__init__(name=name, **kwargs)\nself.add_module('encoder', encoder)\nself.add_module('decoder', decoder)",
"y = self.encoder(x)\nx_hat = self.decoder(y)\nreturn (x_hat, y)"
] | <|body_start_0|>
super(AutoEncoder, self).__init__(name=name, **kwargs)
self.add_module('encoder', encoder)
self.add_module('decoder', decoder)
<|end_body_0|>
<|body_start_1|>
y = self.encoder(x)
x_hat = self.decoder(y)
return (x_hat, y)
<|end_body_1|>
| A class representing a standard autoencoder Attributes ---------- encoder : torch.nn.Module the encoder architecture decoder : torch.nn.Module the decoder architecture Methods ------- forward(x) returns the autoencoder output | AutoEncoder | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AutoEncoder:
"""A class representing a standard autoencoder Attributes ---------- encoder : torch.nn.Module the encoder architecture decoder : torch.nn.Module the decoder architecture Methods ------- forward(x) returns the autoencoder output"""
def __init__(self, encoder, decoder, name='Auto... | stack_v2_sparse_classes_75kplus_train_073428 | 1,622 | permissive | [
{
"docstring": "Parameters ---------- encoder : torch.nn.Module the encoder architecture decoder : torch.nn.Module the decoder architecture name : str (optional) the name of the autoencoder (default is 'AutoEncoder')",
"name": "__init__",
"signature": "def __init__(self, encoder, decoder, name='AutoEnco... | 2 | null | Implement the Python class `AutoEncoder` described below.
Class description:
A class representing a standard autoencoder Attributes ---------- encoder : torch.nn.Module the encoder architecture decoder : torch.nn.Module the decoder architecture Methods ------- forward(x) returns the autoencoder output
Method signatur... | Implement the Python class `AutoEncoder` described below.
Class description:
A class representing a standard autoencoder Attributes ---------- encoder : torch.nn.Module the encoder architecture decoder : torch.nn.Module the decoder architecture Methods ------- forward(x) returns the autoencoder output
Method signatur... | 2615b66dd4addfd5c03d9d91a24c7da414294308 | <|skeleton|>
class AutoEncoder:
"""A class representing a standard autoencoder Attributes ---------- encoder : torch.nn.Module the encoder architecture decoder : torch.nn.Module the decoder architecture Methods ------- forward(x) returns the autoencoder output"""
def __init__(self, encoder, decoder, name='Auto... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AutoEncoder:
"""A class representing a standard autoencoder Attributes ---------- encoder : torch.nn.Module the encoder architecture decoder : torch.nn.Module the decoder architecture Methods ------- forward(x) returns the autoencoder output"""
def __init__(self, encoder, decoder, name='AutoEncoder', **k... | the_stack_v2_python_sparse | ACME/model/autoencoder.py | mauriziokovacic/ACME | train | 3 |
279f0192a9e44244a6febbfa5127f5e402a48c00 | [
"self.folder_id = folder_id\nself.public_folder_item_id_list = public_folder_item_id_list\nself.restore_entire_folder = restore_entire_folder",
"if dictionary is None:\n return None\nfolder_id = dictionary.get('folderId')\npublic_folder_item_id_list = dictionary.get('publicFolderItemIdList')\nrestore_entire_fo... | <|body_start_0|>
self.folder_id = folder_id
self.public_folder_item_id_list = public_folder_item_id_list
self.restore_entire_folder = restore_entire_folder
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
folder_id = dictionary.get('folderId')
... | Implementation of the 'PublicFolder' model. Specifies the O365 PublicFolder details. Attributes: folder_id (string): Specifies the unique ID of the folder. public_folder_item_id_list (list of string): Specifies the PublicFolder items within the folder to be restored incase the user wishes not to restore the entire fold... | PublicFolder | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PublicFolder:
"""Implementation of the 'PublicFolder' model. Specifies the O365 PublicFolder details. Attributes: folder_id (string): Specifies the unique ID of the folder. public_folder_item_id_list (list of string): Specifies the PublicFolder items within the folder to be restored incase the us... | stack_v2_sparse_classes_75kplus_train_073429 | 2,185 | permissive | [
{
"docstring": "Constructor for the PublicFolder class",
"name": "__init__",
"signature": "def __init__(self, folder_id=None, public_folder_item_id_list=None, restore_entire_folder=None)"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: dictionary (dictionary): A dict... | 2 | stack_v2_sparse_classes_30k_train_007923 | Implement the Python class `PublicFolder` described below.
Class description:
Implementation of the 'PublicFolder' model. Specifies the O365 PublicFolder details. Attributes: folder_id (string): Specifies the unique ID of the folder. public_folder_item_id_list (list of string): Specifies the PublicFolder items within ... | Implement the Python class `PublicFolder` described below.
Class description:
Implementation of the 'PublicFolder' model. Specifies the O365 PublicFolder details. Attributes: folder_id (string): Specifies the unique ID of the folder. public_folder_item_id_list (list of string): Specifies the PublicFolder items within ... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class PublicFolder:
"""Implementation of the 'PublicFolder' model. Specifies the O365 PublicFolder details. Attributes: folder_id (string): Specifies the unique ID of the folder. public_folder_item_id_list (list of string): Specifies the PublicFolder items within the folder to be restored incase the us... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PublicFolder:
"""Implementation of the 'PublicFolder' model. Specifies the O365 PublicFolder details. Attributes: folder_id (string): Specifies the unique ID of the folder. public_folder_item_id_list (list of string): Specifies the PublicFolder items within the folder to be restored incase the user wishes not... | the_stack_v2_python_sparse | cohesity_management_sdk/models/public_folder.py | cohesity/management-sdk-python | train | 24 |
f2ee7f09cd7883b0a77fa7228113203c47f4fb27 | [
"limit = df[CLOSE].min()\nif limit > 0:\n limit_df = df[df[CLOSE] <= limit * (2 - LIMIT_DETECT_LIMIT_FACTOR)]\n if not limit_df.empty:\n tm = limit_df.index[-1]\n return tm",
"limit = df[DIF].min()\nif limit < 0:\n return cls.__get_min_limit_tm(df[DIF], limit)",
"limit = df[MACD].min()\ni... | <|body_start_0|>
limit = df[CLOSE].min()
if limit > 0:
limit_df = df[df[CLOSE] <= limit * (2 - LIMIT_DETECT_LIMIT_FACTOR)]
if not limit_df.empty:
tm = limit_df.index[-1]
return tm
<|end_body_0|>
<|body_start_1|>
limit = df[DIF].min()
... | 检测极值：最小值的时间。用于检测3种极值的时间，3种极值分别是：DIF/CLOSE/MACD | MinLimitDetect | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MinLimitDetect:
"""检测极值：最小值的时间。用于检测3种极值的时间，3种极值分别是：DIF/CLOSE/MACD"""
def get_close_limit_tm_in(cls, df):
"""获取区间内close最小值的时间。 :param df: DataFrame类型， 相邻的死叉和金叉之间或两个死叉之间的所有数据[包含死叉点，不包含金叉点] :return:"""
<|body_0|>
def get_dif_limit_tm_in(cls, df):
"""获取区间内DIF最小值的时间。 ... | stack_v2_sparse_classes_75kplus_train_073430 | 36,499 | no_license | [
{
"docstring": "获取区间内close最小值的时间。 :param df: DataFrame类型， 相邻的死叉和金叉之间或两个死叉之间的所有数据[包含死叉点，不包含金叉点] :return:",
"name": "get_close_limit_tm_in",
"signature": "def get_close_limit_tm_in(cls, df)"
},
{
"docstring": "获取区间内DIF最小值的时间。 :param df: DataFrame类型， 相邻的死叉和金叉之间或两个死叉之间的所有数据[包含死叉点，不包含金叉点] :return:",
... | 4 | stack_v2_sparse_classes_30k_train_048916 | Implement the Python class `MinLimitDetect` described below.
Class description:
检测极值：最小值的时间。用于检测3种极值的时间，3种极值分别是：DIF/CLOSE/MACD
Method signatures and docstrings:
- def get_close_limit_tm_in(cls, df): 获取区间内close最小值的时间。 :param df: DataFrame类型， 相邻的死叉和金叉之间或两个死叉之间的所有数据[包含死叉点，不包含金叉点] :return:
- def get_dif_limit_tm_in(cls, ... | Implement the Python class `MinLimitDetect` described below.
Class description:
检测极值：最小值的时间。用于检测3种极值的时间，3种极值分别是：DIF/CLOSE/MACD
Method signatures and docstrings:
- def get_close_limit_tm_in(cls, df): 获取区间内close最小值的时间。 :param df: DataFrame类型， 相邻的死叉和金叉之间或两个死叉之间的所有数据[包含死叉点，不包含金叉点] :return:
- def get_dif_limit_tm_in(cls, ... | 9446d33c0978c325c8b24a876ac2c42fe323dbe6 | <|skeleton|>
class MinLimitDetect:
"""检测极值：最小值的时间。用于检测3种极值的时间，3种极值分别是：DIF/CLOSE/MACD"""
def get_close_limit_tm_in(cls, df):
"""获取区间内close最小值的时间。 :param df: DataFrame类型， 相邻的死叉和金叉之间或两个死叉之间的所有数据[包含死叉点，不包含金叉点] :return:"""
<|body_0|>
def get_dif_limit_tm_in(cls, df):
"""获取区间内DIF最小值的时间。 ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MinLimitDetect:
"""检测极值：最小值的时间。用于检测3种极值的时间，3种极值分别是：DIF/CLOSE/MACD"""
def get_close_limit_tm_in(cls, df):
"""获取区间内close最小值的时间。 :param df: DataFrame类型， 相邻的死叉和金叉之间或两个死叉之间的所有数据[包含死叉点，不包含金叉点] :return:"""
limit = df[CLOSE].min()
if limit > 0:
limit_df = df[df[CLOSE] <= limit... | the_stack_v2_python_sparse | back_forecast/learn_quant/MACD/jukuan_macd_signal.py | lnkyzhang/wayToFreedomOfWealth | train | 3 |
a2c36711728a95b92e9b571bd8dffdf4fbe0c11b | [
"if std is None:\n print(src + ': Please specify a standard output for messages!')\n exit()\nelse:\n self.std = std\nself.std.Print('Initialising GrfNode', fg, bg, style, src)\nsuper(GrfNode, self).__init__(sheetCanvas=sheetCanvas, cat=cat, label=label, center=center, size=size, con_type=con_type, color_ty... | <|body_start_0|>
if std is None:
print(src + ': Please specify a standard output for messages!')
exit()
else:
self.std = std
self.std.Print('Initialising GrfNode', fg, bg, style, src)
super(GrfNode, self).__init__(sheetCanvas=sheetCanvas, cat=cat, labe... | Node item in the Blodiator. Define an instance of 'GrfNode' with appropriate arguments: sheetCanvas = an instance of the canvas. For Blodiator it is an instance of CntSheetCanvas tag = a string used by tkinter to identify the block label = item label size = size of the node inPort = list containing information about in... | GrfNode | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GrfNode:
"""Node item in the Blodiator. Define an instance of 'GrfNode' with appropriate arguments: sheetCanvas = an instance of the canvas. For Blodiator it is an instance of CntSheetCanvas tag = a string used by tkinter to identify the block label = item label size = size of the node inPort = l... | stack_v2_sparse_classes_75kplus_train_073431 | 6,091 | permissive | [
{
"docstring": "Construct a GrfNode input: sheetCanvas = an instance of the canvas. For Blodiator it is an instance of CntSheetCanvas tag = a string used by tkinter to identify the block label = item label size = size of the node inPort = list containing information about input ports of the item outPort = list ... | 3 | stack_v2_sparse_classes_30k_test_001964 | Implement the Python class `GrfNode` described below.
Class description:
Node item in the Blodiator. Define an instance of 'GrfNode' with appropriate arguments: sheetCanvas = an instance of the canvas. For Blodiator it is an instance of CntSheetCanvas tag = a string used by tkinter to identify the block label = item l... | Implement the Python class `GrfNode` described below.
Class description:
Node item in the Blodiator. Define an instance of 'GrfNode' with appropriate arguments: sheetCanvas = an instance of the canvas. For Blodiator it is an instance of CntSheetCanvas tag = a string used by tkinter to identify the block label = item l... | 4afaf5fb11e6c5d807fdfbca862013a42c63d215 | <|skeleton|>
class GrfNode:
"""Node item in the Blodiator. Define an instance of 'GrfNode' with appropriate arguments: sheetCanvas = an instance of the canvas. For Blodiator it is an instance of CntSheetCanvas tag = a string used by tkinter to identify the block label = item label size = size of the node inPort = l... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class GrfNode:
"""Node item in the Blodiator. Define an instance of 'GrfNode' with appropriate arguments: sheetCanvas = an instance of the canvas. For Blodiator it is an instance of CntSheetCanvas tag = a string used by tkinter to identify the block label = item label size = size of the node inPort = list containin... | the_stack_v2_python_sparse | blodiator/graf/grfnode.py | MansourM61/Blodiator | train | 1 |
fbf3aced4752d2c4e6ad34ef18c1d02ae7c5dca7 | [
"self.window_size = window_size\nself.threshold = threshold\nself.threshold_r = threshold_r\nself.perform_NCC(descriptor1, descriptor2)",
"mean1 = np.mean(descriptor1['neighbour'])\nmean2 = np.mean(descriptor2['neighbour'])\nncc_num = 0\nncc_den1 = 0\nncc_den2 = 0\nfor i in range(self.window_size):\n for j in ... | <|body_start_0|>
self.window_size = window_size
self.threshold = threshold
self.threshold_r = threshold_r
self.perform_NCC(descriptor1, descriptor2)
<|end_body_0|>
<|body_start_1|>
mean1 = np.mean(descriptor1['neighbour'])
mean2 = np.mean(descriptor2['neighbour'])
... | NCC | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NCC:
def __init__(self, descriptor1, descriptor2, window_size, threshold, threshold_r):
"""Initialize the required resources to compute NCC value @param descriptor1 The first descriptor list @param descriptor2 The second descriptor list @param window_size The NCC window size @param thres... | stack_v2_sparse_classes_75kplus_train_073432 | 2,961 | no_license | [
{
"docstring": "Initialize the required resources to compute NCC value @param descriptor1 The first descriptor list @param descriptor2 The second descriptor list @param window_size The NCC window size @param threshold The threshold of NCC @param threshold_r The threshold ratio of NCC",
"name": "__init__",
... | 3 | null | Implement the Python class `NCC` described below.
Class description:
Implement the NCC class.
Method signatures and docstrings:
- def __init__(self, descriptor1, descriptor2, window_size, threshold, threshold_r): Initialize the required resources to compute NCC value @param descriptor1 The first descriptor list @para... | Implement the Python class `NCC` described below.
Class description:
Implement the NCC class.
Method signatures and docstrings:
- def __init__(self, descriptor1, descriptor2, window_size, threshold, threshold_r): Initialize the required resources to compute NCC value @param descriptor1 The first descriptor list @para... | d1b048908affb30cba7b976404b601b35fec2cbe | <|skeleton|>
class NCC:
def __init__(self, descriptor1, descriptor2, window_size, threshold, threshold_r):
"""Initialize the required resources to compute NCC value @param descriptor1 The first descriptor list @param descriptor2 The second descriptor list @param window_size The NCC window size @param thres... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class NCC:
def __init__(self, descriptor1, descriptor2, window_size, threshold, threshold_r):
"""Initialize the required resources to compute NCC value @param descriptor1 The first descriptor list @param descriptor2 The second descriptor list @param window_size The NCC window size @param threshold The thres... | the_stack_v2_python_sparse | Hw4/import/NCC.py | GeforceTesla/ECE661_Computer_Vision_Combined | train | 1 | |
2958cf5f388871323e7e7193985c67c505a6fddc | [
"actions = super().get_actions(request)\nif not request.user.is_superuser:\n if 'delete_selected' in actions:\n del actions['delete_selected']\nreturn actions",
"if not hasattr(obj, 'created_by'):\n obj.created_by = request.user\nobj.updated_by = request.user\nobj.save()"
] | <|body_start_0|>
actions = super().get_actions(request)
if not request.user.is_superuser:
if 'delete_selected' in actions:
del actions['delete_selected']
return actions
<|end_body_0|>
<|body_start_1|>
if not hasattr(obj, 'created_by'):
obj.created... | Use this class as the base class for other admin classes inheriting from :class:`django.contrib.admin.ModelAdmin` if so desired | BaseAdmin | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BaseAdmin:
"""Use this class as the base class for other admin classes inheriting from :class:`django.contrib.admin.ModelAdmin` if so desired"""
def get_actions(self, request):
"""override :meth:`django.contrib.admin.ModelAdmin.get_actions` The purpose is to only allow superusers the... | stack_v2_sparse_classes_75kplus_train_073433 | 3,701 | no_license | [
{
"docstring": "override :meth:`django.contrib.admin.ModelAdmin.get_actions` The purpose is to only allow superusers the privilege of deleting objects from `Django Admin Summary pages`",
"name": "get_actions",
"signature": "def get_actions(self, request)"
},
{
"docstring": "override :meth:`djang... | 2 | stack_v2_sparse_classes_30k_train_028668 | Implement the Python class `BaseAdmin` described below.
Class description:
Use this class as the base class for other admin classes inheriting from :class:`django.contrib.admin.ModelAdmin` if so desired
Method signatures and docstrings:
- def get_actions(self, request): override :meth:`django.contrib.admin.ModelAdmin... | Implement the Python class `BaseAdmin` described below.
Class description:
Use this class as the base class for other admin classes inheriting from :class:`django.contrib.admin.ModelAdmin` if so desired
Method signatures and docstrings:
- def get_actions(self, request): override :meth:`django.contrib.admin.ModelAdmin... | d96200e06cd350bdacdd6bdc59b14a6901051a59 | <|skeleton|>
class BaseAdmin:
"""Use this class as the base class for other admin classes inheriting from :class:`django.contrib.admin.ModelAdmin` if so desired"""
def get_actions(self, request):
"""override :meth:`django.contrib.admin.ModelAdmin.get_actions` The purpose is to only allow superusers the... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class BaseAdmin:
"""Use this class as the base class for other admin classes inheriting from :class:`django.contrib.admin.ModelAdmin` if so desired"""
def get_actions(self, request):
"""override :meth:`django.contrib.admin.ModelAdmin.get_actions` The purpose is to only allow superusers the privilege of... | the_stack_v2_python_sparse | p_soc_auto_base/admin.py | serbant/PHSA-SOC | train | 0 |
932426d5171e9a73b11cc8bf8c6be6fa98a0fd07 | [
"node = Node(item)\nif self.is_empty():\n print(self.head)\n self.head = node\nelse:\n cur = self.head\n while cur.next != None:\n cur = cur.next\n cur.next = node\n node.prev = cur",
"node = Node(item)\nnode.next = self.head\nself.head = node\nnode.next.prev = node",
"if pos < 0:\n ... | <|body_start_0|>
node = Node(item)
if self.is_empty():
print(self.head)
self.head = node
else:
cur = self.head
while cur.next != None:
cur = cur.next
cur.next = node
node.prev = cur
<|end_body_0|>
<|body_sta... | 双链表 | DoubleLinkList | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DoubleLinkList:
"""双链表"""
def append(self, item):
"""尾部添加元素"""
<|body_0|>
def add(self, item):
"""链表头部添加"""
<|body_1|>
def insert(self, pos, item):
"""在链表的指定位置添加，这里以0为开始"""
<|body_2|>
def remove(self, item):
"""从链表中删除元素""... | stack_v2_sparse_classes_75kplus_train_073434 | 2,652 | permissive | [
{
"docstring": "尾部添加元素",
"name": "append",
"signature": "def append(self, item)"
},
{
"docstring": "链表头部添加",
"name": "add",
"signature": "def add(self, item)"
},
{
"docstring": "在链表的指定位置添加，这里以0为开始",
"name": "insert",
"signature": "def insert(self, pos, item)"
},
{
... | 4 | stack_v2_sparse_classes_30k_train_001198 | Implement the Python class `DoubleLinkList` described below.
Class description:
双链表
Method signatures and docstrings:
- def append(self, item): 尾部添加元素
- def add(self, item): 链表头部添加
- def insert(self, pos, item): 在链表的指定位置添加，这里以0为开始
- def remove(self, item): 从链表中删除元素 | Implement the Python class `DoubleLinkList` described below.
Class description:
双链表
Method signatures and docstrings:
- def append(self, item): 尾部添加元素
- def add(self, item): 链表头部添加
- def insert(self, pos, item): 在链表的指定位置添加，这里以0为开始
- def remove(self, item): 从链表中删除元素
<|skeleton|>
class DoubleLinkList:
"""双链表"""
... | 912dc05a3bd0ded9544166a68da23ca0a97b84da | <|skeleton|>
class DoubleLinkList:
"""双链表"""
def append(self, item):
"""尾部添加元素"""
<|body_0|>
def add(self, item):
"""链表头部添加"""
<|body_1|>
def insert(self, pos, item):
"""在链表的指定位置添加，这里以0为开始"""
<|body_2|>
def remove(self, item):
"""从链表中删除元素""... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DoubleLinkList:
"""双链表"""
def append(self, item):
"""尾部添加元素"""
node = Node(item)
if self.is_empty():
print(self.head)
self.head = node
else:
cur = self.head
while cur.next != None:
cur = cur.next
c... | the_stack_v2_python_sparse | jiaocheng/08-数据结构与算法/08-双向链表.py | kellanfan/python | train | 3 |
987a6b662bd774b37e9c8d2efaf8ae60bdfd1296 | [
"if clss.__domain_extractor_nlp is not None:\n return clss.__domain_extractor_nlp\nnlp = spacy.load('en_core_web_sm')\nid_re = re.compile('id|ID|Id')\nprefix_re = spacy.util.compile_prefix_regex(nlp.Defaults.prefixes)\ninfix_re = spacy.util.compile_infix_regex(nlp.Defaults.infixes)\nsuffix_re = spacy.util.compil... | <|body_start_0|>
if clss.__domain_extractor_nlp is not None:
return clss.__domain_extractor_nlp
nlp = spacy.load('en_core_web_sm')
id_re = re.compile('id|ID|Id')
prefix_re = spacy.util.compile_prefix_regex(nlp.Defaults.prefixes)
infix_re = spacy.util.compile_infix_reg... | 提供基于spacy的NLP处理包装 这里主要用到的是create_spacy_nlp_for_domain_extractor方法，创建一个可以处理api文档描述文本，抽取其中属于专有名词性质的domain term的pipeline | SpacyNLPFactory | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SpacyNLPFactory:
"""提供基于spacy的NLP处理包装 这里主要用到的是create_spacy_nlp_for_domain_extractor方法，创建一个可以处理api文档描述文本，抽取其中属于专有名词性质的domain term的pipeline"""
def create_spacy_nlp_for_domain_extractor(clss):
"""load a spacy nlp pipeline for extract domain entity and relations :return:"""
<|bod... | stack_v2_sparse_classes_75kplus_train_073435 | 3,348 | permissive | [
{
"docstring": "load a spacy nlp pipeline for extract domain entity and relations :return:",
"name": "create_spacy_nlp_for_domain_extractor",
"signature": "def create_spacy_nlp_for_domain_extractor(clss)"
},
{
"docstring": "load a spacy nlp pipeline for extract domain entity and relations :retur... | 3 | stack_v2_sparse_classes_30k_train_019795 | Implement the Python class `SpacyNLPFactory` described below.
Class description:
提供基于spacy的NLP处理包装 这里主要用到的是create_spacy_nlp_for_domain_extractor方法，创建一个可以处理api文档描述文本，抽取其中属于专有名词性质的domain term的pipeline
Method signatures and docstrings:
- def create_spacy_nlp_for_domain_extractor(clss): load a spacy nlp pipeline for extr... | Implement the Python class `SpacyNLPFactory` described below.
Class description:
提供基于spacy的NLP处理包装 这里主要用到的是create_spacy_nlp_for_domain_extractor方法，创建一个可以处理api文档描述文本，抽取其中属于专有名词性质的domain term的pipeline
Method signatures and docstrings:
- def create_spacy_nlp_for_domain_extractor(clss): load a spacy nlp pipeline for extr... | 74bbcfa62c7e293b2b02f23249ac408aa22b44af | <|skeleton|>
class SpacyNLPFactory:
"""提供基于spacy的NLP处理包装 这里主要用到的是create_spacy_nlp_for_domain_extractor方法，创建一个可以处理api文档描述文本，抽取其中属于专有名词性质的domain term的pipeline"""
def create_spacy_nlp_for_domain_extractor(clss):
"""load a spacy nlp pipeline for extract domain entity and relations :return:"""
<|bod... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SpacyNLPFactory:
"""提供基于spacy的NLP处理包装 这里主要用到的是create_spacy_nlp_for_domain_extractor方法，创建一个可以处理api文档描述文本，抽取其中属于专有名词性质的domain term的pipeline"""
def create_spacy_nlp_for_domain_extractor(clss):
"""load a spacy nlp pipeline for extract domain entity and relations :return:"""
if clss.__domain_e... | the_stack_v2_python_sparse | src/util/apidoc_semantic/spacy_factory.py | SmartServiceGroup/SOworkspace | train | 0 |
e604de2ee2fcf48a388b44ea7bf154e91e27e16d | [
"try:\n from config_parser import config_parser\n self.conf_file = current_file_path + '/../../conf/appviewx.conf'\n self.conf_data = config_parser(self.conf_file)\n self.hostname = socket.gethostbyname(socket.gethostname())\n self.ip = ip\nexcept Exception as e:\n print(colored(e, 'red'))\n lg... | <|body_start_0|>
try:
from config_parser import config_parser
self.conf_file = current_file_path + '/../../conf/appviewx.conf'
self.conf_data = config_parser(self.conf_file)
self.hostname = socket.gethostbyname(socket.gethostname())
self.ip = ip
... | . | InitializeMongoDB | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InitializeMongoDB:
"""."""
def __init__(self, ip=False):
"""."""
