blob_id stringlengths 40 40 | bodies listlengths 2 6 | bodies_text stringlengths 196 6.73k | class_docstring stringlengths 0 700 | class_name stringlengths 1 86 | detected_licenses listlengths 0 45 | format_version stringclasses 1
value | full_text stringlengths 438 7.52k | id stringlengths 40 40 | length_bytes int64 506 50k | license_type stringclasses 2
values | methods listlengths 2 6 | n_methods int64 2 6 | original_id stringlengths 38 40 ⌀ | prompt stringlengths 153 4.25k | prompted_full_text stringlengths 645 10.7k | revision_id stringlengths 40 40 | skeleton stringlengths 162 4.34k | snapshot_name stringclasses 1
value | snapshot_source_dir stringclasses 1
value | solution stringlengths 302 7.33k | source stringclasses 1
value | source_path stringlengths 4 177 | source_repo stringlengths 6 110 | split stringclasses 1
value | star_events_count int64 0 209k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
6fc43cc5de2f4eb3942f4a340d9281a9dffb19cf | [
"levels = []\nif not root:\n return levels\n\ndef helper(node, level):\n if len(levels) == level:\n levels.append([])\n levels[level].append(node.val)\n if node.left:\n helper(node.left, level + 1)\n if node.right:\n helper(node.right, level + 1)\nhelper(root, 0)\nreturn levels[:... | <|body_start_0|>
levels = []
if not root:
return levels
def helper(node, level):
if len(levels) == level:
levels.append([])
levels[level].append(node.val)
if node.left:
helper(node.left, level + 1)
if no... | Tree | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Tree:
def traversal_(self, root: 'TreeNode') -> List[int]:
"""Approach: Recursion Time Complexity: O(N) Space Complexity: O(N) :param root: :return:"""
<|body_0|>
def traversal(self, root: 'TreeNode') -> List[int]:
"""Approach: Iterative/ BFS Time Complexity: O(N) Sp... | stack_v2_sparse_classes_36k_train_002200 | 1,516 | no_license | [
{
"docstring": "Approach: Recursion Time Complexity: O(N) Space Complexity: O(N) :param root: :return:",
"name": "traversal_",
"signature": "def traversal_(self, root: 'TreeNode') -> List[int]"
},
{
"docstring": "Approach: Iterative/ BFS Time Complexity: O(N) Space Complexity: O(N) :param root: ... | 2 | stack_v2_sparse_classes_30k_train_002747 | Implement the Python class `Tree` described below.
Class description:
Implement the Tree class.
Method signatures and docstrings:
- def traversal_(self, root: 'TreeNode') -> List[int]: Approach: Recursion Time Complexity: O(N) Space Complexity: O(N) :param root: :return:
- def traversal(self, root: 'TreeNode') -> Lis... | Implement the Python class `Tree` described below.
Class description:
Implement the Tree class.
Method signatures and docstrings:
- def traversal_(self, root: 'TreeNode') -> List[int]: Approach: Recursion Time Complexity: O(N) Space Complexity: O(N) :param root: :return:
- def traversal(self, root: 'TreeNode') -> Lis... | 65cc78b5afa0db064f9fe8f06597e3e120f7363d | <|skeleton|>
class Tree:
def traversal_(self, root: 'TreeNode') -> List[int]:
"""Approach: Recursion Time Complexity: O(N) Space Complexity: O(N) :param root: :return:"""
<|body_0|>
def traversal(self, root: 'TreeNode') -> List[int]:
"""Approach: Iterative/ BFS Time Complexity: O(N) Sp... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Tree:
def traversal_(self, root: 'TreeNode') -> List[int]:
"""Approach: Recursion Time Complexity: O(N) Space Complexity: O(N) :param root: :return:"""
levels = []
if not root:
return levels
def helper(node, level):
if len(levels) == level:
... | the_stack_v2_python_sparse | revisited_2021/tree/bst_level_order_traversal.py | Shiv2157k/leet_code | train | 1 | |
ef10982b6e273e7456dff909c70456075cd34d19 | [
"logs.log_info('You are using the vgK channel: Kv1p6 ')\nself.time_unit = 1000.0\nself.vrev = -65\nself.m = 1 / (1 + np.exp((V - -20.8) / -8.1))\nself.h = 1 / (1 + np.exp((V - -22.0) / 11.39))\nself._mpower = 1\nself._hpower = 1",
"self._mInf = 1 / (1 + np.exp((V - -20.8) / -8.1))\nself._mTau = 30.0 / (1 + np.exp... | <|body_start_0|>
logs.log_info('You are using the vgK channel: Kv1p6 ')
self.time_unit = 1000.0
self.vrev = -65
self.m = 1 / (1 + np.exp((V - -20.8) / -8.1))
self.h = 1 / (1 + np.exp((V - -22.0) / 11.39))
self._mpower = 1
self._hpower = 1
<|end_body_0|>
<|body_st... | Kv1.6 model from Grupe et al. 1990. Reference: A Grupe et. al; EMBO J. 1990 Jun | Kv1p6 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Kv1p6:
"""Kv1.6 model from Grupe et al. 1990. Reference: A Grupe et. al; EMBO J. 1990 Jun"""
def _init_state(self, V):
"""Run initialization calculation for m and h gates of the channel at starting Vmem value."""
<|body_0|>
def _calculate_state(self, V):
"""Updat... | stack_v2_sparse_classes_36k_train_002201 | 24,227 | no_license | [
{
"docstring": "Run initialization calculation for m and h gates of the channel at starting Vmem value.",
"name": "_init_state",
"signature": "def _init_state(self, V)"
},
{
"docstring": "Update the state of m and h gates of the channel given their present value and present simulation Vmem.",
... | 2 | null | Implement the Python class `Kv1p6` described below.
Class description:
Kv1.6 model from Grupe et al. 1990. Reference: A Grupe et. al; EMBO J. 1990 Jun
Method signatures and docstrings:
- def _init_state(self, V): Run initialization calculation for m and h gates of the channel at starting Vmem value.
- def _calculate_... | Implement the Python class `Kv1p6` described below.
Class description:
Kv1.6 model from Grupe et al. 1990. Reference: A Grupe et. al; EMBO J. 1990 Jun
Method signatures and docstrings:
- def _init_state(self, V): Run initialization calculation for m and h gates of the channel at starting Vmem value.
- def _calculate_... | dd03ff5e3df3ef48d887a6566a6286fcd168880b | <|skeleton|>
class Kv1p6:
"""Kv1.6 model from Grupe et al. 1990. Reference: A Grupe et. al; EMBO J. 1990 Jun"""
def _init_state(self, V):
"""Run initialization calculation for m and h gates of the channel at starting Vmem value."""
<|body_0|>
def _calculate_state(self, V):
"""Updat... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Kv1p6:
"""Kv1.6 model from Grupe et al. 1990. Reference: A Grupe et. al; EMBO J. 1990 Jun"""
def _init_state(self, V):
"""Run initialization calculation for m and h gates of the channel at starting Vmem value."""
logs.log_info('You are using the vgK channel: Kv1p6 ')
self.time_uni... | the_stack_v2_python_sparse | betse/science/channels/vg_k.py | R-Stefano/betse-ml | train | 0 |
bffb5b2ec43fe0dda7a7121250061023acb31905 | [
"assert logits.size() == labels.size() and logits.dim() == 2\nloss = soft_dice_cpp.soft_dice_forward(logits, labels, p, smooth)\nctx.vars = (logits, labels, p, smooth)\nreturn loss",
"logits, labels, p, smooth = ctx.vars\ngrads = soft_dice_cpp.soft_dice_backward(grad_output, logits, labels, p, smooth)\nreturn (gr... | <|body_start_0|>
assert logits.size() == labels.size() and logits.dim() == 2
loss = soft_dice_cpp.soft_dice_forward(logits, labels, p, smooth)
ctx.vars = (logits, labels, p, smooth)
return loss
<|end_body_0|>
<|body_start_1|>
logits, labels, p, smooth = ctx.vars
grads = ... | compute backward directly for better numeric stability | SoftDiceLossV3Func | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SoftDiceLossV3Func:
"""compute backward directly for better numeric stability"""
def forward(ctx, logits, labels, p, smooth):
"""inputs: logits: (N, L) labels: (N, L) outpus: loss: (N,)"""
<|body_0|>
def backward(ctx, grad_output):
"""compute gradient of soft-dic... | stack_v2_sparse_classes_36k_train_002202 | 7,172 | permissive | [
{
"docstring": "inputs: logits: (N, L) labels: (N, L) outpus: loss: (N,)",
"name": "forward",
"signature": "def forward(ctx, logits, labels, p, smooth)"
},
{
"docstring": "compute gradient of soft-dice loss",
"name": "backward",
"signature": "def backward(ctx, grad_output)"
}
] | 2 | stack_v2_sparse_classes_30k_train_004968 | Implement the Python class `SoftDiceLossV3Func` described below.
Class description:
compute backward directly for better numeric stability
Method signatures and docstrings:
- def forward(ctx, logits, labels, p, smooth): inputs: logits: (N, L) labels: (N, L) outpus: loss: (N,)
- def backward(ctx, grad_output): compute... | Implement the Python class `SoftDiceLossV3Func` described below.
Class description:
compute backward directly for better numeric stability
Method signatures and docstrings:
- def forward(ctx, logits, labels, p, smooth): inputs: logits: (N, L) labels: (N, L) outpus: loss: (N,)
- def backward(ctx, grad_output): compute... | 99e04f64fb2ce46c2e6906750a716b93984fbe97 | <|skeleton|>
class SoftDiceLossV3Func:
"""compute backward directly for better numeric stability"""
def forward(ctx, logits, labels, p, smooth):
"""inputs: logits: (N, L) labels: (N, L) outpus: loss: (N,)"""
<|body_0|>
def backward(ctx, grad_output):
"""compute gradient of soft-dic... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SoftDiceLossV3Func:
"""compute backward directly for better numeric stability"""
def forward(ctx, logits, labels, p, smooth):
"""inputs: logits: (N, L) labels: (N, L) outpus: loss: (N,)"""
assert logits.size() == labels.size() and logits.dim() == 2
loss = soft_dice_cpp.soft_dice_f... | the_stack_v2_python_sparse | soft_dice_loss.py | CoinCheung/pytorch-loss | train | 2,079 |
4986d7562765fae465ddffef852a0071fca82fc4 | [
"conv_dt = naive.astimezone(pytz.timezone(tz)).strftime('%Y-%m-%d %H:%M:%S')\nlogger.logic_log('LOSI13022', tz, naive, conv_dt, request=request)\nreturn conv_dt",
"tz_ex = pytz.timezone(tz)\nnaive = naive.replace('/', '-')\nuser_dt = datetime.datetime.strptime(naive, '%Y-%m-%d %H:%M:%S')\ncou_dt = tz_ex.localize(... | <|body_start_0|>
conv_dt = naive.astimezone(pytz.timezone(tz)).strftime('%Y-%m-%d %H:%M:%S')
logger.logic_log('LOSI13022', tz, naive, conv_dt, request=request)
return conv_dt
<|end_body_0|>
<|body_start_1|>
tz_ex = pytz.timezone(tz)
naive = naive.replace('/', '-')
user_d... | TimeConversion | [
"Apache-2.0",
"BSD-3-Clause",
"LGPL-3.0-only",
"MIT",
"LicenseRef-scancode-public-domain"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TimeConversion:
def get_time_conversion(cls, naive, tz, request=None):
"""[概要] 時刻変換処理を行う [戻り値] 変換した時刻"""
<|body_0|>
def get_time_conversion_utc(cls, naive, tz, request=None):
"""[概要] 時刻変換処理を行う [戻り値] utc_dt : 変換した時刻(UTC)"""
<|body_1|>
<|end_skeleton|>
<|body... | stack_v2_sparse_classes_36k_train_002203 | 9,642 | permissive | [
{
"docstring": "[概要] 時刻変換処理を行う [戻り値] 変換した時刻",
"name": "get_time_conversion",
"signature": "def get_time_conversion(cls, naive, tz, request=None)"
},
{
"docstring": "[概要] 時刻変換処理を行う [戻り値] utc_dt : 変換した時刻(UTC)",
"name": "get_time_conversion_utc",
"signature": "def get_time_conversion_utc(cl... | 2 | stack_v2_sparse_classes_30k_train_012301 | Implement the Python class `TimeConversion` described below.
Class description:
Implement the TimeConversion class.
Method signatures and docstrings:
- def get_time_conversion(cls, naive, tz, request=None): [概要] 時刻変換処理を行う [戻り値] 変換した時刻
- def get_time_conversion_utc(cls, naive, tz, request=None): [概要] 時刻変換処理を行う [戻り値] u... | Implement the Python class `TimeConversion` described below.
Class description:
Implement the TimeConversion class.
Method signatures and docstrings:
- def get_time_conversion(cls, naive, tz, request=None): [概要] 時刻変換処理を行う [戻り値] 変換した時刻
- def get_time_conversion_utc(cls, naive, tz, request=None): [概要] 時刻変換処理を行う [戻り値] u... | c00ea4fe1bf4b4a18d545aabeaaf1d95c7664b94 | <|skeleton|>
class TimeConversion:
def get_time_conversion(cls, naive, tz, request=None):
"""[概要] 時刻変換処理を行う [戻り値] 変換した時刻"""
<|body_0|>
def get_time_conversion_utc(cls, naive, tz, request=None):
"""[概要] 時刻変換処理を行う [戻り値] utc_dt : 変換した時刻(UTC)"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TimeConversion:
def get_time_conversion(cls, naive, tz, request=None):
"""[概要] 時刻変換処理を行う [戻り値] 変換した時刻"""
conv_dt = naive.astimezone(pytz.timezone(tz)).strftime('%Y-%m-%d %H:%M:%S')
logger.logic_log('LOSI13022', tz, naive, conv_dt, request=request)
return conv_dt
def get_ti... | the_stack_v2_python_sparse | oase-root/libs/webcommonlibs/common.py | exastro-suite/oase | train | 10 | |
fe4f4fbf0dc7df80f50bafb7bf083f1a1e9d6f1e | [
"super(AttachFile, self).__init__(**kwargs)\nself.dirty_path = os.path.expanduser(path)\nreturn",
"params = {}\nif self._mimetype:\n params['mime'] = self._mimetype\nif self._name:\n params['name'] = self._name\nreturn 'file://{path}{params}'.format(path=self.quote(self.dirty_path), params='?{}'.format(self... | <|body_start_0|>
super(AttachFile, self).__init__(**kwargs)
self.dirty_path = os.path.expanduser(path)
return
<|end_body_0|>
<|body_start_1|>
params = {}
if self._mimetype:
params['mime'] = self._mimetype
if self._name:
params['name'] = self._name... | A wrapper for File based attachment sources | AttachFile | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AttachFile:
"""A wrapper for File based attachment sources"""
def __init__(self, path, **kwargs):
"""Initialize Local File Attachment Object"""
<|body_0|>
def url(self, privacy=False, *args, **kwargs):
"""Returns the URL built dynamically based on specified argum... | stack_v2_sparse_classes_36k_train_002204 | 4,260 | permissive | [
{
"docstring": "Initialize Local File Attachment Object",
"name": "__init__",
"signature": "def __init__(self, path, **kwargs)"
},
{
"docstring": "Returns the URL built dynamically based on specified arguments.",
"name": "url",
"signature": "def url(self, privacy=False, *args, **kwargs)"... | 4 | stack_v2_sparse_classes_30k_train_014842 | Implement the Python class `AttachFile` described below.
Class description:
A wrapper for File based attachment sources
Method signatures and docstrings:
- def __init__(self, path, **kwargs): Initialize Local File Attachment Object
- def url(self, privacy=False, *args, **kwargs): Returns the URL built dynamically bas... | Implement the Python class `AttachFile` described below.
Class description:
A wrapper for File based attachment sources
Method signatures and docstrings:
- def __init__(self, path, **kwargs): Initialize Local File Attachment Object
- def url(self, privacy=False, *args, **kwargs): Returns the URL built dynamically bas... | 784e073eea64d2ee37cc52e7a2391bce35b05720 | <|skeleton|>
class AttachFile:
"""A wrapper for File based attachment sources"""
def __init__(self, path, **kwargs):
"""Initialize Local File Attachment Object"""
<|body_0|>
def url(self, privacy=False, *args, **kwargs):
"""Returns the URL built dynamically based on specified argum... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AttachFile:
"""A wrapper for File based attachment sources"""
def __init__(self, path, **kwargs):
"""Initialize Local File Attachment Object"""
super(AttachFile, self).__init__(**kwargs)
self.dirty_path = os.path.expanduser(path)
return
def url(self, privacy=False, *a... | the_stack_v2_python_sparse | apprise/attachment/AttachFile.py | raman325/apprise | train | 1 |
14ebbb9fbe80ef81332110dc2a3416b7b6b3f6f5 | [
"self._attr_entity_category = EntityCategory.DIAGNOSTIC\nself.entity_domain = ENTITY_DOMAIN\nsuper().__init__(config_entry=config_entry, coordinator=coordinator, description=description)",
"if self.coordinator.data:\n if self.entity_description.state_value:\n return self.entity_description.state_value(s... | <|body_start_0|>
self._attr_entity_category = EntityCategory.DIAGNOSTIC
self.entity_domain = ENTITY_DOMAIN
super().__init__(config_entry=config_entry, coordinator=coordinator, description=description)
<|end_body_0|>
<|body_start_1|>
if self.coordinator.data:
if self.entity_d... | Representation of a binary sensor. | HDHomerunBinarySensor | [
"Unlicense"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HDHomerunBinarySensor:
"""Representation of a binary sensor."""
def __init__(self, config_entry: ConfigEntry, coordinator: DataUpdateCoordinator, description: HDHomerunBinarySensorEntityDescription) -> None:
"""Initialise."""
<|body_0|>
def is_on(self) -> bool:
"... | stack_v2_sparse_classes_36k_train_002205 | 10,682 | permissive | [
{
"docstring": "Initialise.",
"name": "__init__",
"signature": "def __init__(self, config_entry: ConfigEntry, coordinator: DataUpdateCoordinator, description: HDHomerunBinarySensorEntityDescription) -> None"
},
{
"docstring": "Return if the service is on.",
"name": "is_on",
"signature": ... | 2 | stack_v2_sparse_classes_30k_train_018015 | Implement the Python class `HDHomerunBinarySensor` described below.
Class description:
Representation of a binary sensor.
Method signatures and docstrings:
- def __init__(self, config_entry: ConfigEntry, coordinator: DataUpdateCoordinator, description: HDHomerunBinarySensorEntityDescription) -> None: Initialise.
- de... | Implement the Python class `HDHomerunBinarySensor` described below.
Class description:
Representation of a binary sensor.
Method signatures and docstrings:
- def __init__(self, config_entry: ConfigEntry, coordinator: DataUpdateCoordinator, description: HDHomerunBinarySensorEntityDescription) -> None: Initialise.
- de... | 8548d9999ddd54f13d6a307e013abcb8c897a74e | <|skeleton|>
class HDHomerunBinarySensor:
"""Representation of a binary sensor."""
def __init__(self, config_entry: ConfigEntry, coordinator: DataUpdateCoordinator, description: HDHomerunBinarySensorEntityDescription) -> None:
"""Initialise."""
<|body_0|>
def is_on(self) -> bool:
"... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class HDHomerunBinarySensor:
"""Representation of a binary sensor."""
def __init__(self, config_entry: ConfigEntry, coordinator: DataUpdateCoordinator, description: HDHomerunBinarySensorEntityDescription) -> None:
"""Initialise."""
self._attr_entity_category = EntityCategory.DIAGNOSTIC
... | the_stack_v2_python_sparse | custom_components/hdhomerun/binary_sensor.py | bacco007/HomeAssistantConfig | train | 98 |
ec2e87e055675cf26e17f8200c9f425fec1eadab | [
"data = parameter_required(('user_name', 'user_password'))\nuser = an_user.query.filter(an_user.isdelete == '0', an_user.user_name == data.get('user_name')).first_('未找到该账号或该账号被禁用')\nhash_password = hashlib.md5(data.get('user_password').encode('utf-8'))\nif user and hash_password.hexdigest() == user.user_password:\n... | <|body_start_0|>
data = parameter_required(('user_name', 'user_password'))
user = an_user.query.filter(an_user.isdelete == '0', an_user.user_name == data.get('user_name')).first_('未找到该账号或该账号被禁用')
hash_password = hashlib.md5(data.get('user_password').encode('utf-8'))
if user and hash_pass... | CUser | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CUser:
def user_login(self):
"""用户登录"""
<|body_0|>
def user_password_repeat(self):
"""用户修改密码"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
data = parameter_required(('user_name', 'user_password'))
user = an_user.query.filter(an_user.isdele... | stack_v2_sparse_classes_36k_train_002206 | 2,568 | permissive | [
{
"docstring": "用户登录",
"name": "user_login",
"signature": "def user_login(self)"
},
{
"docstring": "用户修改密码",
"name": "user_password_repeat",
"signature": "def user_password_repeat(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_012241 | Implement the Python class `CUser` described below.
Class description:
Implement the CUser class.
Method signatures and docstrings:
- def user_login(self): 用户登录
- def user_password_repeat(self): 用户修改密码 | Implement the Python class `CUser` described below.
Class description:
Implement the CUser class.
Method signatures and docstrings:
- def user_login(self): 用户登录
- def user_password_repeat(self): 用户修改密码
<|skeleton|>
class CUser:
def user_login(self):
"""用户登录"""
<|body_0|>
def user_password_r... | 37a9b0d6e7a3f110ba9285a3715fec2e30bdd7d2 | <|skeleton|>
class CUser:
def user_login(self):
"""用户登录"""
<|body_0|>
def user_password_repeat(self):
"""用户修改密码"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CUser:
def user_login(self):
"""用户登录"""
data = parameter_required(('user_name', 'user_password'))
user = an_user.query.filter(an_user.isdelete == '0', an_user.user_name == data.get('user_name')).first_('未找到该账号或该账号被禁用')
hash_password = hashlib.md5(data.get('user_password').encod... | the_stack_v2_python_sparse | FanstiBgs/control/CUser.py | haobin12358/FanstiBgs | train | 0 | |
a810f7d73afe68b72a8c17cce7cdc34c888b8b6f | [
"self.model = model\nself.mode = mode\nself.epsilon = epsilon\nself.k = k\nself.a = a\nself.rand = random_start\nself.loss_fn = nn.CrossEntropyLoss()\nself.device = torch.device('cuda:0' if torch.cuda.is_available() else 'cpu')\nself.pert_box = pert_box\nself.x_box_min, self.x_box_max = (x_box_min, x_box_max)",
"... | <|body_start_0|>
self.model = model
self.mode = mode
self.epsilon = epsilon
self.k = k
self.a = a
self.rand = random_start
self.loss_fn = nn.CrossEntropyLoss()
self.device = torch.device('cuda:0' if torch.cuda.is_available() else 'cpu')
self.pert_b... | LinfPGDAttack | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LinfPGDAttack:
def __init__(self, mode, x_box_min=-1, x_box_max=0, pert_box=0.3, model=None, epsilon=0.3, k=40, a=0.01, random_start=True):
"""Attack parameter initialization. The attack performs k steps of size a, while always staying within epsilon from the initial point. https://githu... | stack_v2_sparse_classes_36k_train_002207 | 9,669 | no_license | [
{
"docstring": "Attack parameter initialization. The attack performs k steps of size a, while always staying within epsilon from the initial point. https://github.com/MadryLab/mnist_challenge/blob/master/pgd_attack.py",
"name": "__init__",
"signature": "def __init__(self, mode, x_box_min=-1, x_box_max=0... | 2 | null | Implement the Python class `LinfPGDAttack` described below.
Class description:
Implement the LinfPGDAttack class.
Method signatures and docstrings:
- def __init__(self, mode, x_box_min=-1, x_box_max=0, pert_box=0.3, model=None, epsilon=0.3, k=40, a=0.01, random_start=True): Attack parameter initialization. The attack... | Implement the Python class `LinfPGDAttack` described below.
Class description:
Implement the LinfPGDAttack class.
Method signatures and docstrings:
- def __init__(self, mode, x_box_min=-1, x_box_max=0, pert_box=0.3, model=None, epsilon=0.3, k=40, a=0.01, random_start=True): Attack parameter initialization. The attack... | 24aa157bfaee452a5f0312f422c0c385c363d293 | <|skeleton|>
class LinfPGDAttack:
def __init__(self, mode, x_box_min=-1, x_box_max=0, pert_box=0.3, model=None, epsilon=0.3, k=40, a=0.01, random_start=True):
"""Attack parameter initialization. The attack performs k steps of size a, while always staying within epsilon from the initial point. https://githu... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LinfPGDAttack:
def __init__(self, mode, x_box_min=-1, x_box_max=0, pert_box=0.3, model=None, epsilon=0.3, k=40, a=0.01, random_start=True):
"""Attack parameter initialization. The attack performs k steps of size a, while always staying within epsilon from the initial point. https://github.com/MadryLab... | the_stack_v2_python_sparse | attacks/white_box/adv_box/attacks.py | SmartHomePrivacyProject/AdversarialTraffic | train | 2 | |
694cdef58bb4ac0a8809736306c74c5e562104e2 | [
"self.counter = 0\nself.parent = [[0 for j in range(n)] for i in range(m)]\nfor i in range(m):\n for j in range(n):\n if grid[i][j] == '1':\n self.counter += 1\n self.parent[i][j] = (i, j)",
"while self.parent[x][y] != (x, y):\n parent_x, parent_y = self.parent[x][y]\n self.p... | <|body_start_0|>
self.counter = 0
self.parent = [[0 for j in range(n)] for i in range(m)]
for i in range(m):
for j in range(n):
if grid[i][j] == '1':
self.counter += 1
self.parent[i][j] = (i, j)
<|end_body_0|>
<|body_start_1|>
... | UF | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UF:
def __init__(self, m, n, grid):
"""m row n colomn grid"""
<|body_0|>
def find(self, x, y):
"""find the root and do path compression in the mean time"""
<|body_1|>
def union(self, x, y, i, j):
"""union (x, y) and (i, j)"""
<|body_2|>
... | stack_v2_sparse_classes_36k_train_002208 | 9,064 | no_license | [
{
"docstring": "m row n colomn grid",
"name": "__init__",
"signature": "def __init__(self, m, n, grid)"
},
{
"docstring": "find the root and do path compression in the mean time",
"name": "find",
"signature": "def find(self, x, y)"
},
{
"docstring": "union (x, y) and (i, j)",
... | 3 | null | Implement the Python class `UF` described below.
Class description:
Implement the UF class.
Method signatures and docstrings:
- def __init__(self, m, n, grid): m row n colomn grid
- def find(self, x, y): find the root and do path compression in the mean time
- def union(self, x, y, i, j): union (x, y) and (i, j) | Implement the Python class `UF` described below.
Class description:
Implement the UF class.
Method signatures and docstrings:
- def __init__(self, m, n, grid): m row n colomn grid
- def find(self, x, y): find the root and do path compression in the mean time
- def union(self, x, y, i, j): union (x, y) and (i, j)
<|s... | abb19fa2859634f5260d439812525bb14399ae55 | <|skeleton|>
class UF:
def __init__(self, m, n, grid):
"""m row n colomn grid"""
<|body_0|>
def find(self, x, y):
"""find the root and do path compression in the mean time"""
<|body_1|>
def union(self, x, y, i, j):
"""union (x, y) and (i, j)"""
<|body_2|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UF:
def __init__(self, m, n, grid):
"""m row n colomn grid"""
self.counter = 0
self.parent = [[0 for j in range(n)] for i in range(m)]
for i in range(m):
for j in range(n):
if grid[i][j] == '1':
self.counter += 1
... | the_stack_v2_python_sparse | graph/200.number-of-islands.py | caitaozhan/LeetCode | train | 6 | |
c42145706873c6a924e3ab932bfa5561ad9c93c1 | [
"if middle and stranded:\n pickleFileStr = self.fbBasename() + '_mid_strand.pick'\nelif middle:\n pickleFileStr = self.fbBasename() + '_mid.pick'\nelif stranded:\n pickleFileStr = self.fbBasename() + '_strand.pick'\nelse:\n pickleFileStr = self.fbBasename() + '.pick'\nfileExists = os.path.isfile(pickleF... | <|body_start_0|>
if middle and stranded:
pickleFileStr = self.fbBasename() + '_mid_strand.pick'
elif middle:
pickleFileStr = self.fbBasename() + '_mid.pick'
elif stranded:
pickleFileStr = self.fbBasename() + '_strand.pick'
else:
pickleFileS... | stores information about the start or midpoint of read | FileBED | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FileBED:
"""stores information about the start or midpoint of read"""
def getBedDict(self, middle=False, stranded=False):
"""return dictionary where key is chromosome, value is dictionary that dictionary has positions as key and value is number of reads that cover the position dictio... | stack_v2_sparse_classes_36k_train_002209 | 22,678 | no_license | [
{
"docstring": "return dictionary where key is chromosome, value is dictionary that dictionary has positions as key and value is number of reads that cover the position dictionary contains key '##counts##' that stores total number of reads in library",
"name": "getBedDict",
"signature": "def getBedDict(... | 3 | null | Implement the Python class `FileBED` described below.
Class description:
stores information about the start or midpoint of read
Method signatures and docstrings:
- def getBedDict(self, middle=False, stranded=False): return dictionary where key is chromosome, value is dictionary that dictionary has positions as key an... | Implement the Python class `FileBED` described below.
Class description:
stores information about the start or midpoint of read
Method signatures and docstrings:
- def getBedDict(self, middle=False, stranded=False): return dictionary where key is chromosome, value is dictionary that dictionary has positions as key an... | 189bf355f0f878c5603b09a06b3b50b61a11ad93 | <|skeleton|>
class FileBED:
"""stores information about the start or midpoint of read"""
def getBedDict(self, middle=False, stranded=False):
"""return dictionary where key is chromosome, value is dictionary that dictionary has positions as key and value is number of reads that cover the position dictio... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FileBED:
"""stores information about the start or midpoint of read"""
def getBedDict(self, middle=False, stranded=False):
"""return dictionary where key is chromosome, value is dictionary that dictionary has positions as key and value is number of reads that cover the position dictionary contains... | the_stack_v2_python_sparse | python_util/bioFiles.py | bhofmei/analysis-scripts | train | 2 |
f1982f3a13007e1638159e23d6733e4f317d433b | [
"import bisect\nqueue = []\nres = []\nfor num in nums[::-1]:\n loc = bisect.bisect_left(queue, num)\n res.append(loc)\n queue.insert(loc, num)\nreturn res[::-1]",
"arr = []\nres = [0] * len(nums)\nfor idx, num in enumerate(nums):\n arr.append((idx, num))\n\ndef merge_sort(arr):\n if len(arr) <= 1:\... | <|body_start_0|>
import bisect
queue = []
res = []
for num in nums[::-1]:
loc = bisect.bisect_left(queue, num)
res.append(loc)
queue.insert(loc, num)
return res[::-1]
<|end_body_0|>
<|body_start_1|>
arr = []
res = [0] * len(num... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def countSmaller_2div(self, nums):
""":type nums: List[int] :rtype: List[int]"""
<|body_0|>
def countSmaller_merge_sort(self, nums):
""":type nums: List[int] :rtype: List[int]"""
<|body_1|>
def countSmaller_Fenwick_Tree(self, nums):
"""... | stack_v2_sparse_classes_36k_train_002210 | 5,177 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: List[int]",
"name": "countSmaller_2div",
"signature": "def countSmaller_2div(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: List[int]",
"name": "countSmaller_merge_sort",
"signature": "def countSmaller_merge_sort(self, nums)"
... | 5 | stack_v2_sparse_classes_30k_train_020809 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def countSmaller_2div(self, nums): :type nums: List[int] :rtype: List[int]
- def countSmaller_merge_sort(self, nums): :type nums: List[int] :rtype: List[int]
- def countSmaller_F... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def countSmaller_2div(self, nums): :type nums: List[int] :rtype: List[int]
- def countSmaller_merge_sort(self, nums): :type nums: List[int] :rtype: List[int]
- def countSmaller_F... | 3f4284330f9771037ca59e2e6a94122e51e58540 | <|skeleton|>
class Solution:
def countSmaller_2div(self, nums):
""":type nums: List[int] :rtype: List[int]"""
<|body_0|>
def countSmaller_merge_sort(self, nums):
""":type nums: List[int] :rtype: List[int]"""
<|body_1|>
def countSmaller_Fenwick_Tree(self, nums):
"""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def countSmaller_2div(self, nums):
""":type nums: List[int] :rtype: List[int]"""
import bisect
queue = []
res = []
for num in nums[::-1]:
loc = bisect.bisect_left(queue, num)
res.append(loc)
queue.insert(loc, num)
re... | the_stack_v2_python_sparse | Leetcode/315.计算右侧小于当前元素的个数.py | myf-algorithm/Leetcode | train | 1 | |
bfa23529263e6c479f45427434bbf346e2cc932a | [
"n = len(nums)\ntarget_index = n - k\nleft, right = (0, n - 1)\nwhile True:\n index = self._partition(nums, left, right)\n if index == target_index:\n return nums[index]\n elif index < target_index:\n left = index + 1\n else:\n right = index - 1",
"pivot = left\ni, j = (left, righ... | <|body_start_0|>
n = len(nums)
target_index = n - k
left, right = (0, n - 1)
while True:
index = self._partition(nums, left, right)
if index == target_index:
return nums[index]
elif index < target_index:
left = index + 1... | OfficialSolution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OfficialSolution:
def find_kth_largest(self, nums: List[int], k: int) -> int:
"""基于快速排序的选择方法。"""
<|body_0|>
def _partition(self, nums: List[int], left, right: int) -> int:
"""快排分区。"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
n = len(nums)
... | stack_v2_sparse_classes_36k_train_002211 | 2,954 | no_license | [
{
"docstring": "基于快速排序的选择方法。",
"name": "find_kth_largest",
"signature": "def find_kth_largest(self, nums: List[int], k: int) -> int"
},
{
"docstring": "快排分区。",
"name": "_partition",
"signature": "def _partition(self, nums: List[int], left, right: int) -> int"
}
] | 2 | null | Implement the Python class `OfficialSolution` described below.
Class description:
Implement the OfficialSolution class.
Method signatures and docstrings:
- def find_kth_largest(self, nums: List[int], k: int) -> int: 基于快速排序的选择方法。
- def _partition(self, nums: List[int], left, right: int) -> int: 快排分区。 | Implement the Python class `OfficialSolution` described below.
Class description:
Implement the OfficialSolution class.
Method signatures and docstrings:
- def find_kth_largest(self, nums: List[int], k: int) -> int: 基于快速排序的选择方法。
- def _partition(self, nums: List[int], left, right: int) -> int: 快排分区。
<|skeleton|>
cla... | 6932d69353b94ec824dd0ddc86a92453f6673232 | <|skeleton|>
class OfficialSolution:
def find_kth_largest(self, nums: List[int], k: int) -> int:
"""基于快速排序的选择方法。"""
<|body_0|>
def _partition(self, nums: List[int], left, right: int) -> int:
"""快排分区。"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class OfficialSolution:
def find_kth_largest(self, nums: List[int], k: int) -> int:
"""基于快速排序的选择方法。"""
n = len(nums)
target_index = n - k
left, right = (0, n - 1)
while True:
index = self._partition(nums, left, right)
if index == target_index:
... | the_stack_v2_python_sparse | 0215_kth-largest-element-in-an-array.py | Nigirimeshi/leetcode | train | 0 | |
2f169249abe3d136b6566049624a5acf748410e4 | [
"project = AdviserProject.objects.get(id=project_id)\nif not request.user.is_superuser and project.id_company.id != request.user.adviseruser.id_company.id:\n return HttpResponseBadRequest('Permission denied')\nplayers = Player.objects.filter(project=project_id)\ndata = [model_to_dict(i) for i in players]\nreturn... | <|body_start_0|>
project = AdviserProject.objects.get(id=project_id)
if not request.user.is_superuser and project.id_company.id != request.user.adviseruser.id_company.id:
return HttpResponseBadRequest('Permission denied')
players = Player.objects.filter(project=project_id)
da... | Class-based view used for handling adding project to players while edditing. | AdviserProjectToPlayers | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AdviserProjectToPlayers:
"""Class-based view used for handling adding project to players while edditing."""
def get(self, request, project_id):
"""Handling GET method. :param request: Request to View. :param project_id: id of project for which players will be returned :return: Http r... | stack_v2_sparse_classes_36k_train_002212 | 4,916 | no_license | [
{
"docstring": "Handling GET method. :param request: Request to View. :param project_id: id of project for which players will be returned :return: Http response with list of players that have current project",
"name": "get",
"signature": "def get(self, request, project_id)"
},
{
"docstring": "Ha... | 2 | stack_v2_sparse_classes_30k_train_003712 | Implement the Python class `AdviserProjectToPlayers` described below.
Class description:
Class-based view used for handling adding project to players while edditing.
Method signatures and docstrings:
- def get(self, request, project_id): Handling GET method. :param request: Request to View. :param project_id: id of p... | Implement the Python class `AdviserProjectToPlayers` described below.
Class description:
Class-based view used for handling adding project to players while edditing.
Method signatures and docstrings:
- def get(self, request, project_id): Handling GET method. :param request: Request to View. :param project_id: id of p... | 46bbe0fb30ce151e398034720939fb4fecea9ac5 | <|skeleton|>
class AdviserProjectToPlayers:
"""Class-based view used for handling adding project to players while edditing."""
def get(self, request, project_id):
"""Handling GET method. :param request: Request to View. :param project_id: id of project for which players will be returned :return: Http r... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AdviserProjectToPlayers:
"""Class-based view used for handling adding project to players while edditing."""
def get(self, request, project_id):
"""Handling GET method. :param request: Request to View. :param project_id: id of project for which players will be returned :return: Http response with ... | the_stack_v2_python_sparse | itaplay/itaplay/projects/views.py | TarasStankovskyi/itaplay | train | 0 |
06005864f49d8d7056eb9cbf0a53d337c3c907bb | [
"self._go = import_or_raise('plotly.graph_objects', error_msg='Cannot find dependency plotly.graph_objects')\nself.results = results\nself.objective = objective",
"if not interactive_plot:\n plot_obj = SearchIterationPlot(self.results, self.objective)\n return self._go.Figure(plot_obj.best_score_by_iter_fig... | <|body_start_0|>
self._go = import_or_raise('plotly.graph_objects', error_msg='Cannot find dependency plotly.graph_objects')
self.results = results
self.objective = objective
<|end_body_0|>
<|body_start_1|>
if not interactive_plot:
plot_obj = SearchIterationPlot(self.results... | Plots for the AutoMLSearch class. | PipelineSearchPlots | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PipelineSearchPlots:
"""Plots for the AutoMLSearch class."""
def __init__(self, results, objective):
"""Make plots for the AutoMLSearch class. Arguments: data (AutoMLSearch): Automated pipeline search object"""
<|body_0|>
def search_iteration_plot(self, interactive_plot=... | stack_v2_sparse_classes_36k_train_002213 | 4,225 | permissive | [
{
"docstring": "Make plots for the AutoMLSearch class. Arguments: data (AutoMLSearch): Automated pipeline search object",
"name": "__init__",
"signature": "def __init__(self, results, objective)"
},
{
"docstring": "Shows a plot of the best score at each iteration using data gathered during train... | 2 | stack_v2_sparse_classes_30k_train_013227 | Implement the Python class `PipelineSearchPlots` described below.
Class description:
Plots for the AutoMLSearch class.
Method signatures and docstrings:
- def __init__(self, results, objective): Make plots for the AutoMLSearch class. Arguments: data (AutoMLSearch): Automated pipeline search object
- def search_iterat... | Implement the Python class `PipelineSearchPlots` described below.
Class description:
Plots for the AutoMLSearch class.
Method signatures and docstrings:
- def __init__(self, results, objective): Make plots for the AutoMLSearch class. Arguments: data (AutoMLSearch): Automated pipeline search object
- def search_iterat... | 3b5bf62b08a5a5bc6485ba5387a08c32e1857473 | <|skeleton|>
class PipelineSearchPlots:
"""Plots for the AutoMLSearch class."""
def __init__(self, results, objective):
"""Make plots for the AutoMLSearch class. Arguments: data (AutoMLSearch): Automated pipeline search object"""
<|body_0|>
def search_iteration_plot(self, interactive_plot=... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PipelineSearchPlots:
"""Plots for the AutoMLSearch class."""
def __init__(self, results, objective):
"""Make plots for the AutoMLSearch class. Arguments: data (AutoMLSearch): Automated pipeline search object"""
self._go = import_or_raise('plotly.graph_objects', error_msg='Cannot find depe... | the_stack_v2_python_sparse | evalml/automl/pipeline_search_plots.py | ObinnaObeleagu/evalml | train | 1 |
9f8818bdf9c241d76a86cbbbe66aede528f85082 | [
"if not node1 or not node2:\n return\nnode1.next = node2\nself.connect_two_node(node1.left, node1.right)\nself.connect_two_node(node2.left, node2.right)\nself.connect_two_node(node1.right, node2.left)",
"if not root:\n return root\nself.connect_two_node(root.left, root.right)\nreturn root"
] | <|body_start_0|>
if not node1 or not node2:
return
node1.next = node2
self.connect_two_node(node1.left, node1.right)
self.connect_two_node(node2.left, node2.right)
self.connect_two_node(node1.right, node2.left)
<|end_body_0|>
<|body_start_1|>
if not root:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def connect_two_node(self, node1, node2):
"""负责连接每一个节点"""
<|body_0|>
def connect(self, root):
""":type root: Node :rtype: Node"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not node1 or not node2:
return
node1.next... | stack_v2_sparse_classes_36k_train_002214 | 1,152 | no_license | [
{
"docstring": "负责连接每一个节点",
"name": "connect_two_node",
"signature": "def connect_two_node(self, node1, node2)"
},
{
"docstring": ":type root: Node :rtype: Node",
"name": "connect",
"signature": "def connect(self, root)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def connect_two_node(self, node1, node2): 负责连接每一个节点
- def connect(self, root): :type root: Node :rtype: Node | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def connect_two_node(self, node1, node2): 负责连接每一个节点
- def connect(self, root): :type root: Node :rtype: Node
<|skeleton|>
class Solution:
def connect_two_node(self, node1, ... | f1bbd6b3197cd9ac4f0d35a37539c11b02272065 | <|skeleton|>
class Solution:
def connect_two_node(self, node1, node2):
"""负责连接每一个节点"""
<|body_0|>
def connect(self, root):
""":type root: Node :rtype: Node"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def connect_two_node(self, node1, node2):
"""负责连接每一个节点"""
if not node1 or not node2:
return
node1.next = node2
self.connect_two_node(node1.left, node1.right)
self.connect_two_node(node2.left, node2.right)
self.connect_two_node(node1.right, ... | the_stack_v2_python_sparse | leetcode/高频面试/树/116. 填充每个节点的下一个右侧节点指针/connect.py | guohaoyuan/algorithms-for-work | train | 2 | |
d33f5928e4414fbed5d4a09ae32baa2c6f413c19 | [
"super(Encoder, self).__init__()\nself.input_size = input_size\nself.hidden_size = hidden_size\nself.num_layers = num_layers\nif rnn_type == 'LSTM':\n self.model = nn.LSTM(input_size=self.input_size, hidden_size=self.hidden_size, num_layers=self.num_layers, batch_first=batch_first, dropout=dropout)\nelif rnn_typ... | <|body_start_0|>
super(Encoder, self).__init__()
self.input_size = input_size
self.hidden_size = hidden_size
self.num_layers = num_layers
if rnn_type == 'LSTM':
self.model = nn.LSTM(input_size=self.input_size, hidden_size=self.hidden_size, num_layers=self.num_layers, ... | Encoder Network | Encoder | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Encoder:
"""Encoder Network"""
def __init__(self, input_size: int, hidden_size: int, num_layers: int, dropout: float=0, batch_first: bool=True, rnn_type: str='LSTM'):
"""Create Encoder Args: input_size (int): number of features per time step hidden_size (int): number of hidden nodes ... | stack_v2_sparse_classes_36k_train_002215 | 14,969 | permissive | [
{
"docstring": "Create Encoder Args: input_size (int): number of features per time step hidden_size (int): number of hidden nodes per time step num_layers (int): number of layers dropout (float, optional): percentage of nodes that should switched out at any term. Defaults to 0. batch_first (bool, optional): if ... | 2 | stack_v2_sparse_classes_30k_train_015069 | Implement the Python class `Encoder` described below.
Class description:
Encoder Network
Method signatures and docstrings:
- def __init__(self, input_size: int, hidden_size: int, num_layers: int, dropout: float=0, batch_first: bool=True, rnn_type: str='LSTM'): Create Encoder Args: input_size (int): number of features... | Implement the Python class `Encoder` described below.
Class description:
Encoder Network
Method signatures and docstrings:
- def __init__(self, input_size: int, hidden_size: int, num_layers: int, dropout: float=0, batch_first: bool=True, rnn_type: str='LSTM'): Create Encoder Args: input_size (int): number of features... | 5b4a61b5dd0bc259ffe68223877949ef4ebfa5e3 | <|skeleton|>
class Encoder:
"""Encoder Network"""
def __init__(self, input_size: int, hidden_size: int, num_layers: int, dropout: float=0, batch_first: bool=True, rnn_type: str='LSTM'):
"""Create Encoder Args: input_size (int): number of features per time step hidden_size (int): number of hidden nodes ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Encoder:
"""Encoder Network"""
def __init__(self, input_size: int, hidden_size: int, num_layers: int, dropout: float=0, batch_first: bool=True, rnn_type: str='LSTM'):
"""Create Encoder Args: input_size (int): number of features per time step hidden_size (int): number of hidden nodes per time step... | the_stack_v2_python_sparse | src/models/anomalia/layers.py | maurony/ts-vrae | train | 1 |
08e032e28b7cdabc2bc9e7f5312e2d79854f5b8d | [
"self.send_response(200)\nself.send_header('Content-type', 'text/plain')\nself.end_headers()\nself.wfile.write('Ca se passe en POST pour les requetes !')",
"form = FieldStorage(fp=self.rfile, headers=self.headers, environ={'REQUEST_METHOD': 'POST', 'CONTENT_TYPE': self.headers['Content-Type']})\nuser = form.getva... | <|body_start_0|>
self.send_response(200)
self.send_header('Content-type', 'text/plain')
self.end_headers()
self.wfile.write('Ca se passe en POST pour les requetes !')