<|body_0|>
def initialize(self):
"""."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
try:
from config_parser import config_parser
self.conf_file = current_... | stack_v2_sparse_classes_75kplus_train_073436 | 2,724 | no_license | [
{
"docstring": ".",
"name": "__init__",
"signature": "def __init__(self, ip=False)"
},
{
"docstring": ".",
"name": "initialize",
"signature": "def initialize(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_008908 | Implement the Python class `InitializeMongoDB` described below.
Class description:
.
Method signatures and docstrings:
- def __init__(self, ip=False): .
- def initialize(self): . | Implement the Python class `InitializeMongoDB` described below.
Class description:
.
Method signatures and docstrings:
- def __init__(self, ip=False): .
- def initialize(self): .
<|skeleton|>
class InitializeMongoDB:
"""."""
def __init__(self, ip=False):
"""."""
<|body_0|>
def initializ... | e513224364dce05ea4d17ac25ecfa981238b1311 | <|skeleton|>
class InitializeMongoDB:
"""."""
def __init__(self, ip=False):
"""."""
<|body_0|>
def initialize(self):
"""."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class InitializeMongoDB:
"""."""
def __init__(self, ip=False):
"""."""
try:
from config_parser import config_parser
self.conf_file = current_file_path + '/../../conf/appviewx.conf'
self.conf_data = config_parser(self.conf_file)
self.hostname = soc... | the_stack_v2_python_sparse | scripts_avx/scripts/scripts/Mongodb/initialize_mongodb.py | Poonammahunta/Integration | train | 0 |
c9f14608294f5c509f2a1a1bae790550b007c609 | [
"candidates = (('https://example.com/with/a/path', 'https://example.com'), ('http://example.com/path?and=querystring#andfragment', 'http://example.com'), ('http://example.com:12345', 'http://example.com:12345'), ('http://a.b.c.example.com', 'http://a.b.c.example.com'), ('site1.example.com', 'http://site1.example.co... | <|body_start_0|>
candidates = (('https://example.com/with/a/path', 'https://example.com'), ('http://example.com/path?and=querystring#andfragment', 'http://example.com'), ('http://example.com:12345', 'http://example.com:12345'), ('http://a.b.c.example.com', 'http://a.b.c.example.com'), ('site1.example.com', 'htt... | Tests for the Url resource. | TestUrlResource | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestUrlResource:
"""Tests for the Url resource."""
def test_base_address(self) -> None:
"""The address can be reduced to a root URL."""
<|body_0|>
def test_path_case_preservation(self) -> None:
"""Paths are allowed to be case-sensitive."""
<|body_1|>
... | stack_v2_sparse_classes_75kplus_train_073437 | 1,476 | no_license | [
{
"docstring": "The address can be reduced to a root URL.",
"name": "test_base_address",
"signature": "def test_base_address(self) -> None"
},
{
"docstring": "Paths are allowed to be case-sensitive.",
"name": "test_path_case_preservation",
"signature": "def test_path_case_preservation(se... | 3 | stack_v2_sparse_classes_30k_train_030334 | Implement the Python class `TestUrlResource` described below.
Class description:
Tests for the Url resource.
Method signatures and docstrings:
- def test_base_address(self) -> None: The address can be reduced to a root URL.
- def test_path_case_preservation(self) -> None: Paths are allowed to be case-sensitive.
- def... | Implement the Python class `TestUrlResource` described below.
Class description:
Tests for the Url resource.
Method signatures and docstrings:
- def test_base_address(self) -> None: The address can be reduced to a root URL.
- def test_path_case_preservation(self) -> None: Paths are allowed to be case-sensitive.
- def... | 7129415303b94d5d10b2c29ec432f0c7d41cc651 | <|skeleton|>
class TestUrlResource:
"""Tests for the Url resource."""
def test_base_address(self) -> None:
"""The address can be reduced to a root URL."""
<|body_0|>
def test_path_case_preservation(self) -> None:
"""Paths are allowed to be case-sensitive."""
<|body_1|>
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TestUrlResource:
"""Tests for the Url resource."""
def test_base_address(self) -> None:
"""The address can be reduced to a root URL."""
candidates = (('https://example.com/with/a/path', 'https://example.com'), ('http://example.com/path?and=querystring#andfragment', 'http://example.com'), ... | the_stack_v2_python_sparse | resources/url_test.py | lovett/medley | train | 6 |
c55ad944c159909d9053e634b866d1d153444989 | [
"if len(request.files) == 0:\n print('No files found in request')\n print(request)\n return ERROR_400\ncreated_resources = []\nfor file in request.files:\n file = request.files[file]\n print(file)\n if file.filename == '':\n print('Empty filename error:')\n print(json.dumps(file))\n ... | <|body_start_0|>
if len(request.files) == 0:
print('No files found in request')
print(request)
return ERROR_400
created_resources = []
for file in request.files:
file = request.files[file]
print(file)
if file.filename == '':... | FileCollectionManager | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FileCollectionManager:
def post(self, user_identifier):
"""Upload a new file."""
<|body_0|>
def get(self, user_identifier):
"""List all files owned by the given user."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if len(request.files) == 0:
... | stack_v2_sparse_classes_75kplus_train_073438 | 2,736 | no_license | [
{
"docstring": "Upload a new file.",
"name": "post",
"signature": "def post(self, user_identifier)"
},
{
"docstring": "List all files owned by the given user.",
"name": "get",
"signature": "def get(self, user_identifier)"
}
] | 2 | stack_v2_sparse_classes_30k_train_018021 | Implement the Python class `FileCollectionManager` described below.
Class description:
Implement the FileCollectionManager class.
Method signatures and docstrings:
- def post(self, user_identifier): Upload a new file.
- def get(self, user_identifier): List all files owned by the given user. | Implement the Python class `FileCollectionManager` described below.
Class description:
Implement the FileCollectionManager class.
Method signatures and docstrings:
- def post(self, user_identifier): Upload a new file.
- def get(self, user_identifier): List all files owned by the given user.
<|skeleton|>
class FileCo... | f66885351dcbc700d6b6be3a0777643c3420befe | <|skeleton|>
class FileCollectionManager:
def post(self, user_identifier):
"""Upload a new file."""
<|body_0|>
def get(self, user_identifier):
"""List all files owned by the given user."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class FileCollectionManager:
def post(self, user_identifier):
"""Upload a new file."""
if len(request.files) == 0:
print('No files found in request')
print(request)
return ERROR_400
created_resources = []
for file in request.files:
file... | the_stack_v2_python_sparse | src/rickbox/resources/file_collection_manager.py | CodingGrounds/INFO-3103-Final-Project | train | 0 | |
bca6dbcd0dafc1ef9786d14067fd5e5e74b5ddb9 | [
"super(AdamOptimizer, self).__init__(False, name)\nself.learning_rate = learning_rate\nself.learning_rate_scale = learning_rate_scale\nself.weight_decay_rate = weight_decay_rate\nself.beta_1 = beta_1\nself.beta_2 = beta_2\nself.epsilon = epsilon\nself.param_name_to_overridden_parameters = {} if param_name_to_overri... | <|body_start_0|>
super(AdamOptimizer, self).__init__(False, name)
self.learning_rate = learning_rate
self.learning_rate_scale = learning_rate_scale
self.weight_decay_rate = weight_decay_rate
self.beta_1 = beta_1
self.beta_2 = beta_2
self.epsilon = epsilon
... | A basic Adam optimizer that includes "correct" L2 weight decay. Rowan: I modified this from BERT by incorporating the bias correction | AdamOptimizer | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AdamOptimizer:
"""A basic Adam optimizer that includes "correct" L2 weight decay. Rowan: I modified this from BERT by incorporating the bias correction"""
def __init__(self, learning_rate, learning_rate_scale=1.0, weight_decay_rate=0.0, beta_1=0.9, beta_2=0.999, epsilon=1e-06, param_name_to_... | stack_v2_sparse_classes_75kplus_train_073439 | 25,278 | permissive | [
{
"docstring": "Constructs a AdamWeightDecayOptimizer.",
"name": "__init__",
"signature": "def __init__(self, learning_rate, learning_rate_scale=1.0, weight_decay_rate=0.0, beta_1=0.9, beta_2=0.999, epsilon=1e-06, param_name_to_overridden_parameters=None, name='AdamOptimizer', make_things_dependent_on_g... | 3 | stack_v2_sparse_classes_30k_train_054053 | Implement the Python class `AdamOptimizer` described below.
Class description:
A basic Adam optimizer that includes "correct" L2 weight decay. Rowan: I modified this from BERT by incorporating the bias correction
Method signatures and docstrings:
- def __init__(self, learning_rate, learning_rate_scale=1.0, weight_dec... | Implement the Python class `AdamOptimizer` described below.
Class description:
A basic Adam optimizer that includes "correct" L2 weight decay. Rowan: I modified this from BERT by incorporating the bias correction
Method signatures and docstrings:
- def __init__(self, learning_rate, learning_rate_scale=1.0, weight_dec... | 41fb35a3606415deabb47541e59d9d286c398350 | <|skeleton|>
class AdamOptimizer:
"""A basic Adam optimizer that includes "correct" L2 weight decay. Rowan: I modified this from BERT by incorporating the bias correction"""
def __init__(self, learning_rate, learning_rate_scale=1.0, weight_decay_rate=0.0, beta_1=0.9, beta_2=0.999, epsilon=1e-06, param_name_to_... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AdamOptimizer:
"""A basic Adam optimizer that includes "correct" L2 weight decay. Rowan: I modified this from BERT by incorporating the bias correction"""
def __init__(self, learning_rate, learning_rate_scale=1.0, weight_decay_rate=0.0, beta_1=0.9, beta_2=0.999, epsilon=1e-06, param_name_to_overridden_pa... | the_stack_v2_python_sparse | model/optimization.py | zeta1999/piglet | train | 0 |
bfdb3d02836659d92e1dd30c1796092d9441c74b | [
"self.unity_env = unity_env\nself.unity_env.reset()\nengine_configuration_channel = EngineConfigurationChannel()\nengine_configuration_channel.set_configuration_parameters(time_scale=time_scale, width=width, height=height, target_frame_rate=target_frame_rate, quality_level=quality_level)\nself.unity_env.side_channe... | <|body_start_0|>
self.unity_env = unity_env
self.unity_env.reset()
engine_configuration_channel = EngineConfigurationChannel()
engine_configuration_channel.set_configuration_parameters(time_scale=time_scale, width=width, height=height, target_frame_rate=target_frame_rate, quality_level=q... | Game Class Game is a wrapper that takes a UnityEnvironment and makes a set of NeuralNetworks play in this environment. The game stops when all agents are done and returns their scores. An Agent does not play again when he's done. A Game might contain multiple simulations to make multiple neural networks play at the sam... | Game | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Game:
"""Game Class Game is a wrapper that takes a UnityEnvironment and makes a set of NeuralNetworks play in this environment. The game stops when all agents are done and returns their scores. An Agent does not play again when he's done. A Game might contain multiple simulations to make multiple... | stack_v2_sparse_classes_75kplus_train_073440 | 3,309 | permissive | [
{
"docstring": "Initializes the game :param unity_env: (UnityEnvironment) Environment where the game will be played :param time_scale:(float) Speed of the game :param width:(int) Window's width :param height:(int) Window's height :param target_frame_rate:(int) Frame rate :param quality_level:(int) Visual qualit... | 2 | stack_v2_sparse_classes_30k_train_000836 | Implement the Python class `Game` described below.
Class description:
Game Class Game is a wrapper that takes a UnityEnvironment and makes a set of NeuralNetworks play in this environment. The game stops when all agents are done and returns their scores. An Agent does not play again when he's done. A Game might contai... | Implement the Python class `Game` described below.
Class description:
Game Class Game is a wrapper that takes a UnityEnvironment and makes a set of NeuralNetworks play in this environment. The game stops when all agents are done and returns their scores. An Agent does not play again when he's done. A Game might contai... | 2083afb187b72e313c8423217bb3bef20a564d44 | <|skeleton|>
class Game:
"""Game Class Game is a wrapper that takes a UnityEnvironment and makes a set of NeuralNetworks play in this environment. The game stops when all agents are done and returns their scores. An Agent does not play again when he's done. A Game might contain multiple simulations to make multiple... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Game:
"""Game Class Game is a wrapper that takes a UnityEnvironment and makes a set of NeuralNetworks play in this environment. The game stops when all agents are done and returns their scores. An Agent does not play again when he's done. A Game might contain multiple simulations to make multiple neural netwo... | the_stack_v2_python_sparse | game.py | dsapandora/genetic-unity | train | 0 |
3261b46d02181f0bcde4828646ae9c6516cec1dc | [
"self.databases = ['DECIPHER', 'OMIM', 'ORPHA']\nself.diseases = {}\nself._parse_diseases()\nLOG.info(f'Parsed {len(self.diseases)} disease/phenotypes from resource file')",
"if not field:\n return None\nif field.upper() in FREQUENCY_TERMS:\n return FREQUENCY_TERMS[field]\nif field.endswith('%'):\n field... | <|body_start_0|>
self.databases = ['DECIPHER', 'OMIM', 'ORPHA']
self.diseases = {}
self._parse_diseases()
LOG.info(f'Parsed {len(self.diseases)} disease/phenotypes from resource file')
<|end_body_0|>
<|body_start_1|>
if not field:
return None
if field.upper()... | Create an object containing all diseases from the phenotype_annotations.tav.txt file Resources included in this file: DECIPHER, OMIM, ORPHANET | Diseases | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Diseases:
"""Create an object containing all diseases from the phenotype_annotations.tav.txt file Resources included in this file: DECIPHER, OMIM, ORPHANET"""
def init_app(self):
"""Initialize the diseases object when the app is launched"""
<|body_0|>
def _parse_disease_... | stack_v2_sparse_classes_75kplus_train_073441 | 5,230 | permissive | [
{
"docstring": "Initialize the diseases object when the app is launched",
"name": "init_app",
"signature": "def init_app(self)"
},
{
"docstring": "Parse disease frequency (col 8 in phenotype anno file)",
"name": "_parse_disease_frequency",
"signature": "def _parse_disease_frequency(self,... | 5 | stack_v2_sparse_classes_30k_train_006358 | Implement the Python class `Diseases` described below.
Class description:
Create an object containing all diseases from the phenotype_annotations.tav.txt file Resources included in this file: DECIPHER, OMIM, ORPHANET
Method signatures and docstrings:
- def init_app(self): Initialize the diseases object when the app i... | Implement the Python class `Diseases` described below.
Class description:
Create an object containing all diseases from the phenotype_annotations.tav.txt file Resources included in this file: DECIPHER, OMIM, ORPHANET
Method signatures and docstrings:
- def init_app(self): Initialize the diseases object when the app i... | e13c20ce69a627c0dc0cfadab39811dd33eb2320 | <|skeleton|>
class Diseases:
"""Create an object containing all diseases from the phenotype_annotations.tav.txt file Resources included in this file: DECIPHER, OMIM, ORPHANET"""
def init_app(self):
"""Initialize the diseases object when the app is launched"""
<|body_0|>
def _parse_disease_... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Diseases:
"""Create an object containing all diseases from the phenotype_annotations.tav.txt file Resources included in this file: DECIPHER, OMIM, ORPHANET"""
def init_app(self):
"""Initialize the diseases object when the app is launched"""
self.databases = ['DECIPHER', 'OMIM', 'ORPHA']
... | the_stack_v2_python_sparse | patientMatcher/utils/disease.py | Clinical-Genomics/patientMatcher | train | 21 |
098488790d31900f44208d9cd2279a4afd2423c9 | [
"self.seg = WordSegmentation(stop_words_file=stop_words_file, allow_speech_tags=allow_speech_tags)\nself.wc_background = get_default_wc_background()\nif type(wc_background) is str:\n self.wc_background = wc_background\nself.font_path = get_default_font_path()\nif type(font_path) is str:\n self.font_path = fon... | <|body_start_0|>
self.seg = WordSegmentation(stop_words_file=stop_words_file, allow_speech_tags=allow_speech_tags)
self.wc_background = get_default_wc_background()
if type(wc_background) is str:
self.wc_background = wc_background
self.font_path = get_default_font_path()
... | WordCloud | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WordCloud:
def __init__(self, stop_words_file=None, allow_speech_tags=conf.allow_speech_tags, wc_background=None, font_path=None, max_words=200, max_font_size=100, save_path=None, wc_name=None, topK=10):
""":param stop_words_file: -- str，停用词文件路径，若不是str则使用默认停用词文件 :param allow_speech_tags:... | stack_v2_sparse_classes_75kplus_train_073442 | 4,561 | no_license | [
{
"docstring": ":param stop_words_file: -- str，停用词文件路径，若不是str则使用默认停用词文件 :param allow_speech_tags: -- 词性列表 :param wc_background: 词云图背景图片 :param max_words: 最多显示词数，默认200 :param max_font_size: 字体最大值，默认100 :param save_path: 词云图保存地址，默认当前文件夹",
"name": "__init__",
"signature": "def __init__(self, stop_words_fil... | 4 | stack_v2_sparse_classes_30k_train_009742 | Implement the Python class `WordCloud` described below.
Class description:
Implement the WordCloud class.
Method signatures and docstrings:
- def __init__(self, stop_words_file=None, allow_speech_tags=conf.allow_speech_tags, wc_background=None, font_path=None, max_words=200, max_font_size=100, save_path=None, wc_name... | Implement the Python class `WordCloud` described below.
Class description:
Implement the WordCloud class.
Method signatures and docstrings:
- def __init__(self, stop_words_file=None, allow_speech_tags=conf.allow_speech_tags, wc_background=None, font_path=None, max_words=200, max_font_size=100, save_path=None, wc_name... | a477c2926e97c86135623a2c7c844812be3be696 | <|skeleton|>
class WordCloud:
def __init__(self, stop_words_file=None, allow_speech_tags=conf.allow_speech_tags, wc_background=None, font_path=None, max_words=200, max_font_size=100, save_path=None, wc_name=None, topK=10):
""":param stop_words_file: -- str，停用词文件路径，若不是str则使用默认停用词文件 :param allow_speech_tags:... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class WordCloud:
def __init__(self, stop_words_file=None, allow_speech_tags=conf.allow_speech_tags, wc_background=None, font_path=None, max_words=200, max_font_size=100, save_path=None, wc_name=None, topK=10):
""":param stop_words_file: -- str，停用词文件路径，若不是str则使用默认停用词文件 :param allow_speech_tags: -- 词性列表 :para... | the_stack_v2_python_sparse | WordCloud/word_cloud/word_cloud.py | FredZhao04/chinese-nlp | train | 5 | |
c11dcf1fd67c8b7a5d1af7a4b1801a7d46b112ad | [
"super().__init__(dist, sources, target, rv_mode=rv_mode)\nq_size = prod(self._shape) + 1\nbound = min([bound, q_size]) if bound is not None else q_size\nself._construct_auxvars([(self._rvs | self._crvs, bound)])\nentropies = [entropy(dist, source + target) for source in sources]\nmutual_informations = [mutual_info... | <|body_start_0|>
super().__init__(dist, sources, target, rv_mode=rv_mode)
q_size = prod(self._shape) + 1
bound = min([bound, q_size]) if bound is not None else q_size
self._construct_auxvars([(self._rvs | self._crvs, bound)])
entropies = [entropy(dist, source + target) for source... | Optimizer for the Griffith & Ho redundancy. | GHOptimizer | [
"LicenseRef-scancode-unknown-license-reference",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GHOptimizer:
"""Optimizer for the Griffith & Ho redundancy."""
def __init__(self, dist, sources, target, bound=None, rv_mode=None):
"""Initialize the optimizer. Parameters ---------- dist : Distribution The distribution to compute i_gh of. sources : list, None A list of lists. Each i... | stack_v2_sparse_classes_75kplus_train_073443 | 5,217 | permissive | [
{
"docstring": "Initialize the optimizer. Parameters ---------- dist : Distribution The distribution to compute i_gh of. sources : list, None A list of lists. Each inner list specifies the indexes of the random variables used to calculate the intrinsic mutual information. If None, then it is calculated over all... | 3 | stack_v2_sparse_classes_30k_train_004433 | Implement the Python class `GHOptimizer` described below.
Class description:
Optimizer for the Griffith & Ho redundancy.
Method signatures and docstrings:
- def __init__(self, dist, sources, target, bound=None, rv_mode=None): Initialize the optimizer. Parameters ---------- dist : Distribution The distribution to comp... | Implement the Python class `GHOptimizer` described below.
Class description:
Optimizer for the Griffith & Ho redundancy.
Method signatures and docstrings:
- def __init__(self, dist, sources, target, bound=None, rv_mode=None): Initialize the optimizer. Parameters ---------- dist : Distribution The distribution to comp... | b13c5020a2b8524527a4a0db5a81d8549142228c | <|skeleton|>
class GHOptimizer:
"""Optimizer for the Griffith & Ho redundancy."""
def __init__(self, dist, sources, target, bound=None, rv_mode=None):
"""Initialize the optimizer. Parameters ---------- dist : Distribution The distribution to compute i_gh of. sources : list, None A list of lists. Each i... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class GHOptimizer:
"""Optimizer for the Griffith & Ho redundancy."""
def __init__(self, dist, sources, target, bound=None, rv_mode=None):
"""Initialize the optimizer. Parameters ---------- dist : Distribution The distribution to compute i_gh of. sources : list, None A list of lists. Each inner list spe... | the_stack_v2_python_sparse | dit/pid/measures/igh.py | dit/dit | train | 468 |
528a6fc9225110d6602e0ce04cf95e1ddcf68104 | [
"num_inputs = '{} Inputs:\\n'.format(self.size)\ninputs = '\\n'.join(['\"{}\": {:~P}'.format(key, value.value) for key, value in self.data.items()])\nreturn num_inputs + inputs",
"if self.size == 0:\n return ''\nhead = 'DERIVATIVES {}\\n'.format(self.size)\n_ins = []\nderivative: TypeVariable\nfor derivative i... | <|body_start_0|>
num_inputs = '{} Inputs:\n'.format(self.size)
inputs = '\n'.join(['"{}": {:~P}'.format(key, value.value) for key, value in self.data.items()])
return num_inputs + inputs
<|end_body_0|>
<|body_start_1|>
if self.size == 0:
return ''
head = 'DERIVATIVES... | Subclass of :class:`VariableCollection` specific to Derivatives. | DerivativesCollection | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DerivativesCollection:
"""Subclass of :class:`VariableCollection` specific to Derivatives."""
def __repr__(self):
"""Return repr(self)."""
<|body_0|>
def _to_deck(self):
"""Return deck representation of self."""
<|body_1|>
<|end_skeleton|>
<|body_start_... | stack_v2_sparse_classes_75kplus_train_073444 | 1,067 | permissive | [
{
"docstring": "Return repr(self).",
"name": "__repr__",
"signature": "def __repr__(self)"
},
{
"docstring": "Return deck representation of self.",
"name": "_to_deck",
"signature": "def _to_deck(self)"
}
] | 2 | null | Implement the Python class `DerivativesCollection` described below.
Class description:
Subclass of :class:`VariableCollection` specific to Derivatives.
Method signatures and docstrings:
- def __repr__(self): Return repr(self).
- def _to_deck(self): Return deck representation of self. | Implement the Python class `DerivativesCollection` described below.
Class description:
Subclass of :class:`VariableCollection` specific to Derivatives.
Method signatures and docstrings:
- def __repr__(self): Return repr(self).
- def _to_deck(self): Return deck representation of self.
<|skeleton|>
class DerivativesCo... | f2deb5eb340a2814722eead5f8b6278a945c730d | <|skeleton|>
class DerivativesCollection:
"""Subclass of :class:`VariableCollection` specific to Derivatives."""
def __repr__(self):
"""Return repr(self)."""
<|body_0|>
def _to_deck(self):
"""Return deck representation of self."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DerivativesCollection:
"""Subclass of :class:`VariableCollection` specific to Derivatives."""
def __repr__(self):
"""Return repr(self)."""
num_inputs = '{} Inputs:\n'.format(self.size)
inputs = '\n'.join(['"{}": {:~P}'.format(key, value.value) for key, value in self.data.items()])... | the_stack_v2_python_sparse | trnsystor/collections/derivatives.py | sturmianseq/trnsystor | train | 0 |
88f75ed11a9d89b16a53f9560e12f5c143088dc8 | [
"super(CandlestickData, self).__init__()\nself.o = kwargs.get('o')\nself.h = kwargs.get('h')\nself.l = kwargs.get('l')\nself.c = kwargs.get('c')",
"data = data.copy()\nif data.get('o') is not None:\n data['o'] = ctx.convert_decimal_number(data.get('o'))\nif data.get('h') is not None:\n data['h'] = ctx.conve... | <|body_start_0|>
super(CandlestickData, self).__init__()
self.o = kwargs.get('o')
self.h = kwargs.get('h')
self.l = kwargs.get('l')
self.c = kwargs.get('c')
<|end_body_0|>
<|body_start_1|>
data = data.copy()
if data.get('o') is not None:
data['o'] = c... | The price data (open, high, low, close) for the Candlestick representation. | CandlestickData | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CandlestickData:
"""The price data (open, high, low, close) for the Candlestick representation."""
def __init__(self, **kwargs):
"""Create a new CandlestickData instance"""
<|body_0|>
def from_dict(data, ctx):
"""Instantiate a new CandlestickData from a dict (gen... | stack_v2_sparse_classes_75kplus_train_073445 | 11,143 | permissive | [
{
"docstring": "Create a new CandlestickData instance",
"name": "__init__",
"signature": "def __init__(self, **kwargs)"
},
{
"docstring": "Instantiate a new CandlestickData from a dict (generally from loading a JSON response). The data used to instantiate the CandlestickData is a shallow copy of... | 2 | stack_v2_sparse_classes_30k_train_007698 | Implement the Python class `CandlestickData` described below.