<|end_body_0|>
<|body_start_1|>
form = FieldStorage(fp=self.rfile, headers=self.headers, environ={'REQUEST_METHO... | SpeechServerHandler | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SpeechServerHandler:
def do_GET(self):
"""Respond to a GET request"""
<|body_0|>
def do_POST(self):
"""Respond to a POST request"""
<|body_1|>
def buildXMLResponse(cls, data):
"""Build the XML doc response from the data dictionnary"""
<|b... | stack_v2_sparse_classes_36k_train_002216 | 3,003 | no_license | [
{
"docstring": "Respond to a GET request",
"name": "do_GET",
"signature": "def do_GET(self)"
},
{
"docstring": "Respond to a POST request",
"name": "do_POST",
"signature": "def do_POST(self)"
},
{
"docstring": "Build the XML doc response from the data dictionnary",
"name": "b... | 4 | stack_v2_sparse_classes_30k_train_012887 | Implement the Python class `SpeechServerHandler` described below.
Class description:
Implement the SpeechServerHandler class.
Method signatures and docstrings:
- def do_GET(self): Respond to a GET request
- def do_POST(self): Respond to a POST request
- def buildXMLResponse(cls, data): Build the XML doc response from... | Implement the Python class `SpeechServerHandler` described below.
Class description:
Implement the SpeechServerHandler class.
Method signatures and docstrings:
- def do_GET(self): Respond to a GET request
- def do_POST(self): Respond to a POST request
- def buildXMLResponse(cls, data): Build the XML doc response from... | a19dd57beb18bd9e1f6978c4566b92c10d6974bd | <|skeleton|>
class SpeechServerHandler:
def do_GET(self):
"""Respond to a GET request"""
<|body_0|>
def do_POST(self):
"""Respond to a POST request"""
<|body_1|>
def buildXMLResponse(cls, data):
"""Build the XML doc response from the data dictionnary"""
<|b... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SpeechServerHandler:
def do_GET(self):
"""Respond to a GET request"""
self.send_response(200)
self.send_header('Content-type', 'text/plain')
self.end_headers()
self.wfile.write('Ca se passe en POST pour les requetes !')
def do_POST(self):
"""Respond to a PO... | the_stack_v2_python_sparse | src/speechserver/main.py | giliam/mig2013 | train | 2 | |
24f2856da5d448cf2fb35641dea3462c2665a217 | [
"if self is DoorStatusEnum.OPENED:\n return 'opened'\nif self is DoorStatusEnum.CLOSED:\n return 'closed'\nif self is DoorStatusEnum.LOCKED:\n return 'locked'\nif self is DoorStatusEnum.DESTROYED:\n return 'destroyed'\nassert False, 'Missing desc for DoorStatusEnum'\nreturn ''",
"if self in [DoorStatu... | <|body_start_0|>
if self is DoorStatusEnum.OPENED:
return 'opened'
if self is DoorStatusEnum.CLOSED:
return 'closed'
if self is DoorStatusEnum.LOCKED:
return 'locked'
if self is DoorStatusEnum.DESTROYED:
return 'destroyed'
assert Fa... | All possible door statuses | DoorStatusEnum | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DoorStatusEnum:
"""All possible door statuses"""
def desc(self) -> str:
"""desc"""
<|body_0|>
def glyph(self) -> str:
"""what to display"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if self is DoorStatusEnum.OPENED:
return 'opened... | stack_v2_sparse_classes_36k_train_002217 | 4,891 | no_license | [
{
"docstring": "desc",
"name": "desc",
"signature": "def desc(self) -> str"
},
{
"docstring": "what to display",
"name": "glyph",
"signature": "def glyph(self) -> str"
}
] | 2 | null | Implement the Python class `DoorStatusEnum` described below.
Class description:
All possible door statuses
Method signatures and docstrings:
- def desc(self) -> str: desc
- def glyph(self) -> str: what to display | Implement the Python class `DoorStatusEnum` described below.
Class description:
All possible door statuses
Method signatures and docstrings:
- def desc(self) -> str: desc
- def glyph(self) -> str: what to display
<|skeleton|>
class DoorStatusEnum:
"""All possible door statuses"""
def desc(self) -> str:
... | 5e4f00d2b0bd1be33607131db209affdb79f0390 | <|skeleton|>
class DoorStatusEnum:
"""All possible door statuses"""
def desc(self) -> str:
"""desc"""
<|body_0|>
def glyph(self) -> str:
"""what to display"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DoorStatusEnum:
"""All possible door statuses"""
def desc(self) -> str:
"""desc"""
if self is DoorStatusEnum.OPENED:
return 'opened'
if self is DoorStatusEnum.CLOSED:
return 'closed'
if self is DoorStatusEnum.LOCKED:
return 'locked'
... | the_stack_v2_python_sparse | src/hidden.py | lefranco/pnethack | train | 0 |
74ba08f9061f4490e3a4ce0a14648d49fac40c25 | [
"data_segments = []\nwhile compressed_data:\n data = zlib_decompressor.decompress(compressed_data)\n if not data:\n break\n data_segments.append(data)\n compressed_data = getattr(zlib_decompressor, 'unused_data', b'')\nreturn (b''.join(data_segments), compressed_data)",
"zlib_decompressor = zli... | <|body_start_0|>
data_segments = []
while compressed_data:
data = zlib_decompressor.decompress(compressed_data)
if not data:
break
data_segments.append(data)
compressed_data = getattr(zlib_decompressor, 'unused_data', b'')
return (b... | GZip (.gz) file. | GZipFile | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GZipFile:
"""GZip (.gz) file."""
def _ReadCompressedData(self, zlib_decompressor, compressed_data):
"""Reads compressed data. Args: zlib_decompressor (zlib.Decompress): zlib decompressor. compressed_data (bytes): compressed data. Returns: tuple[bytes, bytes]: decompressed data and re... | stack_v2_sparse_classes_36k_train_002218 | 5,252 | permissive | [
{
"docstring": "Reads compressed data. Args: zlib_decompressor (zlib.Decompress): zlib decompressor. compressed_data (bytes): compressed data. Returns: tuple[bytes, bytes]: decompressed data and remaining data.",
"name": "_ReadCompressedData",
"signature": "def _ReadCompressedData(self, zlib_decompresso... | 5 | stack_v2_sparse_classes_30k_train_007820 | Implement the Python class `GZipFile` described below.
Class description:
GZip (.gz) file.
Method signatures and docstrings:
- def _ReadCompressedData(self, zlib_decompressor, compressed_data): Reads compressed data. Args: zlib_decompressor (zlib.Decompress): zlib decompressor. compressed_data (bytes): compressed dat... | Implement the Python class `GZipFile` described below.
Class description:
GZip (.gz) file.
Method signatures and docstrings:
- def _ReadCompressedData(self, zlib_decompressor, compressed_data): Reads compressed data. Args: zlib_decompressor (zlib.Decompress): zlib decompressor. compressed_data (bytes): compressed dat... | 55007dcac48efff42c497e739208ebfb88e4048d | <|skeleton|>
class GZipFile:
"""GZip (.gz) file."""
def _ReadCompressedData(self, zlib_decompressor, compressed_data):
"""Reads compressed data. Args: zlib_decompressor (zlib.Decompress): zlib decompressor. compressed_data (bytes): compressed data. Returns: tuple[bytes, bytes]: decompressed data and re... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GZipFile:
"""GZip (.gz) file."""
def _ReadCompressedData(self, zlib_decompressor, compressed_data):
"""Reads compressed data. Args: zlib_decompressor (zlib.Decompress): zlib decompressor. compressed_data (bytes): compressed data. Returns: tuple[bytes, bytes]: decompressed data and remaining data.... | the_stack_v2_python_sparse | dtformats/gzipfile.py | libyal/dtformats | train | 109 |
ce4f3652ea3f9af32a181eb52fa9f879083b2c91 | [
"orig_query = self.request.get('query')\nlogging.debug('Received raw query %r', orig_query)\nif not self.QUERY_LIMIT_RE.search(orig_query):\n orig_query += ' LIMIT 30'\nquery = orig_query\nquery, columns = self._RemoveSelectFromQuery(query)\nif query == orig_query and columns == self.DEFAULT_COLUMNS:\n orig_q... | <|body_start_0|>
orig_query = self.request.get('query')
logging.debug('Received raw query %r', orig_query)
if not self.QUERY_LIMIT_RE.search(orig_query):
orig_query += ' LIMIT 30'
query = orig_query
query, columns = self._RemoveSelectFromQuery(query)
if query ... | Provide interface for interacting with DB. | MainPage | [
"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 MainPage:
"""Provide interface for interacting with DB."""
def get(self):
"""Support GET to stats page."""
<|body_0|>
def _RemoveSelectFromQuery(self, query):
"""Remove SELECT clause from |query|, return tuple (new_query, columns)."""
<|body_1|>
def ... | stack_v2_sparse_classes_36k_train_002219 | 9,774 | permissive | [
{
"docstring": "Support GET to stats page.",
"name": "get",
"signature": "def get(self)"
},
{
"docstring": "Remove SELECT clause from |query|, return tuple (new_query, columns).",
"name": "_RemoveSelectFromQuery",
"signature": "def _RemoveSelectFromQuery(self, query)"
},
{
"docst... | 5 | stack_v2_sparse_classes_30k_train_019750 | Implement the Python class `MainPage` described below.
Class description:
Provide interface for interacting with DB.
Method signatures and docstrings:
- def get(self): Support GET to stats page.
- def _RemoveSelectFromQuery(self, query): Remove SELECT clause from |query|, return tuple (new_query, columns).
- def _Adj... | Implement the Python class `MainPage` described below.
Class description:
Provide interface for interacting with DB.
Method signatures and docstrings:
- def get(self): Support GET to stats page.
- def _RemoveSelectFromQuery(self, query): Remove SELECT clause from |query|, return tuple (new_query, columns).
- def _Adj... | 72a05af97787001756bae2511b7985e61498c965 | <|skeleton|>
class MainPage:
"""Provide interface for interacting with DB."""
def get(self):
"""Support GET to stats page."""
<|body_0|>
def _RemoveSelectFromQuery(self, query):
"""Remove SELECT clause from |query|, return tuple (new_query, columns)."""
<|body_1|>
def ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MainPage:
"""Provide interface for interacting with DB."""
def get(self):
"""Support GET to stats page."""
orig_query = self.request.get('query')
logging.debug('Received raw query %r', orig_query)
if not self.QUERY_LIMIT_RE.search(orig_query):
orig_query += ' L... | the_stack_v2_python_sparse | third_party/chromite/appengine/chromiumos-build-stats/stats.py | metux/chromium-suckless | train | 5 |
9cca4d0436123088fc965a428d3ef9cdc99d9176 | [
"if not root:\n return True\nif not self.isValidBST(root.left):\n return False\nif not self.isValidBST(root.right):\n return False\nif root.left:\n if not self.get_largest(root.left) < root.val:\n return False\nif root.right:\n if not root.val < self.get_smallest(root.right):\n return F... | <|body_start_0|>
if not root:
return True
if not self.isValidBST(root.left):
return False
if not self.isValidBST(root.right):
return False
if root.left:
if not self.get_largest(root.left) < root.val:
return False
if ... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def isValidBST(self, root):
"""Google Phone Interview Question, 20 Sep 2013 recursive dfs alternative answer: convert the tree the array and judge whether it is sorted :param root: a tree node :return: boolean"""
<|body_0|>
def get_largest(self, root):
"""p... | stack_v2_sparse_classes_36k_train_002220 | 1,874 | permissive | [
{
"docstring": "Google Phone Interview Question, 20 Sep 2013 recursive dfs alternative answer: convert the tree the array and judge whether it is sorted :param root: a tree node :return: boolean",
"name": "isValidBST",
"signature": "def isValidBST(self, root)"
},
{
"docstring": "possible dp :par... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isValidBST(self, root): Google Phone Interview Question, 20 Sep 2013 recursive dfs alternative answer: convert the tree the array and judge whether it is sorted :param root: ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isValidBST(self, root): Google Phone Interview Question, 20 Sep 2013 recursive dfs alternative answer: convert the tree the array and judge whether it is sorted :param root: ... | cbbd4a67ab342ada2421e13f82d660b1d47d4d20 | <|skeleton|>
class Solution:
def isValidBST(self, root):
"""Google Phone Interview Question, 20 Sep 2013 recursive dfs alternative answer: convert the tree the array and judge whether it is sorted :param root: a tree node :return: boolean"""
<|body_0|>
def get_largest(self, root):
"""p... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def isValidBST(self, root):
"""Google Phone Interview Question, 20 Sep 2013 recursive dfs alternative answer: convert the tree the array and judge whether it is sorted :param root: a tree node :return: boolean"""
if not root:
return True
if not self.isValidBST(roo... | the_stack_v2_python_sparse | 098 Validate Binary Search Tree.py | Aminaba123/LeetCode | train | 1 | |
b6d751bee3e871bce59453d32b8c4bb19b1aa645 | [
"self.parser = reqparse.RequestParser()\nself.parser.add_argument('name')\nself.parser.add_argument('token')\nsuper(CtaStrategyStart, self).__init__()",
"args = self.parser.parse_args()\ntoken = args['token']\nname = 'strategyHedge_syt'\nengine = me.getApp('CtaStrategy')\nif not name:\n engine.startAll()\nelse... | <|body_start_0|>
self.parser = reqparse.RequestParser()
self.parser.add_argument('name')
self.parser.add_argument('token')
super(CtaStrategyStart, self).__init__()
<|end_body_0|>
<|body_start_1|>
args = self.parser.parse_args()
token = args['token']
name = 'strat... | 启动策略 | CtaStrategyStart | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CtaStrategyStart:
"""启动策略"""
def __init__(self):
"""初始化"""
<|body_0|>
def post(self):
"""订阅"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.parser = reqparse.RequestParser()
self.parser.add_argument('name')
self.parser.add_a... | stack_v2_sparse_classes_36k_train_002221 | 24,002 | permissive | [
{
"docstring": "初始化",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "订阅",
"name": "post",
"signature": "def post(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_002190 | Implement the Python class `CtaStrategyStart` described below.
Class description:
启动策略
Method signatures and docstrings:
- def __init__(self): 初始化
- def post(self): 订阅 | Implement the Python class `CtaStrategyStart` described below.
Class description:
启动策略
Method signatures and docstrings:
- def __init__(self): 初始化
- def post(self): 订阅
<|skeleton|>
class CtaStrategyStart:
"""启动策略"""
def __init__(self):
"""初始化"""
<|body_0|>
def post(self):
"""订阅"... | c316649161086da2543d39bf0455d0f793cdd08f | <|skeleton|>
class CtaStrategyStart:
"""启动策略"""
def __init__(self):
"""初始化"""
<|body_0|>
def post(self):
"""订阅"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CtaStrategyStart:
"""启动策略"""
def __init__(self):
"""初始化"""
self.parser = reqparse.RequestParser()
self.parser.add_argument('name')
self.parser.add_argument('token')
super(CtaStrategyStart, self).__init__()
def post(self):
"""订阅"""
args = self.p... | the_stack_v2_python_sparse | WebTrader/webServer.py | webclinic017/riskBacktestingPlatform | train | 0 |
b724ba1afa0a4071f6114d4d6c9ba8ecc0f136aa | [
"super(RunTaskTemplateResponse, self).__init__(id=id, status=status, inputs=inputs, outputs=outputs, condition=condition, task_template_id_input=task_template_id_input, cascade_status_input=cascade_status_input, created=created, modified=modified, **kwargs)\nif outputs is None:\n self.task_id_output = task_id_ou... | <|body_start_0|>
super(RunTaskTemplateResponse, self).__init__(id=id, status=status, inputs=inputs, outputs=outputs, condition=condition, task_template_id_input=task_template_id_input, cascade_status_input=cascade_status_input, created=created, modified=modified, **kwargs)
if outputs is None:
... | Fetchcore response to run a task template as a subtask. | RunTaskTemplateResponse | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RunTaskTemplateResponse:
"""Fetchcore response to run a task template as a subtask."""
def __init__(self, id=None, status=ResponseStatus.NEW, task_template_id_input=None, cascade_status_input=None, inputs=None, outputs=None, condition=None, task_id_output=None, created=None, modified=None, *... | stack_v2_sparse_classes_36k_train_002222 | 3,046 | no_license | [
{
"docstring": ":param int id: The resource ID of the response. :param str status: Status of this response. :param int task_template_id_input: The ID of the task template to run. :param bool cascade_status_input: Whether to propagate the response's status to the action. :param inputs: Input parameters of the re... | 3 | null | Implement the Python class `RunTaskTemplateResponse` described below.
Class description:
Fetchcore response to run a task template as a subtask.
Method signatures and docstrings:
- def __init__(self, id=None, status=ResponseStatus.NEW, task_template_id_input=None, cascade_status_input=None, inputs=None, outputs=None,... | Implement the Python class `RunTaskTemplateResponse` described below.
Class description:
Fetchcore response to run a task template as a subtask.
Method signatures and docstrings:
- def __init__(self, id=None, status=ResponseStatus.NEW, task_template_id_input=None, cascade_status_input=None, inputs=None, outputs=None,... | 7c30438f145c5e59522bb0f27a3914ce21a13c33 | <|skeleton|>
class RunTaskTemplateResponse:
"""Fetchcore response to run a task template as a subtask."""
def __init__(self, id=None, status=ResponseStatus.NEW, task_template_id_input=None, cascade_status_input=None, inputs=None, outputs=None, condition=None, task_id_output=None, created=None, modified=None, *... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RunTaskTemplateResponse:
"""Fetchcore response to run a task template as a subtask."""
def __init__(self, id=None, status=ResponseStatus.NEW, task_template_id_input=None, cascade_status_input=None, inputs=None, outputs=None, condition=None, task_id_output=None, created=None, modified=None, **kwargs):
... | the_stack_v2_python_sparse | fetchapp/lib/python2.7/site-packages/fetchcore/resources/tasks/actions/responses/definitions/run_task_template/run_task_template_response.py | JasonVranek/jason_fetchcore | train | 0 |
cce9e38d3fb535d24e3727d984e4b18c3695ed43 | [
"context = super(CreateAllGroupView, self).get_context_data(**kwargs)\ncontext['submit_text'] = 'Create'\ncontext['intro_text'] = 'You can use this form to create a new group that contains all currently active contacts.'\nreturn context",
"g, created = RecipientGroup.objects.get_or_create(name=form.cleaned_data['... | <|body_start_0|>
context = super(CreateAllGroupView, self).get_context_data(**kwargs)
context['submit_text'] = 'Create'
context['intro_text'] = 'You can use this form to create a new group that contains all currently active contacts.'
return context
<|end_body_0|>
<|body_start_1|>
... | View to handle creation of an 'all' group. | CreateAllGroupView | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CreateAllGroupView:
"""View to handle creation of an 'all' group."""
def get_context_data(self, **kwargs):
"""Inject intro and button text into context."""
<|body_0|>
def form_valid(self, form):
"""Create the group and add all active users."""
<|body_1|>
... | stack_v2_sparse_classes_36k_train_002223 | 1,363 | permissive | [
{
"docstring": "Inject intro and button text into context.",
"name": "get_context_data",
"signature": "def get_context_data(self, **kwargs)"
},
{
"docstring": "Create the group and add all active users.",
"name": "form_valid",
"signature": "def form_valid(self, form)"
}
] | 2 | stack_v2_sparse_classes_30k_train_019377 | Implement the Python class `CreateAllGroupView` described below.
Class description:
View to handle creation of an 'all' group.
Method signatures and docstrings:
- def get_context_data(self, **kwargs): Inject intro and button text into context.
- def form_valid(self, form): Create the group and add all active users. | Implement the Python class `CreateAllGroupView` described below.
Class description:
View to handle creation of an 'all' group.
Method signatures and docstrings:
- def get_context_data(self, **kwargs): Inject intro and button text into context.
- def form_valid(self, form): Create the group and add all active users.
... | 1827547b5a8cf94bf1708bb4029c0b0e834416a9 | <|skeleton|>
class CreateAllGroupView:
"""View to handle creation of an 'all' group."""
def get_context_data(self, **kwargs):
"""Inject intro and button text into context."""
<|body_0|>
def form_valid(self, form):
"""Create the group and add all active users."""
<|body_1|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CreateAllGroupView:
"""View to handle creation of an 'all' group."""
def get_context_data(self, **kwargs):
"""Inject intro and button text into context."""
context = super(CreateAllGroupView, self).get_context_data(**kwargs)
context['submit_text'] = 'Create'
context['intro... | the_stack_v2_python_sparse | apostello/views/recipient_groups.py | armenzg/apostello | train | 0 |
c88efdd63f9d9c079d2673fd0bcc97e673a92a32 | [
"self.env = env\nself.lr = lr\nself.model_saving_file_path = model_saving_file_path\nself.model_saving_interval = model_saving_interval\nself.training_logs_file_path = training_logs_file_path\nif model is not None:\n self.model = model\nelse:\n self.model = Sequential()\n self.model.add(Dense(16, input_dim... | <|body_start_0|>
self.env = env
self.lr = lr
self.model_saving_file_path = model_saving_file_path
self.model_saving_interval = model_saving_interval
self.training_logs_file_path = training_logs_file_path
if model is not None:
self.model = model
else:
... | This class is responsible for the following. 1. Map observations to Q values using a neural network. 3. Update the model using the experience supplied by the agent. 4. Implement an epsilon greedy policy based on the model. This implementation assumes a continuous observation space and a discrete action space. | NeuralNetwork | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NeuralNetwork:
"""This class is responsible for the following. 1. Map observations to Q values using a neural network. 3. Update the model using the experience supplied by the agent. 4. Implement an epsilon greedy policy based on the model. This implementation assumes a continuous observation spa... | stack_v2_sparse_classes_36k_train_002224 | 6,369 | no_license | [
{
"docstring": "Arguments: env -- A Gym environment (can be vanilla or wrapped). We need this for infering input and output dimensions of the model. lr -- Learning rate model -- A compiled Keras model. If None, then the model is created. training_logs_file_path -- The file where we should save the logs for trai... | 3 | stack_v2_sparse_classes_30k_train_019752 | Implement the Python class `NeuralNetwork` described below.
Class description:
This class is responsible for the following. 1. Map observations to Q values using a neural network. 3. Update the model using the experience supplied by the agent. 4. Implement an epsilon greedy policy based on the model. This implementati... | Implement the Python class `NeuralNetwork` described below.
Class description:
This class is responsible for the following. 1. Map observations to Q values using a neural network. 3. Update the model using the experience supplied by the agent. 4. Implement an epsilon greedy policy based on the model. This implementati... | 09645ba04e43c7d6408b6e4b8cbbc4743c2fa5d8 | <|skeleton|>
class NeuralNetwork:
"""This class is responsible for the following. 1. Map observations to Q values using a neural network. 3. Update the model using the experience supplied by the agent. 4. Implement an epsilon greedy policy based on the model. This implementation assumes a continuous observation spa... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NeuralNetwork:
"""This class is responsible for the following. 1. Map observations to Q values using a neural network. 3. Update the model using the experience supplied by the agent. 4. Implement an epsilon greedy policy based on the model. This implementation assumes a continuous observation space and a disc... | the_stack_v2_python_sparse | 09_fn_approx_neural_network/reference_implementation/fn_approx_neural_network/model_and_policy.py | lakhotiaharshit/practical_rl_for_coders | train | 0 |
952c8476516bd959c5c594912f888eb02f23a609 | [
"assert evictinterval > dedupinterval, '%r <= %r' % (evictinterval, dedupinterval)\nsuper(ReaderThread, self).__init__()\nself.readerq = ReaderQueue(100000)\nself.lines_collected = 0\nself.lines_dropped = 0\nself.dedupinterval = dedupinterval\nself.evictinterval = evictinterval\nself.run_state = run_state",
"LOG.... | <|body_start_0|>
assert evictinterval > dedupinterval, '%r <= %r' % (evictinterval, dedupinterval)
super(ReaderThread, self).__init__()
self.readerq = ReaderQueue(100000)
self.lines_collected = 0
self.lines_dropped = 0
self.dedupinterval = dedupinterval
self.evict... | The main ReaderThread is responsible for reading from the collectors and assuring that we always read from the input no matter what. All data read is put into the self.readerq Queue, which is consumed by the SenderThread. | ReaderThread | [
"PSF-2.0",
"LGPL-2.0-or-later",
"BSD-3-Clause",
"Apache-2.0",
"BSD-2-Clause",
"MPL-2.0",
"LGPL-3.0-only",
"GPL-3.0-only"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ReaderThread:
"""The main ReaderThread is responsible for reading from the collectors and assuring that we always read from the input no matter what. All data read is put into the self.readerq Queue, which is consumed by the SenderThread."""
def __init__(self, dedupinterval, evictinterval, r... | stack_v2_sparse_classes_36k_train_002225 | 49,877 | permissive | [
{
"docstring": "Constructor. Args: dedupinterval: If a metric sends the same value over successive intervals, suppress sending the same value to the TSD until this many seconds have elapsed. This helps graphs over narrow time ranges still see timeseries with suppressed datapoints. evictinterval: In order to imp... | 3 | stack_v2_sparse_classes_30k_train_010644 | Implement the Python class `ReaderThread` described below.
Class description:
The main ReaderThread is responsible for reading from the collectors and assuring that we always read from the input no matter what. All data read is put into the self.readerq Queue, which is consumed by the SenderThread.
Method signatures ... | Implement the Python class `ReaderThread` described below.
Class description:
The main ReaderThread is responsible for reading from the collectors and assuring that we always read from the input no matter what. All data read is put into the self.readerq Queue, which is consumed by the SenderThread.
Method signatures ... | 5099a498edc47ab841965b483c2c32af49eb7dae | <|skeleton|>
class ReaderThread:
"""The main ReaderThread is responsible for reading from the collectors and assuring that we always read from the input no matter what. All data read is put into the self.readerq Queue, which is consumed by the SenderThread."""
def __init__(self, dedupinterval, evictinterval, r... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ReaderThread:
"""The main ReaderThread is responsible for reading from the collectors and assuring that we always read from the input no matter what. All data read is put into the self.readerq Queue, which is consumed by the SenderThread."""
def __init__(self, dedupinterval, evictinterval, run_state=None... | the_stack_v2_python_sparse | scalyr_agent/third_party/tcollector/tcollector.py | scalyr/scalyr-agent-2 | train | 75 |
9680a3db51fa62145d5b9823a41ba15568c1e153 | [
"self.machinesets = []\nfor machineset_path in glob.glob(f'{ASSETS_DIR}/openshift/99_openshift-cluster-api_worker-machineset-*.yaml'):\n with open(machineset_path) as f:\n self.machinesets.append(yaml.load(f, Loader=yaml.FullLoader))\nwith open(f'{ASSETS_DIR}/manifests/cluster-config.yaml') as f:\n clu... | <|body_start_0|>
self.machinesets = []
for machineset_path in glob.glob(f'{ASSETS_DIR}/openshift/99_openshift-cluster-api_worker-machineset-*.yaml'):
with open(machineset_path) as f:
self.machinesets.append(yaml.load(f, Loader=yaml.FullLoader))
with open(f'{ASSETS_DIR... | ConvertMachineSet | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ConvertMachineSet:
def setUp(self):
"""Parse the MachineSets into a Python data structure."""
<|body_0|>
def test_flavor(self):
"""Assert that worker machinesets take flavor from machinepool."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.mach... | stack_v2_sparse_classes_36k_train_002226 | 2,668 | permissive | [
{
"docstring": "Parse the MachineSets into a Python data structure.",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "Assert that worker machinesets take flavor from machinepool.",
"name": "test_flavor",
"signature": "def test_flavor(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_001358 | Implement the Python class `ConvertMachineSet` described below.
Class description:
Implement the ConvertMachineSet class.
Method signatures and docstrings:
- def setUp(self): Parse the MachineSets into a Python data structure.
- def test_flavor(self): Assert that worker machinesets take flavor from machinepool. | Implement the Python class `ConvertMachineSet` described below.
Class description:
Implement the ConvertMachineSet class.
Method signatures and docstrings:
- def setUp(self): Parse the MachineSets into a Python data structure.
- def test_flavor(self): Assert that worker machinesets take flavor from machinepool.
<|sk... | d7f39ed4836c9f57ada762ec393943ba1b5ce451 | <|skeleton|>
class ConvertMachineSet:
def setUp(self):
"""Parse the MachineSets into a Python data structure."""
<|body_0|>
def test_flavor(self):
"""Assert that worker machinesets take flavor from machinepool."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ConvertMachineSet:
def setUp(self):
"""Parse the MachineSets into a Python data structure."""
self.machinesets = []
for machineset_path in glob.glob(f'{ASSETS_DIR}/openshift/99_openshift-cluster-api_worker-machineset-*.yaml'):
with open(machineset_path) as f:
... | the_stack_v2_python_sparse | scripts/openstack/manifest-tests/convert/test_convert.py | openshift/installer | train | 1,541 | |
6d0c6787512ab67073c125a994031ad5987d3918 | [
"self._args = args\nrecorder_str = self._get_recorder(self._args.log)\ncriteria_dict = self._get_criteria(self._args.criteria)\nmap_name = self._get_recorder_map(recorder_str)\nworld = self._client.load_world(map_name)\ntown_map = world.get_map()\nlog = MetricsLog(recorder_str)\nmetric_class = self._get_metric_clas... | <|body_start_0|>
self._args = args
recorder_str = self._get_recorder(self._args.log)
criteria_dict = self._get_criteria(self._args.criteria)
map_name = self._get_recorder_map(recorder_str)
world = self._client.load_world(map_name)
town_map = world.get_map()
log = ... | Main class of the metrics module. Handles the parsing and execution of the metrics. | MetricsManager | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MetricsManager:
"""Main class of the metrics module. Handles the parsing and execution of the metrics."""
def __init__(self, args):
"""Initialization of the metrics manager. This creates the client, needed to parse the information from the recorder, extract the metrics class, and run... | stack_v2_sparse_classes_36k_train_002227 | 5,255 | permissive | [
{
"docstring": "Initialization of the metrics manager. This creates the client, needed to parse the information from the recorder, extract the metrics class, and runs it",
"name": "__init__",
"signature": "def __init__(self, args)"
},
{
"docstring": "Parses the log argument into readable informa... | 5 | null | Implement the Python class `MetricsManager` described below.
Class description:
Main class of the metrics module. Handles the parsing and execution of the metrics.
Method signatures and docstrings:
- def __init__(self, args): Initialization of the metrics manager. This creates the client, needed to parse the informat... | Implement the Python class `MetricsManager` described below.
Class description:
Main class of the metrics module. Handles the parsing and execution of the metrics.
Method signatures and docstrings:
- def __init__(self, args): Initialization of the metrics manager. This creates the client, needed to parse the informat... | 7fe8bf9581c7df140947468c6d90d7217a299d1b | <|skeleton|>
class MetricsManager:
"""Main class of the metrics module. Handles the parsing and execution of the metrics."""
def __init__(self, args):
"""Initialization of the metrics manager. This creates the client, needed to parse the information from the recorder, extract the metrics class, and run... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MetricsManager:
"""Main class of the metrics module. Handles the parsing and execution of the metrics."""
def __init__(self, args):
"""Initialization of the metrics manager. This creates the client, needed to parse the information from the recorder, extract the metrics class, and runs it"""
... | the_stack_v2_python_sparse | scenario_runner/metrics_manager.py | leotimus/WorldOnRails | train | 1 |
655e61a395ab91d28f7be26099d56e71decb9594 | [
"pre = p = j = head\nfor t in range(n - 1):\n p = p.next\nwhile p.next:\n pre = j\n j = j.next\n p = p.next\nif pre == j:\n if pre == p:\n return None\n else:\n head = pre.next\n return head\nelse:\n pre.next = j.next\n return head",
"p = j = head\nfor _ in range(n):\n... | <|body_start_0|>
pre = p = j = head
for t in range(n - 1):
p = p.next
while p.next:
pre = j
j = j.next
p = p.next
if pre == j:
if pre == p:
return None
else:
head = pre.next
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def removeNthFromEnd(self, head, n):
""":type head: ListNode :type n: int :rtype: ListNode"""
<|body_0|>
def removeNthFromEnd2(self, head, n):
"""an improved logic"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
pre = p = j = head
... | stack_v2_sparse_classes_36k_train_002228 | 1,033 | no_license | [
{
"docstring": ":type head: ListNode :type n: int :rtype: ListNode",
"name": "removeNthFromEnd",
"signature": "def removeNthFromEnd(self, head, n)"
},
{
"docstring": "an improved logic",
"name": "removeNthFromEnd2",
"signature": "def removeNthFromEnd2(self, head, n)"
}
] | 2 | stack_v2_sparse_classes_30k_train_008401 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def removeNthFromEnd(self, head, n): :type head: ListNode :type n: int :rtype: ListNode
- def removeNthFromEnd2(self, head, n): an improved logic | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def removeNthFromEnd(self, head, n): :type head: ListNode :type n: int :rtype: ListNode
- def removeNthFromEnd2(self, head, n): an improved logic
<|skeleton|>
class Solution:
... | 9c5f6621988ce3b15394e7a5d5b949f87e0d6265 | <|skeleton|>
class Solution:
def removeNthFromEnd(self, head, n):
""":type head: ListNode :type n: int :rtype: ListNode"""
<|body_0|>
def removeNthFromEnd2(self, head, n):
"""an improved logic"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def removeNthFromEnd(self, head, n):
""":type head: ListNode :type n: int :rtype: ListNode"""
pre = p = j = head
for t in range(n - 1):
p = p.next
while p.next:
pre = j
j = j.next
p = p.next
if pre == j:
... | the_stack_v2_python_sparse | leetcode/2016/19_removeNthFromEnd.py | YulongWu/AlgoExercise_CPP | train | 1 | |
4ef99eb3f6d05e24033249d1e8c7946b9babd241 | [
"if any((isinstance(x, (Collapse, Ordered)) for x in node.clauses)):\n raise NotImplementedError(_ERROR_MESSAGE)\nnode.loops.stmt = ensure_compound(self.visit(node.loops.stmt))\nreturn node",
"node = self.generic_visit(node)\ncond = transform_loop_condition(node.cond)\nstmt = transform_loop_statement(node.stmt... | <|body_start_0|>
if any((isinstance(x, (Collapse, Ordered)) for x in node.clauses)):
raise NotImplementedError(_ERROR_MESSAGE)
node.loops.stmt = ensure_compound(self.visit(node.loops.stmt))
return node
<|end_body_0|>
<|body_start_1|>
node = self.generic_visit(node)
c... | NodeTransformer to change for loops to while loops | ForToWhile | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ForToWhile:
"""NodeTransformer to change for loops to while loops"""
def visit_OmpFor(self, node):
"""Don't transform the omp for loop, but go inside it to transform any loops that may be nested inside it."""
<|body_0|>
def visit_For(self, node):
"""Transform a f... | stack_v2_sparse_classes_36k_train_002229 | 3,043 | no_license | [
{
"docstring": "Don't transform the omp for loop, but go inside it to transform any loops that may be nested inside it.",
"name": "visit_OmpFor",
"signature": "def visit_OmpFor(self, node)"
},
{
"docstring": "Transform a for loop to a while loop",
"name": "visit_For",
"signature": "def v... | 2 | null | Implement the Python class `ForToWhile` described below.
Class description:
NodeTransformer to change for loops to while loops
Method signatures and docstrings:
- def visit_OmpFor(self, node): Don't transform the omp for loop, but go inside it to transform any loops that may be nested inside it.
- def visit_For(self,... | Implement the Python class `ForToWhile` described below.
Class description:
NodeTransformer to change for loops to while loops
Method signatures and docstrings:
- def visit_OmpFor(self, node): Don't transform the omp for loop, but go inside it to transform any loops that may be nested inside it.
- def visit_For(self,... | 51bd9de9f264545d78c03e3cb75fe1aa2a421444 | <|skeleton|>
class ForToWhile:
"""NodeTransformer to change for loops to while loops"""
def visit_OmpFor(self, node):
"""Don't transform the omp for loop, but go inside it to transform any loops that may be nested inside it."""
<|body_0|>
def visit_For(self, node):
"""Transform a f... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ForToWhile:
"""NodeTransformer to change for loops to while loops"""
def visit_OmpFor(self, node):
"""Don't transform the omp for loop, but go inside it to transform any loops that may be nested inside it."""
if any((isinstance(x, (Collapse, Ordered)) for x in node.clauses)):
... | the_stack_v2_python_sparse | transforms/for_to_while.py | mrchristensen/Censor | train | 0 |
5de0369b91676178df943a9061d6d0da7076aaaa | [
"super().__init__(self.PARAMS, parameters)\nself.summary_name = parameters['summary_name']\nself.summary_filename = parameters['summary_filename']\nself.type_tag = parameters['type_tag'].lower()\nself.append_timecode = parameters.get('append_timecode', False)",
"df_new = df.copy()\nsummary = dispatcher.summary_di... | <|body_start_0|>
super().__init__(self.PARAMS, parameters)
self.summary_name = parameters['summary_name']
self.summary_filename = parameters['summary_filename']
self.type_tag = parameters['type_tag'].lower()
self.append_timecode = parameters.get('append_timecode', False)
<|end_bo... | Summarize a HED type tag in a collection of tabular files. Required remodeling parameters: - **summary_name** (*str*): The name of the summary. - **summary_filename** (*str*): Base filename of the summary. - **type_tag** (*str*):Type tag to get_summary (e.g. `condition-variable` or `task` tags). The purpose of this op ... | SummarizeHedTypeOp | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SummarizeHedTypeOp:
"""Summarize a HED type tag in a collection of tabular files. Required remodeling parameters: - **summary_name** (*str*): The name of the summary. - **summary_filename** (*str*): Base filename of the summary. - **type_tag** (*str*):Type tag to get_summary (e.g. `condition-vari... | stack_v2_sparse_classes_36k_train_002230 | 10,497 | permissive | [
{
"docstring": "Constructor for the summarize hed type operation. Parameters: parameters (dict): Dictionary with the parameter values for required and optional parameters. :raises KeyError: - If a required parameter is missing. - If an unexpected parameter is provided. :raises TypeError: - If a parameter has th... | 2 | null | Implement the Python class `SummarizeHedTypeOp` described below.
Class description:
Summarize a HED type tag in a collection of tabular files. Required remodeling parameters: - **summary_name** (*str*): The name of the summary. - **summary_filename** (*str*): Base filename of the summary. - **type_tag** (*str*):Type t... | Implement the Python class `SummarizeHedTypeOp` described below.
Class description:
Summarize a HED type tag in a collection of tabular files. Required remodeling parameters: - **summary_name** (*str*): The name of the summary. - **summary_filename** (*str*): Base filename of the summary. - **type_tag** (*str*):Type t... | b871cae44bdf0ee68c688562c3b0af50b93343f5 | <|skeleton|>
class SummarizeHedTypeOp:
"""Summarize a HED type tag in a collection of tabular files. Required remodeling parameters: - **summary_name** (*str*): The name of the summary. - **summary_filename** (*str*): Base filename of the summary. - **type_tag** (*str*):Type tag to get_summary (e.g. `condition-vari... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SummarizeHedTypeOp:
"""Summarize a HED type tag in a collection of tabular files. Required remodeling parameters: - **summary_name** (*str*): The name of the summary. - **summary_filename** (*str*): Base filename of the summary. - **type_tag** (*str*):Type tag to get_summary (e.g. `condition-variable` or `tas... | the_stack_v2_python_sparse | hed/tools/remodeling/operations/summarize_hed_type_op.py | hed-standard/hed-python | train | 5 |
5dcdc54368092f46aa396b1723e004a8af661fa1 | [
"super(FasterRcnnResnetV1FeatureExtractor, self).__init__(reuse_weights=reuse_weights)\nself._resnet_name = resnet_name\nself._resnet_fn = resnet_fn\nself._output_stride = output_stride\nself._weight_decay = weight_decay",
"with slim.arg_scope(resnet_utils.resnet_arg_scope(batch_norm_epsilon=1e-05, batch_norm_sca... | <|body_start_0|>
super(FasterRcnnResnetV1FeatureExtractor, self).__init__(reuse_weights=reuse_weights)
self._resnet_name = resnet_name
self._resnet_fn = resnet_fn
self._output_stride = output_stride
self._weight_decay = weight_decay
<|end_body_0|>
<|body_start_1|>
with s... | ResNet feature extractor for Faster RCNN model. | FasterRcnnResnetV1FeatureExtractor | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FasterRcnnResnetV1FeatureExtractor:
"""ResNet feature extractor for Faster RCNN model."""
def __init__(self, resnet_name, resnet_fn, output_stride, weight_decay=0.0, reuse_weights=None):
"""Constructor. Args: resnet_name: string scalar, ResNet model name (e.g. 'resnet_v1_101') resnet... | stack_v2_sparse_classes_36k_train_002231 | 3,880 | no_license | [
{
"docstring": "Constructor. Args: resnet_name: string scalar, ResNet model name (e.g. 'resnet_v1_101') resnet_fn: a callable that takes as input the input feature maps and generates the output feature map. output_stride: int scalar, output stride (e.g. 16, 32). weight_decay: float scalar, weight decay. reuse_w... | 3 | null | Implement the Python class `FasterRcnnResnetV1FeatureExtractor` described below.
Class description:
ResNet feature extractor for Faster RCNN model.
Method signatures and docstrings:
- def __init__(self, resnet_name, resnet_fn, output_stride, weight_decay=0.0, reuse_weights=None): Constructor. Args: resnet_name: strin... | Implement the Python class `FasterRcnnResnetV1FeatureExtractor` described below.
Class description:
ResNet feature extractor for Faster RCNN model.
Method signatures and docstrings:
- def __init__(self, resnet_name, resnet_fn, output_stride, weight_decay=0.0, reuse_weights=None): Constructor. Args: resnet_name: strin... | 5a53e02c690632bcf140d1b17327959609aab395 | <|skeleton|>
class FasterRcnnResnetV1FeatureExtractor:
"""ResNet feature extractor for Faster RCNN model."""
def __init__(self, resnet_name, resnet_fn, output_stride, weight_decay=0.0, reuse_weights=None):
"""Constructor. Args: resnet_name: string scalar, ResNet model name (e.g. 'resnet_v1_101') resnet... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FasterRcnnResnetV1FeatureExtractor:
"""ResNet feature extractor for Faster RCNN model."""
def __init__(self, resnet_name, resnet_fn, output_stride, weight_decay=0.0, reuse_weights=None):
"""Constructor. Args: resnet_name: string scalar, ResNet model name (e.g. 'resnet_v1_101') resnet_fn: a callab... | the_stack_v2_python_sparse | feature_extractors/faster_rcnn_resnet_v1.py | chao-ji/tf-detection | train | 2 |
31b553c5b2974bcc10b05798119d3f925969d73f | [
"PowerSpectrumSeries.__init__(self, *args, **kwargs)\nself.__cache = cache.Cache(maxsize=1000)\nif self.overlay.ndim < 4:\n raise ValueError('Overlay is not a 4D image')",
"display = self.displayCtx.getDisplay(self.overlay)\nopts = display.opts\ncoords = opts.getVoxel()\nif coords is not None:\n return '{} ... | <|body_start_0|>
PowerSpectrumSeries.__init__(self, *args, **kwargs)
self.__cache = cache.Cache(maxsize=1000)
if self.overlay.ndim < 4:
raise ValueError('Overlay is not a 4D image')
<|end_body_0|>
<|body_start_1|>
display = self.displayCtx.getDisplay(self.overlay)
op... | The ``VoxelPowerSpectrumSeries`` class encapsulates the power spectrum of a single voxel from a 4D :class:`.Image` overlay. The voxel is dictated by the :attr:`.DisplayContext.location` property. | VoxelPowerSpectrumSeries | [
"BSD-3-Clause",
"CC-BY-3.0",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VoxelPowerSpectrumSeries:
"""The ``VoxelPowerSpectrumSeries`` class encapsulates the power spectrum of a single voxel from a 4D :class:`.Image` overlay. The voxel is dictated by the :attr:`.DisplayContext.location` property."""
def __init__(self, *args, **kwargs):
"""Create a ``Voxel... | stack_v2_sparse_classes_36k_train_002232 | 8,639 | permissive | [
{
"docstring": "Create a ``VoxelPowerSpectrumSeries``. All arguments are passed to the :meth:`PowerSpectrumSeries.__init__` method. A :exc:`ValueError` is raised if the overlay is not a 4D :class:`.Image`.",
"name": "__init__",
"signature": "def __init__(self, *args, **kwargs)"
},
{
"docstring":... | 3 | stack_v2_sparse_classes_30k_train_011897 | Implement the Python class `VoxelPowerSpectrumSeries` described below.
Class description:
The ``VoxelPowerSpectrumSeries`` class encapsulates the power spectrum of a single voxel from a 4D :class:`.Image` overlay. The voxel is dictated by the :attr:`.DisplayContext.location` property.
Method signatures and docstrings... | Implement the Python class `VoxelPowerSpectrumSeries` described below.
Class description:
The ``VoxelPowerSpectrumSeries`` class encapsulates the power spectrum of a single voxel from a 4D :class:`.Image` overlay. The voxel is dictated by the :attr:`.DisplayContext.location` property.
Method signatures and docstrings... | 46ccb4fe2b2346eb57576247f49714032b61307a | <|skeleton|>
class VoxelPowerSpectrumSeries:
"""The ``VoxelPowerSpectrumSeries`` class encapsulates the power spectrum of a single voxel from a 4D :class:`.Image` overlay. The voxel is dictated by the :attr:`.DisplayContext.location` property."""
def __init__(self, *args, **kwargs):
"""Create a ``Voxel... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class VoxelPowerSpectrumSeries:
"""The ``VoxelPowerSpectrumSeries`` class encapsulates the power spectrum of a single voxel from a 4D :class:`.Image` overlay. The voxel is dictated by the :attr:`.DisplayContext.location` property."""
def __init__(self, *args, **kwargs):
"""Create a ``VoxelPowerSpectrum... | the_stack_v2_python_sparse | fsleyes/plotting/powerspectrumseries.py | sanjayankur31/fsleyes | train | 1 |
052627879465d8e25019a29266d9427fabaa0fca | [
"self.lines = []\ndict_one = {'timestamp': '2019-02-23T12:51:52', 'stuff': 'from bar to foobar', 'correct': False, 'random_number': 13245, 'vital_stats': 'gangverk'}\nself.lines.append(dict_one)\ndict_two = {'timestamp': '2019-06-17T20:11:23', 'stuff': 'fra sjalfstaedi til sjalfstaedis', 'correct': True, 'random_nu... | <|body_start_0|>
self.lines = []
dict_one = {'timestamp': '2019-02-23T12:51:52', 'stuff': 'from bar to foobar', 'correct': False, 'random_number': 13245, 'vital_stats': 'gangverk'}
self.lines.append(dict_one)
dict_two = {'timestamp': '2019-06-17T20:11:23', 'stuff': 'fra sjalfstaedi til s... | Test Timesketch importer. | TimesketchImporterTest | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TimesketchImporterTest:
"""Test Timesketch importer."""
def setUp(self):
"""Set up the test data frame."""