Class description:
The price data (open, high, low, close) for the Candlestick representation.
Method signatures and docstrings:
- def __init__(self, **kwargs): Create a new CandlestickData instance
- def from_dict(data, ctx): Instantiate a new Candlestick... | Implement the Python class `CandlestickData` described below.
Class description:
The price data (open, high, low, close) for the Candlestick representation.
Method signatures and docstrings:
- def __init__(self, **kwargs): Create a new CandlestickData instance
- def from_dict(data, ctx): Instantiate a new Candlestick... | 055f51e55c52d6dd5cfd38550a48892a0fb09b0d | <|skeleton|>
class CandlestickData:
"""The price data (open, high, low, close) for the Candlestick representation."""
def __init__(self, **kwargs):
"""Create a new CandlestickData instance"""
<|body_0|>
def from_dict(data, ctx):
"""Instantiate a new CandlestickData from a dict (gen... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CandlestickData:
"""The price data (open, high, low, close) for the Candlestick representation."""
def __init__(self, **kwargs):
"""Create a new CandlestickData instance"""
super(CandlestickData, self).__init__()
self.o = kwargs.get('o')
self.h = kwargs.get('h')
se... | the_stack_v2_python_sparse | forex/env-python2/lib/python2.7/site-packages/v20/instrument.py | phroiland/forex_algos | train | 1 |
a4e96ee2fd58e1422659ef8ed5f3b4c87ed2b370 | [
"all_tags = cls.objects.all()\nstyling = {t.pk: {'style': t.style, 'desc': t.description} for t in all_tags}\nreturn styling",
"if isinstance(value, list):\n count = cls.objects.raw({'_id': {'$in': value}}).count()\n if count == len(value):\n return True\nreturn False"
] | <|body_start_0|>
all_tags = cls.objects.all()
styling = {t.pk: {'style': t.style, 'desc': t.description} for t in all_tags}
return styling
<|end_body_0|>
<|body_start_1|>
if isinstance(value, list):
count = cls.objects.raw({'_id': {'$in': value}}).count()
if coun... | Tag | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Tag:
def get_display_data(cls):
"""Get a dict with the styling for each tag"""
<|body_0|>
def validate_field(cls, value):
"""Validate field for sample form submission."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
all_tags = cls.objects.all()
... | stack_v2_sparse_classes_75kplus_train_073446 | 1,421 | no_license | [
{
"docstring": "Get a dict with the styling for each tag",
"name": "get_display_data",
"signature": "def get_display_data(cls)"
},
{
"docstring": "Validate field for sample form submission.",
"name": "validate_field",
"signature": "def validate_field(cls, value)"
}
] | 2 | null | Implement the Python class `Tag` described below.
Class description:
Implement the Tag class.
Method signatures and docstrings:
- def get_display_data(cls): Get a dict with the styling for each tag
- def validate_field(cls, value): Validate field for sample form submission. | Implement the Python class `Tag` described below.
Class description:
Implement the Tag class.
Method signatures and docstrings:
- def get_display_data(cls): Get a dict with the styling for each tag
- def validate_field(cls, value): Validate field for sample form submission.
<|skeleton|>
class Tag:
def get_displ... | 34fe159927eaa3884acf354c62b8213b0cd33368 | <|skeleton|>
class Tag:
def get_display_data(cls):
"""Get a dict with the styling for each tag"""
<|body_0|>
def validate_field(cls, value):
"""Validate field for sample form submission."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Tag:
def get_display_data(cls):
"""Get a dict with the styling for each tag"""
all_tags = cls.objects.all()
styling = {t.pk: {'style': t.style, 'desc': t.description} for t in all_tags}
return styling
def validate_field(cls, value):
"""Validate field for sample for... | the_stack_v2_python_sparse | app/minilims/models/tag.py | ssi-dk/miniLIMS | train | 4 | |
d33f5928e4414fbed5d4a09ae32baa2c6f413c19 | [
"super().__init__()\nassert attention_size % n_heads == 0\nself.hidden_size = hidden_size\nself.n_heads = n_heads\nself.head_size = attention_size // n_heads\nself.attention_size = attention_size\nself.hidden_to_query = nn.Linear(hidden_size, attention_size)\nself.hidden_to_key = nn.Linear(hidden_size, attention_si... | <|body_start_0|>
super().__init__()
assert attention_size % n_heads == 0
self.hidden_size = hidden_size
self.n_heads = n_heads
self.head_size = attention_size // n_heads
self.attention_size = attention_size
self.hidden_to_query = nn.Linear(hidden_size, attention_s... | Multihead self-attention | MultiHeadAttention | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MultiHeadAttention:
"""Multihead self-attention"""
def __init__(self, hidden_size: int, attention_size: int, n_heads: int, dropout: float, device: str):
"""Constructor Args: hidden_size (int): hidden size of the input. attention_size (int): attention size n_heads (int): number of hea... | stack_v2_sparse_classes_75kplus_train_073447 | 14,969 | permissive | [
{
"docstring": "Constructor Args: hidden_size (int): hidden size of the input. attention_size (int): attention size n_heads (int): number of heads (attention heads) dropout (double): dropout rate device (string): cuda or cpu",
"name": "__init__",
"signature": "def __init__(self, hidden_size: int, attent... | 2 | stack_v2_sparse_classes_30k_train_024123 | Implement the Python class `MultiHeadAttention` described below.
Class description:
Multihead self-attention
Method signatures and docstrings:
- def __init__(self, hidden_size: int, attention_size: int, n_heads: int, dropout: float, device: str): Constructor Args: hidden_size (int): hidden size of the input. attentio... | Implement the Python class `MultiHeadAttention` described below.
Class description:
Multihead self-attention
Method signatures and docstrings:
- def __init__(self, hidden_size: int, attention_size: int, n_heads: int, dropout: float, device: str): Constructor Args: hidden_size (int): hidden size of the input. attentio... | 5b4a61b5dd0bc259ffe68223877949ef4ebfa5e3 | <|skeleton|>
class MultiHeadAttention:
"""Multihead self-attention"""
def __init__(self, hidden_size: int, attention_size: int, n_heads: int, dropout: float, device: str):
"""Constructor Args: hidden_size (int): hidden size of the input. attention_size (int): attention size n_heads (int): number of hea... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MultiHeadAttention:
"""Multihead self-attention"""
def __init__(self, hidden_size: int, attention_size: int, n_heads: int, dropout: float, device: str):
"""Constructor Args: hidden_size (int): hidden size of the input. attention_size (int): attention size n_heads (int): number of heads (attention... | the_stack_v2_python_sparse | src/models/anomalia/layers.py | maurony/ts-vrae | train | 1 |
e04f2bacd02be1e7f467af55b3799871e093afdb | [
"file1 = MockAffectedFile('some/dir/file1.html', ['<!DOCTYPE html>', '<html>', '<body>', '<p>Test</p>', '</body>', '</html>'])\nfile2 = MockAffectedFile('some/dir2/file2.html', ['<html>', '<body>', '<p>Test</p>', '</body>', '</html>'])\nfile3 = MockAffectedFile('file3.html', ['<!--Some comment-->', '<!docTYPE ht... | <|body_start_0|>
file1 = MockAffectedFile('some/dir/file1.html', ['<!DOCTYPE html>', '<html>', '<body>', '<p>Test</p>', '</body>', '</html>'])
file2 = MockAffectedFile('some/dir2/file2.html', ['<html>', '<body>', '<p>Test</p>', '</body>', '</html>'])
file3 = MockAffectedFile('file3.html', ['<!--... | PresubmitTest | [
"BSD-3-Clause",
"Apache-2.0",
"LGPL-2.0-or-later",
"MIT",
"GPL-1.0-or-later",
"LicenseRef-scancode-warranty-disclaimer",
"LGPL-2.1-only",
"GPL-2.0-only",
"LGPL-2.0-only",
"BSD-2-Clause",
"LicenseRef-scancode-other-copyleft"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PresubmitTest:
def testCheckForDoctypeHTML(self):
"""This verifies that we correctly identify missing DOCTYPE html tags."""
<|body_0|>
def testCheckForDoctypeHTMLExceptions(self):
"""This test makes sure that we don't raise <!DOCTYPE html> errors for WPT importer."""... | stack_v2_sparse_classes_75kplus_train_073448 | 3,449 | permissive | [
{
"docstring": "This verifies that we correctly identify missing DOCTYPE html tags.",
"name": "testCheckForDoctypeHTML",
"signature": "def testCheckForDoctypeHTML(self)"
},
{
"docstring": "This test makes sure that we don't raise <!DOCTYPE html> errors for WPT importer.",
"name": "testCheckF... | 2 | null | Implement the Python class `PresubmitTest` described below.
Class description:
Implement the PresubmitTest class.
Method signatures and docstrings:
- def testCheckForDoctypeHTML(self): This verifies that we correctly identify missing DOCTYPE html tags.
- def testCheckForDoctypeHTMLExceptions(self): This test makes su... | Implement the Python class `PresubmitTest` described below.
Class description:
Implement the PresubmitTest class.
Method signatures and docstrings:
- def testCheckForDoctypeHTML(self): This verifies that we correctly identify missing DOCTYPE html tags.
- def testCheckForDoctypeHTMLExceptions(self): This test makes su... | 87244f4ee50062e59667bf8b9ca4d5291b6818d7 | <|skeleton|>
class PresubmitTest:
def testCheckForDoctypeHTML(self):
"""This verifies that we correctly identify missing DOCTYPE html tags."""
<|body_0|>
def testCheckForDoctypeHTMLExceptions(self):
"""This test makes sure that we don't raise <!DOCTYPE html> errors for WPT importer."""... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PresubmitTest:
def testCheckForDoctypeHTML(self):
"""This verifies that we correctly identify missing DOCTYPE html tags."""
file1 = MockAffectedFile('some/dir/file1.html', ['<!DOCTYPE html>', '<html>', '<body>', '<p>Test</p>', '</body>', '</html>'])
file2 = MockAffectedFile('some/dir2/... | the_stack_v2_python_sparse | chromium/third_party/blink/web_tests/PRESUBMIT_test.py | ric2b/Vivaldi-browser | train | 166 | |
884a3a594bfe5af3db29950f4b949eaf774cbc8a | [
"result = []\nfields = resource.fields\ntake_field = query.state.get('field')\nstate = cls._get_query_state(query, level=level)\nif state is True:\n take = {resource.id_name: True}\n group = None\nelse:\n take = state.get('take')\n group = state.get('group')\nif group:\n return [Record(name=name, typ... | <|body_start_0|>
result = []
fields = resource.fields
take_field = query.state.get('field')
state = cls._get_query_state(query, level=level)
if state is True:
take = {resource.id_name: True}
group = None
else:
take = state.get('take')
... | Selection | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Selection:
def _take_fields(cls, resource, action, level=None, query=None, request=None):
"""Get a subset of a resource's fields to be used for an action Arguments: resource: a Resource action: action string (ex: "get") level: level string (ex: "a.b") query: a Query request: a Django Req... | stack_v2_sparse_classes_75kplus_train_073449 | 24,219 | permissive | [
{
"docstring": "Get a subset of a resource's fields to be used for an action Arguments: resource: a Resource action: action string (ex: \"get\") level: level string (ex: \"a.b\") query: a Query request: a Django Request object",
"name": "_take_fields",
"signature": "def _take_fields(cls, resource, actio... | 2 | null | Implement the Python class `Selection` described below.
Class description:
Implement the Selection class.
Method signatures and docstrings:
- def _take_fields(cls, resource, action, level=None, query=None, request=None): Get a subset of a resource's fields to be used for an action Arguments: resource: a Resource acti... | Implement the Python class `Selection` described below.
Class description:
Implement the Selection class.
Method signatures and docstrings:
- def _take_fields(cls, resource, action, level=None, query=None, request=None): Get a subset of a resource's fields to be used for an action Arguments: resource: a Resource acti... | 217a5298a7a4be85991f6cf229f30ddbfdcb1215 | <|skeleton|>
class Selection:
def _take_fields(cls, resource, action, level=None, query=None, request=None):
"""Get a subset of a resource's fields to be used for an action Arguments: resource: a Resource action: action string (ex: "get") level: level string (ex: "a.b") query: a Query request: a Django Req... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Selection:
def _take_fields(cls, resource, action, level=None, query=None, request=None):
"""Get a subset of a resource's fields to be used for an action Arguments: resource: a Resource action: action string (ex: "get") level: level string (ex: "a.b") query: a Query request: a Django Request object"""... | the_stack_v2_python_sparse | pyresource/executor.py | aleontiev/pyresource | train | 1 | |
6bc2ef7fd787ba4bea29300d401f5a7241ed65d8 | [
"wx.Panel.__init__(self, parent)\nself.widget = wxVTKRenderWindowInteractor(self, -1)\nself.widget.Enable(1)\nself.widget.AddObserver()\nself.sizer = wx.BoxSizer(wx.VERTICAL)\nself.sizer.Add(self.widget, 1, wx.EXPAND)\nself.SetSizer(self.sizer)\nself.Layout()\nself.ren = vtk.vtkRenderer()\nself.filename = ''\nself.... | <|body_start_0|>
wx.Panel.__init__(self, parent)
self.widget = wxVTKRenderWindowInteractor(self, -1)
self.widget.Enable(1)
self.widget.AddObserver()
self.sizer = wx.BoxSizer(wx.VERTICAL)
self.sizer.Add(self.widget, 1, wx.EXPAND)
self.SetSizer(self.sizer)
s... | Vtk Viewer | VtkViewer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VtkViewer:
"""Vtk Viewer"""
def __init__(self, parent):
""":param parent: :return:"""
<|body_0|>
def renderthis(self):
""":return:"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
wx.Panel.__init__(self, parent)
self.widget = wxVTKRenderW... | stack_v2_sparse_classes_75kplus_train_073450 | 2,472 | no_license | [
{
"docstring": ":param parent: :return:",
"name": "__init__",
"signature": "def __init__(self, parent)"
},
{
"docstring": ":return:",
"name": "renderthis",
"signature": "def renderthis(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_018344 | Implement the Python class `VtkViewer` described below.
Class description:
Vtk Viewer
Method signatures and docstrings:
- def __init__(self, parent): :param parent: :return:
- def renderthis(self): :return: | Implement the Python class `VtkViewer` described below.
Class description:
Vtk Viewer
Method signatures and docstrings:
- def __init__(self, parent): :param parent: :return:
- def renderthis(self): :return:
<|skeleton|>
class VtkViewer:
"""Vtk Viewer"""
def __init__(self, parent):
""":param parent: ... | e78511f30935b006385b571472487bb081aa36d8 | <|skeleton|>
class VtkViewer:
"""Vtk Viewer"""
def __init__(self, parent):
""":param parent: :return:"""
<|body_0|>
def renderthis(self):
""":return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class VtkViewer:
"""Vtk Viewer"""
def __init__(self, parent):
""":param parent: :return:"""
wx.Panel.__init__(self, parent)
self.widget = wxVTKRenderWindowInteractor(self, -1)
self.widget.Enable(1)
self.widget.AddObserver()
self.sizer = wx.BoxSizer(wx.VERTICAL)
... | the_stack_v2_python_sparse | boaui/view/vtk.py | JoenyBui/boa-gui | train | 0 |
a763c9d6e4f909126e046c04ee2baa79a24923ea | [
"if m < n:\n m, n = (n, m)\nmul = lambda x, y: reduce(operator.mul, range(x, y), 1)\nreturn mul(m, m + n - 1) / mul(1, n)",
"if m < n:\n m, n = (n, m)\ndp = [0] * n\ndp[0] = 1\nfor x in range(m):\n for y in range(n - 1):\n dp[y + 1] += dp[y]\nreturn dp[n - 1]",
"dp = [[0] * n for x in range(m)]\... | <|body_start_0|>
if m < n:
m, n = (n, m)
mul = lambda x, y: reduce(operator.mul, range(x, y), 1)
return mul(m, m + n - 1) / mul(1, n)
<|end_body_0|>
<|body_start_1|>
if m < n:
m, n = (n, m)
dp = [0] * n
dp[0] = 1
for x in range(m):
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def uniquePaths(self, m, n):
""":type m: int :type n: int :rtype: int"""
<|body_0|>
def uniquePaths_v1(self, m, n):
""":type m: int :type n: int :rtype: int"""
<|body_1|>
def uniquePaths_v0(self, m, n):
""":type m: int :type n: int :rty... | stack_v2_sparse_classes_75kplus_train_073451 | 3,652 | no_license | [
{
"docstring": ":type m: int :type n: int :rtype: int",
"name": "uniquePaths",
"signature": "def uniquePaths(self, m, n)"
},
{
"docstring": ":type m: int :type n: int :rtype: int",
"name": "uniquePaths_v1",
"signature": "def uniquePaths_v1(self, m, n)"
},
{
"docstring": ":type m:... | 3 | stack_v2_sparse_classes_30k_train_022185 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def uniquePaths(self, m, n): :type m: int :type n: int :rtype: int
- def uniquePaths_v1(self, m, n): :type m: int :type n: int :rtype: int
- def uniquePaths_v0(self, m, n): :type... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def uniquePaths(self, m, n): :type m: int :type n: int :rtype: int
- def uniquePaths_v1(self, m, n): :type m: int :type n: int :rtype: int
- def uniquePaths_v0(self, m, n): :type... | b5e09f24e8e96454dc99e20281e853fb9fcc85ed | <|skeleton|>
class Solution:
def uniquePaths(self, m, n):
""":type m: int :type n: int :rtype: int"""
<|body_0|>
def uniquePaths_v1(self, m, n):
""":type m: int :type n: int :rtype: int"""
<|body_1|>
def uniquePaths_v0(self, m, n):
""":type m: int :type n: int :rty... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def uniquePaths(self, m, n):
""":type m: int :type n: int :rtype: int"""
if m < n:
m, n = (n, m)
mul = lambda x, y: reduce(operator.mul, range(x, y), 1)
return mul(m, m + n - 1) / mul(1, n)
def uniquePaths_v1(self, m, n):
""":type m: int :type... | the_stack_v2_python_sparse | python/62_Unique_Paths.py | Moby5/myleetcode | train | 2 | |
6a5191e22116da27b0396f70bd54d80cfcdb8d5f | [
"try:\n type_key, identifier = key.split(':', maxsplit=1)\nexcept ValueError as e:\n msg = f\"'{key}' is not a valid source. There should be a single colon ':' sign somewhere. Original error: {e}\"\n raise UnknownSourceIdentifierException(msg) from e\nfor id_type in self.types:\n if id_type.key == type_... | <|body_start_0|>
try:
type_key, identifier = key.split(':', maxsplit=1)
except ValueError as e:
msg = f"'{key}' is not a valid source. There should be a single colon ':' sign somewhere. Original error: {e}"
raise UnknownSourceIdentifierException(msg) from e
fo... | Creates SourceIdentifier objects based on key input | SourceIdentifierFactory | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SourceIdentifierFactory:
"""Creates SourceIdentifier objects based on key input"""
def get_source_identifier_for_key(self, key: str) -> SourceIdentifier:
"""Cast given key input back to identifier object Parameters ---------- key: str Key to cast, like 'folder:/myfolder' Raises -----... | stack_v2_sparse_classes_75kplus_train_073452 | 20,389 | permissive | [
{
"docstring": "Cast given key input back to identifier object Parameters ---------- key: str Key to cast, like 'folder:/myfolder' Raises ------ UnknownSourceIdentifierException: When the key cannot be cast to any known identifier Returns ------- Instance of SourceIdentifier or subtype The type that the given k... | 2 | stack_v2_sparse_classes_30k_train_046160 | Implement the Python class `SourceIdentifierFactory` described below.
Class description:
Creates SourceIdentifier objects based on key input
Method signatures and docstrings:
- def get_source_identifier_for_key(self, key: str) -> SourceIdentifier: Cast given key input back to identifier object Parameters ---------- k... | Implement the Python class `SourceIdentifierFactory` described below.
Class description:
Creates SourceIdentifier objects based on key input
Method signatures and docstrings:
- def get_source_identifier_for_key(self, key: str) -> SourceIdentifier: Cast given key input back to identifier object Parameters ---------- k... | d0d5437c9bbce60ee79165214ef87c69d47095c7 | <|skeleton|>
class SourceIdentifierFactory:
"""Creates SourceIdentifier objects based on key input"""
def get_source_identifier_for_key(self, key: str) -> SourceIdentifier:
"""Cast given key input back to identifier object Parameters ---------- key: str Key to cast, like 'folder:/myfolder' Raises -----... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SourceIdentifierFactory:
"""Creates SourceIdentifier objects based on key input"""
def get_source_identifier_for_key(self, key: str) -> SourceIdentifier:
"""Cast given key input back to identifier object Parameters ---------- key: str Key to cast, like 'folder:/myfolder' Raises ------ UnknownSour... | the_stack_v2_python_sparse | anonapi/parameters.py | sjoerdk/anonapi | train | 0 |
462e99cf8b33bcb1239c1fd08f749f48d975500d | [
"for sdir in self.static_dirs:\n if self.path.startswith(sdir):\n SimpleHTTPServer.SimpleHTTPRequestHandler.do_GET(self)\n return\ni = self.path.rfind('?')\nif i >= 0:\n path, query = (self.path[:i], self.path[i + 1:])\nelse:\n path = self.path\n query = ''\nself.handle_query(path, query)"... | <|body_start_0|>
for sdir in self.static_dirs:
if self.path.startswith(sdir):
SimpleHTTPServer.SimpleHTTPRequestHandler.do_GET(self)
return
i = self.path.rfind('?')
if i >= 0:
path, query = (self.path[:i], self.path[i + 1:])
else:
... | SimpleAppServer | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SimpleAppServer:
def do_GET(self):
"""GETリクエストを処理する"""
<|body_0|>
def do_POST(self):
"""POSTリクエストを処理する"""
<|body_1|>
def handle_query(self, path, query):
"""クエリ付きのGET，POSTリクエストをハンドリングする"""
<|body_2|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_75kplus_train_073453 | 2,403 | permissive | [
{
"docstring": "GETリクエストを処理する",
"name": "do_GET",
"signature": "def do_GET(self)"
},
{
"docstring": "POSTリクエストを処理する",
"name": "do_POST",
"signature": "def do_POST(self)"
},
{
"docstring": "クエリ付きのGET，POSTリクエストをハンドリングする",
"name": "handle_query",
"signature": "def handle_que... | 3 | stack_v2_sparse_classes_30k_train_022050 | Implement the Python class `SimpleAppServer` described below.
Class description:
Implement the SimpleAppServer class.
Method signatures and docstrings:
- def do_GET(self): GETリクエストを処理する
- def do_POST(self): POSTリクエストを処理する
- def handle_query(self, path, query): クエリ付きのGET，POSTリクエストをハンドリングする | Implement the Python class `SimpleAppServer` described below.
Class description:
Implement the SimpleAppServer class.
Method signatures and docstrings:
- def do_GET(self): GETリクエストを処理する
- def do_POST(self): POSTリクエストを処理する
- def handle_query(self, path, query): クエリ付きのGET，POSTリクエストをハンドリングする
<|skeleton|>
class SimpleAp... | b96eaae97c82b82a388aee567e702a63072ae6ac | <|skeleton|>
class SimpleAppServer:
def do_GET(self):
"""GETリクエストを処理する"""
<|body_0|>
def do_POST(self):
"""POSTリクエストを処理する"""
<|body_1|>
def handle_query(self, path, query):
"""クエリ付きのGET，POSTリクエストをハンドリングする"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SimpleAppServer:
def do_GET(self):
"""GETリクエストを処理する"""
for sdir in self.static_dirs:
if self.path.startswith(sdir):
SimpleHTTPServer.SimpleHTTPRequestHandler.do_GET(self)
return
i = self.path.rfind('?')
if i >= 0:
path, qu... | the_stack_v2_python_sparse | cgi-bin/simpleappserver.py | kyon-bll/min_py_web | train | 0 | |
c5908d688aabaf9bd6015ccad3ce505013901897 | [
"if root is None:\n return 'S,'\nelse:\n left = self.serialize(root.left)\n right = self.serialize(root.right)\nreturn str(root.val) + ',' + str(left) + str(right)",
"def deserializeHelper(queue):\n node = queue.popleft()\n if node == 'S':\n return None\n root = TreeNode(node)\n root.l... | <|body_start_0|>
if root is None:
return 'S,'
else:
left = self.serialize(root.left)
right = self.serialize(root.right)
return str(root.val) + ',' + str(left) + str(right)
<|end_body_0|>
<|body_start_1|>
def deserializeHelper(queue):
node ... | 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_073454 | 1,474 | 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_test_002595 | 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:... | fea3d75e99433dc67a7b4e303e25ed0ad9343f5f | <|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 root is None:
return 'S,'
else:
left = self.serialize(root.left)
right = self.serialize(root.right)
return str(root.val) + ',' + st... | the_stack_v2_python_sparse | puthon_files/serialize-and-deserialize-binary-tree.py | aashishravindran/interview_prep | train | 0 | |
68dca3034b3bcac8b1df73b794e4ec83db614e93 | [
"user = super().save_user(request, sociallogin, form)\nuser.username = smart_str(base64.urlsafe_b64encode(hashlib.sha1(smart_bytes(user.email)).digest()).rstrip(b'='))\nuser.save()\nreturn user",
"email = sociallogin.account.extra_data.get('email')\nif not email:\n return\ntry:\n user = User.objects.get(ema... | <|body_start_0|>
user = super().save_user(request, sociallogin, form)
user.username = smart_str(base64.urlsafe_b64encode(hashlib.sha1(smart_bytes(user.email)).digest()).rstrip(b'='))
user.save()
return user
<|end_body_0|>
<|body_start_1|>
email = sociallogin.account.extra_data.g... | PontoonSocialAdapter | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PontoonSocialAdapter:
def save_user(self, request, sociallogin, form=None):
"""Generates an unique username in the same way as it was done in django-browserid. This is required to avoid collisions and the backward compatibility."""