<|body_0|>
def test_adding_data_frames(self):
"""Test adding a data frame to the importer."""
<|body_1|>
def test_adding_dict(self):
""... | stack_v2_sparse_classes_36k_train_002233 | 6,646 | permissive | [
{
"docstring": "Set up the test data frame.",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "Test adding a data frame to the importer.",
"name": "test_adding_data_frames",
"signature": "def test_adding_data_frames(self)"
},
{
"docstring": "Test adding a dict t... | 5 | null | Implement the Python class `TimesketchImporterTest` described below.
Class description:
Test Timesketch importer.
Method signatures and docstrings:
- def setUp(self): Set up the test data frame.
- def test_adding_data_frames(self): Test adding a data frame to the importer.
- def test_adding_dict(self): Test adding a ... | Implement the Python class `TimesketchImporterTest` described below.
Class description:
Test Timesketch importer.
Method signatures and docstrings:
- def setUp(self): Set up the test data frame.
- def test_adding_data_frames(self): Test adding a data frame to the importer.
- def test_adding_dict(self): Test adding a ... | 24f471b58ca4a87cb053961b5f05c07a544ca7b8 | <|skeleton|>
class TimesketchImporterTest:
"""Test Timesketch importer."""
def setUp(self):
"""Set up the test data frame."""
<|body_0|>
def test_adding_data_frames(self):
"""Test adding a data frame to the importer."""
<|body_1|>
def test_adding_dict(self):
""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TimesketchImporterTest:
"""Test Timesketch importer."""
def setUp(self):
"""Set up the test data frame."""
self.lines = []
dict_one = {'timestamp': '2019-02-23T12:51:52', 'stuff': 'from bar to foobar', 'correct': False, 'random_number': 13245, 'vital_stats': 'gangverk'}
se... | the_stack_v2_python_sparse | importer_client/python/timesketch_import_client/importer_test.py | google/timesketch | train | 2,263 |
8b7de4ed9111fb86c3463ffd0880b574d7323835 | [
"from collections import deque\nfrom collections import Counter\nself.capacity = capacity\nself.cache = dict()\nself.keyQueue = deque()\nself.keyCounter = Counter()",
"if len(self.keyQueue) > 2 * self.capacity:\n self.keyCounter.clear()\n from collections import deque\n newKeyQueue = deque()\n while l... | <|body_start_0|>
from collections import deque
from collections import Counter
self.capacity = capacity
self.cache = dict()
self.keyQueue = deque()
self.keyCounter = Counter()
<|end_body_0|>
<|body_start_1|>
if len(self.keyQueue) > 2 * self.capacity:
... | LRUCache | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LRUCache:
def __init__(self, capacity):
""":type capacity: int"""
<|body_0|>
def _shrinkKeyQueue(self):
"""When keyQueue has lots of keys appearing multiple times, we need to go over it and make it concise This is required, just to save space"""
<|body_1|>
... | stack_v2_sparse_classes_36k_train_002234 | 2,015 | no_license | [
{
"docstring": ":type capacity: int",
"name": "__init__",
"signature": "def __init__(self, capacity)"
},
{
"docstring": "When keyQueue has lots of keys appearing multiple times, we need to go over it and make it concise This is required, just to save space",
"name": "_shrinkKeyQueue",
"s... | 4 | stack_v2_sparse_classes_30k_train_003387 | Implement the Python class `LRUCache` described below.
Class description:
Implement the LRUCache class.
Method signatures and docstrings:
- def __init__(self, capacity): :type capacity: int
- def _shrinkKeyQueue(self): When keyQueue has lots of keys appearing multiple times, we need to go over it and make it concise ... | Implement the Python class `LRUCache` described below.
Class description:
Implement the LRUCache class.
Method signatures and docstrings:
- def __init__(self, capacity): :type capacity: int
- def _shrinkKeyQueue(self): When keyQueue has lots of keys appearing multiple times, we need to go over it and make it concise ... | 6e051eb554d9cf6f424f1e0a77f3072adf7f64c4 | <|skeleton|>
class LRUCache:
def __init__(self, capacity):
""":type capacity: int"""
<|body_0|>
def _shrinkKeyQueue(self):
"""When keyQueue has lots of keys appearing multiple times, we need to go over it and make it concise This is required, just to save space"""
<|body_1|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LRUCache:
def __init__(self, capacity):
""":type capacity: int"""
from collections import deque
from collections import Counter
self.capacity = capacity
self.cache = dict()
self.keyQueue = deque()
self.keyCounter = Counter()
def _shrinkKeyQueue(self... | the_stack_v2_python_sparse | 146. LRU Cache.py | vincent-kangzhou/LeetCode-Python | train | 0 | |
782003429c9eed71dea3055aabf4fd7e1e34df8e | [
"product_id = self.cleaned_data['product']\ntry:\n product = Product.objects.get(id=product_id)\nexcept Product.DoesNotExist:\n raise forms.ValidationError(\"Ce produit n'existe pas !\")\nreturn product",
"group_member_id = self.cleaned_data['group_member']\ntry:\n group_member = GroupMember.objects.get(... | <|body_start_0|>
product_id = self.cleaned_data['product']
try:
product = Product.objects.get(id=product_id)
except Product.DoesNotExist:
raise forms.ValidationError("Ce produit n'existe pas !")
return product
<|end_body_0|>
<|body_start_1|>
group_member_... | Form to to permit community member (GroupMember objects), to rent products (Product object) | GroupMemberRentalForm | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GroupMemberRentalForm:
"""Form to to permit community member (GroupMember objects), to rent products (Product object)"""
def clean_product(self):
"""Return the Product object since the id input by user, if it exists"""
<|body_0|>
def clean_group_member(self):
"""... | stack_v2_sparse_classes_36k_train_002235 | 4,015 | no_license | [
{
"docstring": "Return the Product object since the id input by user, if it exists",
"name": "clean_product",
"signature": "def clean_product(self)"
},
{
"docstring": "Return the GroupMember object since the id input by user, if it exists",
"name": "clean_group_member",
"signature": "def... | 4 | stack_v2_sparse_classes_30k_test_000505 | Implement the Python class `GroupMemberRentalForm` described below.
Class description:
Form to to permit community member (GroupMember objects), to rent products (Product object)
Method signatures and docstrings:
- def clean_product(self): Return the Product object since the id input by user, if it exists
- def clean... | Implement the Python class `GroupMemberRentalForm` described below.
Class description:
Form to to permit community member (GroupMember objects), to rent products (Product object)
Method signatures and docstrings:
- def clean_product(self): Return the Product object since the id input by user, if it exists
- def clean... | cf0b982a6df2b8b4318d12d344ef0827394eedfd | <|skeleton|>
class GroupMemberRentalForm:
"""Form to to permit community member (GroupMember objects), to rent products (Product object)"""
def clean_product(self):
"""Return the Product object since the id input by user, if it exists"""
<|body_0|>
def clean_group_member(self):
"""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GroupMemberRentalForm:
"""Form to to permit community member (GroupMember objects), to rent products (Product object)"""
def clean_product(self):
"""Return the Product object since the id input by user, if it exists"""
product_id = self.cleaned_data['product']
try:
pro... | the_stack_v2_python_sparse | group_member/forms.py | cleliofavoccia/Share | train | 0 |
50fbd1041198fbd05fd2c8c54a1eb0dfc2d9e081 | [
"self._center = center\nassert width is not None or width_fun is not None, 'Must specify width'\nif isinstance(center, numpy.ndarray) and width is not None:\n assert center.shape[0] == width.shape[0], 'for N element center, width must be Nx2'\n assert width.ndim == 2, 'for N element center, width must be Nx2'... | <|body_start_0|>
self._center = center
assert width is not None or width_fun is not None, 'Must specify width'
if isinstance(center, numpy.ndarray) and width is not None:
assert center.shape[0] == width.shape[0], 'for N element center, width must be Nx2'
assert width.ndim... | Implement a deadband | Deadband | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Deadband:
"""Implement a deadband"""
def __init__(self, center, width=None, width_fun=None):
"""Constructor Arguments: center: center of the deadband width: width, can be a scalar for symmetric deadband or a vector for variable upper / lower bounds. If center is a N vector then this ... | stack_v2_sparse_classes_36k_train_002236 | 5,273 | permissive | [
{
"docstring": "Constructor Arguments: center: center of the deadband width: width, can be a scalar for symmetric deadband or a vector for variable upper / lower bounds. If center is a N vector then this should be Nx2 matrix of bounds. Optional (can specify fun) width_fun: width function, evaluates a point and ... | 3 | stack_v2_sparse_classes_30k_val_000426 | Implement the Python class `Deadband` described below.
Class description:
Implement a deadband
Method signatures and docstrings:
- def __init__(self, center, width=None, width_fun=None): Constructor Arguments: center: center of the deadband width: width, can be a scalar for symmetric deadband or a vector for variable... | Implement the Python class `Deadband` described below.
Class description:
Implement a deadband
Method signatures and docstrings:
- def __init__(self, center, width=None, width_fun=None): Constructor Arguments: center: center of the deadband width: width, can be a scalar for symmetric deadband or a vector for variable... | 6827886916e36432ce1d806f0a78edef6c9270d9 | <|skeleton|>
class Deadband:
"""Implement a deadband"""
def __init__(self, center, width=None, width_fun=None):
"""Constructor Arguments: center: center of the deadband width: width, can be a scalar for symmetric deadband or a vector for variable upper / lower bounds. If center is a N vector then this ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Deadband:
"""Implement a deadband"""
def __init__(self, center, width=None, width_fun=None):
"""Constructor Arguments: center: center of the deadband width: width, can be a scalar for symmetric deadband or a vector for variable upper / lower bounds. If center is a N vector then this should be Nx2... | the_stack_v2_python_sparse | pybots/src/filters/nonlinearities.py | aivian/robots | train | 0 |
523180d9ca36ae28f02cb325e7ff8bdde9ad6886 | [
"oldpath = sys.path\nmod = tested._import_argmod(sys)\nself.assertEqual(mod, sys)",
"with mock.patch('SConsArguments.Importer.GetDefaultArgpath') as mock_GetDefaultArgpath, mock.patch('SConsArguments.Importer._load_module_file') as mock_load_module_file:\n mock_GetDefaultArgpath.return_value = ['site_scons/sit... | <|body_start_0|>
oldpath = sys.path
mod = tested._import_argmod(sys)
self.assertEqual(mod, sys)
<|end_body_0|>
<|body_start_1|>
with mock.patch('SConsArguments.Importer.GetDefaultArgpath') as mock_GetDefaultArgpath, mock.patch('SConsArguments.Importer._load_module_file') as mock_load_mo... | Test__import_argmod | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Test__import_argmod:
def test__import_argmod_1(self):
"""Test SConsArguments.Importer._import_argmod(sys)"""
<|body_0|>
def test__import_argmod_2(self):
"""Test SConsArguments.Importer._import_argmod('foo')"""
<|body_1|>
def test__import_argmod_3(self):
... | stack_v2_sparse_classes_36k_train_002237 | 42,804 | permissive | [
{
"docstring": "Test SConsArguments.Importer._import_argmod(sys)",
"name": "test__import_argmod_1",
"signature": "def test__import_argmod_1(self)"
},
{
"docstring": "Test SConsArguments.Importer._import_argmod('foo')",
"name": "test__import_argmod_2",
"signature": "def test__import_argmo... | 4 | stack_v2_sparse_classes_30k_train_000905 | Implement the Python class `Test__import_argmod` described below.
Class description:
Implement the Test__import_argmod class.
Method signatures and docstrings:
- def test__import_argmod_1(self): Test SConsArguments.Importer._import_argmod(sys)
- def test__import_argmod_2(self): Test SConsArguments.Importer._import_ar... | Implement the Python class `Test__import_argmod` described below.
Class description:
Implement the Test__import_argmod class.
Method signatures and docstrings:
- def test__import_argmod_1(self): Test SConsArguments.Importer._import_argmod(sys)
- def test__import_argmod_2(self): Test SConsArguments.Importer._import_ar... | f4b783fc79fe3fc16e8d0f58308099a67752d299 | <|skeleton|>
class Test__import_argmod:
def test__import_argmod_1(self):
"""Test SConsArguments.Importer._import_argmod(sys)"""
<|body_0|>
def test__import_argmod_2(self):
"""Test SConsArguments.Importer._import_argmod('foo')"""
<|body_1|>
def test__import_argmod_3(self):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Test__import_argmod:
def test__import_argmod_1(self):
"""Test SConsArguments.Importer._import_argmod(sys)"""
oldpath = sys.path
mod = tested._import_argmod(sys)
self.assertEqual(mod, sys)
def test__import_argmod_2(self):
"""Test SConsArguments.Importer._import_argm... | the_stack_v2_python_sparse | unit_tests/SConsArgumentsT/ImporterTests.py | mcqueen256/scons-arguments | train | 0 | |
8820a38633b04c945c8e979593fcdaba162d1494 | [
"super().__init__(coordinator, serial)\nself.battery_cam_type = bool(self.data['device_category'] == DeviceCatagories.BATTERY_CAMERA_DEVICE_CATEGORY.value)\nself._attr_unique_id = f'{serial}_Light'\nself._attr_is_on = self.data['switches'][DeviceSwitchType.ALARM_LIGHT.value]\nself._attr_brightness = round(percentag... | <|body_start_0|>
super().__init__(coordinator, serial)
self.battery_cam_type = bool(self.data['device_category'] == DeviceCatagories.BATTERY_CAMERA_DEVICE_CATEGORY.value)
self._attr_unique_id = f'{serial}_Light'
self._attr_is_on = self.data['switches'][DeviceSwitchType.ALARM_LIGHT.value]... | Representation of a EZVIZ light. | EzvizLight | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EzvizLight:
"""Representation of a EZVIZ light."""
def __init__(self, coordinator: EzvizDataUpdateCoordinator, serial: str) -> None:
"""Initialize the light."""
<|body_0|>
async def async_turn_on(self, **kwargs: Any) -> None:
"""Turn on light."""
<|body_1... | stack_v2_sparse_classes_36k_train_002238 | 4,518 | permissive | [
{
"docstring": "Initialize the light.",
"name": "__init__",
"signature": "def __init__(self, coordinator: EzvizDataUpdateCoordinator, serial: str) -> None"
},
{
"docstring": "Turn on light.",
"name": "async_turn_on",
"signature": "async def async_turn_on(self, **kwargs: Any) -> None"
}... | 4 | null | Implement the Python class `EzvizLight` described below.
Class description:
Representation of a EZVIZ light.
Method signatures and docstrings:
- def __init__(self, coordinator: EzvizDataUpdateCoordinator, serial: str) -> None: Initialize the light.
- async def async_turn_on(self, **kwargs: Any) -> None: Turn on light... | Implement the Python class `EzvizLight` described below.
Class description:
Representation of a EZVIZ light.
Method signatures and docstrings:
- def __init__(self, coordinator: EzvizDataUpdateCoordinator, serial: str) -> None: Initialize the light.
- async def async_turn_on(self, **kwargs: Any) -> None: Turn on light... | 80caeafcb5b6e2f9da192d0ea6dd1a5b8244b743 | <|skeleton|>
class EzvizLight:
"""Representation of a EZVIZ light."""
def __init__(self, coordinator: EzvizDataUpdateCoordinator, serial: str) -> None:
"""Initialize the light."""
<|body_0|>
async def async_turn_on(self, **kwargs: Any) -> None:
"""Turn on light."""
<|body_1... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EzvizLight:
"""Representation of a EZVIZ light."""
def __init__(self, coordinator: EzvizDataUpdateCoordinator, serial: str) -> None:
"""Initialize the light."""
super().__init__(coordinator, serial)
self.battery_cam_type = bool(self.data['device_category'] == DeviceCatagories.BATT... | the_stack_v2_python_sparse | homeassistant/components/ezviz/light.py | home-assistant/core | train | 35,501 |
baa42aee071b62915a90015f799a829a341cfda1 | [
"if bypass_roles is None:\n return []\n\ndef _coerce_to_int(input: int | str) -> int | str:\n try:\n return int(input)\n except ValueError:\n return input\nreturn map(_coerce_to_int, bypass_roles)",
"if not isinstance(ctx.author, Member):\n return True\nreturn all((member_role.id not in ... | <|body_start_0|>
if bypass_roles is None:
return []
def _coerce_to_int(input: int | str) -> int | str:
try:
return int(input)
except ValueError:
return input
return map(_coerce_to_int, bypass_roles)
<|end_body_0|>
<|body_start... | A setting entry which tells whether the roles the member has allow them to bypass the filter. | RoleBypass | [
"MIT",
"BSD-3-Clause",
"Python-2.0",
"BSD-2-Clause",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RoleBypass:
"""A setting entry which tells whether the roles the member has allow them to bypass the filter."""
def init_if_bypass_roles_none(cls, bypass_roles: Sequence[int | str] | None) -> Sequence[int | str]:
"""Initialize an empty sequence if the value is None. This also coerces... | stack_v2_sparse_classes_36k_train_002239 | 1,617 | permissive | [
{
"docstring": "Initialize an empty sequence if the value is None. This also coerces each element of bypass_roles to an int, if possible.",
"name": "init_if_bypass_roles_none",
"signature": "def init_if_bypass_roles_none(cls, bypass_roles: Sequence[int | str] | None) -> Sequence[int | str]"
},
{
... | 2 | stack_v2_sparse_classes_30k_train_009669 | Implement the Python class `RoleBypass` described below.
Class description:
A setting entry which tells whether the roles the member has allow them to bypass the filter.
Method signatures and docstrings:
- def init_if_bypass_roles_none(cls, bypass_roles: Sequence[int | str] | None) -> Sequence[int | str]: Initialize ... | Implement the Python class `RoleBypass` described below.
Class description:
A setting entry which tells whether the roles the member has allow them to bypass the filter.
Method signatures and docstrings:
- def init_if_bypass_roles_none(cls, bypass_roles: Sequence[int | str] | None) -> Sequence[int | str]: Initialize ... | f2048684291cc6358565e96ef3562512fbeb2505 | <|skeleton|>
class RoleBypass:
"""A setting entry which tells whether the roles the member has allow them to bypass the filter."""
def init_if_bypass_roles_none(cls, bypass_roles: Sequence[int | str] | None) -> Sequence[int | str]:
"""Initialize an empty sequence if the value is None. This also coerces... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RoleBypass:
"""A setting entry which tells whether the roles the member has allow them to bypass the filter."""
def init_if_bypass_roles_none(cls, bypass_roles: Sequence[int | str] | None) -> Sequence[int | str]:
"""Initialize an empty sequence if the value is None. This also coerces each element... | the_stack_v2_python_sparse | bot/exts/filtering/_settings_types/validations/bypass_roles.py | python-discord/bot | train | 1,479 |
a0c16dfd3b725f1560b3ba91ac35af2e347383bf | [
"n = len(s)\nfor i in range(int(n / 2)):\n if s[i] != s[n - i - 1]:\n return self.valid(s[i:n - i - 1]) or self.valid(s[i + 1:n - i])\nreturn True",
"n = len(s)\nfor i in range(int(n / 2)):\n if s[i] != s[n - i - 1]:\n return False\nreturn True"
] | <|body_start_0|>
n = len(s)
for i in range(int(n / 2)):
if s[i] != s[n - i - 1]:
return self.valid(s[i:n - i - 1]) or self.valid(s[i + 1:n - i])
return True
<|end_body_0|>
<|body_start_1|>
n = len(s)
for i in range(int(n / 2)):
if s[i] != ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def validPalindrome(self, s):
""":type s: str :rtype: bool"""
<|body_0|>
def valid(self, s):
""":type s: str :rtype: bool"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
n = len(s)
for i in range(int(n / 2)):
if s[i] !=... | stack_v2_sparse_classes_36k_train_002240 | 568 | no_license | [
{
"docstring": ":type s: str :rtype: bool",
"name": "validPalindrome",
"signature": "def validPalindrome(self, s)"
},
{
"docstring": ":type s: str :rtype: bool",
"name": "valid",
"signature": "def valid(self, s)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def validPalindrome(self, s): :type s: str :rtype: bool
- def valid(self, s): :type s: str :rtype: bool | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def validPalindrome(self, s): :type s: str :rtype: bool
- def valid(self, s): :type s: str :rtype: bool
<|skeleton|>
class Solution:
def validPalindrome(self, s):
"... | 7d7740f4db4f8500c84eff353420c61242321f2e | <|skeleton|>
class Solution:
def validPalindrome(self, s):
""":type s: str :rtype: bool"""
<|body_0|>
def valid(self, s):
""":type s: str :rtype: bool"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def validPalindrome(self, s):
""":type s: str :rtype: bool"""
n = len(s)
for i in range(int(n / 2)):
if s[i] != s[n - i - 1]:
return self.valid(s[i:n - i - 1]) or self.valid(s[i + 1:n - i])
return True
def valid(self, s):
""":t... | the_stack_v2_python_sparse | problems/valid_palindrome.py | vchub/daily-python | train | 0 | |
b3a486a5572cf1997231f36f6b3148b1325be99c | [
"self.completion_percentage = completion_percentage\nself.error_message = error_message\nself.events = events\nself.in_progress = in_progress\nself.message = message\nself.seconds_remaining = seconds_remaining\nself.warnings_found = warnings_found",
"if dictionary is None:\n return None\ncompletion_percentage ... | <|body_start_0|>
self.completion_percentage = completion_percentage
self.error_message = error_message
self.events = events
self.in_progress = in_progress
self.message = message
self.seconds_remaining = seconds_remaining
self.warnings_found = warnings_found
<|end_... | Implementation of the 'ClusterCreationProgressResult' model. Specifies the values returned after a successful request to get the Cluster creation progress. Attributes: completion_percentage (int): Specifies an approximate completion percentage for the Cluster creation process. error_message (string): Specifies a descri... | ClusterCreationProgressResult | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ClusterCreationProgressResult:
"""Implementation of the 'ClusterCreationProgressResult' model. Specifies the values returned after a successful request to get the Cluster creation progress. Attributes: completion_percentage (int): Specifies an approximate completion percentage for the Cluster cre... | stack_v2_sparse_classes_36k_train_002241 | 3,737 | permissive | [
{
"docstring": "Constructor for the ClusterCreationProgressResult class",
"name": "__init__",
"signature": "def __init__(self, completion_percentage=None, error_message=None, events=None, in_progress=None, message=None, seconds_remaining=None, warnings_found=None)"
},
{
"docstring": "Creates an ... | 2 | null | Implement the Python class `ClusterCreationProgressResult` described below.
Class description:
Implementation of the 'ClusterCreationProgressResult' model. Specifies the values returned after a successful request to get the Cluster creation progress. Attributes: completion_percentage (int): Specifies an approximate co... | Implement the Python class `ClusterCreationProgressResult` described below.
Class description:
Implementation of the 'ClusterCreationProgressResult' model. Specifies the values returned after a successful request to get the Cluster creation progress. Attributes: completion_percentage (int): Specifies an approximate co... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class ClusterCreationProgressResult:
"""Implementation of the 'ClusterCreationProgressResult' model. Specifies the values returned after a successful request to get the Cluster creation progress. Attributes: completion_percentage (int): Specifies an approximate completion percentage for the Cluster cre... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ClusterCreationProgressResult:
"""Implementation of the 'ClusterCreationProgressResult' model. Specifies the values returned after a successful request to get the Cluster creation progress. Attributes: completion_percentage (int): Specifies an approximate completion percentage for the Cluster creation process... | the_stack_v2_python_sparse | cohesity_management_sdk/models/cluster_creation_progress_result.py | cohesity/management-sdk-python | train | 24 |
9cfa265a1dbfe5f394575eb74dc3fca408a743a5 | [
"try:\n rule = SigmaRule.query.filter_by(rule_uuid=rule_uuid).first()\nexcept Exception as e:\n error_msg = 'Unable to get the Sigma rule {0!s}'.format(e)\n logger.error(error_msg, exc_info=True)\n abort(HTTP_STATUS_CODE_INTERNAL_SERVER_ERROR, error_msg)\nif not rule:\n abort(HTTP_STATUS_CODE_NOT_FOU... | <|body_start_0|>
try:
rule = SigmaRule.query.filter_by(rule_uuid=rule_uuid).first()
except Exception as e:
error_msg = 'Unable to get the Sigma rule {0!s}'.format(e)
logger.error(error_msg, exc_info=True)
abort(HTTP_STATUS_CODE_INTERNAL_SERVER_ERROR, error... | Resource to read / delete / create / update a Sigma rule. | SigmaRuleResource | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SigmaRuleResource:
"""Resource to read / delete / create / update a Sigma rule."""
def get(self, rule_uuid):
"""Fetches a single Sigma rule from the database. Fetches a single Sigma rule selected by the `UUID` in `/sigmarule/<string:rule_uuid>/` and returns a JSON represantion of the... | stack_v2_sparse_classes_36k_train_002242 | 12,205 | permissive | [
{
"docstring": "Fetches a single Sigma rule from the database. Fetches a single Sigma rule selected by the `UUID` in `/sigmarule/<string:rule_uuid>/` and returns a JSON represantion of the rule. Args: rule_uuid: UUID of the rule. Returns: JSON sigma rule representation e.g.: {\"objects\": [return_rule], \"meta\... | 3 | stack_v2_sparse_classes_30k_train_015442 | Implement the Python class `SigmaRuleResource` described below.
Class description:
Resource to read / delete / create / update a Sigma rule.
Method signatures and docstrings:
- def get(self, rule_uuid): Fetches a single Sigma rule from the database. Fetches a single Sigma rule selected by the `UUID` in `/sigmarule/<s... | Implement the Python class `SigmaRuleResource` described below.
Class description:
Resource to read / delete / create / update a Sigma rule.
Method signatures and docstrings:
- def get(self, rule_uuid): Fetches a single Sigma rule from the database. Fetches a single Sigma rule selected by the `UUID` in `/sigmarule/<s... | 24f471b58ca4a87cb053961b5f05c07a544ca7b8 | <|skeleton|>
class SigmaRuleResource:
"""Resource to read / delete / create / update a Sigma rule."""
def get(self, rule_uuid):
"""Fetches a single Sigma rule from the database. Fetches a single Sigma rule selected by the `UUID` in `/sigmarule/<string:rule_uuid>/` and returns a JSON represantion of the... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SigmaRuleResource:
"""Resource to read / delete / create / update a Sigma rule."""
def get(self, rule_uuid):
"""Fetches a single Sigma rule from the database. Fetches a single Sigma rule selected by the `UUID` in `/sigmarule/<string:rule_uuid>/` and returns a JSON represantion of the rule. Args: ... | the_stack_v2_python_sparse | timesketch/api/v1/resources/sigma.py | google/timesketch | train | 2,263 |
02d9431ebfa90f74cf89bce310719b888383bdac | [
"if isinstance(other, GitIgnoreSpec):\n return super().__eq__(other)\nelif isinstance(other, PathSpec):\n return False\nelse:\n return NotImplemented",
"if pattern_factory is None:\n pattern_factory = GitWildMatchPattern\nelif (isinstance(lines, str) or callable(lines)) and _is_iterable(pattern_factor... | <|body_start_0|>
if isinstance(other, GitIgnoreSpec):
return super().__eq__(other)
elif isinstance(other, PathSpec):
return False
else:
return NotImplemented
<|end_body_0|>
<|body_start_1|>
if pattern_factory is None:
pattern_factory = Git... | The :class:`GitIgnoreSpec` class extends :class:`PathSpec` to replicate *.gitignore* behavior. | GitIgnoreSpec | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GitIgnoreSpec:
"""The :class:`GitIgnoreSpec` class extends :class:`PathSpec` to replicate *.gitignore* behavior."""
def __eq__(self, other: object) -> bool:
"""Tests the equality of this gitignore-spec with *other* (:class:`GitIgnoreSpec`) by comparing their :attr:`~PathSpec.patterns... | stack_v2_sparse_classes_36k_train_002243 | 3,895 | permissive | [
{
"docstring": "Tests the equality of this gitignore-spec with *other* (:class:`GitIgnoreSpec`) by comparing their :attr:`~PathSpec.patterns` attributes. A non-:class:`GitIgnoreSpec` will not compare equal.",
"name": "__eq__",
"signature": "def __eq__(self, other: object) -> bool"
},
{
"docstrin... | 3 | null | Implement the Python class `GitIgnoreSpec` described below.
Class description:
The :class:`GitIgnoreSpec` class extends :class:`PathSpec` to replicate *.gitignore* behavior.
Method signatures and docstrings:
- def __eq__(self, other: object) -> bool: Tests the equality of this gitignore-spec with *other* (:class:`Git... | Implement the Python class `GitIgnoreSpec` described below.
Class description:
The :class:`GitIgnoreSpec` class extends :class:`PathSpec` to replicate *.gitignore* behavior.
Method signatures and docstrings:
- def __eq__(self, other: object) -> bool: Tests the equality of this gitignore-spec with *other* (:class:`Git... | d72e5310ed4a8165d7ee516d79e0accccaf7748c | <|skeleton|>
class GitIgnoreSpec:
"""The :class:`GitIgnoreSpec` class extends :class:`PathSpec` to replicate *.gitignore* behavior."""
def __eq__(self, other: object) -> bool:
"""Tests the equality of this gitignore-spec with *other* (:class:`GitIgnoreSpec`) by comparing their :attr:`~PathSpec.patterns... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GitIgnoreSpec:
"""The :class:`GitIgnoreSpec` class extends :class:`PathSpec` to replicate *.gitignore* behavior."""
def __eq__(self, other: object) -> bool:
"""Tests the equality of this gitignore-spec with *other* (:class:`GitIgnoreSpec`) by comparing their :attr:`~PathSpec.patterns` attributes.... | the_stack_v2_python_sparse | robocorp-python-ls-core/src/robocorp_ls_core/libs/robotidy_lib/pathspec/gitignore.py | robocorp/robotframework-lsp | train | 167 |
ff3fca948cf5e82e00dd85cc1c6b96e8278eb91c | [
"partial = kwargs.pop('partial', False)\ninstance = self.get_object()\nserializer = self.get_serializer(instance, data=request.data, partial=partial)\nserializer.is_valid(raise_exception=True)\nif Credential.objects.filter(owner=request.user, name=serializer.validated_data['name'], linux_user=serializer.validated_d... | <|body_start_0|>
partial = kwargs.pop('partial', False)
instance = self.get_object()
serializer = self.get_serializer(instance, data=request.data, partial=partial)
serializer.is_valid(raise_exception=True)
if Credential.objects.filter(owner=request.user, name=serializer.validated... | UpdateCredentialView | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UpdateCredentialView:
def update(self, request, *args, **kwargs):
"""Overwritten the default `update` method in order to catch unique constraint violation."""
<|body_0|>
def perform_update(self, serializer):
"""Overwrite the default 'perform_update' method in order t... | stack_v2_sparse_classes_36k_train_002244 | 43,758 | permissive | [
{
"docstring": "Overwritten the default `update` method in order to catch unique constraint violation.",
"name": "update",
"signature": "def update(self, request, *args, **kwargs)"
},
{
"docstring": "Overwrite the default 'perform_update' method in order to properly handle tags received as value... | 2 | null | Implement the Python class `UpdateCredentialView` described below.
Class description:
Implement the UpdateCredentialView class.
Method signatures and docstrings:
- def update(self, request, *args, **kwargs): Overwritten the default `update` method in order to catch unique constraint violation.
- def perform_update(se... | Implement the Python class `UpdateCredentialView` described below.
Class description:
Implement the UpdateCredentialView class.
Method signatures and docstrings:
- def update(self, request, *args, **kwargs): Overwritten the default `update` method in order to catch unique constraint violation.
- def perform_update(se... | 702254c48677cf5a6f2fe298bced854299868eef | <|skeleton|>
class UpdateCredentialView:
def update(self, request, *args, **kwargs):
"""Overwritten the default `update` method in order to catch unique constraint violation."""
<|body_0|>
def perform_update(self, serializer):
"""Overwrite the default 'perform_update' method in order t... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UpdateCredentialView:
def update(self, request, *args, **kwargs):
"""Overwritten the default `update` method in order to catch unique constraint violation."""
partial = kwargs.pop('partial', False)
instance = self.get_object()
serializer = self.get_serializer(instance, data=req... | the_stack_v2_python_sparse | backend/device_registry/api_views.py | a-martynovich/api | train | 0 | |
cf06d4c271acece9e23a2de1b3090a1d352d3749 | [
"Expr.__init__(self, template, line)\nself._var = var\nself._nodes = nodes",
"try:\n var = self._env.get(self._var)\n params = [node.eval() for node in self._nodes]\nexcept KeyError:\n raise UnknownVariableError('.'.join(self._var), self._template._filename, self._line)\ntry:\n for param in params:\n ... | <|body_start_0|>
Expr.__init__(self, template, line)
self._var = var
self._nodes = nodes
<|end_body_0|>
<|body_start_1|>
try:
var = self._env.get(self._var)
params = [node.eval() for node in self._nodes]
except KeyError:
raise UnknownVariableE... | An array index expression node. | IndexExpr | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IndexExpr:
"""An array index expression node."""
def __init__(self, template, line, var, nodes):
"""Initialize the node."""
<|body_0|>
def eval(self):
"""Evaluate the expression."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
Expr.__init__(self... | stack_v2_sparse_classes_36k_train_002245 | 3,521 | permissive | [
{
"docstring": "Initialize the node.",
"name": "__init__",
"signature": "def __init__(self, template, line, var, nodes)"
},
{
"docstring": "Evaluate the expression.",
"name": "eval",
"signature": "def eval(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_002781 | Implement the Python class `IndexExpr` described below.
Class description:
An array index expression node.
Method signatures and docstrings:
- def __init__(self, template, line, var, nodes): Initialize the node.
- def eval(self): Evaluate the expression. | Implement the Python class `IndexExpr` described below.
Class description:
An array index expression node.
Method signatures and docstrings:
- def __init__(self, template, line, var, nodes): Initialize the node.
- def eval(self): Evaluate the expression.
<|skeleton|>
class IndexExpr:
"""An array index expression... | 6aeee9b229d3f62aace98a51d9014781bbe6cb52 | <|skeleton|>
class IndexExpr:
"""An array index expression node."""
def __init__(self, template, line, var, nodes):
"""Initialize the node."""
<|body_0|>
def eval(self):
"""Evaluate the expression."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class IndexExpr:
"""An array index expression node."""
def __init__(self, template, line, var, nodes):
"""Initialize the node."""
Expr.__init__(self, template, line)
self._var = var
self._nodes = nodes
def eval(self):
"""Evaluate the expression."""
try:
... | the_stack_v2_python_sparse | mrbaviirc/template/expr.py | brianvanderburg2/mrbaviirc | train | 0 |
660e8c3008156b24758079d3954032cbafaf2d3c | [
"create_count = 0\nnext(csvreader)\nfor row in csvreader:\n ci, created = CoinifyInvoice.objects.get_or_create(coinify_id=row[0], coinify_id_alpha=row[1], coinify_created=timezone.make_aware(datetime.strptime(row[2], '%Y-%m-%d %H:%M:%S'), timezone=timezone.utc), payment_amount=Decimal(row[3]), payment_currency=r... | <|body_start_0|>
create_count = 0
next(csvreader)
for row in csvreader:
ci, created = CoinifyInvoice.objects.get_or_create(coinify_id=row[0], coinify_id_alpha=row[1], coinify_created=timezone.make_aware(datetime.strptime(row[2], '%Y-%m-%d %H:%M:%S'), timezone=timezone.utc), payment_a... | CoinifyCSVImporter | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CoinifyCSVImporter:
def import_coinify_invoice_csv(csvreader):
"""Import a CSV file with Coinify invoices exported from their webinterface. Assumes a CSV structure like this: id,id_alpha,created,payment_amount,payment_currency,payment_btc_amount,description,custom,credited_amount,credite... | stack_v2_sparse_classes_36k_train_002246 | 47,704 | permissive | [
{
"docstring": "Import a CSV file with Coinify invoices exported from their webinterface. Assumes a CSV structure like this: id,id_alpha,created,payment_amount,payment_currency,payment_btc_amount,description,custom,credited_amount,credited_currency,state,payment_type,original_payment_id 54276,sdJGd,\"2020-02-06... | 3 | null | Implement the Python class `CoinifyCSVImporter` described below.
Class description:
Implement the CoinifyCSVImporter class.
Method signatures and docstrings:
- def import_coinify_invoice_csv(csvreader): Import a CSV file with Coinify invoices exported from their webinterface. Assumes a CSV structure like this: id,id_... | Implement the Python class `CoinifyCSVImporter` described below.
Class description:
Implement the CoinifyCSVImporter class.
Method signatures and docstrings:
- def import_coinify_invoice_csv(csvreader): Import a CSV file with Coinify invoices exported from their webinterface. Assumes a CSV structure like this: id,id_... | 767deb7f58429e9162e0c2ef79be9f0f38f37ce1 | <|skeleton|>
class CoinifyCSVImporter:
def import_coinify_invoice_csv(csvreader):
"""Import a CSV file with Coinify invoices exported from their webinterface. Assumes a CSV structure like this: id,id_alpha,created,payment_amount,payment_currency,payment_btc_amount,description,custom,credited_amount,credite... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CoinifyCSVImporter:
def import_coinify_invoice_csv(csvreader):
"""Import a CSV file with Coinify invoices exported from their webinterface. Assumes a CSV structure like this: id,id_alpha,created,payment_amount,payment_currency,payment_btc_amount,description,custom,credited_amount,credited_currency,sta... | the_stack_v2_python_sparse | src/economy/utils.py | bornhack/bornhack-website | train | 9 | |
ccfe61d89057966b67f4f46610e52cc9d70595cb | [
"self.size = 0\nself.head = None\nself.tail = None",
"if self.head == None:\n self.addAtHead(index)\nx = self.head\nif index < self.size:\n for _ in range(index):\n x = x.next\n return x.key\nreturn -1",
"if not self.head:\n self.head = Node(val)\nelse:\n new_node = Node(val)\n new_node... | <|body_start_0|>
self.size = 0
self.head = None
self.tail = None
<|end_body_0|>
<|body_start_1|>
if self.head == None:
self.addAtHead(index)
x = self.head
if index < self.size:
for _ in range(index):
x = x.next
return x... | MyLinkedList | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MyLinkedList:
def __init__(self):
"""Initialize your data structure here."""
<|body_0|>
def get(self, index: int) -> int:
"""Get the value of the index-th node in the linked list. If the index is invalid, return -addAtIndexaddAtIndex1."""
<|body_1|>
def ... | stack_v2_sparse_classes_36k_train_002247 | 2,808 | no_license | [
{
"docstring": "Initialize your data structure here.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Get the value of the index-th node in the linked list. If the index is invalid, return -addAtIndexaddAtIndex1.",
"name": "get",
"signature": "def get(self, inde... | 6 | stack_v2_sparse_classes_30k_train_013411 | Implement the Python class `MyLinkedList` described below.
Class description:
Implement the MyLinkedList class.
Method signatures and docstrings:
- def __init__(self): Initialize your data structure here.
- def get(self, index: int) -> int: Get the value of the index-th node in the linked list. If the index is invali... | Implement the Python class `MyLinkedList` described below.
Class description:
Implement the MyLinkedList class.
Method signatures and docstrings:
- def __init__(self): Initialize your data structure here.
- def get(self, index: int) -> int: Get the value of the index-th node in the linked list. If the index is invali... | 8482bd12369b1f18faa4ac19bc3423750fea4695 | <|skeleton|>
class MyLinkedList:
def __init__(self):
"""Initialize your data structure here."""
<|body_0|>
def get(self, index: int) -> int:
"""Get the value of the index-th node in the linked list. If the index is invalid, return -addAtIndexaddAtIndex1."""
<|body_1|>
def ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MyLinkedList:
def __init__(self):
"""Initialize your data structure here."""
self.size = 0
self.head = None
self.tail = None
def get(self, index: int) -> int:
"""Get the value of the index-th node in the linked list. If the index is invalid, return -addAtIndexaddAt... | the_stack_v2_python_sparse | dataStructures/linkedLists/linkedList.py | robahall/algosds | train | 0 | |
5ff24d115c0b53d9962b8aad7c909328bbd9859b | [
"try:\n driver = HomeElement(self.driver)\n driver.get(self.url)\n driver.new_table_click(location=1)\n driver.full_windows_screen(self.screenshots_path, 1920, 980)\n self.first = driver.news_assert(url=self.data[0])\n self.assertEqual(self.first, self.second)\nexcept Exception:\n self.error = ... | <|body_start_0|>
try:
driver = HomeElement(self.driver)
driver.get(self.url)
driver.new_table_click(location=1)
driver.full_windows_screen(self.screenshots_path, 1920, 980)
self.first = driver.news_assert(url=self.data[0])
self.assertEqual(... | :param: RE_LOGIN: 需要切换账号登录，当RE_LOGIN = True时，需要将LOGIN_INFO的value值全填写完成， 如果请求的账号中只有一家公司,那么company中的value就可以忽略不填写，否则会报错... :param: MODULE: 为当前运行的模块，根据当前运行的模块调用common中的对应的用例方法，需保留此变量方法 | TestNewCenter | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestNewCenter:
""":param: RE_LOGIN: 需要切换账号登录，当RE_LOGIN = True时，需要将LOGIN_INFO的value值全填写完成， 如果请求的账号中只有一家公司,那么company中的value就可以忽略不填写，否则会报错... :param: MODULE: 为当前运行的模块，根据当前运行的模块调用common中的对应的用例方法，需保留此变量方法"""
def test_good_news_table_one(self):
"""验证GoodNews是否能正常打开并跳转; 1、打开首页; 2、点击GoodNews... | stack_v2_sparse_classes_36k_train_002248 | 3,012 | no_license | [
{
"docstring": "验证GoodNews是否能正常打开并跳转; 1、打开首页; 2、点击GoodNews; 3、断言跳转的url是否包含{/news/71.html}",
"name": "test_good_news_table_one",
"signature": "def test_good_news_table_one(self)"
},
{
"docstring": "验证GoodNewsTwo是否能正常打开并跳转; 1、打开首页; 2、点击GoodNewsTwo; 3、断言跳转的url是否包含{/news/48.html}",
"name": "test... | 3 | null | Implement the Python class `TestNewCenter` described below.
Class description:
:param: RE_LOGIN: 需要切换账号登录，当RE_LOGIN = True时，需要将LOGIN_INFO的value值全填写完成， 如果请求的账号中只有一家公司,那么company中的value就可以忽略不填写，否则会报错... :param: MODULE: 为当前运行的模块，根据当前运行的模块调用common中的对应的用例方法，需保留此变量方法
Method signatures and docstrings:
- def test_good_news_ta... | Implement the Python class `TestNewCenter` described below.
Class description:
:param: RE_LOGIN: 需要切换账号登录，当RE_LOGIN = True时，需要将LOGIN_INFO的value值全填写完成， 如果请求的账号中只有一家公司,那么company中的value就可以忽略不填写，否则会报错... :param: MODULE: 为当前运行的模块，根据当前运行的模块调用common中的对应的用例方法，需保留此变量方法
Method signatures and docstrings:
- def test_good_news_ta... | 86bb051e62abdf2ed5bbdbea4c9008a6c1f49060 | <|skeleton|>
class TestNewCenter:
""":param: RE_LOGIN: 需要切换账号登录，当RE_LOGIN = True时，需要将LOGIN_INFO的value值全填写完成， 如果请求的账号中只有一家公司,那么company中的value就可以忽略不填写，否则会报错... :param: MODULE: 为当前运行的模块，根据当前运行的模块调用common中的对应的用例方法，需保留此变量方法"""
def test_good_news_table_one(self):
"""验证GoodNews是否能正常打开并跳转; 1、打开首页; 2、点击GoodNews... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestNewCenter:
""":param: RE_LOGIN: 需要切换账号登录，当RE_LOGIN = True时，需要将LOGIN_INFO的value值全填写完成， 如果请求的账号中只有一家公司,那么company中的value就可以忽略不填写，否则会报错... :param: MODULE: 为当前运行的模块，根据当前运行的模块调用common中的对应的用例方法，需保留此变量方法"""
def test_good_news_table_one(self):
"""验证GoodNews是否能正常打开并跳转; 1、打开首页; 2、点击GoodNews; 3、断言跳转的url是... | the_stack_v2_python_sparse | Manufacture/home/new_center_st.py | yushu1987/UI | train | 0 |
c814413a89f1a2ba365ccf859a397170ddd11655 | [
"super().__init__()\nself.reference_sequence_length = reference_sequence_length\nself.reference_hidden_size = reference_hidden_size\nself.context_sequence_length = context_sequence_length\nself.context_hidden_size = context_hidden_size\nself.attention_size = attention_size\nself.individual_nonlinearity = individual... | <|body_start_0|>
super().__init__()
self.reference_sequence_length = reference_sequence_length
self.reference_hidden_size = reference_hidden_size
self.context_sequence_length = context_sequence_length
self.context_hidden_size = context_hidden_size
self.attention_size = at... | Implements context attention as in the PaccMann paper (Figure 2C) in Molecular Pharmaceutics. With the additional option of having a hidden size in the context. NOTE: In tensorflow, weights were initialized from N(0,0.1). Instead, pytorch uses U(-stddev, stddev) where stddev=1./math.sqrt(weight.size(1)). | ContextAttentionLayer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ContextAttentionLayer:
"""Implements context attention as in the PaccMann paper (Figure 2C) in Molecular Pharmaceutics. With the additional option of having a hidden size in the context. NOTE: In tensorflow, weights were initialized from N(0,0.1). Instead, pytorch uses U(-stddev, stddev) where st... | stack_v2_sparse_classes_36k_train_002249 | 25,239 | no_license | [
{
"docstring": "Constructor Arguments: reference_hidden_size (int): Hidden size of the reference input over which the attention will be computed (H). reference_sequence_length (int): Sequence length of the reference (T). context_hidden_size (int): This is either simply the amount of features used as context (G)... | 2 | stack_v2_sparse_classes_30k_train_003737 | Implement the Python class `ContextAttentionLayer` described below.
Class description:
Implements context attention as in the PaccMann paper (Figure 2C) in Molecular Pharmaceutics. With the additional option of having a hidden size in the context. NOTE: In tensorflow, weights were initialized from N(0,0.1). Instead, p... | Implement the Python class `ContextAttentionLayer` described below.