<|body_0|>
def pre_social_login(self, reque... | stack_v2_sparse_classes_75kplus_train_073455 | 1,402 | permissive | [
{
"docstring": "Generates an unique username in the same way as it was done in django-browserid. This is required to avoid collisions and the backward compatibility.",
"name": "save_user",
"signature": "def save_user(self, request, sociallogin, form=None)"
},
{
"docstring": "Connect existing Pon... | 2 | null | Implement the Python class `PontoonSocialAdapter` described below.
Class description:
Implement the PontoonSocialAdapter class.
Method signatures and docstrings:
- def save_user(self, request, sociallogin, form=None): Generates an unique username in the same way as it was done in django-browserid. This is required to... | Implement the Python class `PontoonSocialAdapter` described below.
Class description:
Implement the PontoonSocialAdapter class.
Method signatures and docstrings:
- def save_user(self, request, sociallogin, form=None): Generates an unique username in the same way as it was done in django-browserid. This is required to... | 0c4f74e15b1e442a9cee9b1cd636214b24f5352b | <|skeleton|>
class PontoonSocialAdapter:
def save_user(self, request, sociallogin, form=None):
"""Generates an unique username in the same way as it was done in django-browserid. This is required to avoid collisions and the backward compatibility."""
<|body_0|>
def pre_social_login(self, reque... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PontoonSocialAdapter:
def save_user(self, request, sociallogin, form=None):
"""Generates an unique username in the same way as it was done in django-browserid. This is required to avoid collisions and the backward compatibility."""
user = super().save_user(request, sociallogin, form)
u... | the_stack_v2_python_sparse | pontoon/base/adapter.py | mozilla/pontoon | train | 1,367 | |
288c94d00404f22d6d2df134956367cb603c4fea | [
"self._ambig_finder = ambig_finder\nself._num_ambiguous = num_ambiguous\nself._alphabet_letters = ambig_finder.all_unambiguous()",
"new_org = organism.copy()\nwhile 1:\n seq_genome = new_org.genome.toseq()\n all_ambiguous = self._ambig_finder.find_ambiguous(seq_genome.tostring())\n if len(all_ambiguous) ... | <|body_start_0|>
self._ambig_finder = ambig_finder
self._num_ambiguous = num_ambiguous
self._alphabet_letters = ambig_finder.all_unambiguous()
<|end_body_0|>
<|body_start_1|>
new_org = organism.copy()
while 1:
seq_genome = new_org.genome.toseq()
all_ambig... | Perform repair to reduce the number of Ambiguous genes in a genome. In cases where ambiguous genes are allowed in a genome (for example, where you have a wild card character like '*' that will match anything), these can come to dominate a genome since, really, the best fitness is someting like '*******'. This repair pr... | AmbiguousRepair | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AmbiguousRepair:
"""Perform repair to reduce the number of Ambiguous genes in a genome. In cases where ambiguous genes are allowed in a genome (for example, where you have a wild card character like '*' that will match anything), these can come to dominate a genome since, really, the best fitness... | stack_v2_sparse_classes_75kplus_train_073456 | 2,341 | permissive | [
{
"docstring": "Initialize the repair class. Arguments: o ambig_finder - A class implementing the function find_ambiguous which will return a list of all ambiguous positions in a sequence. It also must have the function all_unambiguous, which will return all allowed unambiguous letters. o num_ambiguous - The mi... | 2 | null | Implement the Python class `AmbiguousRepair` described below.
Class description:
Perform repair to reduce the number of Ambiguous genes in a genome. In cases where ambiguous genes are allowed in a genome (for example, where you have a wild card character like '*' that will match anything), these can come to dominate a... | Implement the Python class `AmbiguousRepair` described below.
Class description:
Perform repair to reduce the number of Ambiguous genes in a genome. In cases where ambiguous genes are allowed in a genome (for example, where you have a wild card character like '*' that will match anything), these can come to dominate a... | 1d9a8e84a8572809ee3260ede44290e14de3bdd1 | <|skeleton|>
class AmbiguousRepair:
"""Perform repair to reduce the number of Ambiguous genes in a genome. In cases where ambiguous genes are allowed in a genome (for example, where you have a wild card character like '*' that will match anything), these can come to dominate a genome since, really, the best fitness... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AmbiguousRepair:
"""Perform repair to reduce the number of Ambiguous genes in a genome. In cases where ambiguous genes are allowed in a genome (for example, where you have a wild card character like '*' that will match anything), these can come to dominate a genome since, really, the best fitness is someting ... | the_stack_v2_python_sparse | bin/last_wrapper/Bio/GA/Repair/Stabilizing.py | LyonsLab/coge | train | 41 |
3b786df6b51e839673cd16770e2710942cc4da40 | [
"n = str(n)[::-1]\nst = ''\nroman_lst = ['', 'I', 'V', 'X', 'L', 'C', 'D', 'M']\nindex = 0\nfor ch in n if len(n) < 4 else n[:3]:\n index += 2\n if int(ch):\n roman_dict = {0: '*', 1: f'{roman_lst[index - 1]}', 2: f'{roman_lst[index - 1] * 2}', 3: f'{roman_lst[index - 1] * 3}', 4: f'{roman_lst[index - ... | <|body_start_0|>
n = str(n)[::-1]
st = ''
roman_lst = ['', 'I', 'V', 'X', 'L', 'C', 'D', 'M']
index = 0
for ch in n if len(n) < 4 else n[:3]:
index += 2
if int(ch):
roman_dict = {0: '*', 1: f'{roman_lst[index - 1]}', 2: f'{roman_lst[index -... | RomanNumerals | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RomanNumerals:
def to_roman(n):
"""Функция переводит число в римское Принцип работы: Получаем число, его преобразуем в строку и переворачиваем, далее идем по строке и отталкиваясь от индекса в строке создаем соответсвенный словарь из римских цифр. Первая цифра в строке это единицы, потом... | stack_v2_sparse_classes_75kplus_train_073457 | 4,897 | no_license | [
{
"docstring": "Функция переводит число в римское Принцип работы: Получаем число, его преобразуем в строку и переворачиваем, далее идем по строке и отталкиваясь от индекса в строке создаем соответсвенный словарь из римских цифр. Первая цифра в строке это единицы, потом десятки, сотни и тысяча. Для каждого измер... | 2 | stack_v2_sparse_classes_30k_train_033728 | Implement the Python class `RomanNumerals` described below.
Class description:
Implement the RomanNumerals class.
Method signatures and docstrings:
- def to_roman(n): Функция переводит число в римское Принцип работы: Получаем число, его преобразуем в строку и переворачиваем, далее идем по строке и отталкиваясь от инд... | Implement the Python class `RomanNumerals` described below.
Class description:
Implement the RomanNumerals class.
Method signatures and docstrings:
- def to_roman(n): Функция переводит число в римское Принцип работы: Получаем число, его преобразуем в строку и переворачиваем, далее идем по строке и отталкиваясь от инд... | 8f676985ca7ee9dc592778f5958352f183ce8029 | <|skeleton|>
class RomanNumerals:
def to_roman(n):
"""Функция переводит число в римское Принцип работы: Получаем число, его преобразуем в строку и переворачиваем, далее идем по строке и отталкиваясь от индекса в строке создаем соответсвенный словарь из римских цифр. Первая цифра в строке это единицы, потом... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class RomanNumerals:
def to_roman(n):
"""Функция переводит число в римское Принцип работы: Получаем число, его преобразуем в строку и переворачиваем, далее идем по строке и отталкиваясь от индекса в строке создаем соответсвенный словарь из римских цифр. Первая цифра в строке это единицы, потом десятки, сотн... | the_stack_v2_python_sparse | 4/Roman Numerals Helper 4kyu.py | VIVERA83/Codewars | train | 0 | |
919cc4e5efa5b8fac7ea50e9b2e720279c093c3b | [
"home_dir = os.path.expanduser('~')\ncredential_dir = os.path.join(home_dir, '.credentials')\nif not os.path.exists(credential_dir):\n os.makedirs(credential_dir)\ncredential_path = os.path.join(credential_dir, GmailApiUsage.APPLICATION_NAME + '.json')\nstore = Storage(credential_path)\ncredentials = store.get()... | <|body_start_0|>
home_dir = os.path.expanduser('~')
credential_dir = os.path.join(home_dir, '.credentials')
if not os.path.exists(credential_dir):
os.makedirs(credential_dir)
credential_path = os.path.join(credential_dir, GmailApiUsage.APPLICATION_NAME + '.json')
stor... | GmailApiUsage | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GmailApiUsage:
def get_credentials():
"""Gets valid user credentials from storage. If nothing has been stored, or if the stored credentials are invalid, the OAuth2 flow is completed to obtain the new credentials. Returns: Credentials, the obtained credential."""
<|body_0|>
d... | stack_v2_sparse_classes_75kplus_train_073458 | 3,464 | permissive | [
{
"docstring": "Gets valid user credentials from storage. If nothing has been stored, or if the stored credentials are invalid, the OAuth2 flow is completed to obtain the new credentials. Returns: Credentials, the obtained credential.",
"name": "get_credentials",
"signature": "def get_credentials()"
}... | 4 | stack_v2_sparse_classes_30k_train_044245 | Implement the Python class `GmailApiUsage` described below.
Class description:
Implement the GmailApiUsage class.
Method signatures and docstrings:
- def get_credentials(): Gets valid user credentials from storage. If nothing has been stored, or if the stored credentials are invalid, the OAuth2 flow is completed to o... | Implement the Python class `GmailApiUsage` described below.
Class description:
Implement the GmailApiUsage class.
Method signatures and docstrings:
- def get_credentials(): Gets valid user credentials from storage. If nothing has been stored, or if the stored credentials are invalid, the OAuth2 flow is completed to o... | f714ed8172aa290d3f13ff8b7f09f888a5b33640 | <|skeleton|>
class GmailApiUsage:
def get_credentials():
"""Gets valid user credentials from storage. If nothing has been stored, or if the stored credentials are invalid, the OAuth2 flow is completed to obtain the new credentials. Returns: Credentials, the obtained credential."""
<|body_0|>
d... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class GmailApiUsage:
def get_credentials():
"""Gets valid user credentials from storage. If nothing has been stored, or if the stored credentials are invalid, the OAuth2 flow is completed to obtain the new credentials. Returns: Credentials, the obtained credential."""
home_dir = os.path.expanduser('... | the_stack_v2_python_sparse | incubation-python/relative_scheduler/modules/gmailapiusage.py | yk0242/incubation | train | 1 | |
39bb95010a9bc20217a54ffe3de7f367839d3b19 | [
"if not validate_contract_document(self.request, 'add'):\n return\ndocument = upload_file(self.request)\nself.context.documents.append(document)\nif save_auction(self.request):\n self.LOGGER.info('Created auction contract document {}'.format(document.id), extra=context_unpack(self.request, {'MESSAGE_ID': 'auc... | <|body_start_0|>
if not validate_contract_document(self.request, 'add'):
return
document = upload_file(self.request)
self.context.documents.append(document)
if save_auction(self.request):
self.LOGGER.info('Created auction contract document {}'.format(document.id),... | BaseAuctionAwardContractDocumentResource | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BaseAuctionAwardContractDocumentResource:
def collection_post(self):
"""Auction Contract Prolongation Document Upload"""
<|body_0|>
def get(self):
"""Auction Contract Document Read"""
<|body_1|>
def collection_get(self):
"""Auction Contract Prolo... | stack_v2_sparse_classes_75kplus_train_073459 | 4,208 | permissive | [
{
"docstring": "Auction Contract Prolongation Document Upload",
"name": "collection_post",
"signature": "def collection_post(self)"
},
{
"docstring": "Auction Contract Document Read",
"name": "get",
"signature": "def get(self)"
},
{
"docstring": "Auction Contract Prolongation Doc... | 4 | null | Implement the Python class `BaseAuctionAwardContractDocumentResource` described below.
Class description:
Implement the BaseAuctionAwardContractDocumentResource class.
Method signatures and docstrings:
- def collection_post(self): Auction Contract Prolongation Document Upload
- def get(self): Auction Contract Documen... | Implement the Python class `BaseAuctionAwardContractDocumentResource` described below.
Class description:
Implement the BaseAuctionAwardContractDocumentResource class.
Method signatures and docstrings:
- def collection_post(self): Auction Contract Prolongation Document Upload
- def get(self): Auction Contract Documen... | b4ed171f990e2b27b2547160df7d5ac968a1c477 | <|skeleton|>
class BaseAuctionAwardContractDocumentResource:
def collection_post(self):
"""Auction Contract Prolongation Document Upload"""
<|body_0|>
def get(self):
"""Auction Contract Document Read"""
<|body_1|>
def collection_get(self):
"""Auction Contract Prolo... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class BaseAuctionAwardContractDocumentResource:
def collection_post(self):
"""Auction Contract Prolongation Document Upload"""
if not validate_contract_document(self.request, 'add'):
return
document = upload_file(self.request)
self.context.documents.append(document)
... | the_stack_v2_python_sparse | openprocurement/auctions/core/plugins/contracting/v3/views/prolongation_document.py | openprocurement/openprocurement.auctions.core | train | 2 | |
818c4333209496ccd5b47f9f8ccb3b6d6dbcdc0d | [
"super().__init__(logger)\nself.logger = logger\nself.filename = filename\nself.load_data()",
"fh = FileHandler(self.logger, self.filename)\nfor entry in fh.get('entries'):\n self.add(key=entry.get('encoding'), value=entry.get('modality'))"
] | <|body_start_0|>
super().__init__(logger)
self.logger = logger
self.filename = filename
self.load_data()
<|end_body_0|>
<|body_start_1|>
fh = FileHandler(self.logger, self.filename)
for entry in fh.get('entries'):
self.add(key=entry.get('encoding'), value=ent... | Encoding format to modality mappings class. | Encodings | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Encodings:
"""Encoding format to modality mappings class."""
def __init__(self, logger, filename):
"""Initialize the Encodings object. Parameters: logger (aida.Logger) filename (str)"""
<|body_0|>
def load_data(self):
"""Reads the file containing the mappings int... | stack_v2_sparse_classes_75kplus_train_073460 | 1,050 | no_license | [
{
"docstring": "Initialize the Encodings object. Parameters: logger (aida.Logger) filename (str)",
"name": "__init__",
"signature": "def __init__(self, logger, filename)"
},
{
"docstring": "Reads the file containing the mappings into Encodings.",
"name": "load_data",
"signature": "def lo... | 2 | null | Implement the Python class `Encodings` described below.
Class description:
Encoding format to modality mappings class.
Method signatures and docstrings:
- def __init__(self, logger, filename): Initialize the Encodings object. Parameters: logger (aida.Logger) filename (str)
- def load_data(self): Reads the file contai... | Implement the Python class `Encodings` described below.
Class description:
Encoding format to modality mappings class.
Method signatures and docstrings:
- def __init__(self, logger, filename): Initialize the Encodings object. Parameters: logger (aida.Logger) filename (str)
- def load_data(self): Reads the file contai... | a0b379ba0e78e8e5eceeda465f75bba5c288aea4 | <|skeleton|>
class Encodings:
"""Encoding format to modality mappings class."""
def __init__(self, logger, filename):
"""Initialize the Encodings object. Parameters: logger (aida.Logger) filename (str)"""
<|body_0|>
def load_data(self):
"""Reads the file containing the mappings int... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Encodings:
"""Encoding format to modality mappings class."""
def __init__(self, logger, filename):
"""Initialize the Encodings object. Parameters: logger (aida.Logger) filename (str)"""
super().__init__(logger)
self.logger = logger
self.filename = filename
self.loa... | the_stack_v2_python_sparse | python/aida/encodings.py | shahraj81/aida | train | 8 |
28f1c2035d5bd40880fc34bf9ced71900512d0f4 | [
"filterInputValue = request.GET.get('filterInputValue', '')\nfilterDbType = request.GET.get('filterDbType[]', '')\nfilterDbType = json.loads(filterDbType) if len(filterDbType) > 2 else None\nobj = DataSourceConfig.objects.filter()\nif filterInputValue:\n obj = obj.filter(host__contains=filterInputValue)\nif filt... | <|body_start_0|>
filterInputValue = request.GET.get('filterInputValue', '')
filterDbType = request.GET.get('filterDbType[]', '')
filterDbType = json.loads(filterDbType) if len(filterDbType) > 2 else None
obj = DataSourceConfig.objects.filter()
if filterInputValue:
obj... | DataSourceConfigList | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DataSourceConfigList:
def get(self, request, *args, **kwargs):
"""数据源列表"""
<|body_0|>
def put(self, request, *args, **kwargs):
"""编辑数据源"""
<|body_1|>
def post(self, request, *args, **kwargs):
"""创建数据源"""
<|body_2|>
def delete(self, r... | stack_v2_sparse_classes_75kplus_train_073461 | 9,325 | no_license | [
{
"docstring": "数据源列表",
"name": "get",
"signature": "def get(self, request, *args, **kwargs)"
},
{
"docstring": "编辑数据源",
"name": "put",
"signature": "def put(self, request, *args, **kwargs)"
},
{
"docstring": "创建数据源",
"name": "post",
"signature": "def post(self, request, ... | 4 | stack_v2_sparse_classes_30k_train_032208 | Implement the Python class `DataSourceConfigList` described below.
Class description:
Implement the DataSourceConfigList class.
Method signatures and docstrings:
- def get(self, request, *args, **kwargs): 数据源列表
- def put(self, request, *args, **kwargs): 编辑数据源
- def post(self, request, *args, **kwargs): 创建数据源
- def de... | Implement the Python class `DataSourceConfigList` described below.
Class description:
Implement the DataSourceConfigList class.
Method signatures and docstrings:
- def get(self, request, *args, **kwargs): 数据源列表
- def put(self, request, *args, **kwargs): 编辑数据源
- def post(self, request, *args, **kwargs): 创建数据源
- def de... | f2523d6e51cde1b53ac6f453f8066b4b90c523b9 | <|skeleton|>
class DataSourceConfigList:
def get(self, request, *args, **kwargs):
"""数据源列表"""
<|body_0|>
def put(self, request, *args, **kwargs):
"""编辑数据源"""
<|body_1|>
def post(self, request, *args, **kwargs):
"""创建数据源"""
<|body_2|>
def delete(self, r... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DataSourceConfigList:
def get(self, request, *args, **kwargs):
"""数据源列表"""
filterInputValue = request.GET.get('filterInputValue', '')
filterDbType = request.GET.get('filterDbType[]', '')
filterDbType = json.loads(filterDbType) if len(filterDbType) > 2 else None
obj = Da... | the_stack_v2_python_sparse | api/db/rest/dataSourceConfig.py | zhuzhanhao1/backend | train | 0 | |
2f3a43ab7610f3425b5a914020cd5e9b7bb41dd5 | [
"ContextLemmatizer.__init__(self, context_to_lemmatize, backoff)\nself.include = include\nself._context_to_tag = context_to_lemmatize if context_to_lemmatize else {}",
"from cltk.tag.pos import POSTag\ntagger = POSTag('latin')\ntokens = ' '.join(tokens)\ntags = tagger.tag_ngram_123_backoff(tokens)\ntags = [tag[1]... | <|body_start_0|>
ContextLemmatizer.__init__(self, context_to_lemmatize, backoff)
self.include = include
self._context_to_tag = context_to_lemmatize if context_to_lemmatize else {}
<|end_body_0|>
<|body_start_1|>
from cltk.tag.pos import POSTag
tagger = POSTag('latin')
to... | Lemmatizer that combines context with POS-tagging based on training data. Subclasses define context. The code for _train closely follows ContextTagger in https://github.com/nltk/nltk/blob/develop/nltk/tag/sequential.py This lemmatizer is included here as proof of concept that lemma disambiguation can be made based on t... | ContextPOSLemmatizer | [
"MIT",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ContextPOSLemmatizer:
"""Lemmatizer that combines context with POS-tagging based on training data. Subclasses define context. The code for _train closely follows ContextTagger in https://github.com/nltk/nltk/blob/develop/nltk/tag/sequential.py This lemmatizer is included here as proof of concept ... | stack_v2_sparse_classes_75kplus_train_073462 | 23,254 | permissive | [
{
"docstring": "Setup ContextPOSLemmatizer(). :param context_to_lemmatize: List of tuples of the form (TOKEN, LEMMA); this should be 'gold standard' data that can be used to train on a given context, e.g. unigrams, bigrams, etc. :param include: List of tokens to include, all other tokens return None from choose... | 4 | stack_v2_sparse_classes_30k_train_049786 | Implement the Python class `ContextPOSLemmatizer` described below.
Class description:
Lemmatizer that combines context with POS-tagging based on training data. Subclasses define context. The code for _train closely follows ContextTagger in https://github.com/nltk/nltk/blob/develop/nltk/tag/sequential.py This lemmatize... | Implement the Python class `ContextPOSLemmatizer` described below.
Class description:
Lemmatizer that combines context with POS-tagging based on training data. Subclasses define context. The code for _train closely follows ContextTagger in https://github.com/nltk/nltk/blob/develop/nltk/tag/sequential.py This lemmatize... | 085420eaed7055fbcb311714eebb67861fd1b241 | <|skeleton|>
class ContextPOSLemmatizer:
"""Lemmatizer that combines context with POS-tagging based on training data. Subclasses define context. The code for _train closely follows ContextTagger in https://github.com/nltk/nltk/blob/develop/nltk/tag/sequential.py This lemmatizer is included here as proof of concept ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ContextPOSLemmatizer:
"""Lemmatizer that combines context with POS-tagging based on training data. Subclasses define context. The code for _train closely follows ContextTagger in https://github.com/nltk/nltk/blob/develop/nltk/tag/sequential.py This lemmatizer is included here as proof of concept that lemma di... | the_stack_v2_python_sparse | cltk/lemmatize/latin/backoff.py | jerryfrancis-97/cltk | train | 1 |
8e2da36d495a27d8af5b87156ad02433e3de00c4 | [
"nums = list(map(int, s))\nn = len(nums)\ndp = [[0] * (n + 1) for _ in range(k + 1)]\ndp[0][0] = 1\nfor c in range(1, k + 1):\n dpSum = [0] * (n + 1)\n for i in range(1, n + 1):\n dpSum[i] = dpSum[i - 1] + (dp[c - 1][i - 1] if IS_PRIME[nums[i - 1]] else 0)\n dpSum[i] %= MOD\n for i in range(1... | <|body_start_0|>
nums = list(map(int, s))
n = len(nums)
dp = [[0] * (n + 1) for _ in range(k + 1)]
dp[0][0] = 1
for c in range(1, k + 1):
dpSum = [0] * (n + 1)
for i in range(1, n + 1):
dpSum[i] = dpSum[i - 1] + (dp[c - 1][i - 1] if IS_PRIM... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def beautifulPartitions(self, s: str, k: int, minLength: int) -> int:
"""dp[count][index]表示前index个字符分成count个子串的方案数 维护一维前缀和数组"""
<|body_0|>
def beautifulPartitions2(self, s: str, k: int, minLength: int) -> int:
"""维护二维前缀和数组"""
<|body_1|>
<|end_skele... | stack_v2_sparse_classes_75kplus_train_073463 | 3,061 | no_license | [
{
"docstring": "dp[count][index]表示前index个字符分成count个子串的方案数 维护一维前缀和数组",
"name": "beautifulPartitions",
"signature": "def beautifulPartitions(self, s: str, k: int, minLength: int) -> int"
},
{
"docstring": "维护二维前缀和数组",
"name": "beautifulPartitions2",
"signature": "def beautifulPartitions2(s... | 2 | stack_v2_sparse_classes_30k_train_030149 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def beautifulPartitions(self, s: str, k: int, minLength: int) -> int: dp[count][index]表示前index个字符分成count个子串的方案数 维护一维前缀和数组
- def beautifulPartitions2(self, s: str, k: int, minLeng... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def beautifulPartitions(self, s: str, k: int, minLength: int) -> int: dp[count][index]表示前index个字符分成count个子串的方案数 维护一维前缀和数组
- def beautifulPartitions2(self, s: str, k: int, minLeng... | 7e79e26bb8f641868561b186e34c1127ed63c9e0 | <|skeleton|>
class Solution:
def beautifulPartitions(self, s: str, k: int, minLength: int) -> int:
"""dp[count][index]表示前index个字符分成count个子串的方案数 维护一维前缀和数组"""
<|body_0|>
def beautifulPartitions2(self, s: str, k: int, minLength: int) -> int:
"""维护二维前缀和数组"""
<|body_1|>
<|end_skele... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def beautifulPartitions(self, s: str, k: int, minLength: int) -> int:
"""dp[count][index]表示前index个字符分成count个子串的方案数 维护一维前缀和数组"""
nums = list(map(int, s))
n = len(nums)
dp = [[0] * (n + 1) for _ in range(k + 1)]
dp[0][0] = 1
for c in range(1, k + 1):
... | the_stack_v2_python_sparse | 11_动态规划/dp优化/前缀和优化/6244. 完美分割的方案数-index+remain的前缀和优化.py | 981377660LMT/algorithm-study | train | 225 | |
a9c58b23c11564becd9e282401af5923ff01a27b | [
"l = 0\nnode = head\nwhile node:\n node = node.next\n l += 1\n\ndef reverse(node):\n pre = None\n while node:\n pre, node.next, node = (node, pre, node.next)\n return pre\ni = l // 2\nnode = head\nwhile i > 0:\n node = node.next\n i -= 1\nnode = reverse(node)\nwhile node:\n if node.va... | <|body_start_0|>
l = 0
node = head
while node:
node = node.next
l += 1
def reverse(node):
pre = None
while node:
pre, node.next, node = (node, pre, node.next)
return pre
i = l // 2
node = head
... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def isPalindrome(self, head: Optional[ListNode]) -> bool:
"""2022-08-23 Runtime: 947 ms, faster than 78.82% Memory Usage: 39 MB, less than 76.71% The number of nodes in the list is in the range [1, 10^5]. 0 <= Node.val <= 9"""
<|body_0|>
def isPalindrome2(self, hea... | stack_v2_sparse_classes_75kplus_train_073464 | 3,203 | permissive | [
{
"docstring": "2022-08-23 Runtime: 947 ms, faster than 78.82% Memory Usage: 39 MB, less than 76.71% The number of nodes in the list is in the range [1, 10^5]. 0 <= Node.val <= 9",
"name": "isPalindrome",
"signature": "def isPalindrome(self, head: Optional[ListNode]) -> bool"
},
{
"docstring": "... | 2 | stack_v2_sparse_classes_30k_train_043236 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isPalindrome(self, head: Optional[ListNode]) -> bool: 2022-08-23 Runtime: 947 ms, faster than 78.82% Memory Usage: 39 MB, less than 76.71% The number of nodes in the list is ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isPalindrome(self, head: Optional[ListNode]) -> bool: 2022-08-23 Runtime: 947 ms, faster than 78.82% Memory Usage: 39 MB, less than 76.71% The number of nodes in the list is ... | 4dd1e54d8d08f7e6590bc76abd08ecaacaf775e5 | <|skeleton|>
class Solution:
def isPalindrome(self, head: Optional[ListNode]) -> bool:
"""2022-08-23 Runtime: 947 ms, faster than 78.82% Memory Usage: 39 MB, less than 76.71% The number of nodes in the list is in the range [1, 10^5]. 0 <= Node.val <= 9"""
<|body_0|>
def isPalindrome2(self, hea... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def isPalindrome(self, head: Optional[ListNode]) -> bool:
"""2022-08-23 Runtime: 947 ms, faster than 78.82% Memory Usage: 39 MB, less than 76.71% The number of nodes in the list is in the range [1, 10^5]. 0 <= Node.val <= 9"""
l = 0
node = head
while node:
... | the_stack_v2_python_sparse | src/234-PalindromeLinkedList.py | Jiezhi/myleetcode | train | 1 | |
05668b57bdb7acb5d38f6d265e74ea38e2cb1b71 | [
"try:\n plugin = module.Plugin\nexcept AttributeError:\n return False\ncommand = data[invocation_length:]\ntry:\n result = plugin.run(self, command)\nexcept TypeError:\n result = plugin().run(self, command)\nplugin_ran = True\nreturn (plugin_ran, result)",
"if plugin_list:\n plugin_ran = False\n ... | <|body_start_0|>
try:
plugin = module.Plugin
except AttributeError:
return False
command = data[invocation_length:]
try:
result = plugin.run(self, command)
except TypeError:
result = plugin().run(self, command)
plugin_ran = ... | PluginRunner | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PluginRunner:
def run_plugin(self, module, data, invocation_length):
"""Run the plugin in the given module. :param self: :param module: :param data: :param invocation_length: :return:"""
<|body_0|>
def process_plugins(self, plugin_list, data, help_mode_on=False):
"""... | stack_v2_sparse_classes_75kplus_train_073465 | 4,870 | no_license | [
{
"docstring": "Run the plugin in the given module. :param self: :param module: :param data: :param invocation_length: :return:",
"name": "run_plugin",
"signature": "def run_plugin(self, module, data, invocation_length)"
},
{
"docstring": "Process plugins to see if the data should be intercepted... | 2 | stack_v2_sparse_classes_30k_train_025715 | Implement the Python class `PluginRunner` described below.
Class description:
Implement the PluginRunner class.
Method signatures and docstrings:
- def run_plugin(self, module, data, invocation_length): Run the plugin in the given module. :param self: :param module: :param data: :param invocation_length: :return:
- d... | Implement the Python class `PluginRunner` described below.
Class description:
Implement the PluginRunner class.
Method signatures and docstrings:
- def run_plugin(self, module, data, invocation_length): Run the plugin in the given module. :param self: :param module: :param data: :param invocation_length: :return:
- d... | fb0aa92ea05dc05416a0a2cf3cc7a698b25f1d38 | <|skeleton|>
class PluginRunner:
def run_plugin(self, module, data, invocation_length):
"""Run the plugin in the given module. :param self: :param module: :param data: :param invocation_length: :return:"""
<|body_0|>
def process_plugins(self, plugin_list, data, help_mode_on=False):
"""... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PluginRunner:
def run_plugin(self, module, data, invocation_length):
"""Run the plugin in the given module. :param self: :param module: :param data: :param invocation_length: :return:"""
try:
plugin = module.Plugin
except AttributeError:
return False
com... | the_stack_v2_python_sparse | common.py | RattleyCooper/Oyster | train | 2 | |
4419dea815d26a4e279ad6cebfd09bcb6f76da3d | [
"super(Reinforce, self).__init__()\nself.num_actions = num_actions\nself.hidden_size = 100\nself.dense1 = tf.keras.layers.Dense(self.hidden_size, activation='relu')\nself.dense2 = tf.keras.layers.Dense(self.num_actions, activation='softmax')\nself.optimizer = tf.keras.optimizers.Adam(learning_rate=0.001)",
"dense... | <|body_start_0|>
super(Reinforce, self).__init__()
self.num_actions = num_actions
self.hidden_size = 100
self.dense1 = tf.keras.layers.Dense(self.hidden_size, activation='relu')
self.dense2 = tf.keras.layers.Dense(self.num_actions, activation='softmax')
self.optimizer = t... | Reinforce | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Reinforce:
def __init__(self, state_size, num_actions):
"""The Reinforce class that inherits from tf.keras.Model The forward pass calculates the policy for the agent given a batch of states. :param state_size: number of parameters that define the state. You don't necessarily have to use ... | stack_v2_sparse_classes_75kplus_train_073466 | 3,018 | no_license | [
{
"docstring": "The Reinforce class that inherits from tf.keras.Model The forward pass calculates the policy for the agent given a batch of states. :param state_size: number of parameters that define the state. You don't necessarily have to use this, but it can be used as the input size for your first dense lay... | 3 | stack_v2_sparse_classes_30k_train_019976 | Implement the Python class `Reinforce` described below.
Class description:
Implement the Reinforce class.
Method signatures and docstrings:
- def __init__(self, state_size, num_actions): The Reinforce class that inherits from tf.keras.Model The forward pass calculates the policy for the agent given a batch of states.... | Implement the Python class `Reinforce` described below.
Class description:
Implement the Reinforce class.
Method signatures and docstrings:
- def __init__(self, state_size, num_actions): The Reinforce class that inherits from tf.keras.Model The forward pass calculates the policy for the agent given a batch of states.... | 8f0ed6982ae6aba938cbf39af0e2a6259478db1c | <|skeleton|>
class Reinforce:
def __init__(self, state_size, num_actions):
"""The Reinforce class that inherits from tf.keras.Model The forward pass calculates the policy for the agent given a batch of states. :param state_size: number of parameters that define the state. You don't necessarily have to use ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Reinforce:
def __init__(self, state_size, num_actions):
"""The Reinforce class that inherits from tf.keras.Model The forward pass calculates the policy for the agent given a batch of states. :param state_size: number of parameters that define the state. You don't necessarily have to use this, but it c... | the_stack_v2_python_sparse | hw6_REINFORCE/reinforce.py | YingSun0314/DeepLearningProjects | train | 0 | |
07d47f79f36d6e5240a735aa454c163d4648f02d | [
"AbstractCommModule.__init__(self, sim_env, MessageClass)\nself.physical_lay = StdPhysicalLayer(sim_env)\nself.datalink_lay = StdDatalinkLayer(sim_env)\nself.transp_lay = SegmentTransportLayer(sim_env, MessageClass)\nself.datalink_lay.physical_lay = self.physical_lay\nself.transp_lay.datalink_lay = self.datalink_la... | <|body_start_0|>
AbstractCommModule.__init__(self, sim_env, MessageClass)
self.physical_lay = StdPhysicalLayer(sim_env)
self.datalink_lay = StdDatalinkLayer(sim_env)
self.transp_lay = SegmentTransportLayer(sim_env, MessageClass)
self.datalink_lay.physical_lay = self.physical_lay
... | This class implements a communication module, that simply forwards the messages to the next layer | SegmentCommModule | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SegmentCommModule:
"""This class implements a communication module, that simply forwards the messages to the next layer"""
def __init__(self, sim_env, MessageClass):
"""Constructor Input: sim_env simpy.Environment environment of this component MessageClass AbstractBusMessage class th... | stack_v2_sparse_classes_75kplus_train_073467 | 3,492 | permissive | [
{
"docstring": "Constructor Input: sim_env simpy.Environment environment of this component MessageClass AbstractBusMessage class that is used for sending and receiving Output: -",
"name": "__init__",
"signature": "def __init__(self, sim_env, MessageClass)"
},
{
"docstring": "sets the initial set... | 4 | stack_v2_sparse_classes_30k_train_038691 | Implement the Python class `SegmentCommModule` described below.
Class description:
This class implements a communication module, that simply forwards the messages to the next layer
Method signatures and docstrings:
- def __init__(self, sim_env, MessageClass): Constructor Input: sim_env simpy.Environment environment o... | Implement the Python class `SegmentCommModule` described below.
Class description:
This class implements a communication module, that simply forwards the messages to the next layer
Method signatures and docstrings:
- def __init__(self, sim_env, MessageClass): Constructor Input: sim_env simpy.Environment environment o... | b2e395611e9b5111aeda7ab128f3486354bbbf0d | <|skeleton|>
class SegmentCommModule:
"""This class implements a communication module, that simply forwards the messages to the next layer"""
def __init__(self, sim_env, MessageClass):
"""Constructor Input: sim_env simpy.Environment environment of this component MessageClass AbstractBusMessage class th... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SegmentCommModule:
"""This class implements a communication module, that simply forwards the messages to the next layer"""
def __init__(self, sim_env, MessageClass):
"""Constructor Input: sim_env simpy.Environment environment of this component MessageClass AbstractBusMessage class that is used fo... | the_stack_v2_python_sparse | ECUSimulation/components/base/ecu/software/impl_comm_module_segment.py | PhilippMundhenk/IVNS | train | 15 |
e9af86f6c1091cc9e7270711bba8db7bc0151066 | [
"msg = '\\n\\nRunning SMA strategy | SMA1 = %d & SMA2 = %d' % (SMA1, SMA2)\nmsg += '\\nfixed costs %.2f | ' % self.ftc\nmsg += 'proportional costs %.4f' % self.ptc\nprint(msg)\nprint('=' * 55)\nself.position = 0\nself.amount = self._amount\nself.data['SMA1'] = self.data['price'].rolling(SMA1).mean()\nself.data['SMA... | <|body_start_0|>
msg = '\n\nRunning SMA strategy | SMA1 = %d & SMA2 = %d' % (SMA1, SMA2)
msg += '\nfixed costs %.2f | ' % self.ftc
msg += 'proportional costs %.4f' % self.ptc
print(msg)
print('=' * 55)
self.position = 0
self.amount = self._amount
self.data... | BacktestLongOnly | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BacktestLongOnly:
def run_sma_strategy(self, SMA1, SMA2):
"""Backtesting a SMA-based strategy. Parameters ========== SMA1, SMA2: int shorter and longer term simple moving average (in days)"""
<|body_0|>
def run_momentum_strategy(self, momentum):
"""Backtesting a mome... | stack_v2_sparse_classes_75kplus_train_073468 | 4,494 | no_license | [
{
"docstring": "Backtesting a SMA-based strategy. Parameters ========== SMA1, SMA2: int shorter and longer term simple moving average (in days)",
"name": "run_sma_strategy",
"signature": "def run_sma_strategy(self, SMA1, SMA2)"
},
{
"docstring": "Backtesting a momentum-based strategy. Parameters... | 3 | stack_v2_sparse_classes_30k_train_054732 | Implement the Python class `BacktestLongOnly` described below.
Class description:
Implement the BacktestLongOnly class.
Method signatures and docstrings:
- def run_sma_strategy(self, SMA1, SMA2): Backtesting a SMA-based strategy. Parameters ========== SMA1, SMA2: int shorter and longer term simple moving average (in ... | Implement the Python class `BacktestLongOnly` described below.
Class description:
Implement the BacktestLongOnly class.
Method signatures and docstrings:
- def run_sma_strategy(self, SMA1, SMA2): Backtesting a SMA-based strategy. Parameters ========== SMA1, SMA2: int shorter and longer term simple moving average (in ... | bfc8baa153aec70caa8981b8e9215bb0be7f3163 | <|skeleton|>
class BacktestLongOnly:
def run_sma_strategy(self, SMA1, SMA2):
"""Backtesting a SMA-based strategy. Parameters ========== SMA1, SMA2: int shorter and longer term simple moving average (in days)"""
<|body_0|>
def run_momentum_strategy(self, momentum):
"""Backtesting a mome... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class BacktestLongOnly:
def run_sma_strategy(self, SMA1, SMA2):
"""Backtesting a SMA-based strategy. Parameters ========== SMA1, SMA2: int shorter and longer term simple moving average (in days)"""
msg = '\n\nRunning SMA strategy | SMA1 = %d & SMA2 = %d' % (SMA1, SMA2)
msg += '\nfixed costs ... | the_stack_v2_python_sparse | code/pyquants/pyalgo/ch06/BacktestLongOnly.py | godknowspe/NoahsArk | train | 1 | |
10588a2066278dd569a97052c4e08cc9e91967af | [
"if head == None:\n return head\nif head.next == None:\n return head\nprev = head\ncurr = head.next\nprev.next = None\nwhile curr.next != None:\n next = curr.next\n curr.next = prev\n prev = curr\n curr = next\ncurr.next = prev\nreturn curr",
"if head == None:\n return\nif head.next == None:\... | <|body_start_0|>
if head == None:
return head
if head.next == None:
return head
prev = head
curr = head.next
prev.next = None
while curr.next != None:
next = curr.next
curr.next = prev
prev = curr
cur... | Solution format for LeetCode | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
"""Solution format for LeetCode"""
def reverseList(self, head):
""":type head: ListNode :rtype: ListNode :method calls: Time O(n) Space O(1)"""
<|body_0|>
def reverseList_recur(self, head):
""":type head: ListNode :rtype: ListNode :method calls: reverse... | stack_v2_sparse_classes_75kplus_train_073469 | 5,212 | no_license | [
{
"docstring": ":type head: ListNode :rtype: ListNode :method calls: Time O(n) Space O(1)",
"name": "reverseList",
"signature": "def reverseList(self, head)"
},
{
"docstring": ":type head: ListNode :rtype: ListNode :method calls: reverseList Recursion on self - editing the .next values Time O(n)... | 4 | null | Implement the Python class `Solution` described below.
Class description:
Solution format for LeetCode
Method signatures and docstrings:
- def reverseList(self, head): :type head: ListNode :rtype: ListNode :method calls: Time O(n) Space O(1)
- def reverseList_recur(self, head): :type head: ListNode :rtype: ListNode :... | Implement the Python class `Solution` described below.
Class description:
Solution format for LeetCode
Method signatures and docstrings:
- def reverseList(self, head): :type head: ListNode :rtype: ListNode :method calls: Time O(n) Space O(1)
- def reverseList_recur(self, head): :type head: ListNode :rtype: ListNode :... | d91f60431aa7767d1a854e0e27a26023fc8ec45c | <|skeleton|>
class Solution:
"""Solution format for LeetCode"""
def reverseList(self, head):
""":type head: ListNode :rtype: ListNode :method calls: Time O(n) Space O(1)"""
<|body_0|>
def reverseList_recur(self, head):
""":type head: ListNode :rtype: ListNode :method calls: reverse... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
"""Solution format for LeetCode"""
def reverseList(self, head):
""":type head: ListNode :rtype: ListNode :method calls: Time O(n) Space O(1)"""
if head == None:
return head
if head.next == None:
return head
prev = head
curr = head.... | the_stack_v2_python_sparse | Algorithms_LinkedLists/Code/206_ReverseLinkedList/v1.py | AKHeit/LeetCode | train | 0 |
b80897f57926e3eadcbd4652303aa9a7af84b1df | [
"RlAgentHierarchical.__init__(self, rlEnvironment, gpuId, hasHistory, nSamples)\nself.level = 5\nself.InitializeCaffe(caffeDirPostfix)",
"action = [prevDesc.image, copy(imageCoord)]\nT = copy(prevDesc.T)\nT[0:3, 3] = baseCoord\ndesc = HandDescriptor(T)\nreturn (action, desc)",
"idx1 = int(self.nSamples / 3)\nid... | <|body_start_0|>
RlAgentHierarchical.__init__(self, rlEnvironment, gpuId, hasHistory, nSamples)
self.level = 5
self.InitializeCaffe(caffeDirPostfix)
<|end_body_0|>
<|body_start_1|>
action = [prevDesc.image, copy(imageCoord)]
T = copy(prevDesc.T)
T[0:3, 3] = baseCoord
... | RlAgentLevel5 | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RlAgentLevel5:
def __init__(self, rlEnvironment, gpuId, hasHistory, nSamples, caffeDirPostfix=''):
"""Initializes agent in the given environment."""
<|body_0|>
def ComposeAction(self, prevDesc, baseCoord, imageCoord):
"""Creates a new action and hand descriptor objec... | stack_v2_sparse_classes_75kplus_train_073470 | 2,859 | permissive | [
{
"docstring": "Initializes agent in the given environment.",
"name": "__init__",
"signature": "def __init__(self, rlEnvironment, gpuId, hasHistory, nSamples, caffeDirPostfix='')"
},
{
"docstring": "Creates a new action and hand descriptor objects.",
"name": "ComposeAction",
"signature":... | 4 | stack_v2_sparse_classes_30k_train_034180 | Implement the Python class `RlAgentLevel5` described below.
Class description:
Implement the RlAgentLevel5 class.
Method signatures and docstrings:
- def __init__(self, rlEnvironment, gpuId, hasHistory, nSamples, caffeDirPostfix=''): Initializes agent in the given environment.
- def ComposeAction(self, prevDesc, base... | Implement the Python class `RlAgentLevel5` described below.
Class description:
Implement the RlAgentLevel5 class.
Method signatures and docstrings:
- def __init__(self, rlEnvironment, gpuId, hasHistory, nSamples, caffeDirPostfix=''): Initializes agent in the given environment.
- def ComposeAction(self, prevDesc, base... | 78a5c14f09291ae13505198e36f92f0956ccfc49 | <|skeleton|>
class RlAgentLevel5:
def __init__(self, rlEnvironment, gpuId, hasHistory, nSamples, caffeDirPostfix=''):
"""Initializes agent in the given environment."""
<|body_0|>
def ComposeAction(self, prevDesc, baseCoord, imageCoord):
"""Creates a new action and hand descriptor objec... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class RlAgentLevel5:
def __init__(self, rlEnvironment, gpuId, hasHistory, nSamples, caffeDirPostfix=''):
"""Initializes agent in the given environment."""
RlAgentHierarchical.__init__(self, rlEnvironment, gpuId, hasHistory, nSamples)
self.level = 5
self.InitializeCaffe(caffeDirPostfi... | the_stack_v2_python_sparse | python/rl_agent_level5.py | musyoku/chainer-6dof-grasping-attention-focus | train | 0 | |
e26234a67f3341844e1e1f056f8a5ca1b9d66456 | [
"question = 'Jaki jest Twoj ojczysty język?'\nmy_survey = AnonymousSurvey(question)\nmy_survey.store_response('angielski')\nself.assertIn('angielski', my_survey.responses)",
"question = 'Jaki jest Twoj ojczysty język?'\nmy_survey = AnonymousSurvey(question)\nresponses = ['angielski', 'hiszpański', 'polski']\nfor ... | <|body_start_0|>
question = 'Jaki jest Twoj ojczysty język?'
my_survey = AnonymousSurvey(question)
my_survey.store_response('angielski')
self.assertIn('angielski', my_survey.responses)
<|end_body_0|>
<|body_start_1|>
question = 'Jaki jest Twoj ojczysty język?'
my_survey ... | Testy dla klasy AnonymousSurvey. | TestAnonymousSurvey | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestAnonymousSurvey:
"""Testy dla klasy AnonymousSurvey."""
def test_store_single_response(self):
"""Sprawdzenie, czy pojedyncza odpowiedź jest prawidłowo przechowywana."""
<|body_0|>
def test_store_three_responses(self):
"""Sprawdzenie, czy trzy pojedyncze odpow... | stack_v2_sparse_classes_75kplus_train_073471 | 1,128 | no_license | [
{
"docstring": "Sprawdzenie, czy pojedyncza odpowiedź jest prawidłowo przechowywana.",
"name": "test_store_single_response",
"signature": "def test_store_single_response(self)"
},
{
"docstring": "Sprawdzenie, czy trzy pojedyncze odpowiedzi są prawidłowo przechowywane.",
"name": "test_store_t... | 2 | stack_v2_sparse_classes_30k_train_002125 | Implement the Python class `TestAnonymousSurvey` described below.
Class description:
Testy dla klasy AnonymousSurvey.
Method signatures and docstrings:
- def test_store_single_response(self): Sprawdzenie, czy pojedyncza odpowiedź jest prawidłowo przechowywana.
- def test_store_three_responses(self): Sprawdzenie, czy ... | Implement the Python class `TestAnonymousSurvey` described below.
Class description:
Testy dla klasy AnonymousSurvey.
Method signatures and docstrings:
- def test_store_single_response(self): Sprawdzenie, czy pojedyncza odpowiedź jest prawidłowo przechowywana.
- def test_store_three_responses(self): Sprawdzenie, czy ... | 969f95132822d8bd21c30403d8e0bf6aadb9914f | <|skeleton|>
class TestAnonymousSurvey:
"""Testy dla klasy AnonymousSurvey."""
def test_store_single_response(self):
"""Sprawdzenie, czy pojedyncza odpowiedź jest prawidłowo przechowywana."""
<|body_0|>
def test_store_three_responses(self):
"""Sprawdzenie, czy trzy pojedyncze odpow... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TestAnonymousSurvey:
"""Testy dla klasy AnonymousSurvey."""
def test_store_single_response(self):
"""Sprawdzenie, czy pojedyncza odpowiedź jest prawidłowo przechowywana."""
question = 'Jaki jest Twoj ojczysty język?'
my_survey = AnonymousSurvey(question)
my_survey.store_re... | the_stack_v2_python_sparse | ksiazka_zrob_to_sam/test_survey.py | Licho59/learning_python_eric_matthes_book | train | 0 |
3ad3b4cc0f1520ceff2cfa1d891f8134ed348dc5 | [
"self.current_epoch = 0\nself.current_epoch_logged_images = set()\nself.max_imgs_to_log_per_epoch = 16\nself.bbox_interval = opt.bbox_interval\nself.clearml = clearml\nself.task = None\nself.data_dict = None\nif self.clearml:\n self.task = Task.init(project_name='YOLOv5', task_name='training', tags=['YOLOv5'], o... | <|body_start_0|>
self.current_epoch = 0
self.current_epoch_logged_images = set()
self.max_imgs_to_log_per_epoch = 16
self.bbox_interval = opt.bbox_interval
self.clearml = clearml
self.task = None
self.data_dict = None
if self.clearml:
self.task... | Log training runs, datasets, models, and predictions to ClearML. This logger sends information to ClearML at app.clear.ml or to your own hosted server. By default, this information includes hyperparameters, system configuration and metrics, model metrics, code information and basic data metrics and analyses. By providi... | ClearmlLogger | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ClearmlLogger:
"""Log training runs, datasets, models, and predictions to ClearML. This logger sends information to ClearML at app.clear.ml or to your own hosted server. By default, this information includes hyperparameters, system configuration and metrics, model metrics, code information and ba... | stack_v2_sparse_classes_75kplus_train_073472 | 7,470 | permissive | [
{
"docstring": "- Initialize ClearML Task, this object will capture the experiment - Upload dataset version to ClearML Data if opt.upload_dataset is True arguments: opt (namespace) -- Commandline arguments for this run hyp (dict) -- Hyperparameters for this run",
"name": "__init__",
"signature": "def __... | 3 | stack_v2_sparse_classes_30k_train_019126 | Implement the Python class `ClearmlLogger` described below.
Class description:
Log training runs, datasets, models, and predictions to ClearML. This logger sends information to ClearML at app.clear.ml or to your own hosted server. By default, this information includes hyperparameters, system configuration and metrics,... | Implement the Python class `ClearmlLogger` described below.