Class description:
Implements context attention as in the PaccMann paper (Figure 2C) in Molecular Pharmaceutics. With the additional option of having a hidden size in the context. NOTE: In tensorflow, weights were initialized from N(0,0.1). Instead, p... | e88840528fa963066f85940ffeb31687773be2ba | <|skeleton|>
class ContextAttentionLayer:
"""Implements context attention as in the PaccMann paper (Figure 2C) in Molecular Pharmaceutics. With the additional option of having a hidden size in the context. NOTE: In tensorflow, weights were initialized from N(0,0.1). Instead, pytorch uses U(-stddev, stddev) where st... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ContextAttentionLayer:
"""Implements context attention as in the PaccMann paper (Figure 2C) in Molecular Pharmaceutics. With the additional option of having a hidden size in the context. NOTE: In tensorflow, weights were initialized from N(0,0.1). Instead, pytorch uses U(-stddev, stddev) where stddev=1./math.... | the_stack_v2_python_sparse | Utility/layers.py | kaicd/KAICD_pipeline | train | 0 |
031e2e91533d1e57107a7a8d3ee840508aab3b85 | [
"group = {}\nfor s in strs:\n key = [0] * 26\n for c in s:\n key[ord(c) - ord('a')] += 1\n key = tuple(key)\n if group.get(key):\n group[key].append(s)\n else:\n group[key] = [s]\nreturn group.values()",
"group = {}\nfor s in strs:\n key = tuple(sorted(s))\n if group.get(... | <|body_start_0|>
group = {}
for s in strs:
key = [0] * 26
for c in s:
key[ord(c) - ord('a')] += 1
key = tuple(key)
if group.get(key):
group[key].append(s)
else:
group[key] = [s]
return gro... | GroupAnagrams | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GroupAnagrams:
def group(strs):
"""Use this method when the range of the chars are known (like lowercase chars only). :type strs: List[str] :rtype: List[List[str]]"""
<|body_0|>
def group_sorted(strs):
"""Use this method when the range of the chars are unknown. :type... | stack_v2_sparse_classes_36k_train_002250 | 977 | permissive | [
{
"docstring": "Use this method when the range of the chars are known (like lowercase chars only). :type strs: List[str] :rtype: List[List[str]]",
"name": "group",
"signature": "def group(strs)"
},
{
"docstring": "Use this method when the range of the chars are unknown. :type strs: List[str] :rt... | 2 | stack_v2_sparse_classes_30k_train_007772 | Implement the Python class `GroupAnagrams` described below.
Class description:
Implement the GroupAnagrams class.
Method signatures and docstrings:
- def group(strs): Use this method when the range of the chars are known (like lowercase chars only). :type strs: List[str] :rtype: List[List[str]]
- def group_sorted(str... | Implement the Python class `GroupAnagrams` described below.
Class description:
Implement the GroupAnagrams class.
Method signatures and docstrings:
- def group(strs): Use this method when the range of the chars are known (like lowercase chars only). :type strs: List[str] :rtype: List[List[str]]
- def group_sorted(str... | 77838c37e3fdae0f2ec628aa7ddc59f4a5949bbe | <|skeleton|>
class GroupAnagrams:
def group(strs):
"""Use this method when the range of the chars are known (like lowercase chars only). :type strs: List[str] :rtype: List[List[str]]"""
<|body_0|>
def group_sorted(strs):
"""Use this method when the range of the chars are unknown. :type... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GroupAnagrams:
def group(strs):
"""Use this method when the range of the chars are known (like lowercase chars only). :type strs: List[str] :rtype: List[List[str]]"""
group = {}
for s in strs:
key = [0] * 26
for c in s:
key[ord(c) - ord('a')] += ... | the_stack_v2_python_sparse | Python/dev/arrays/group_anagrams.py | faisaldialpad/hellouniverse | train | 0 | |
04c9e321302ed20e361babd26f733f857436c8c1 | [
"if len(matrix) == 0 or len(matrix[0]) == 0:\n return 0\nmaxSide = 0\nrows, columns = (len(matrix), len(matrix[0]))\ndp = [[0] * columns for _ in range(rows)]\nfor i in range(rows):\n for j in range(columns):\n if matrix[i][j] == '1':\n if i == 0 or j == 0:\n dp[i][j] = 1\n ... | <|body_start_0|>
if len(matrix) == 0 or len(matrix[0]) == 0:
return 0
maxSide = 0
rows, columns = (len(matrix), len(matrix[0]))
dp = [[0] * columns for _ in range(rows)]
for i in range(rows):
for j in range(columns):
if matrix[i][j] == '1':... | Solution | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maximalSquare(self, matrix: List[List[str]]) -> int:
"""方法二：动态规划 时间复杂度：O(mn) 空间复杂度：O(mn) :param matrix: :return:"""
<|body_0|>
def maximalSquare_optimize(self, matrix: List[List[str]]) -> int:
"""方法二：动态规划 时间复杂度：O(mn) 空间复杂度：O(0) :param matrix: :return:""... | stack_v2_sparse_classes_36k_train_002251 | 2,226 | permissive | [
{
"docstring": "方法二：动态规划 时间复杂度：O(mn) 空间复杂度：O(mn) :param matrix: :return:",
"name": "maximalSquare",
"signature": "def maximalSquare(self, matrix: List[List[str]]) -> int"
},
{
"docstring": "方法二：动态规划 时间复杂度：O(mn) 空间复杂度：O(0) :param matrix: :return:",
"name": "maximalSquare_optimize",
"signa... | 2 | stack_v2_sparse_classes_30k_train_012490 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maximalSquare(self, matrix: List[List[str]]) -> int: 方法二：动态规划 时间复杂度：O(mn) 空间复杂度：O(mn) :param matrix: :return:
- def maximalSquare_optimize(self, matrix: List[List[str]]) -> i... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maximalSquare(self, matrix: List[List[str]]) -> int: 方法二：动态规划 时间复杂度：O(mn) 空间复杂度：O(mn) :param matrix: :return:
- def maximalSquare_optimize(self, matrix: List[List[str]]) -> i... | 62419b49000e79962bcdc99cd98afd2fb82ea345 | <|skeleton|>
class Solution:
def maximalSquare(self, matrix: List[List[str]]) -> int:
"""方法二：动态规划 时间复杂度：O(mn) 空间复杂度：O(mn) :param matrix: :return:"""
<|body_0|>
def maximalSquare_optimize(self, matrix: List[List[str]]) -> int:
"""方法二：动态规划 时间复杂度：O(mn) 空间复杂度：O(0) :param matrix: :return:""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def maximalSquare(self, matrix: List[List[str]]) -> int:
"""方法二：动态规划 时间复杂度：O(mn) 空间复杂度：O(mn) :param matrix: :return:"""
if len(matrix) == 0 or len(matrix[0]) == 0:
return 0
maxSide = 0
rows, columns = (len(matrix), len(matrix[0]))
dp = [[0] * colum... | the_stack_v2_python_sparse | LeetCode 热题 HOT 100/maximalSquare.py | MaoningGuan/LeetCode | train | 3 | |
e34073f3c78763a7000b9d6e760914c7f68b695b | [
"if self.r_ear and self.l_ear:\n ear_dist = distance(self.r_ear, self.l_ear)\n if distance(self.r_wrist, self.r_ear) < ear_dist / 3 and distance(self.l_wrist, self.l_ear) < ear_dist / 3:\n return 'HANDS_ON_EARS'\nif self.shoulders_width and self.r_ear:\n near_dist = self.shoulders_width / 3\n if ... | <|body_start_0|>
if self.r_ear and self.l_ear:
ear_dist = distance(self.r_ear, self.l_ear)
if distance(self.r_wrist, self.r_ear) < ear_dist / 3 and distance(self.l_wrist, self.l_ear) < ear_dist / 3:
return 'HANDS_ON_EARS'
if self.shoulders_width and self.r_ear:
... | Check Arm poses Attention - this is currently disabled!!!!!!!!!! | ArmPose | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ArmPose:
"""Check Arm poses Attention - this is currently disabled!!!!!!!!!!"""
def get_both_arms_pose(self):
"""Both hands up - Check if both hands are on the ears"""
<|body_0|>
def get_right_arm_pose(self, controller, vert_angle_right_arm):
"""Right ear and rig... | stack_v2_sparse_classes_36k_train_002252 | 7,610 | permissive | [
{
"docstring": "Both hands up - Check if both hands are on the ears",
"name": "get_both_arms_pose",
"signature": "def get_both_arms_pose(self)"
},
{
"docstring": "Right ear and right hand on the same side",
"name": "get_right_arm_pose",
"signature": "def get_right_arm_pose(self, controll... | 3 | stack_v2_sparse_classes_30k_train_014804 | Implement the Python class `ArmPose` described below.
Class description:
Check Arm poses Attention - this is currently disabled!!!!!!!!!!
Method signatures and docstrings:
- def get_both_arms_pose(self): Both hands up - Check if both hands are on the ears
- def get_right_arm_pose(self, controller, vert_angle_right_ar... | Implement the Python class `ArmPose` described below.
Class description:
Check Arm poses Attention - this is currently disabled!!!!!!!!!!
Method signatures and docstrings:
- def get_both_arms_pose(self): Both hands up - Check if both hands are on the ears
- def get_right_arm_pose(self, controller, vert_angle_right_ar... | d276f7727d3a14fadb54c04d0771839bbe3ae14c | <|skeleton|>
class ArmPose:
"""Check Arm poses Attention - this is currently disabled!!!!!!!!!!"""
def get_both_arms_pose(self):
"""Both hands up - Check if both hands are on the ears"""
<|body_0|>
def get_right_arm_pose(self, controller, vert_angle_right_arm):
"""Right ear and rig... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ArmPose:
"""Check Arm poses Attention - this is currently disabled!!!!!!!!!!"""
def get_both_arms_pose(self):
"""Both hands up - Check if both hands are on the ears"""
if self.r_ear and self.l_ear:
ear_dist = distance(self.r_ear, self.l_ear)
if distance(self.r_wris... | the_stack_v2_python_sparse | gesturecontrol/posecheck.py | jmhuer/DJITelloAutonomy2 | train | 0 |
11d7ad0146b63656733bc07d42cab8febb365031 | [
"super().__init__()\nout_channels = channels * self.expansion\nif cardinality == 1:\n rc = channels\nelse:\n width_ratio = channels * (width / self.start_filts)\n rc = cardinality * math.floor(width_ratio)\nself.conv_reduce = ConvNd(n_dim, in_channels, rc, kernel_size=1, stride=1, padding=0, bias=False)\ns... | <|body_start_0|>
super().__init__()
out_channels = channels * self.expansion
if cardinality == 1:
rc = channels
else:
width_ratio = channels * (width / self.start_filts)
rc = cardinality * math.floor(width_ratio)
self.conv_reduce = ConvNd(n_dim... | _BottleneckX | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class _BottleneckX:
def __init__(self, in_channels: int, channels: int, stride: Union[int, Sequence[int]], cardinality: int, width: int, n_dim: int, norm_layer: str):
"""Parameters ---------- in_channels : int number of input channels stride : int stride of 3x3 convolution layer cardinality : ... | stack_v2_sparse_classes_36k_train_002253 | 12,047 | permissive | [
{
"docstring": "Parameters ---------- in_channels : int number of input channels stride : int stride of 3x3 convolution layer cardinality : int number of convolution groups width : int width of resnext block n_dim : int dimensionality of convolutions norm_layer: str type of normalization layer",
"name": "__... | 2 | stack_v2_sparse_classes_30k_train_002309 | Implement the Python class `_BottleneckX` described below.
Class description:
Implement the _BottleneckX class.
Method signatures and docstrings:
- def __init__(self, in_channels: int, channels: int, stride: Union[int, Sequence[int]], cardinality: int, width: int, n_dim: int, norm_layer: str): Parameters ---------- i... | Implement the Python class `_BottleneckX` described below.
Class description:
Implement the _BottleneckX class.
Method signatures and docstrings:
- def __init__(self, in_channels: int, channels: int, stride: Union[int, Sequence[int]], cardinality: int, width: int, n_dim: int, norm_layer: str): Parameters ---------- i... | 1078f5030b8aac2bf022daf5fa14d66f74c3c893 | <|skeleton|>
class _BottleneckX:
def __init__(self, in_channels: int, channels: int, stride: Union[int, Sequence[int]], cardinality: int, width: int, n_dim: int, norm_layer: str):
"""Parameters ---------- in_channels : int number of input channels stride : int stride of 3x3 convolution layer cardinality : ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class _BottleneckX:
def __init__(self, in_channels: int, channels: int, stride: Union[int, Sequence[int]], cardinality: int, width: int, n_dim: int, norm_layer: str):
"""Parameters ---------- in_channels : int number of input channels stride : int stride of 3x3 convolution layer cardinality : int number of ... | the_stack_v2_python_sparse | dlutils/models/resnext.py | justusschock/dl-utils | train | 15 | |
79d49aea9d87b6460e6df937a2e497fe637e2e91 | [
"if request.user.has_perm(VIEW_TEAM):\n teams = Team.objects.all()\n serializer = TeamSerializer(teams, many=True)\n return Response(serializer.data)\nreturn Response(status=status.HTTP_401_UNAUTHORIZED)",
"if request.user.has_perm(ADD_TEAM):\n serializer = TeamSerializer(data=request.data)\n if se... | <|body_start_0|>
if request.user.has_perm(VIEW_TEAM):
teams = Team.objects.all()
serializer = TeamSerializer(teams, many=True)
return Response(serializer.data)
return Response(status=status.HTTP_401_UNAUTHORIZED)
<|end_body_0|>
<|body_start_1|>
if request.use... | Contains HTTP methods GET, POST used on /usermanagement/teams/. | TeamList | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TeamList:
"""Contains HTTP methods GET, POST used on /usermanagement/teams/."""
def get(self, request, format='None'):
"""# Implement the GET method. Parameter : request (HttpRequest) : the request coming from the front-end Return : response (Response) : the response. GET request : l... | stack_v2_sparse_classes_36k_train_002254 | 10,635 | permissive | [
{
"docstring": "# Implement the GET method. Parameter : request (HttpRequest) : the request coming from the front-end Return : response (Response) : the response. GET request : list all teams and return the data.",
"name": "get",
"signature": "def get(self, request, format='None')"
},
{
"docstri... | 2 | stack_v2_sparse_classes_30k_train_017827 | Implement the Python class `TeamList` described below.
Class description:
Contains HTTP methods GET, POST used on /usermanagement/teams/.
Method signatures and docstrings:
- def get(self, request, format='None'): # Implement the GET method. Parameter : request (HttpRequest) : the request coming from the front-end Ret... | Implement the Python class `TeamList` described below.
Class description:
Contains HTTP methods GET, POST used on /usermanagement/teams/.
Method signatures and docstrings:
- def get(self, request, format='None'): # Implement the GET method. Parameter : request (HttpRequest) : the request coming from the front-end Ret... | 56511ebac83a5dc1fb8768a98bc675e88530a447 | <|skeleton|>
class TeamList:
"""Contains HTTP methods GET, POST used on /usermanagement/teams/."""
def get(self, request, format='None'):
"""# Implement the GET method. Parameter : request (HttpRequest) : the request coming from the front-end Return : response (Response) : the response. GET request : l... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TeamList:
"""Contains HTTP methods GET, POST used on /usermanagement/teams/."""
def get(self, request, format='None'):
"""# Implement the GET method. Parameter : request (HttpRequest) : the request coming from the front-end Return : response (Response) : the response. GET request : list all teams... | the_stack_v2_python_sparse | usersmanagement/views/views_team.py | Open-CMMS/openCMMS_backend | train | 4 |
bae80197544cbf18f48a07764f8173d1257b9c45 | [
"super(BasicBlock, self).__init__()\nself.conv1 = nn.Conv2d(in_channels, channels, kernel_size=3, stride=stride, padding=1, bias=False)\nself.bn1 = nn.BatchNorm2d(channels)\nself.relu = nn.ReLU(inplace=True)\nself.conv2 = nn.Conv2d(channels, channels, kernel_size=3, stride=1, padding=1, bias=False)\nself.bn2 = nn.B... | <|body_start_0|>
super(BasicBlock, self).__init__()
self.conv1 = nn.Conv2d(in_channels, channels, kernel_size=3, stride=stride, padding=1, bias=False)
self.bn1 = nn.BatchNorm2d(channels)
self.relu = nn.ReLU(inplace=True)
self.conv2 = nn.Conv2d(channels, channels, kernel_size=3, s... | Basic block for ResNet. It applies two 3x3 convolutions to the input. After each convolution applies a batch normalization. You can provide a downsample module to downsample the input and sum to the output (Residual connection) if not provided it assumes that the input has the same dimension of the output. This block h... | BasicBlock | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BasicBlock:
"""Basic block for ResNet. It applies two 3x3 convolutions to the input. After each convolution applies a batch normalization. You can provide a downsample module to downsample the input and sum to the output (Residual connection) if not provided it assumes that the input has the same... | stack_v2_sparse_classes_36k_train_002255 | 14,825 | no_license | [
{
"docstring": "Initialize the block and set all the modules needed. Args: in_channels (int): Number of channels of the input feature map. channels (int): Number of channels that the block must have. Also, this is the number of channels to output. stride (int): The stride of the convolutional layers. downsample... | 2 | stack_v2_sparse_classes_30k_test_000421 | Implement the Python class `BasicBlock` described below.
Class description:
Basic block for ResNet. It applies two 3x3 convolutions to the input. After each convolution applies a batch normalization. You can provide a downsample module to downsample the input and sum to the output (Residual connection) if not provided... | Implement the Python class `BasicBlock` described below.
Class description:
Basic block for ResNet. It applies two 3x3 convolutions to the input. After each convolution applies a batch normalization. You can provide a downsample module to downsample the input and sum to the output (Residual connection) if not provided... | a22aa5b00369c2692bf4fa537bce20144d14d5cb | <|skeleton|>
class BasicBlock:
"""Basic block for ResNet. It applies two 3x3 convolutions to the input. After each convolution applies a batch normalization. You can provide a downsample module to downsample the input and sum to the output (Residual connection) if not provided it assumes that the input has the same... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BasicBlock:
"""Basic block for ResNet. It applies two 3x3 convolutions to the input. After each convolution applies a batch normalization. You can provide a downsample module to downsample the input and sum to the output (Residual connection) if not provided it assumes that the input has the same dimension of... | the_stack_v2_python_sparse | torchsight/models/resnet.py | SetaSouto/torchsight | train | 2 |
61aeabe7ad3cae689711c244d57a675c1721b50a | [
"try:\n return template_api.get(pk)\nexcept exceptions.DoesNotExist:\n raise Http404",
"try:\n template_object = self.get_object(pk)\n serializer = TemplateSerializer(template_object)\n return Response(serializer.data)\nexcept Http404:\n content = {'message': 'Template not found.'}\n return R... | <|body_start_0|>
try:
return template_api.get(pk)
except exceptions.DoesNotExist:
raise Http404
<|end_body_0|>
<|body_start_1|>
try:
template_object = self.get_object(pk)
serializer = TemplateSerializer(template_object)
return Response... | Retrieve a Template. | TemplateDetail | [
"LicenseRef-scancode-public-domain"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TemplateDetail:
"""Retrieve a Template."""
def get_object(self, pk):
"""Get Template from db Args: pk: ObjectId Returns: Template"""
<|body_0|>
def get(self, request, pk):
"""Retrieve a Template Args: request: HTTP request pk: ObjectId Returns: - code: 200 conten... | stack_v2_sparse_classes_36k_train_002256 | 3,008 | permissive | [
{
"docstring": "Get Template from db Args: pk: ObjectId Returns: Template",
"name": "get_object",
"signature": "def get_object(self, pk)"
},
{
"docstring": "Retrieve a Template Args: request: HTTP request pk: ObjectId Returns: - code: 200 content: Template - code: 404 content: Object was not fou... | 2 | stack_v2_sparse_classes_30k_train_009678 | Implement the Python class `TemplateDetail` described below.
Class description:
Retrieve a Template.
Method signatures and docstrings:
- def get_object(self, pk): Get Template from db Args: pk: ObjectId Returns: Template
- def get(self, request, pk): Retrieve a Template Args: request: HTTP request pk: ObjectId Return... | Implement the Python class `TemplateDetail` described below.
Class description:
Retrieve a Template.
Method signatures and docstrings:
- def get_object(self, pk): Get Template from db Args: pk: ObjectId Returns: Template
- def get(self, request, pk): Retrieve a Template Args: request: HTTP request pk: ObjectId Return... | 568cb75a40ccff1d74a1a757866112535efd769a | <|skeleton|>
class TemplateDetail:
"""Retrieve a Template."""
def get_object(self, pk):
"""Get Template from db Args: pk: ObjectId Returns: Template"""
<|body_0|>
def get(self, request, pk):
"""Retrieve a Template Args: request: HTTP request pk: ObjectId Returns: - code: 200 conten... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TemplateDetail:
"""Retrieve a Template."""
def get_object(self, pk):
"""Get Template from db Args: pk: ObjectId Returns: Template"""
try:
return template_api.get(pk)
except exceptions.DoesNotExist:
raise Http404
def get(self, request, pk):
"""R... | the_stack_v2_python_sparse | core_main_app/rest/template/views.py | adilmania/core_main_app | train | 0 |
5a05b1ae9131016628b39c4b06236f05dee2d6bf | [
"if storage is None:\n raise ImportError(_STORAGE_REQUIRED)\nif client is not None:\n self.client = client\nelif credentials is not None:\n self.client = storage.Client(credentials=credentials, project=project)\nelse:\n self.client = storage.Client()\nself.bucket_name = bucket_name",
"if self.bucket_n... | <|body_start_0|>
if storage is None:
raise ImportError(_STORAGE_REQUIRED)
if client is not None:
self.client = client
elif credentials is not None:
self.client = storage.Client(credentials=credentials, project=project)
else:
self.client = s... | Uploads Pandas DataFrame to a bucket in Google Cloud Storage. | GcsClient | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GcsClient:
"""Uploads Pandas DataFrame to a bucket in Google Cloud Storage."""
def __init__(self, bucket_name=None, client=None, credentials=None, project=None):
"""Constructor. Args: bucket_name (Optional[str]): The name of Google Cloud Storage bucket for this client to send request... | stack_v2_sparse_classes_36k_train_002257 | 5,631 | permissive | [
{
"docstring": "Constructor. Args: bucket_name (Optional[str]): The name of Google Cloud Storage bucket for this client to send requests to. client (Optional[storage.Client]): A Google Cloud Storage Client instance. credentials (Optional[google.auth.credentials.Credentials]): The authorization credentials to at... | 3 | stack_v2_sparse_classes_30k_train_012443 | Implement the Python class `GcsClient` described below.
Class description:
Uploads Pandas DataFrame to a bucket in Google Cloud Storage.
Method signatures and docstrings:
- def __init__(self, bucket_name=None, client=None, credentials=None, project=None): Constructor. Args: bucket_name (Optional[str]): The name of Go... | Implement the Python class `GcsClient` described below.
Class description:
Uploads Pandas DataFrame to a bucket in Google Cloud Storage.