Class description:
Log training runs, datasets, models, and predictions to ClearML. This logger sends information to ClearML at app.clear.ml or to your own hosted server. By default, this information includes hyperparameters, system configuration and metrics,... | 017c50ee6a0a388caca193fd5a06ba237150bd05 | <|skeleton|>
class ClearmlLogger:
"""Log training runs, datasets, models, and predictions to ClearML. This logger sends information to ClearML at app.clear.ml or to your own hosted server. By default, this information includes hyperparameters, system configuration and metrics, model metrics, code information and ba... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ClearmlLogger:
"""Log training runs, datasets, models, and predictions to ClearML. This logger sends information to ClearML at app.clear.ml or to your own hosted server. By default, this information includes hyperparameters, system configuration and metrics, model metrics, code information and basic data metr... | the_stack_v2_python_sparse | Modules/object_detection/py_nodes/yolov5_tensorrt_server/utils/loggers/clearml/clearml_utils.py | amov-lab/Prometheus | train | 2,129 |
8e51b0b6bfae44443262781e402c34f42b9914d2 | [
"template = db.Template.find_one(template_name=template_name)\nif not template:\n return self.make_response('No such template found', HTTP.NOT_FOUND)\nreturn self.make_response({'template': template})",
"self.reqparse.add_argument('template', type=str, required=True)\nargs = self.reqparse.parse_args()\ntemplat... | <|body_start_0|>
template = db.Template.find_one(template_name=template_name)
if not template:
return self.make_response('No such template found', HTTP.NOT_FOUND)
return self.make_response({'template': template})
<|end_body_0|>
<|body_start_1|>
self.reqparse.add_argument('te... | TemplateGet | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TemplateGet:
def get(self, template_name):
"""Get a specific template"""
<|body_0|>
def put(self, template_name):
"""Update a template"""
<|body_1|>
def delete(self, template_name):
"""Delete a template"""
<|body_2|>
<|end_skeleton|>
<|... | stack_v2_sparse_classes_75kplus_train_073473 | 4,164 | permissive | [
{
"docstring": "Get a specific template",
"name": "get",
"signature": "def get(self, template_name)"
},
{
"docstring": "Update a template",
"name": "put",
"signature": "def put(self, template_name)"
},
{
"docstring": "Delete a template",
"name": "delete",
"signature": "de... | 3 | stack_v2_sparse_classes_30k_train_029002 | Implement the Python class `TemplateGet` described below.
Class description:
Implement the TemplateGet class.
Method signatures and docstrings:
- def get(self, template_name): Get a specific template
- def put(self, template_name): Update a template
- def delete(self, template_name): Delete a template | Implement the Python class `TemplateGet` described below.
Class description:
Implement the TemplateGet class.
Method signatures and docstrings:
- def get(self, template_name): Get a specific template
- def put(self, template_name): Update a template
- def delete(self, template_name): Delete a template
<|skeleton|>
c... | 29a26c705381fdba3538b4efedb25b9e09b387ed | <|skeleton|>
class TemplateGet:
def get(self, template_name):
"""Get a specific template"""
<|body_0|>
def put(self, template_name):
"""Update a template"""
<|body_1|>
def delete(self, template_name):
"""Delete a template"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TemplateGet:
def get(self, template_name):
"""Get a specific template"""
template = db.Template.find_one(template_name=template_name)
if not template:
return self.make_response('No such template found', HTTP.NOT_FOUND)
return self.make_response({'template': template... | the_stack_v2_python_sparse | backend/cloud_inquisitor/plugins/views/templates.py | RiotGames/cloud-inquisitor | train | 468 | |
d324e67eaae90d43573dfcbe087f529668e8f132 | [
"seen = set()\nfor i in range(len(arr)):\n sub_array_sum = 0\n sub_array = []\n for j in range(i, len(arr)):\n sub_array_sum += arr[j]\n sub_array.append(arr[j])\n if sub_array_sum == k and tuple(sub_array) not in seen:\n seen.add(tuple(sub_array))\nreturn len(seen)",
"sum... | <|body_start_0|>
seen = set()
for i in range(len(arr)):
sub_array_sum = 0
sub_array = []
for j in range(i, len(arr)):
sub_array_sum += arr[j]
sub_array.append(arr[j])
if sub_array_sum == k and tuple(sub_array) not in see... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def brute_force(self, arr: List[int], k: int) -> int:
"""Check every subarray Complexity ---- Time : O(N^2) Space : O(N^2)"""
<|body_0|>
def cumulative_sum(self, arr: List[int], k: int) -> int:
"""We can use the difference of cumulative sums. Cumulative sum... | stack_v2_sparse_classes_75kplus_train_073474 | 3,284 | no_license | [
{
"docstring": "Check every subarray Complexity ---- Time : O(N^2) Space : O(N^2)",
"name": "brute_force",
"signature": "def brute_force(self, arr: List[int], k: int) -> int"
},
{
"docstring": "We can use the difference of cumulative sums. Cumulative sums are often helpful when dealing with suba... | 3 | stack_v2_sparse_classes_30k_train_005992 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def brute_force(self, arr: List[int], k: int) -> int: Check every subarray Complexity ---- Time : O(N^2) Space : O(N^2)
- def cumulative_sum(self, arr: List[int], k: int) -> int:... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def brute_force(self, arr: List[int], k: int) -> int: Check every subarray Complexity ---- Time : O(N^2) Space : O(N^2)
- def cumulative_sum(self, arr: List[int], k: int) -> int:... | c0d49423885832b616ae3c7cd58e8f24c17cfd4d | <|skeleton|>
class Solution:
def brute_force(self, arr: List[int], k: int) -> int:
"""Check every subarray Complexity ---- Time : O(N^2) Space : O(N^2)"""
<|body_0|>
def cumulative_sum(self, arr: List[int], k: int) -> int:
"""We can use the difference of cumulative sums. Cumulative sum... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def brute_force(self, arr: List[int], k: int) -> int:
"""Check every subarray Complexity ---- Time : O(N^2) Space : O(N^2)"""
seen = set()
for i in range(len(arr)):
sub_array_sum = 0
sub_array = []
for j in range(i, len(arr)):
... | the_stack_v2_python_sparse | Arrays/sub_array_sum_k.py | miaviles/Data-Structures-Algorithms-Python | train | 0 | |
081f8a4bcc2495d402ea78be82d4401fd787ca91 | [
"self.name = name\nself.ntuple = ntuple\nself.cuts = cuts",
"try:\n method = getattr(self.ntuple, attr)\nexcept AttributeError:\n log.error('Attribute `{0}` not found on DataStore'.format(attr))\nelse:\n return method"
] | <|body_start_0|>
self.name = name
self.ntuple = ntuple
self.cuts = cuts
<|end_body_0|>
<|body_start_1|>
try:
method = getattr(self.ntuple, attr)
except AttributeError:
log.error('Attribute `{0}` not found on DataStore'.format(attr))
else:
... | Container class for ntuple metadata for plotting. | DataStore | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DataStore:
"""Container class for ntuple metadata for plotting."""
def __init__(self, name, ntuple, cuts=''):
"""Initialise an instance of the DataStore class. Keyword arguments: name -- String assigned to DataStore.name ntuple -- Lc2pXX object assigned to DataStore.ntuple cuts -- St... | stack_v2_sparse_classes_75kplus_train_073475 | 2,979 | no_license | [
{
"docstring": "Initialise an instance of the DataStore class. Keyword arguments: name -- String assigned to DataStore.name ntuple -- Lc2pXX object assigned to DataStore.ntuple cuts -- String of requirements on ntuple entries assigned to DataStore.cuts (default \"\")",
"name": "__init__",
"signature": "... | 2 | stack_v2_sparse_classes_30k_train_054254 | Implement the Python class `DataStore` described below.
Class description:
Container class for ntuple metadata for plotting.
Method signatures and docstrings:
- def __init__(self, name, ntuple, cuts=''): Initialise an instance of the DataStore class. Keyword arguments: name -- String assigned to DataStore.name ntuple... | Implement the Python class `DataStore` described below.
Class description:
Container class for ntuple metadata for plotting.
Method signatures and docstrings:
- def __init__(self, name, ntuple, cuts=''): Initialise an instance of the DataStore class. Keyword arguments: name -- String assigned to DataStore.name ntuple... | e62d698a363d7e0d77affd9f0327f9567239a1d7 | <|skeleton|>
class DataStore:
"""Container class for ntuple metadata for plotting."""
def __init__(self, name, ntuple, cuts=''):
"""Initialise an instance of the DataStore class. Keyword arguments: name -- String assigned to DataStore.name ntuple -- Lc2pXX object assigned to DataStore.ntuple cuts -- St... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DataStore:
"""Container class for ntuple metadata for plotting."""
def __init__(self, name, ntuple, cuts=''):
"""Initialise an instance of the DataStore class. Keyword arguments: name -- String assigned to DataStore.name ntuple -- Lc2pXX object assigned to DataStore.ntuple cuts -- String of requi... | the_stack_v2_python_sparse | python/lc2pxx/containers.py | alexpearce/Lc2pXX-SVN | train | 0 |
a02aae8b0ad9829c94253ecbd7d633c80ff9b73a | [
"super().__init__(config)\nself.in_proj_weight = nn.Parameter(torch.cat([fsmt_layer.self_attn.q_proj.weight, fsmt_layer.self_attn.k_proj.weight, fsmt_layer.self_attn.v_proj.weight]))\nself.in_proj_bias = nn.Parameter(torch.cat([fsmt_layer.self_attn.q_proj.bias, fsmt_layer.self_attn.k_proj.bias, fsmt_layer.self_attn... | <|body_start_0|>
super().__init__(config)
self.in_proj_weight = nn.Parameter(torch.cat([fsmt_layer.self_attn.q_proj.weight, fsmt_layer.self_attn.k_proj.weight, fsmt_layer.self_attn.v_proj.weight]))
self.in_proj_bias = nn.Parameter(torch.cat([fsmt_layer.self_attn.q_proj.bias, fsmt_layer.self_attn... | FSMTEncoderLayerBetterTransformer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FSMTEncoderLayerBetterTransformer:
def __init__(self, fsmt_layer, config):
"""A simple conversion of the FSMT Encoder layer to its `BetterTransformer` implementation. Args: fsmt_layer (`torch.nn.Module`): The original FSMT Layer where the weights needs to be retrieved."""
<|body_... | stack_v2_sparse_classes_75kplus_train_073476 | 43,670 | no_license | [
{
"docstring": "A simple conversion of the FSMT Encoder layer to its `BetterTransformer` implementation. Args: fsmt_layer (`torch.nn.Module`): The original FSMT Layer where the weights needs to be retrieved.",
"name": "__init__",
"signature": "def __init__(self, fsmt_layer, config)"
},
{
"docstr... | 2 | stack_v2_sparse_classes_30k_train_041015 | Implement the Python class `FSMTEncoderLayerBetterTransformer` described below.
Class description:
Implement the FSMTEncoderLayerBetterTransformer class.
Method signatures and docstrings:
- def __init__(self, fsmt_layer, config): A simple conversion of the FSMT Encoder layer to its `BetterTransformer` implementation.... | Implement the Python class `FSMTEncoderLayerBetterTransformer` described below.
Class description:
Implement the FSMTEncoderLayerBetterTransformer class.
Method signatures and docstrings:
- def __init__(self, fsmt_layer, config): A simple conversion of the FSMT Encoder layer to its `BetterTransformer` implementation.... | 7e55a422588c1d1e00f35a3d3a3ff896cce59e18 | <|skeleton|>
class FSMTEncoderLayerBetterTransformer:
def __init__(self, fsmt_layer, config):
"""A simple conversion of the FSMT Encoder layer to its `BetterTransformer` implementation. Args: fsmt_layer (`torch.nn.Module`): The original FSMT Layer where the weights needs to be retrieved."""
<|body_... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class FSMTEncoderLayerBetterTransformer:
def __init__(self, fsmt_layer, config):
"""A simple conversion of the FSMT Encoder layer to its `BetterTransformer` implementation. Args: fsmt_layer (`torch.nn.Module`): The original FSMT Layer where the weights needs to be retrieved."""
super().__init__(conf... | the_stack_v2_python_sparse | generated/test_huggingface_optimum.py | jansel/pytorch-jit-paritybench | train | 35 | |
c1924c508526bc1ad59661667524d6f30cd546fc | [
"if level == len(self.out_channels) - 1:\n return nn.Conv2d(out_channels, boxes_per_location * self.num_categories, kernel_size=1)\nreturn SeparableConv2d(out_channels, boxes_per_location * self.num_categories, kernel_size=3, stride=1, padding=1)",
"if level == len(self.out_channels) - 1:\n return nn.Conv2d... | <|body_start_0|>
if level == len(self.out_channels) - 1:
return nn.Conv2d(out_channels, boxes_per_location * self.num_categories, kernel_size=1)
return SeparableConv2d(out_channels, boxes_per_location * self.num_categories, kernel_size=3, stride=1, padding=1)
<|end_body_0|>
<|body_start_1|>... | description | SSDLiteBoxPredictor | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SSDLiteBoxPredictor:
"""description"""
def category_block(self, level: int, out_channels: int, boxes_per_location: int) -> nn.Module:
""":param level: :type level: :param out_channels: :type out_channels: :param boxes_per_location: :type boxes_per_location: :return: :rtype:"""
... | stack_v2_sparse_classes_75kplus_train_073477 | 1,739 | permissive | [
{
"docstring": ":param level: :type level: :param out_channels: :type out_channels: :param boxes_per_location: :type boxes_per_location: :return: :rtype:",
"name": "category_block",
"signature": "def category_block(self, level: int, out_channels: int, boxes_per_location: int) -> nn.Module"
},
{
... | 2 | stack_v2_sparse_classes_30k_train_048589 | Implement the Python class `SSDLiteBoxPredictor` described below.
Class description:
description
Method signatures and docstrings:
- def category_block(self, level: int, out_channels: int, boxes_per_location: int) -> nn.Module: :param level: :type level: :param out_channels: :type out_channels: :param boxes_per_locat... | Implement the Python class `SSDLiteBoxPredictor` described below.
Class description:
description
Method signatures and docstrings:
- def category_block(self, level: int, out_channels: int, boxes_per_location: int) -> nn.Module: :param level: :type level: :param out_channels: :type out_channels: :param boxes_per_locat... | 06839b08d8e8f274c02a6bcd31bf1b32d3dc04e4 | <|skeleton|>
class SSDLiteBoxPredictor:
"""description"""
def category_block(self, level: int, out_channels: int, boxes_per_location: int) -> nn.Module:
""":param level: :type level: :param out_channels: :type out_channels: :param boxes_per_location: :type boxes_per_location: :return: :rtype:"""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SSDLiteBoxPredictor:
"""description"""
def category_block(self, level: int, out_channels: int, boxes_per_location: int) -> nn.Module:
""":param level: :type level: :param out_channels: :type out_channels: :param boxes_per_location: :type boxes_per_location: :return: :rtype:"""
if level ==... | the_stack_v2_python_sparse | neodroidvision/detection/single_stage/ssd/architecture/nms_box_heads/ssd_lite_box_predictor.py | aivclab/vision | train | 1 |
cdc3ee5efc52eac849a22d7d405c65592590d056 | [
"if not root:\n return 0\nif root.left and root.right:\n return min(self.minDepth(root.left), self.minDepth(root.right)) + 1\nelse:\n return max(self.minDepth(root.left), self.minDepth(root.right)) + 1",
"if not root:\n return 0\ni = 1\ns = [root]\nwhile s:\n ss = []\n for node in s:\n if... | <|body_start_0|>
if not root:
return 0
if root.left and root.right:
return min(self.minDepth(root.left), self.minDepth(root.right)) + 1
else:
return max(self.minDepth(root.left), self.minDepth(root.right)) + 1
<|end_body_0|>
<|body_start_1|>
if not ro... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def minDepth(self, root):
""":type root: TreeNode :rtype: int"""
<|body_0|>
def minDepth(self, root):
""":type root: TreeNode :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not root:
return 0
if root.lef... | stack_v2_sparse_classes_75kplus_train_073478 | 1,091 | no_license | [
{
"docstring": ":type root: TreeNode :rtype: int",
"name": "minDepth",
"signature": "def minDepth(self, root)"
},
{
"docstring": ":type root: TreeNode :rtype: int",
"name": "minDepth",
"signature": "def minDepth(self, root)"
}
] | 2 | stack_v2_sparse_classes_30k_train_026624 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def minDepth(self, root): :type root: TreeNode :rtype: int
- def minDepth(self, root): :type root: TreeNode :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def minDepth(self, root): :type root: TreeNode :rtype: int
- def minDepth(self, root): :type root: TreeNode :rtype: int
<|skeleton|>
class Solution:
def minDepth(self, root... | c4e6c9590bb8531feeb4ac88d9ce95f823ef07e7 | <|skeleton|>
class Solution:
def minDepth(self, root):
""":type root: TreeNode :rtype: int"""
<|body_0|>
def minDepth(self, root):
""":type root: TreeNode :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def minDepth(self, root):
""":type root: TreeNode :rtype: int"""
if not root:
return 0
if root.left and root.right:
return min(self.minDepth(root.left), self.minDepth(root.right)) + 1
else:
return max(self.minDepth(root.left), self.... | the_stack_v2_python_sparse | Facebook/phone/Binary Tree - Minimum Depth.py | armsky/Preps | train | 0 | |
6cfb4c27f0a897695d4b0bf229f64f5d0d5bb378 | [
"if headA is None or headB is None:\n return\ncur1 = headA\nwhile cur1:\n cur2 = headB\n while cur2:\n if cur1 == cur2:\n return cur1\n else:\n cur2 = cur2.next\n cur1 = cur1.next\nreturn",
"listA = []\nif headA is None or headB is None:\n return\ncur1 = headA\nw... | <|body_start_0|>
if headA is None or headB is None:
return
cur1 = headA
while cur1:
cur2 = headB
while cur2:
if cur1 == cur2:
return cur1
else:
cur2 = cur2.next
cur1 = cur1.nex... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def getIntersectionNode(self, headA, headB):
"""采用边遍历边判断的方法,实现了功能,但是提交超时 :type head1, head1: ListNode :rtype: ListNode"""
<|body_0|>
def getIntersectionNode2(self, headA, headB):
"""采用先遍历后判断的逻辑,此种方法把链表的存储优势浪费了,使用庞大的列表,对空间的需求和遍历也是绝大的开支,仍超时 :param headA: :par... | stack_v2_sparse_classes_75kplus_train_073479 | 3,348 | no_license | [
{
"docstring": "采用边遍历边判断的方法,实现了功能,但是提交超时 :type head1, head1: ListNode :rtype: ListNode",
"name": "getIntersectionNode",
"signature": "def getIntersectionNode(self, headA, headB)"
},
{
"docstring": "采用先遍历后判断的逻辑,此种方法把链表的存储优势浪费了,使用庞大的列表,对空间的需求和遍历也是绝大的开支,仍超时 :param headA: :param headB: :return:",
... | 4 | stack_v2_sparse_classes_30k_train_041973 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def getIntersectionNode(self, headA, headB): 采用边遍历边判断的方法,实现了功能,但是提交超时 :type head1, head1: ListNode :rtype: ListNode
- def getIntersectionNode2(self, headA, headB): 采用先遍历后判断的逻辑,此种... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def getIntersectionNode(self, headA, headB): 采用边遍历边判断的方法,实现了功能,但是提交超时 :type head1, head1: ListNode :rtype: ListNode
- def getIntersectionNode2(self, headA, headB): 采用先遍历后判断的逻辑,此种... | 16b6fc4247c91a919d38bf18835f10fc29fccca7 | <|skeleton|>
class Solution:
def getIntersectionNode(self, headA, headB):
"""采用边遍历边判断的方法,实现了功能,但是提交超时 :type head1, head1: ListNode :rtype: ListNode"""
<|body_0|>
def getIntersectionNode2(self, headA, headB):
"""采用先遍历后判断的逻辑,此种方法把链表的存储优势浪费了,使用庞大的列表,对空间的需求和遍历也是绝大的开支,仍超时 :param headA: :par... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def getIntersectionNode(self, headA, headB):
"""采用边遍历边判断的方法,实现了功能,但是提交超时 :type head1, head1: ListNode :rtype: ListNode"""
if headA is None or headB is None:
return
cur1 = headA
while cur1:
cur2 = headB
while cur2:
if... | the_stack_v2_python_sparse | problem_160.py | SeanLau/leetcode | train | 0 | |
d64c5aeff121913a1510df28d366c82ecdf00dc5 | [
"self.connection = connection\nself.title = title\nself.manager = manager\nself.deadline = deadline",
"cursor = self.connection.cursor()\nwrite_project = 'INSERT INTO project SELECT NULL,?,?,? WHERE NOT EXISTS (SELECT NULL FROM project WHERE title=?)'\ncursor.execute(write_project, (self.title, self.manager, self... | <|body_start_0|>
self.connection = connection
self.title = title
self.manager = manager
self.deadline = deadline
<|end_body_0|>
<|body_start_1|>
cursor = self.connection.cursor()
write_project = 'INSERT INTO project SELECT NULL,?,?,? WHERE NOT EXISTS (SELECT NULL FROM pr... | ProjectRepository | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProjectRepository:
def __init__(self, connection: sqlite3.Connection, title: str, manager: str, deadline: int):
"""Хранилище атрибутов проекта :param connection: соединение с СУБД :param title: Наименование проекта :param manager: ФИО руководителя :param deadline: Дата сдачи"""
<... | stack_v2_sparse_classes_75kplus_train_073480 | 1,367 | no_license | [
{
"docstring": "Хранилище атрибутов проекта :param connection: соединение с СУБД :param title: Наименование проекта :param manager: ФИО руководителя :param deadline: Дата сдачи",
"name": "__init__",
"signature": "def __init__(self, connection: sqlite3.Connection, title: str, manager: str, deadline: int)... | 2 | null | Implement the Python class `ProjectRepository` described below.
Class description:
Implement the ProjectRepository class.
Method signatures and docstrings:
- def __init__(self, connection: sqlite3.Connection, title: str, manager: str, deadline: int): Хранилище атрибутов проекта :param connection: соединение с СУБД :p... | Implement the Python class `ProjectRepository` described below.
Class description:
Implement the ProjectRepository class.
Method signatures and docstrings:
- def __init__(self, connection: sqlite3.Connection, title: str, manager: str, deadline: int): Хранилище атрибутов проекта :param connection: соединение с СУБД :p... | b56b8f8c5b73e1363e2595b93daae0dbfc9ea70c | <|skeleton|>
class ProjectRepository:
def __init__(self, connection: sqlite3.Connection, title: str, manager: str, deadline: int):
"""Хранилище атрибутов проекта :param connection: соединение с СУБД :param title: Наименование проекта :param manager: ФИО руководителя :param deadline: Дата сдачи"""
<... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ProjectRepository:
def __init__(self, connection: sqlite3.Connection, title: str, manager: str, deadline: int):
"""Хранилище атрибутов проекта :param connection: соединение с СУБД :param title: Наименование проекта :param manager: ФИО руководителя :param deadline: Дата сдачи"""
self.connection... | the_stack_v2_python_sparse | csv-consolidation/ProjectRepository.py | SbWereWolf/tensor-employee | train | 0 | |
49a9cd289962c290240368efa084ef814dea3d5c | [
"ebuild_path = 'chromeos-base/platform2/platform2-9999.ebuild'\ncomponents = ['chromeos-base', 'platform2', 'platform2-9999']\nfor path in (ebuild_path, './' + ebuild_path, 'foo.bar/' + ebuild_path):\n self.assertEquals(components, portage_util.SplitEbuildPath(path))",
"pv = 'bar-1.2.3_rc1-r5'\npackage, versio... | <|body_start_0|>
ebuild_path = 'chromeos-base/platform2/platform2-9999.ebuild'
components = ['chromeos-base', 'platform2', 'platform2-9999']
for path in (ebuild_path, './' + ebuild_path, 'foo.bar/' + ebuild_path):
self.assertEquals(components, portage_util.SplitEbuildPath(path))
<|en... | Tests related to Proejct Mapping. | ProjectMappingTest | [
"LGPL-2.0-or-later",
"GPL-1.0-or-later",
"MIT",
"Apache-2.0",
"BSD-3-Clause",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProjectMappingTest:
"""Tests related to Proejct Mapping."""
def testSplitEbuildPath(self):
"""Test if we can split an ebuild path into its components."""
<|body_0|>
def testSplitPV(self):
"""Test splitting PVs into package and version components."""
<|bod... | stack_v2_sparse_classes_75kplus_train_073481 | 44,982 | permissive | [
{
"docstring": "Test if we can split an ebuild path into its components.",
"name": "testSplitEbuildPath",
"signature": "def testSplitEbuildPath(self)"
},
{
"docstring": "Test splitting PVs into package and version components.",
"name": "testSplitPV",
"signature": "def testSplitPV(self)"
... | 4 | stack_v2_sparse_classes_30k_train_012924 | Implement the Python class `ProjectMappingTest` described below.
Class description:
Tests related to Proejct Mapping.
Method signatures and docstrings:
- def testSplitEbuildPath(self): Test if we can split an ebuild path into its components.
- def testSplitPV(self): Test splitting PVs into package and version compone... | Implement the Python class `ProjectMappingTest` described below.
Class description:
Tests related to Proejct Mapping.
Method signatures and docstrings:
- def testSplitEbuildPath(self): Test if we can split an ebuild path into its components.
- def testSplitPV(self): Test splitting PVs into package and version compone... | 72a05af97787001756bae2511b7985e61498c965 | <|skeleton|>
class ProjectMappingTest:
"""Tests related to Proejct Mapping."""
def testSplitEbuildPath(self):
"""Test if we can split an ebuild path into its components."""
<|body_0|>
def testSplitPV(self):
"""Test splitting PVs into package and version components."""
<|bod... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ProjectMappingTest:
"""Tests related to Proejct Mapping."""
def testSplitEbuildPath(self):
"""Test if we can split an ebuild path into its components."""
ebuild_path = 'chromeos-base/platform2/platform2-9999.ebuild'
components = ['chromeos-base', 'platform2', 'platform2-9999']
... | the_stack_v2_python_sparse | third_party/chromite/lib/portage_util_unittest.py | metux/chromium-suckless | train | 5 |
1646348048a6d86ba2c09fe12dcd69fc868de6bc | [
"client = mock_client()\nargs = {'user-profile': {'userName': 'mock_user_name'}}\nwith requests_mock.Mocker() as m:\n m.get(userUri, json={'totalResults': 0, 'Resources': []})\n m.post(userUri, json=APP_USER_OUTPUT)\n user_profile = IAMCommand(get_user_iam_attrs=['userName']).create_user(client, args)\nout... | <|body_start_0|>
client = mock_client()
args = {'user-profile': {'userName': 'mock_user_name'}}
with requests_mock.Mocker() as m:
m.get(userUri, json={'totalResults': 0, 'Resources': []})
m.post(userUri, json=APP_USER_OUTPUT)
user_profile = IAMCommand(get_user... | TestCreateUserCommand | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestCreateUserCommand:
def test_success(self):
"""Given: - An app client object - A user-profile argument that contains an email of a non-existing user in the application When: - Calling function create_user_command Then: - Ensure a User Profile object with the user data is returned"""
... | stack_v2_sparse_classes_75kplus_train_073482 | 23,298 | permissive | [
{
"docstring": "Given: - An app client object - A user-profile argument that contains an email of a non-existing user in the application When: - Calling function create_user_command Then: - Ensure a User Profile object with the user data is returned",
"name": "test_success",
"signature": "def test_succe... | 2 | null | Implement the Python class `TestCreateUserCommand` described below.
Class description:
Implement the TestCreateUserCommand class.
Method signatures and docstrings:
- def test_success(self): Given: - An app client object - A user-profile argument that contains an email of a non-existing user in the application When: -... | Implement the Python class `TestCreateUserCommand` described below.
Class description:
Implement the TestCreateUserCommand class.
Method signatures and docstrings:
- def test_success(self): Given: - An app client object - A user-profile argument that contains an email of a non-existing user in the application When: -... | 890def5a0e0ae8d6eaa538148249ddbc851dbb6b | <|skeleton|>
class TestCreateUserCommand:
def test_success(self):
"""Given: - An app client object - A user-profile argument that contains an email of a non-existing user in the application When: - Calling function create_user_command Then: - Ensure a User Profile object with the user data is returned"""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TestCreateUserCommand:
def test_success(self):
"""Given: - An app client object - A user-profile argument that contains an email of a non-existing user in the application When: - Calling function create_user_command Then: - Ensure a User Profile object with the user data is returned"""
client ... | the_stack_v2_python_sparse | Packs/AWS-ILM/Integrations/AWSILM/AWSILM_test.py | demisto/content | train | 1,023 | |
11331107fe0ce95c76bcbab6a19bd133db27cb35 | [
"self.name = name\nself.output_dest = output_dest\nlog.debug('Mapper {0} initialized. Output={1}'.format(name, output_dest))",
"input_file = key\nparams = val\noutput_file = '{0}/{1}_mapped.pkl'.format(self.output_dest, input_file)\nSavePickles(output_file, [(key, val)])\nSendPickle(self.output_dest, [(key, val)]... | <|body_start_0|>
self.name = name
self.output_dest = output_dest
log.debug('Mapper {0} initialized. Output={1}'.format(name, output_dest))
<|end_body_0|>
<|body_start_1|>
input_file = key
params = val
output_file = '{0}/{1}_mapped.pkl'.format(self.output_dest, input_file... | A class that handles Mapping jobs Need to specify the Map() function | BaseMapper | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BaseMapper:
"""A class that handles Mapping jobs Need to specify the Map() function"""
def __init__(self, name, output_dest=None):
"""initialize the mapper. the mapper should have a name. output_dir specifies the folder to output map results. this class can also hold global parameter... | stack_v2_sparse_classes_75kplus_train_073483 | 7,956 | permissive | [
{
"docstring": "initialize the mapper. the mapper should have a name. output_dir specifies the folder to output map results. this class can also hold global parameters that are used by the Map() function. usually the output_dest is specified so that the mapper knows where to store the results.",
"name": "__... | 2 | null | Implement the Python class `BaseMapper` described below.
Class description:
A class that handles Mapping jobs Need to specify the Map() function
Method signatures and docstrings:
- def __init__(self, name, output_dest=None): initialize the mapper. the mapper should have a name. output_dir specifies the folder to outp... | Implement the Python class `BaseMapper` described below.
Class description:
A class that handles Mapping jobs Need to specify the Map() function
Method signatures and docstrings:
- def __init__(self, name, output_dest=None): initialize the mapper. the mapper should have a name. output_dir specifies the folder to outp... | cf89cff095b542371d10af976fc687a3fb1da471 | <|skeleton|>
class BaseMapper:
"""A class that handles Mapping jobs Need to specify the Map() function"""
def __init__(self, name, output_dest=None):
"""initialize the mapper. the mapper should have a name. output_dir specifies the folder to output map results. this class can also hold global parameter... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class BaseMapper:
"""A class that handles Mapping jobs Need to specify the Map() function"""
def __init__(self, name, output_dest=None):
"""initialize the mapper. the mapper should have a name. output_dir specifies the folder to output map results. this class can also hold global parameters that are us... | the_stack_v2_python_sparse | ex/pp/mr.py | excelly/xpy-ml | train | 0 |
092caac84c8b61f34b216d0d84a15297f2403b5f | [
"try:\n data = PDPManager.get_pdp(user_id=user_id, pdp_id=uuid)\nexcept Exception as e:\n LOG.error(e, exc_info=True)\n return ({'result': False, 'error': str(e)}, 500)\nreturn {'pdps': data}",
"try:\n data = PDPManager.add_pdp(user_id=user_id, pdp_id=None, value=request.json)\n add_pod(uuid=uuid, ... | <|body_start_0|>
try:
data = PDPManager.get_pdp(user_id=user_id, pdp_id=uuid)
except Exception as e:
LOG.error(e, exc_info=True)
return ({'result': False, 'error': str(e)}, 500)
return {'pdps': data}
<|end_body_0|>
<|body_start_1|>
try:
da... | Endpoint for pdp requests | PDP | [
"Apache-2.0",
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PDP:
"""Endpoint for pdp requests"""
def get(self, uuid=None, user_id=None):
"""Retrieve all pdp :param uuid: uuid of the pdp :param user_id: user ID who do the request :return: { "pdp_id1": { "name": "...", "security_pipeline": [...], "keystone_project_id": "keystone_project_id1", "... | stack_v2_sparse_classes_75kplus_train_073484 | 4,520 | permissive | [
{
"docstring": "Retrieve all pdp :param uuid: uuid of the pdp :param user_id: user ID who do the request :return: { \"pdp_id1\": { \"name\": \"...\", \"security_pipeline\": [...], \"keystone_project_id\": \"keystone_project_id1\", \"description\": \"...\", } } :internal_api: get_pdp",
"name": "get",
"si... | 4 | null | Implement the Python class `PDP` described below.
Class description:
Endpoint for pdp requests
Method signatures and docstrings:
- def get(self, uuid=None, user_id=None): Retrieve all pdp :param uuid: uuid of the pdp :param user_id: user ID who do the request :return: { "pdp_id1": { "name": "...", "security_pipeline"... | Implement the Python class `PDP` described below.
Class description:
Endpoint for pdp requests
Method signatures and docstrings:
- def get(self, uuid=None, user_id=None): Retrieve all pdp :param uuid: uuid of the pdp :param user_id: user ID who do the request :return: { "pdp_id1": { "name": "...", "security_pipeline"... | daaba34fa2ed4426bc0fde359e54a5e1b872208c | <|skeleton|>
class PDP:
"""Endpoint for pdp requests"""
def get(self, uuid=None, user_id=None):
"""Retrieve all pdp :param uuid: uuid of the pdp :param user_id: user ID who do the request :return: { "pdp_id1": { "name": "...", "security_pipeline": [...], "keystone_project_id": "keystone_project_id1", "... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PDP:
"""Endpoint for pdp requests"""
def get(self, uuid=None, user_id=None):
"""Retrieve all pdp :param uuid: uuid of the pdp :param user_id: user ID who do the request :return: { "pdp_id1": { "name": "...", "security_pipeline": [...], "keystone_project_id": "keystone_project_id1", "description":... | the_stack_v2_python_sparse | moonv4/moon_manager/moon_manager/api/pdp.py | hashnfv/hashnfv-moon | train | 0 |
86bb8e150a073f505cc8ccdef7240e736f27bb50 | [
"if IP_NOT_FOUND:\n return HttpResponseNotFound(IP_NOT_FOUND_MSG)\nreturn Response([{'ruleId': 0, 'ruleIp': blockedIp, 'ruleReason': 'string'}])",
"if IP_NOT_FOUND:\n return HttpResponseNotFound(IP_NOT_FOUND_MSG)\nif len(request.data) != 1:\n return HttpResponseBadRequest()\nreturn Response([{'ruleId': 0... | <|body_start_0|>
if IP_NOT_FOUND:
return HttpResponseNotFound(IP_NOT_FOUND_MSG)
return Response([{'ruleId': 0, 'ruleIp': blockedIp, 'ruleReason': 'string'}])
<|end_body_0|>
<|body_start_1|>
if IP_NOT_FOUND:
return HttpResponseNotFound(IP_NOT_FOUND_MSG)
if len(req... | [GET] /rtbh/{blockedIp} Get all rules with specified blockedIp on RTBH [PUT] /rtbh/{blockedIp} Change the reason for all rules with specified IP [DELETE] /rtbh/{blockedIp} Delete all rules for specified IP | RtbhBlockedIp | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RtbhBlockedIp:
"""[GET] /rtbh/{blockedIp} Get all rules with specified blockedIp on RTBH [PUT] /rtbh/{blockedIp} Change the reason for all rules with specified IP [DELETE] /rtbh/{blockedIp} Delete all rules for specified IP"""
def get(self, request, blockedIp, **kwargs):
""":param bl... | stack_v2_sparse_classes_75kplus_train_073485 | 4,134 | permissive | [
{
"docstring": ":param blockedIp: any ipv4",
"name": "get",
"signature": "def get(self, request, blockedIp, **kwargs)"
},
{
"docstring": ":param blockedIp: any ipv4",
"name": "put",
"signature": "def put(self, request, blockedIp, **kwargs)"
},
{
"docstring": ":param blockedIp: an... | 3 | stack_v2_sparse_classes_30k_train_047139 | Implement the Python class `RtbhBlockedIp` described below.
Class description:
[GET] /rtbh/{blockedIp} Get all rules with specified blockedIp on RTBH [PUT] /rtbh/{blockedIp} Change the reason for all rules with specified IP [DELETE] /rtbh/{blockedIp} Delete all rules for specified IP
Method signatures and docstrings:... | Implement the Python class `RtbhBlockedIp` described below.
Class description:
[GET] /rtbh/{blockedIp} Get all rules with specified blockedIp on RTBH [PUT] /rtbh/{blockedIp} Change the reason for all rules with specified IP [DELETE] /rtbh/{blockedIp} Delete all rules for specified IP
Method signatures and docstrings:... | 73e4ac0ced6c3ac46d24ac5c3feb01a1e88bd36b | <|skeleton|>
class RtbhBlockedIp:
"""[GET] /rtbh/{blockedIp} Get all rules with specified blockedIp on RTBH [PUT] /rtbh/{blockedIp} Change the reason for all rules with specified IP [DELETE] /rtbh/{blockedIp} Delete all rules for specified IP"""
def get(self, request, blockedIp, **kwargs):
""":param bl... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class RtbhBlockedIp:
"""[GET] /rtbh/{blockedIp} Get all rules with specified blockedIp on RTBH [PUT] /rtbh/{blockedIp} Change the reason for all rules with specified IP [DELETE] /rtbh/{blockedIp} Delete all rules for specified IP"""
def get(self, request, blockedIp, **kwargs):
""":param blockedIp: any ... | the_stack_v2_python_sparse | crusoe_act/act-component/rtbh-wrapper/rtbh_wrapper_project/views.py | wumingruiye/CRUSOE | train | 0 |
857652691705971b1fcc0a08a758667bc9d00c81 | [
"self._counter = Counter()\nself._interval = interval\nself.filters = filters\nself._verbose = verbose",
"is_in_filters = self.filters is None or tag in self.filters\nat_interval = is_none_or_zero_or_negative_or_mod_zero(self._interval, self._counter[tag])\nreturn is_in_filters and at_interval"
] | <|body_start_0|>
self._counter = Counter()
self._interval = interval
self.filters = filters
self._verbose = verbose
<|end_body_0|>
<|body_start_1|>
is_in_filters = self.filters is None or tag in self.filters
at_interval = is_none_or_zero_or_negative_or_mod_zero(self._int... | CounterFilter | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CounterFilter:
def __init__(self, *, interval: Optional[int]=1, filters: Iterable=None, verbose: bool=False):
""":param interval: :param filters: :param verbose:"""
<|body_0|>
def filter(self, tag: str) -> bool:
"""returns a boolean value, true if to be included, Fal... | stack_v2_sparse_classes_75kplus_train_073486 | 1,314 | permissive | [
{
"docstring": ":param interval: :param filters: :param verbose:",
"name": "__init__",
"signature": "def __init__(self, *, interval: Optional[int]=1, filters: Iterable=None, verbose: bool=False)"
},
{
"docstring": "returns a boolean value, true if to be included, False if to be excluded tag is i... | 2 | stack_v2_sparse_classes_30k_train_034283 | Implement the Python class `CounterFilter` described below.
Class description:
Implement the CounterFilter class.
Method signatures and docstrings:
- def __init__(self, *, interval: Optional[int]=1, filters: Iterable=None, verbose: bool=False): :param interval: :param filters: :param verbose:
- def filter(self, tag: ... | Implement the Python class `CounterFilter` described below.
Class description:
Implement the CounterFilter class.
Method signatures and docstrings:
- def __init__(self, *, interval: Optional[int]=1, filters: Iterable=None, verbose: bool=False): :param interval: :param filters: :param verbose:
- def filter(self, tag: ... | 94a402cab47a2bd6241608308371490079af4d53 | <|skeleton|>
class CounterFilter:
def __init__(self, *, interval: Optional[int]=1, filters: Iterable=None, verbose: bool=False):
""":param interval: :param filters: :param verbose:"""
<|body_0|>
def filter(self, tag: str) -> bool:
"""returns a boolean value, true if to be included, Fal... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CounterFilter:
def __init__(self, *, interval: Optional[int]=1, filters: Iterable=None, verbose: bool=False):
""":param interval: :param filters: :param verbose:"""
self._counter = Counter()
self._interval = interval
self.filters = filters
self._verbose = verbose
d... | the_stack_v2_python_sparse | draugr/python_utilities/counter_filter.py | cnheider/draugr | train | 4 | |
2529ffeb5f01748be399fedc3721a03c34b27286 | [
"self.en = Signal()\nself.data_in = Signal(width)\nself.data_out = Signal(width)",
"m = Module()\nm.d.comb += self.data_out.eq(Mux(self.en, self.data_in[::-1], self.data_in))\nreturn m"
] | <|body_start_0|>
self.en = Signal()
self.data_in = Signal(width)
self.data_out = Signal(width)
<|end_body_0|>
<|body_start_1|>
m = Module()
m.d.comb += self.data_out.eq(Mux(self.en, self.data_in[::-1], self.data_in))
return m
<|end_body_1|>
| A conditional bit reverser. Attributes: data_in: The input data. data_out: The output data. en: Whether reversing is enabled or disabled. | _ConditionalReverser | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class _ConditionalReverser:
"""A conditional bit reverser. Attributes: data_in: The input data. data_out: The output data. en: Whether reversing is enabled or disabled."""
def __init__(self, width: int):
"""Constructs a conditional reverser. Args: width: The number of bits in the reverser.... | stack_v2_sparse_classes_75kplus_train_073487 | 7,020 | no_license | [
{
"docstring": "Constructs a conditional reverser. Args: width: The number of bits in the reverser.",
"name": "__init__",
"signature": "def __init__(self, width: int)"
},
{
"docstring": "Implements the logic for the reverser.",
"name": "elaborate",
"signature": "def elaborate(self, _: Pl... | 2 | null | Implement the Python class `_ConditionalReverser` described below.
Class description:
A conditional bit reverser. Attributes: data_in: The input data. data_out: The output data. en: Whether reversing is enabled or disabled.
Method signatures and docstrings:
- def __init__(self, width: int): Constructs a conditional r... | Implement the Python class `_ConditionalReverser` described below.
Class description:
A conditional bit reverser. Attributes: data_in: The input data. data_out: The output data. en: Whether reversing is enabled or disabled.
Method signatures and docstrings:
- def __init__(self, width: int): Constructs a conditional r... | 9e652e1ca6dd5c2488ec30560b175d6d20ee003f | <|skeleton|>
class _ConditionalReverser:
"""A conditional bit reverser. Attributes: data_in: The input data. data_out: The output data. en: Whether reversing is enabled or disabled."""
def __init__(self, width: int):
"""Constructs a conditional reverser. Args: width: The number of bits in the reverser.... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class _ConditionalReverser:
"""A conditional bit reverser. Attributes: data_in: The input data. data_out: The output data. en: Whether reversing is enabled or disabled."""
def __init__(self, width: int):
"""Constructs a conditional reverser. Args: width: The number of bits in the reverser."""
s... | the_stack_v2_python_sparse | shift_card.py | ElMahdiElAnnabi/riscv-reboot | train | 0 |
ebcb97e058c714c3c336aa38be84fa4228d4f6f6 | [
"if not root:\n return []\nres = []\nqueue = [root]\nwhile queue:\n level_node = []\n temp = []\n for i in queue:\n level_node.append(i.val)\n if i.left:\n temp.append(i.left)\n if i.right:\n temp.append(i.right)\n res.append(level_node)\n queue = temp\nr... | <|body_start_0|>
if not root:
return []
res = []
queue = [root]
while queue:
level_node = []
temp = []
for i in queue:
level_node.append(i.val)
if i.left:
temp.append(i.left)
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def levelOrder(self, root: TreeNode) -> List[List[int]]:
"""bfs 迭代：相对来说用队列就能实现"""
<|body_0|>
def levelOrder1(self, root: TreeNode) -> List[List[int]]:
"""递归"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not root:
return []... | stack_v2_sparse_classes_75kplus_train_073488 | 1,795 | no_license | [
{
"docstring": "bfs 迭代：相对来说用队列就能实现",
"name": "levelOrder",
"signature": "def levelOrder(self, root: TreeNode) -> List[List[int]]"
},
{
"docstring": "递归",
"name": "levelOrder1",
"signature": "def levelOrder1(self, root: TreeNode) -> List[List[int]]"
}
] | 2 | stack_v2_sparse_classes_30k_train_047088 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def levelOrder(self, root: TreeNode) -> List[List[int]]: bfs 迭代：相对来说用队列就能实现
- def levelOrder1(self, root: TreeNode) -> List[List[int]]: 递归 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def levelOrder(self, root: TreeNode) -> List[List[int]]: bfs 迭代：相对来说用队列就能实现
- def levelOrder1(self, root: TreeNode) -> List[List[int]]: 递归
<|skeleton|>
class Solution:
def ... | 069bb0b751ef7f469036b9897436eb5d138ffa24 | <|skeleton|>
class Solution:
def levelOrder(self, root: TreeNode) -> List[List[int]]:
"""bfs 迭代：相对来说用队列就能实现"""
<|body_0|>
def levelOrder1(self, root: TreeNode) -> List[List[int]]:
"""递归"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def levelOrder(self, root: TreeNode) -> List[List[int]]:
"""bfs 迭代：相对来说用队列就能实现"""
if not root:
return []
res = []
queue = [root]
while queue:
level_node = []
temp = []
for i in queue:
level_node.a... | the_stack_v2_python_sparse | 算法/Week_02/102. 二叉树的层序遍历.py | RichieSong/algorithm | train | 0 | |
05d3c1e0dbc1523cd98da14d955a1e866336697c | [
"super().__init__(name=name)\nself.self_attention = MultiHeadAttention(config)\nself.norm1 = tf.keras.layers.LayerNormalization(epsilon=config['layernorm_epsilon'])\nself.ende_attn = MultiHeadAttention(config)\nself.norm2 = tf.keras.layers.LayerNormalization(epsilon=config['layernorm_epsilon'])\nself.ffn = Position... | <|body_start_0|>
super().__init__(name=name)
self.self_attention = MultiHeadAttention(config)
self.norm1 = tf.keras.layers.LayerNormalization(epsilon=config['layernorm_epsilon'])
self.ende_attn = MultiHeadAttention(config)
self.norm2 = tf.keras.layers.LayerNormalization(epsilon=c... | Decoder Layer Class | DecoderLayer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DecoderLayer:
"""Decoder Layer Class"""
def __init__(self, config, name='decoder_layer'):
"""생성자 :param config: Config 객체 :param name: layer name"""
<|body_0|>
def call(self, dec_embed, enc_out, self_mask, ende_mask):
"""layer 실행 :param dec_embed: dec_embed 또는 이전... | stack_v2_sparse_classes_75kplus_train_073489 | 14,325 | permissive | [
{
"docstring": "생성자 :param config: Config 객체 :param name: layer name",
"name": "__init__",
"signature": "def __init__(self, config, name='decoder_layer')"
},
{
"docstring": "layer 실행 :param dec_embed: dec_embed 또는 이전 DecoderLayer의 출력 :param enc_out: 마지막 EncoderLayer의 출력 :param self_mask: dec_tok... | 2 | null | Implement the Python class `DecoderLayer` described below.
Class description:
Decoder Layer Class
Method signatures and docstrings:
- def __init__(self, config, name='decoder_layer'): 생성자 :param config: Config 객체 :param name: layer name
- def call(self, dec_embed, enc_out, self_mask, ende_mask): layer 실행 :param dec_e... | Implement the Python class `DecoderLayer` described below.
Class description:
Decoder Layer Class
Method signatures and docstrings:
- def __init__(self, config, name='decoder_layer'): 생성자 :param config: Config 객체 :param name: layer name
- def call(self, dec_embed, enc_out, self_mask, ende_mask): layer 실행 :param dec_e... | cf8588ead07a098de9dd1e4f177374ba7ce08d74 | <|skeleton|>
class DecoderLayer:
"""Decoder Layer Class"""
def __init__(self, config, name='decoder_layer'):
"""생성자 :param config: Config 객체 :param name: layer name"""
<|body_0|>
def call(self, dec_embed, enc_out, self_mask, ende_mask):
"""layer 실행 :param dec_embed: dec_embed 또는 이전... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DecoderLayer:
"""Decoder Layer Class"""
def __init__(self, config, name='decoder_layer'):
"""생성자 :param config: Config 객체 :param name: layer name"""
super().__init__(name=name)
self.self_attention = MultiHeadAttention(config)
self.norm1 = tf.keras.layers.LayerNormalization... | the_stack_v2_python_sparse | transformer/model.py | paul-hyun/tf_transformers | train | 10 |
79c85aaa703b43d9372579604d67a66d96a30b1c | [
"self._mapping = OrderedDict()\nself._counter = itertools.count()\nif data is not None:\n self.update(data)",
"try:\n float(val)\nexcept ValueError:\n try:\n dateutil.parser.parse(val)\n except (ValueError, TypeError):\n return False\nreturn True",
"data = np.atleast_1d(np.array(data, ... | <|body_start_0|>
self._mapping = OrderedDict()
self._counter = itertools.count()
if data is not None:
self.update(data)
<|end_body_0|>
<|body_start_1|>
try:
float(val)
except ValueError:
try:
dateutil.parser.parse(val)
... | UnitData | [
"Apache-2.0",
"CC0-1.0",
"BSD-3-Clause",
"MIT",
"Bitstream-Charter",
"LicenseRef-scancode-warranty-disclaimer",
"LicenseRef-scancode-bakoma-fonts-1995",
"LicenseRef-scancode-unknown-license-reference",
"OFL-1.1"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UnitData:
def __init__(self, data=None):
"""Create mapping between unique categorical values and integer ids. Parameters ---------- data : iterable sequence of string values"""
<|body_0|>
def _str_is_convertible(val):
"""Helper method to check whether a string can be... | stack_v2_sparse_classes_75kplus_train_073490 | 7,316 | permissive | [
{
"docstring": "Create mapping between unique categorical values and integer ids. Parameters ---------- data : iterable sequence of string values",
"name": "__init__",
"signature": "def __init__(self, data=None)"
},
{
"docstring": "Helper method to check whether a string can be parsed as float o... | 3 | null | Implement the Python class `UnitData` described below.
Class description:
Implement the UnitData class.
Method signatures and docstrings:
- def __init__(self, data=None): Create mapping between unique categorical values and integer ids. Parameters ---------- data : iterable sequence of string values
- def _str_is_con... | Implement the Python class `UnitData` described below.
Class description:
Implement the UnitData class.
Method signatures and docstrings:
- def __init__(self, data=None): Create mapping between unique categorical values and integer ids. Parameters ---------- data : iterable sequence of string values
- def _str_is_con... | f5042e35b945aded77b23470ead62d7eacefde92 | <|skeleton|>
class UnitData:
def __init__(self, data=None):
"""Create mapping between unique categorical values and integer ids. Parameters ---------- data : iterable sequence of string values"""
<|body_0|>
def _str_is_convertible(val):
"""Helper method to check whether a string can be... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class UnitData:
def __init__(self, data=None):
"""Create mapping between unique categorical values and integer ids. Parameters ---------- data : iterable sequence of string values"""
self._mapping = OrderedDict()
self._counter = itertools.count()
if data is not None:
self... | the_stack_v2_python_sparse | contrib/python/matplotlib/py3/matplotlib/category.py | catboost/catboost | train | 8,012 | |
dd11237c18979426a3189f3a5532be868d85eaa5 | [
"self.head = head\nself.len = 0\ncurr = self.head\nwhile curr != None:\n self.len += 1\n curr = curr.next",
"rnd.seed()\ncurr = self.head\nstop = rnd.randrange(self.len)\nwhile stop != 0:\n stop -= 1\n curr = curr.next\nreturn curr.val"
] | <|body_start_0|>
self.head = head
self.len = 0
curr = self.head
while curr != None:
self.len += 1
curr = curr.next
<|end_body_0|>
<|body_start_1|>
rnd.seed()
curr = self.head
stop = rnd.randrange(self.len)
while stop != 0:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def __init__(self, head):
"""@param head The linked list's head. Note that the head is guaranteed to be not null, so it contains at least one node. :type head: ListNode"""
<|body_0|>
def getRandom(self):
"""Returns a random node's value. :rtype: int"""
... | stack_v2_sparse_classes_75kplus_train_073491 | 1,684 | no_license | [
{
"docstring": "@param head The linked list's head. Note that the head is guaranteed to be not null, so it contains at least one node. :type head: ListNode",
"name": "__init__",
"signature": "def __init__(self, head)"
},
{
"docstring": "Returns a random node's value. :rtype: int",
"name": "g... | 2 | stack_v2_sparse_classes_30k_train_049894 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def __init__(self, head): @param head The linked list's head. Note that the head is guaranteed to be not null, so it contains at least one node. :type head: ListNode
- def getRan... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def __init__(self, head): @param head The linked list's head. Note that the head is guaranteed to be not null, so it contains at least one node. :type head: ListNode
- def getRan... | 8cda0518440488992d7e2c70cb8555ec7b34083f | <|skeleton|>
class Solution:
def __init__(self, head):
"""@param head The linked list's head. Note that the head is guaranteed to be not null, so it contains at least one node. :type head: ListNode"""
<|body_0|>
def getRandom(self):
"""Returns a random node's value. :rtype: int"""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def __init__(self, head):
"""@param head The linked list's head. Note that the head is guaranteed to be not null, so it contains at least one node. :type head: ListNode"""
self.head = head
self.len = 0
curr = self.head
while curr != None:
self.len ... | the_stack_v2_python_sparse | 382/main.py | szhongren/leetcode | train | 0 | |
4bb21fd1fef767aad4d4f8cdbc0366c39cdf5898 | [
"self.folder_with_objects_fullname_list = folder_with_objects_fullname_list\nself.expected_objects_count = expected_objects_count\nself.each_object_size_width = each_object_size_width\nself.each_object_size_height = each_object_size_height\nself.pixel_depth = pixel_depth",
"try:\n print('► convert {} to pickle... | <|body_start_0|>
self.folder_with_objects_fullname_list = folder_with_objects_fullname_list
self.expected_objects_count = expected_objects_count
self.each_object_size_width = each_object_size_width
self.each_object_size_height = each_object_size_height
self.pixel_depth = pixel_de... | PickleMaker | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PickleMaker:
def __init__(self, folder_with_objects_fullname_list, expected_objects_count, each_object_size_width=config.TRAIN_OBJECT_WIDTH, each_object_size_height=config.TRAIN_OBJECT_HEIGHT, pixel_depth=255.0):
"""Construct the PickleMaker that can convert objects under folders of fold... | stack_v2_sparse_classes_75kplus_train_073492 | 6,873 | permissive | [
{
"docstring": "Construct the PickleMaker that can convert objects under folders of folder_with_objects_fullname_list to a collection of 2-D, a 3-D collection. A validated result collection should contain rows not less than expected_objects_count. Give each_object_size_width/height to avoid unsituable training ... | 4 | stack_v2_sparse_classes_30k_train_037101 | Implement the Python class `PickleMaker` described below.
Class description:
Implement the PickleMaker class.
Method signatures and docstrings:
- def __init__(self, folder_with_objects_fullname_list, expected_objects_count, each_object_size_width=config.TRAIN_OBJECT_WIDTH, each_object_size_height=config.TRAIN_OBJECT_... | Implement the Python class `PickleMaker` described below.
Class description:
Implement the PickleMaker class.
Method signatures and docstrings:
- def __init__(self, folder_with_objects_fullname_list, expected_objects_count, each_object_size_width=config.TRAIN_OBJECT_WIDTH, each_object_size_height=config.TRAIN_OBJECT_... | 2d7296a4deebb0cd086be34ad7d66f5042cdf6e6 | <|skeleton|>
class PickleMaker:
def __init__(self, folder_with_objects_fullname_list, expected_objects_count, each_object_size_width=config.TRAIN_OBJECT_WIDTH, each_object_size_height=config.TRAIN_OBJECT_HEIGHT, pixel_depth=255.0):
"""Construct the PickleMaker that can convert objects under folders of fold... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PickleMaker:
def __init__(self, folder_with_objects_fullname_list, expected_objects_count, each_object_size_width=config.TRAIN_OBJECT_WIDTH, each_object_size_height=config.TRAIN_OBJECT_HEIGHT, pixel_depth=255.0):
"""Construct the PickleMaker that can convert objects under folders of folder_with_object... | the_stack_v2_python_sparse | machine_learning/pickle_maker.py | XinyueZ/some-python-codes | train | 0 | |
b2e672df28e20bae58e436d87c4e8fa4647d551f | [
"super(mp_conv_residual, self).__init__()\nself.conv1 = torch.nn.Sequential(torch.nn.Conv2d(nin, nmed, 1), SyncBatchNorm(nmed), torch.nn.ReLU(inplace=True))\nself.mp_conv = mp_conv_v2(nmed, nmed, netype, extension=extension)\nself.conv2 = torch.nn.Sequential(torch.nn.Conv2d(nmed, nin, 1), SyncBatchNorm(nin), torch.... | <|body_start_0|>
super(mp_conv_residual, self).__init__()
self.conv1 = torch.nn.Sequential(torch.nn.Conv2d(nin, nmed, 1), SyncBatchNorm(nmed), torch.nn.ReLU(inplace=True))
self.mp_conv = mp_conv_v2(nmed, nmed, netype, extension=extension)
self.conv2 = torch.nn.Sequential(torch.nn.Conv2d(... | mp_conv_residual | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class mp_conv_residual:
def __init__(self, nin, nmed, netype, extension=mp_conv_type.ORIG_WITH_DIFF, with_residual=True, with_hop=False):
"""Residual block for graph conv network. :param nin: number of input units :param nmed: number of units in the graph conv layer :param netype: number of ed... | stack_v2_sparse_classes_75kplus_train_073493 | 1,915 | permissive | [
{
"docstring": "Residual block for graph conv network. :param nin: number of input units :param nmed: number of units in the graph conv layer :param netype: number of edge types :param extension: organization type of edge features :param with_residual: use residual link or not",
"name": "__init__",
"sig... | 2 | stack_v2_sparse_classes_30k_train_042154 | Implement the Python class `mp_conv_residual` described below.
Class description:
Implement the mp_conv_residual class.
Method signatures and docstrings:
- def __init__(self, nin, nmed, netype, extension=mp_conv_type.ORIG_WITH_DIFF, with_residual=True, with_hop=False): Residual block for graph conv network. :param ni... | Implement the Python class `mp_conv_residual` described below.
Class description:
Implement the mp_conv_residual class.
Method signatures and docstrings:
- def __init__(self, nin, nmed, netype, extension=mp_conv_type.ORIG_WITH_DIFF, with_residual=True, with_hop=False): Residual block for graph conv network. :param ni... | d7d480aa63d1e69cb94128610ec72938cc7873e8 | <|skeleton|>
class mp_conv_residual:
def __init__(self, nin, nmed, netype, extension=mp_conv_type.ORIG_WITH_DIFF, with_residual=True, with_hop=False):
"""Residual block for graph conv network. :param nin: number of input units :param nmed: number of units in the graph conv layer :param netype: number of ed... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class mp_conv_residual:
def __init__(self, nin, nmed, netype, extension=mp_conv_type.ORIG_WITH_DIFF, with_residual=True, with_hop=False):
"""Residual block for graph conv network. :param nin: number of input units :param nmed: number of units in the graph conv layer :param netype: number of edge types :para... | the_stack_v2_python_sparse | lib/mpnn/mp_nn_residual.py | richardodliu/Factor-Graph-Neural-Network | train | 0 | |
62ab12c509c4f0594b4c7b1dfffa017d440cca99 | [
"x = str(x)\nlength = len(x) // 2\nfor i in range(length):\n if x[i] != x[-(i + 1)]:\n return False\n i += 1\nreturn True",
"if x < 0:\n return False\ny, z = (x, 0)\nwhile y:\n z = z * 10 + y % 10\n y //= 10\nreturn y == x",
"if x < 0:\n return False\nranger = 1\nwhile x / ranger >= 10:... | <|body_start_0|>
x = str(x)
length = len(x) // 2
for i in range(length):
if x[i] != x[-(i + 1)]:
return False
i += 1
return True
<|end_body_0|>
<|body_start_1|>
if x < 0:
return False
y, z = (x, 0)
while y:
... | 给定一个数字，判断是否是回文数。（不能装换成字符串） Determine whether an integer is a palindrome. An integer is a palindrome when it reads the same backward as forward. Example 1: Input: 121 Output: true Example 2: Input: -121 Output: false Explanation: From left to right, it reads -121. From right to left, it becomes 121-. Therefore it is not... | PalindromeNumber | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PalindromeNumber:
"""给定一个数字，判断是否是回文数。（不能装换成字符串） Determine whether an integer is a palindrome. An integer is a palindrome when it reads the same backward as forward. Example 1: Input: 121 Output: true Example 2: Input: -121 Output: false Explanation: From left to right, it reads -121. From right t... | stack_v2_sparse_classes_75kplus_train_073494 | 2,017 | no_license | [
{
"docstring": "装换成字符串方式 :param x: int :rtype: bool",
"name": "symb",
"signature": "def symb(self, x)"
},
{
"docstring": "不转换成字符串 :param x: int :rtype: bool",
"name": "noConvertToStr",
"signature": "def noConvertToStr(self, x)"
},
{
"docstring": ":type x: int :rtype: bool",
"... | 3 | null | Implement the Python class `PalindromeNumber` described below.
Class description:
给定一个数字，判断是否是回文数。（不能装换成字符串） Determine whether an integer is a palindrome. An integer is a palindrome when it reads the same backward as forward. Example 1: Input: 121 Output: true Example 2: Input: -121 Output: false Explanation: From lef... | Implement the Python class `PalindromeNumber` described below.
Class description:
给定一个数字，判断是否是回文数。（不能装换成字符串） Determine whether an integer is a palindrome. An integer is a palindrome when it reads the same backward as forward. Example 1: Input: 121 Output: true Example 2: Input: -121 Output: false Explanation: From lef... | 7a6de1767eaabb6464ea4c90756606d59b868d7c | <|skeleton|>
class PalindromeNumber:
"""给定一个数字，判断是否是回文数。（不能装换成字符串） Determine whether an integer is a palindrome. An integer is a palindrome when it reads the same backward as forward. Example 1: Input: 121 Output: true Example 2: Input: -121 Output: false Explanation: From left to right, it reads -121. From right t... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PalindromeNumber:
"""给定一个数字，判断是否是回文数。（不能装换成字符串） Determine whether an integer is a palindrome. An integer is a palindrome when it reads the same backward as forward. Example 1: Input: 121 Output: true Example 2: Input: -121 Output: false Explanation: From left to right, it reads -121. From right to left, it be... | the_stack_v2_python_sparse | demo/9.PalindromeNumber.py | symbooo/LeetCodeSymb | train | 0 |
09d707a2eb39c19aa1b140514f7446f8baf7f4c0 | [
"for i, (k, hero_id) in enumerate(asdict(self).items()):\n if hero_id == -1:\n continue\n if i < 5:\n faction = 'Radiant'\n else:\n faction = 'Dire'\n if i >= 10:\n faction = ''\n print(f\"{faction:>7} {k}: {const.HERO_LOOKUP.from_offset(hero_id)['pretty_name']}\")",
"dr... | <|body_start_0|>
for i, (k, hero_id) in enumerate(asdict(self).items()):
if hero_id == -1:
continue
if i < 5:
faction = 'Radiant'
else:
faction = 'Dire'
if i >= 10:
faction = ''
print(f"{f... | Draft struct which represent the drafting state of the game | DraftStatus | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DraftStatus:
"""Draft struct which represent the drafting state of the game"""
def summary(self):
"""Examples -------- >>> draft = DraftStatus() >>> draft.Pick4 = 1 >>> draft.Ban01 = 2 >>> draft.Pick5 = 3 >>> draft.summary() Radiant Pick4: Axe Dire Pick5: Bloodseeker Dire Ban01: Bane... | stack_v2_sparse_classes_75kplus_train_073495 | 9,052 | permissive | [
{
"docstring": "Examples -------- >>> draft = DraftStatus() >>> draft.Pick4 = 1 >>> draft.Ban01 = 2 >>> draft.Pick5 = 3 >>> draft.summary() Radiant Pick4: Axe Dire Pick5: Bloodseeker Dire Ban01: Bane",
"name": "summary",
"signature": "def summary(self)"
},
{
"docstring": "Generate a one-hot enco... | 2 | stack_v2_sparse_classes_30k_train_031369 | Implement the Python class `DraftStatus` described below.
Class description:
Draft struct which represent the drafting state of the game
Method signatures and docstrings:
- def summary(self): Examples -------- >>> draft = DraftStatus() >>> draft.Pick4 = 1 >>> draft.Ban01 = 2 >>> draft.Pick5 = 3 >>> draft.summary() Ra... | Implement the Python class `DraftStatus` described below.
Class description:
Draft struct which represent the drafting state of the game
Method signatures and docstrings:
- def summary(self): Examples -------- >>> draft = DraftStatus() >>> draft.Pick4 = 1 >>> draft.Ban01 = 2 >>> draft.Pick5 = 3 >>> draft.summary() Ra... | bd0efd8fc2b064d6bf58993e59a6ad4ac6713b39 | <|skeleton|>
class DraftStatus:
"""Draft struct which represent the drafting state of the game"""
def summary(self):
"""Examples -------- >>> draft = DraftStatus() >>> draft.Pick4 = 1 >>> draft.Ban01 = 2 >>> draft.Pick5 = 3 >>> draft.summary() Radiant Pick4: Axe Dire Pick5: Bloodseeker Dire Ban01: Bane... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DraftStatus:
"""Draft struct which represent the drafting state of the game"""
def summary(self):
"""Examples -------- >>> draft = DraftStatus() >>> draft.Pick4 = 1 >>> draft.Ban01 = 2 >>> draft.Pick5 = 3 >>> draft.summary() Radiant Pick4: Axe Dire Pick5: Bloodseeker Dire Ban01: Bane"""
f... | the_stack_v2_python_sparse | luafun/draft.py | Delaunay/dota2env | train | 3 |
83f3204fa991a623d37f90d788c34e45f3827d20 | [
"cost_calc = cc.CostCalculator()\ncompressed_model_cost = cost_calc.compute_network_cost(compressed_layers)\nif cost_metric is CostMetric.memory:\n savings = network_cost.memory - compressed_model_cost.memory\n ratio = savings / network_cost.memory\nelse:\n savings = network_cost.mac - compressed_model_cos... | <|body_start_0|>
cost_calc = cc.CostCalculator()
compressed_model_cost = cost_calc.compute_network_cost(compressed_layers)
if cost_metric is CostMetric.memory:
savings = network_cost.memory - compressed_model_cost.memory
ratio = savings / network_cost.memory
else:... | A class for calculating the statistics for a model | ModelStats | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ModelStats:
"""A class for calculating the statistics for a model"""
def compute_compression_ratio(compressed_layers, cost_metric, network_cost):
"""Computes the compression ratio of a model :param compressed_layers: layers which are compressed :param cost_metric: cost metric is memo... | stack_v2_sparse_classes_75kplus_train_073496 | 4,927 | permissive | [
{
"docstring": "Computes the compression ratio of a model :param compressed_layers: layers which are compressed :param cost_metric: cost metric is memory or mac :param network_cost: mac and memory cost calculated for the entire network :return: It returns the compression ratio for a network",
"name": "compu... | 3 | stack_v2_sparse_classes_30k_train_051987 | Implement the Python class `ModelStats` described below.
Class description:
A class for calculating the statistics for a model
Method signatures and docstrings:
- def compute_compression_ratio(compressed_layers, cost_metric, network_cost): Computes the compression ratio of a model :param compressed_layers: layers whi... | Implement the Python class `ModelStats` described below.
Class description:
A class for calculating the statistics for a model
Method signatures and docstrings:
- def compute_compression_ratio(compressed_layers, cost_metric, network_cost): Computes the compression ratio of a model :param compressed_layers: layers whi... | 5a406e657082b6a4f6e4bf48f0e46e085cb1e351 | <|skeleton|>
class ModelStats:
"""A class for calculating the statistics for a model"""
def compute_compression_ratio(compressed_layers, cost_metric, network_cost):
"""Computes the compression ratio of a model :param compressed_layers: layers which are compressed :param cost_metric: cost metric is memo... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ModelStats:
"""A class for calculating the statistics for a model"""
def compute_compression_ratio(compressed_layers, cost_metric, network_cost):
"""Computes the compression ratio of a model :param compressed_layers: layers which are compressed :param cost_metric: cost metric is memory or mac :pa... | the_stack_v2_python_sparse | TrainingExtensions/torch/src/python/aimet_torch/svd/model_stats_calculator.py | quic/aimet | train | 1,676 |
b8e410bd007bb3e40d6c70652a925be9743f85c6 | [
"current_graph = _ops.get_default_graph()\nassert current_graph, 'A channel is scoped within a tf.Graph'\nself._dtype = dtype\nself._send_device = send_device\nself._recv_device = recv_device\nself._name = current_graph.unique_name(name if name else 'channel')\nassert shape is not None\nshape = _tensor_shape.Tensor... | <|body_start_0|>
current_graph = _ops.get_default_graph()
assert current_graph, 'A channel is scoped within a tf.Graph'
self._dtype = dtype
self._send_device = send_device
self._recv_device = recv_device
self._name = current_graph.unique_name(name if name else 'channel')
... | A communication channel to transfer tensors in order. | Channel | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Channel:
"""A communication channel to transfer tensors in order."""
def __init__(self, dtype, shape, send_device, recv_device, name=None):
"""Construct a channel. Args: dtype: The dtype of tensors sent through the channel. shape: The shape of tensors sent through the channel. Must b... | stack_v2_sparse_classes_75kplus_train_073497 | 8,532 | permissive | [
{
"docstring": "Construct a channel. Args: dtype: The dtype of tensors sent through the channel. shape: The shape of tensors sent through the channel. Must be a fully defined shape for TPUs. send_device: A fully-specified tensorflow device. recv_device: A fully-specified tensorflow device. name: A name for the ... | 3 | stack_v2_sparse_classes_30k_train_026805 | Implement the Python class `Channel` described below.
Class description:
A communication channel to transfer tensors in order.
Method signatures and docstrings:
- def __init__(self, dtype, shape, send_device, recv_device, name=None): Construct a channel. Args: dtype: The dtype of tensors sent through the channel. sha... | Implement the Python class `Channel` described below.
Class description:
A communication channel to transfer tensors in order.
Method signatures and docstrings:
- def __init__(self, dtype, shape, send_device, recv_device, name=None): Construct a channel. Args: dtype: The dtype of tensors sent through the channel. sha... | 2441edc7fee78903502ebd528ab4dc309db0001d | <|skeleton|>
class Channel:
"""A communication channel to transfer tensors in order."""
def __init__(self, dtype, shape, send_device, recv_device, name=None):
"""Construct a channel. Args: dtype: The dtype of tensors sent through the channel. shape: The shape of tensors sent through the channel. Must b... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Channel:
"""A communication channel to transfer tensors in order."""
def __init__(self, dtype, shape, send_device, recv_device, name=None):
"""Construct a channel. Args: dtype: The dtype of tensors sent through the channel. shape: The shape of tensors sent through the channel. Must be a fully def... | the_stack_v2_python_sparse | lingvo/core/sendrecv.py | yaq007/lingvo | train | 4 |
a382d535819289cbc09352fc4023e17f6cd869e8 | [
"if not nums:\n return\nmax_num = max(nums)\nmax_index = nums.index(max_num)\nroot = TreeNode(max_num)\nroot.left = self.constructMaximumBinaryTree(nums[:max_index])\nroot.right = self.constructMaximumBinaryTree(nums[max_index + 1:])\nreturn root",
"stack = []\nleft = None\nroot = None\nnums.append(float('inf'... | <|body_start_0|>
if not nums:
return
max_num = max(nums)
max_index = nums.index(max_num)
root = TreeNode(max_num)
root.left = self.constructMaximumBinaryTree(nums[:max_index])
root.right = self.constructMaximumBinaryTree(nums[max_index + 1:])
return ro... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def _constructMaximumBinaryTree(self, nums):
""":type nums: List[int] :rtype: TreeNode"""
<|body_0|>
def __constructMaximumBinaryTree(self, nums):
""":type nums: List[int] :rtype: TreeNode"""
<|body_1|>
def ___constructMaximumBinaryTree(self, n... | stack_v2_sparse_classes_75kplus_train_073498 | 4,039 | permissive | [
{
"docstring": ":type nums: List[int] :rtype: TreeNode",
"name": "_constructMaximumBinaryTree",
"signature": "def _constructMaximumBinaryTree(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: TreeNode",
"name": "__constructMaximumBinaryTree",
"signature": "def __constructMaxi... | 4 | stack_v2_sparse_classes_30k_train_031797 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def _constructMaximumBinaryTree(self, nums): :type nums: List[int] :rtype: TreeNode
- def __constructMaximumBinaryTree(self, nums): :type nums: List[int] :rtype: TreeNode
- def _... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def _constructMaximumBinaryTree(self, nums): :type nums: List[int] :rtype: TreeNode
- def __constructMaximumBinaryTree(self, nums): :type nums: List[int] :rtype: TreeNode
- def _... | 0dd67edca4e0b0323cb5a7239f02ea46383cd15a | <|skeleton|>
class Solution:
def _constructMaximumBinaryTree(self, nums):
""":type nums: List[int] :rtype: TreeNode"""
<|body_0|>
def __constructMaximumBinaryTree(self, nums):
""":type nums: List[int] :rtype: TreeNode"""
<|body_1|>
def ___constructMaximumBinaryTree(self, n... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def _constructMaximumBinaryTree(self, nums):
""":type nums: List[int] :rtype: TreeNode"""
if not nums:
return
max_num = max(nums)
max_index = nums.index(max_num)
root = TreeNode(max_num)
root.left = self.constructMaximumBinaryTree(nums[:max... | the_stack_v2_python_sparse | 654.maximum-binary-tree.py | windard/leeeeee | train | 0 | |
29f9e77c9dd029e8d3b8fea2a9ea71203365d02a | [
"status = ErrorCode.SUCCESS\ntry:\n tid = self.get_argument('tid')\nexcept Exception as e:\n status = ErrorCode.ILLEGAL_DATA_FORMAT\n logging.exception('[UWEB] Invalid data format. Exception: %s', e.args)\n self.write_ret(status)\n return\ntry:\n res = QueryHelper.get_bind_single(tid, self.db)\n ... | <|body_start_0|>
status = ErrorCode.SUCCESS
try:
tid = self.get_argument('tid')
except Exception as e:
status = ErrorCode.ILLEGAL_DATA_FORMAT
logging.exception('[UWEB] Invalid data format. Exception: %s', e.args)
self.write_ret(status)
... | Handle singles-bind for corp. :url /bindsingle | BindSingleHandler | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BindSingleHandler:
"""Handle singles-bind for corp. :url /bindsingle"""
def get(self):
"""Get all singles binded by the terminal."""
<|body_0|>
def post(self):
"""Handle single bind."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
status = Error... | stack_v2_sparse_classes_75kplus_train_073499 | 2,433 | no_license | [
{
"docstring": "Get all singles binded by the terminal.",
"name": "get",
"signature": "def get(self)"
},
{
"docstring": "Handle single bind.",
"name": "post",
"signature": "def post(self)"
}
] | 2 | null | Implement the Python class `BindSingleHandler` described below.
Class description:
Handle singles-bind for corp. :url /bindsingle
Method signatures and docstrings:
- def get(self): Get all singles binded by the terminal.
- def post(self): Handle single bind. | Implement the Python class `BindSingleHandler` described below.
Class description:
Handle singles-bind for corp. :url /bindsingle
Method signatures and docstrings:
- def get(self): Get all singles binded by the terminal.
- def post(self): Handle single bind.
<|skeleton|>
class BindSingleHandler:
"""Handle single... | 3b095a325581b1fc48497c234f0ad55e928586a1 | <|skeleton|>
class BindSingleHandler:
"""Handle singles-bind for corp. :url /bindsingle"""
def get(self):
"""Get all singles binded by the terminal."""
<|body_0|>
def post(self):
"""Handle single bind."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class BindSingleHandler:
"""Handle singles-bind for corp. :url /bindsingle"""
def get(self):
"""Get all singles binded by the terminal."""
status = ErrorCode.SUCCESS
try:
tid = self.get_argument('tid')
except Exception as e:
status = ErrorCode.ILLEGAL_DAT... | the_stack_v2_python_sparse | apps/uweb/handlers/bindsingle.py | jcsy521/ydws | train | 0 |
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