Method signatures and docstrings:
- def __init__(self, bucket_name=None, client=None, credentials=None, project=None): Constructor. Args: bucket_name (Optional[str]): The name of Go... | 18cc1a4a45f9aa8cff5f9c0799166e509063f74e | <|skeleton|>
class GcsClient:
"""Uploads Pandas DataFrame to a bucket in Google Cloud Storage."""
def __init__(self, bucket_name=None, client=None, credentials=None, project=None):
"""Constructor. Args: bucket_name (Optional[str]): The name of Google Cloud Storage bucket for this client to send request... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GcsClient:
"""Uploads Pandas DataFrame to a bucket in Google Cloud Storage."""
def __init__(self, bucket_name=None, client=None, credentials=None, project=None):
"""Constructor. Args: bucket_name (Optional[str]): The name of Google Cloud Storage bucket for this client to send requests to. client ... | the_stack_v2_python_sparse | google/cloud/automl_v1beta1/services/tables/gcs_client.py | googleapis/python-automl | train | 90 |
00f7e48f26ccbff5fc6938d1b5f2dd403b2806bb | [
"self.timepoints = timepoints\nself.output_ids = output_ids\nself.output = output\nself.output_sensi = output_sensi\nself.output_weight = output_weight\nself.output_sigmay = output_sigmay\nself.x_names = x_names\nif x_names is None and output_sensi is not None:\n self.x_names = [f'parameter_{i_par}' for i_par in... | <|body_start_0|>
self.timepoints = timepoints
self.output_ids = output_ids
self.output = output
self.output_sensi = output_sensi
self.output_weight = output_weight
self.output_sigmay = output_sigmay
self.x_names = x_names
if x_names is None and output_sens... | Light-weight wrapper for the prediction of one simulation condition. It should provide a common api how amici predictions should look like in pyPESTO. | PredictionConditionResult | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PredictionConditionResult:
"""Light-weight wrapper for the prediction of one simulation condition. It should provide a common api how amici predictions should look like in pyPESTO."""
def __init__(self, timepoints: np.ndarray, output_ids: Sequence[str], output: np.ndarray=None, output_sensi:... | stack_v2_sparse_classes_36k_train_002258 | 12,223 | permissive | [
{
"docstring": "Initialize PredictionConditionResult. Parameters ---------- timepoints: Output timepoints for this simulation condition output_ids: IDs of outputs for this simulation condition output: Postprocessed outputs (ndarray) output_sensi: Sensitivities of postprocessed outputs (ndarray) output_weight: L... | 3 | stack_v2_sparse_classes_30k_train_012403 | Implement the Python class `PredictionConditionResult` described below.
Class description:
Light-weight wrapper for the prediction of one simulation condition. It should provide a common api how amici predictions should look like in pyPESTO.
Method signatures and docstrings:
- def __init__(self, timepoints: np.ndarra... | Implement the Python class `PredictionConditionResult` described below.
Class description:
Light-weight wrapper for the prediction of one simulation condition. It should provide a common api how amici predictions should look like in pyPESTO.
Method signatures and docstrings:
- def __init__(self, timepoints: np.ndarra... | 9a754573a7b77d30d5dc1f67a8dc1be6c29f1640 | <|skeleton|>
class PredictionConditionResult:
"""Light-weight wrapper for the prediction of one simulation condition. It should provide a common api how amici predictions should look like in pyPESTO."""
def __init__(self, timepoints: np.ndarray, output_ids: Sequence[str], output: np.ndarray=None, output_sensi:... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PredictionConditionResult:
"""Light-weight wrapper for the prediction of one simulation condition. It should provide a common api how amici predictions should look like in pyPESTO."""
def __init__(self, timepoints: np.ndarray, output_ids: Sequence[str], output: np.ndarray=None, output_sensi: np.ndarray=N... | the_stack_v2_python_sparse | pypesto/result/predict.py | ICB-DCM/pyPESTO | train | 174 |
a7e50911c603063dc3788e06b329ba278c078121 | [
"if self.bot.selfbot:\n return\ntarget = member.server\ncemotes = member.server.emojis\nem_string = ''\nif cemotes:\n em_string = 'Try some custom emotes: ' + ' '.join([str(i) for i in cemotes]) + '! '\n if len(em_string) >= 1980 - len(welcome):\n em_string = ''\nbc = await self.store.get_prop(membe... | <|body_start_0|>
if self.bot.selfbot:
return
target = member.server
cemotes = member.server.emojis
em_string = ''
if cemotes:
em_string = 'Try some custom emotes: ' + ' '.join([str(i) for i in cemotes]) + '! '
if len(em_string) >= 1980 - len(we... | Welcomes and goodbyes. 🤗 | Welcome | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Welcome:
"""Welcomes and goodbyes. 🤗"""
async def on_member_join(self, member: discord.Member):
"""On_member_join event for newly joined members."""
<|body_0|>
async def on_member_remove(self, member: discord.Member):
"""On_member_remove event for members leavin... | stack_v2_sparse_classes_36k_train_002259 | 2,002 | permissive | [
{
"docstring": "On_member_join event for newly joined members.",
"name": "on_member_join",
"signature": "async def on_member_join(self, member: discord.Member)"
},
{
"docstring": "On_member_remove event for members leaving.",
"name": "on_member_remove",
"signature": "async def on_member_... | 2 | stack_v2_sparse_classes_30k_train_003363 | Implement the Python class `Welcome` described below.
Class description:
Welcomes and goodbyes. 🤗
Method signatures and docstrings:
- async def on_member_join(self, member: discord.Member): On_member_join event for newly joined members.
- async def on_member_remove(self, member: discord.Member): On_member_remove eve... | Implement the Python class `Welcome` described below.
Class description:
Welcomes and goodbyes. 🤗
Method signatures and docstrings:
- async def on_member_join(self, member: discord.Member): On_member_join event for newly joined members.
- async def on_member_remove(self, member: discord.Member): On_member_remove eve... | edab25451b3620e6fea9a8f1b0afcaa9e1637faa | <|skeleton|>
class Welcome:
"""Welcomes and goodbyes. 🤗"""
async def on_member_join(self, member: discord.Member):
"""On_member_join event for newly joined members."""
<|body_0|>
async def on_member_remove(self, member: discord.Member):
"""On_member_remove event for members leavin... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Welcome:
"""Welcomes and goodbyes. 🤗"""
async def on_member_join(self, member: discord.Member):
"""On_member_join event for newly joined members."""
if self.bot.selfbot:
return
target = member.server
cemotes = member.server.emojis
em_string = ''
... | the_stack_v2_python_sparse | default_cogs/welcome.py | xrxbsx/goldmine | train | 2 |
f7a9655c9fa4e3f485dd2dc898fcb34c7f503fa6 | [
"def max(a, b):\n if a > b:\n return a\n return b\nif len(nums) == 0:\n return 0\nif len(nums) == 1:\n return nums[0]\nif len(nums) == 2:\n return max(nums[0], nums[1])\n\ndef my_rob(nums):\n cur, pre = (0, 0)\n for num in nums:\n cur, pre = (max(pre + num, cur), cur)\n return ... | <|body_start_0|>
def max(a, b):
if a > b:
return a
return b
if len(nums) == 0:
return 0
if len(nums) == 1:
return nums[0]
if len(nums) == 2:
return max(nums[0], nums[1])
def my_rob(nums):
cur... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def rob(self, nums: List[int]) -> int:
"""213. 打家劫舍 II 执行用时： 32 ms , 在所有 Python3 提交中击败了 95.86% 的用户 内存消耗： 14.8 MB , 在所有 Python3 提交中击败了 75.00% 的用 :param nums: :return:"""
<|body_0|>
def rob5(self, nums: List[int]) -> int:
"""213. 打家劫舍 II 执行用时： 40 ms , 在所有 Pyt... | stack_v2_sparse_classes_36k_train_002260 | 3,370 | no_license | [
{
"docstring": "213. 打家劫舍 II 执行用时： 32 ms , 在所有 Python3 提交中击败了 95.86% 的用户 内存消耗： 14.8 MB , 在所有 Python3 提交中击败了 75.00% 的用 :param nums: :return:",
"name": "rob",
"signature": "def rob(self, nums: List[int]) -> int"
},
{
"docstring": "213. 打家劫舍 II 执行用时： 40 ms , 在所有 Python3 提交中击败了 60.10% 的用户 内存消耗： 15 M... | 4 | stack_v2_sparse_classes_30k_train_010507 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def rob(self, nums: List[int]) -> int: 213. 打家劫舍 II 执行用时： 32 ms , 在所有 Python3 提交中击败了 95.86% 的用户 内存消耗： 14.8 MB , 在所有 Python3 提交中击败了 75.00% 的用 :param nums: :return:
- def rob5(self... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def rob(self, nums: List[int]) -> int: 213. 打家劫舍 II 执行用时： 32 ms , 在所有 Python3 提交中击败了 95.86% 的用户 内存消耗： 14.8 MB , 在所有 Python3 提交中击败了 75.00% 的用 :param nums: :return:
- def rob5(self... | d613ed8a5a2c15ace7d513965b372d128845d66a | <|skeleton|>
class Solution:
def rob(self, nums: List[int]) -> int:
"""213. 打家劫舍 II 执行用时： 32 ms , 在所有 Python3 提交中击败了 95.86% 的用户 内存消耗： 14.8 MB , 在所有 Python3 提交中击败了 75.00% 的用 :param nums: :return:"""
<|body_0|>
def rob5(self, nums: List[int]) -> int:
"""213. 打家劫舍 II 执行用时： 40 ms , 在所有 Pyt... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def rob(self, nums: List[int]) -> int:
"""213. 打家劫舍 II 执行用时： 32 ms , 在所有 Python3 提交中击败了 95.86% 的用户 内存消耗： 14.8 MB , 在所有 Python3 提交中击败了 75.00% 的用 :param nums: :return:"""
def max(a, b):
if a > b:
return a
return b
if len(nums) == 0:
... | the_stack_v2_python_sparse | array/rob.py | nomboy/leetcode | train | 0 | |
368805339ecb374d96d348d36e86426af6571248 | [
"format_file = DataSaver.FORMAT_CSV\nkwargs = locals()\n_apply_datasaver(format_file, kwargs, last_uuid)\nreturn None",
"format_file = DataSaver.FORMAT_JSON\nkwargs = locals()\n_apply_datasaver(format_file, kwargs, last_uuid)\nreturn None",
"format_file = DataSaver.FORMAT_PARQUET\nkwargs = locals()\n_apply_data... | <|body_start_0|>
format_file = DataSaver.FORMAT_CSV
kwargs = locals()
_apply_datasaver(format_file, kwargs, last_uuid)
return None
<|end_body_0|>
<|body_start_1|>
format_file = DataSaver.FORMAT_JSON
kwargs = locals()
_apply_datasaver(format_file, kwargs, last_uui... | Save | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Save:
def csv(filepath, header=True, mode=DataSaver.MODE_OVERWRITE, sep=',', na_rep='', float_format=None, columns=None, encoding=None, quoting=None, quotechar='"', date_format=None, doublequote=True, escapechar=None, decimal='.'):
"""Saves a csv file. :param filepath: :param header: :pa... | stack_v2_sparse_classes_36k_train_002261 | 3,936 | permissive | [
{
"docstring": "Saves a csv file. :param filepath: :param header: :param mode: :param sep: :param na_rep: :param float_format: :param columns: :param encoding: :param quoting: :param quotechar: :param date_format: :param doublequote: :param escapechar: :param decimal: :return:",
"name": "csv",
"signatur... | 4 | stack_v2_sparse_classes_30k_train_019938 | Implement the Python class `Save` described below.
Class description:
Implement the Save class.
Method signatures and docstrings:
- def csv(filepath, header=True, mode=DataSaver.MODE_OVERWRITE, sep=',', na_rep='', float_format=None, columns=None, encoding=None, quoting=None, quotechar='"', date_format=None, doublequo... | Implement the Python class `Save` described below.
Class description:
Implement the Save class.
Method signatures and docstrings:
- def csv(filepath, header=True, mode=DataSaver.MODE_OVERWRITE, sep=',', na_rep='', float_format=None, columns=None, encoding=None, quoting=None, quotechar='"', date_format=None, doublequo... | 09ab7c474c8badc9932de3e1148f62ffba16b0b2 | <|skeleton|>
class Save:
def csv(filepath, header=True, mode=DataSaver.MODE_OVERWRITE, sep=',', na_rep='', float_format=None, columns=None, encoding=None, quoting=None, quotechar='"', date_format=None, doublequote=True, escapechar=None, decimal='.'):
"""Saves a csv file. :param filepath: :param header: :pa... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Save:
def csv(filepath, header=True, mode=DataSaver.MODE_OVERWRITE, sep=',', na_rep='', float_format=None, columns=None, encoding=None, quoting=None, quotechar='"', date_format=None, doublequote=True, escapechar=None, decimal='.'):
"""Saves a csv file. :param filepath: :param header: :param mode: :par... | the_stack_v2_python_sparse | ddf_library/bases/data_saver.py | eubr-bigsea/Compss-Python | train | 3 | |
1f11d1aa9246b51483f9f881a0aef16d0bbd2b22 | [
"super(VGG19, self).__init__()\nassert len(output_blocks) >= 1, 'Need at least one output block'\nself.output_blocks = sorted(output_blocks)\nlast_needed_block = self.output_blocks[-1]\nassert last_needed_block <= 5, 'VGG19 has at most 6 blocks'\nlayers = models.vgg19(pretrained=True).features\nself.blocks = nn.Mod... | <|body_start_0|>
super(VGG19, self).__init__()
assert len(output_blocks) >= 1, 'Need at least one output block'
self.output_blocks = sorted(output_blocks)
last_needed_block = self.output_blocks[-1]
assert last_needed_block <= 5, 'VGG19 has at most 6 blocks'
layers = model... | Pretrained VGG19 network, without fully connected layers | VGG19 | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VGG19:
"""Pretrained VGG19 network, without fully connected layers"""
def __init__(self, output_blocks=[LAST_FEATURE_MAP], requires_grad=False):
"""Build pretrained VGG19 Parameters ---------- output_blocks : list of int Indices of feature blocks to return. Each feature block ends be... | stack_v2_sparse_classes_36k_train_002262 | 2,538 | permissive | [
{
"docstring": "Build pretrained VGG19 Parameters ---------- output_blocks : list of int Indices of feature blocks to return. Each feature block ends before a max-pooling layer, i.e. the output of a feature block is the output of the last convolutional layer and activation right before the feature map is downsc... | 2 | stack_v2_sparse_classes_30k_val_000452 | Implement the Python class `VGG19` described below.
Class description:
Pretrained VGG19 network, without fully connected layers
Method signatures and docstrings:
- def __init__(self, output_blocks=[LAST_FEATURE_MAP], requires_grad=False): Build pretrained VGG19 Parameters ---------- output_blocks : list of int Indice... | Implement the Python class `VGG19` described below.
Class description:
Pretrained VGG19 network, without fully connected layers
Method signatures and docstrings:
- def __init__(self, output_blocks=[LAST_FEATURE_MAP], requires_grad=False): Build pretrained VGG19 Parameters ---------- output_blocks : list of int Indice... | 1df1fd37e7adc812b7a5e3859801d8d4a5ff5905 | <|skeleton|>
class VGG19:
"""Pretrained VGG19 network, without fully connected layers"""
def __init__(self, output_blocks=[LAST_FEATURE_MAP], requires_grad=False):
"""Build pretrained VGG19 Parameters ---------- output_blocks : list of int Indices of feature blocks to return. Each feature block ends be... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class VGG19:
"""Pretrained VGG19 network, without fully connected layers"""
def __init__(self, output_blocks=[LAST_FEATURE_MAP], requires_grad=False):
"""Build pretrained VGG19 Parameters ---------- output_blocks : list of int Indices of feature blocks to return. Each feature block ends before a max-po... | the_stack_v2_python_sparse | srgan/models/vgg.py | ZrbTz/HypernetworkSiren | train | 1 |
6970ae1111edcedbc0605d81bc5c3dccbab5ff99 | [
"email_template = EmailTemplate.objects.create(**validated_data)\nemail_template.save()\nreturn email_template",
"instance.template = validated_data.get('template')\ninstance.subject = validated_data.get('subject')\ninstance.save()\nreturn instance"
] | <|body_start_0|>
email_template = EmailTemplate.objects.create(**validated_data)
email_template.save()
return email_template
<|end_body_0|>
<|body_start_1|>
instance.template = validated_data.get('template')
instance.subject = validated_data.get('subject')
instance.save(... | EmailTempaltesSerializer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EmailTempaltesSerializer:
def create(self, validated_data):
"""Create email tempate details."""
<|body_0|>
def update(self, instance, validated_data):
"""updates email tempate details."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
email_template =... | stack_v2_sparse_classes_36k_train_002263 | 1,279 | no_license | [
{
"docstring": "Create email tempate details.",
"name": "create",
"signature": "def create(self, validated_data)"
},
{
"docstring": "updates email tempate details.",
"name": "update",
"signature": "def update(self, instance, validated_data)"
}
] | 2 | null | Implement the Python class `EmailTempaltesSerializer` described below.
Class description:
Implement the EmailTempaltesSerializer class.
Method signatures and docstrings:
- def create(self, validated_data): Create email tempate details.
- def update(self, instance, validated_data): updates email tempate details. | Implement the Python class `EmailTempaltesSerializer` described below.
Class description:
Implement the EmailTempaltesSerializer class.
Method signatures and docstrings:
- def create(self, validated_data): Create email tempate details.
- def update(self, instance, validated_data): updates email tempate details.
<|sk... | 5d5bc4c1eecbf627d38260e4d314d8451d67a4f5 | <|skeleton|>
class EmailTempaltesSerializer:
def create(self, validated_data):
"""Create email tempate details."""
<|body_0|>
def update(self, instance, validated_data):
"""updates email tempate details."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EmailTempaltesSerializer:
def create(self, validated_data):
"""Create email tempate details."""
email_template = EmailTemplate.objects.create(**validated_data)
email_template.save()
return email_template
def update(self, instance, validated_data):
"""updates email ... | the_stack_v2_python_sparse | curation-api/src/patients/serializers/email_templates.py | mohanj1919/django_app_test | train | 0 | |
77bddbc3ebbf3c71dba50cf099459bad3a0b1691 | [
"n = len(nums)\nself.tree = [0] * (2 * n)\nfor i in range(n, 2 * n, 1):\n self.tree[i] = nums[i - n]\nfor i in range(n - 1, 0, -1):\n self.tree[i] = self.tree[2 * i] + self.tree[2 * i + 1]\nself.nums = nums\nself.n = n\nreturn",
"n = self.n\nself.nums[index] = val\nindex += n\nself.tree[index] = val\nindex ... | <|body_start_0|>
n = len(nums)
self.tree = [0] * (2 * n)
for i in range(n, 2 * n, 1):
self.tree[i] = nums[i - n]
for i in range(n - 1, 0, -1):
self.tree[i] = self.tree[2 * i] + self.tree[2 * i + 1]
self.nums = nums
self.n = n
return
<|end_b... | NumArray | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NumArray:
def __init__(self, nums):
""":type nums: List[int]"""
<|body_0|>
def update(self, index, val):
""":type index: int :type val: int :rtype: None"""
<|body_1|>
def sumRange(self, left, right):
""":type left: int :type right: int :rtype: in... | stack_v2_sparse_classes_36k_train_002264 | 2,072 | no_license | [
{
"docstring": ":type nums: List[int]",
"name": "__init__",
"signature": "def __init__(self, nums)"
},
{
"docstring": ":type index: int :type val: int :rtype: None",
"name": "update",
"signature": "def update(self, index, val)"
},
{
"docstring": ":type left: int :type right: int ... | 3 | stack_v2_sparse_classes_30k_train_002304 | Implement the Python class `NumArray` described below.
Class description:
Implement the NumArray class.
Method signatures and docstrings:
- def __init__(self, nums): :type nums: List[int]
- def update(self, index, val): :type index: int :type val: int :rtype: None
- def sumRange(self, left, right): :type left: int :t... | Implement the Python class `NumArray` described below.
Class description:
Implement the NumArray class.
Method signatures and docstrings:
- def __init__(self, nums): :type nums: List[int]
- def update(self, index, val): :type index: int :type val: int :rtype: None
- def sumRange(self, left, right): :type left: int :t... | ad1eabfa27dda65b743d7d93524f1ec8f1e0ebfc | <|skeleton|>
class NumArray:
def __init__(self, nums):
""":type nums: List[int]"""
<|body_0|>
def update(self, index, val):
""":type index: int :type val: int :rtype: None"""
<|body_1|>
def sumRange(self, left, right):
""":type left: int :type right: int :rtype: in... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NumArray:
def __init__(self, nums):
""":type nums: List[int]"""
n = len(nums)
self.tree = [0] * (2 * n)
for i in range(n, 2 * n, 1):
self.tree[i] = nums[i - n]
for i in range(n - 1, 0, -1):
self.tree[i] = self.tree[2 * i] + self.tree[2 * i + 1]
... | the_stack_v2_python_sparse | code/leetcode-307.py | kiyoxi2020/leetcode | train | 3 | |
ae8d8edf697aafed9bb5dbb4c318b53b0bf4417d | [
"tiling_options = {'verbose': 0, 'mode': 'LASSO', 'print_summary': True}\nself.problem = dict(problem.items() + {'tiling_options': tiling_options}.items())\nnp.random.seed(problem['random_seed'])\nrandom_state = np.random.get_state()\nself.problem['random_state'] = random_state\nA, y, u_real, v_real = create_specif... | <|body_start_0|>
tiling_options = {'verbose': 0, 'mode': 'LASSO', 'print_summary': True}
self.problem = dict(problem.items() + {'tiling_options': tiling_options}.items())
np.random.seed(problem['random_seed'])
random_state = np.random.get_state()
self.problem['random_state'] = ra... | Test class implementing a test that compares the tiling results with the scipy implementation of the Lasso-path algorithm. Concretely, we use the problem setup defined in the beginning of this file, and we create the support tiling for this problem. Afterwards, we run the scipy-lasso algorithm for each single beta in t... | CompareToScipyLASSOTestCase | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CompareToScipyLASSOTestCase:
"""Test class implementing a test that compares the tiling results with the scipy implementation of the Lasso-path algorithm. Concretely, we use the problem setup defined in the beginning of this file, and we create the support tiling for this problem. Afterwards, we ... | stack_v2_sparse_classes_36k_train_002265 | 9,738 | no_license | [
{
"docstring": "Set up for the tests by calculating the tiling and the lars-path for some distinct beta's given in problem['betas_to_test'].",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "Tests the support and sign pattern equality of the scipy implementation and our tiling... | 2 | stack_v2_sparse_classes_30k_train_006293 | Implement the Python class `CompareToScipyLASSOTestCase` described below.
Class description:
Test class implementing a test that compares the tiling results with the scipy implementation of the Lasso-path algorithm. Concretely, we use the problem setup defined in the beginning of this file, and we create the support t... | Implement the Python class `CompareToScipyLASSOTestCase` described below.
Class description:
Test class implementing a test that compares the tiling results with the scipy implementation of the Lasso-path algorithm. Concretely, we use the problem setup defined in the beginning of this file, and we create the support t... | 2238f0a2bdd4c5acb01564977eada2be8450f413 | <|skeleton|>
class CompareToScipyLASSOTestCase:
"""Test class implementing a test that compares the tiling results with the scipy implementation of the Lasso-path algorithm. Concretely, we use the problem setup defined in the beginning of this file, and we create the support tiling for this problem. Afterwards, we ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CompareToScipyLASSOTestCase:
"""Test class implementing a test that compares the tiling results with the scipy implementation of the Lasso-path algorithm. Concretely, we use the problem setup defined in the beginning of this file, and we create the support tiling for this problem. Afterwards, we run the scipy... | the_stack_v2_python_sparse | test_utils/test_scipy_comparison.py | soply/mpgraph | train | 0 |
7e31dccdfcf4efe2d5b4db6dd40fd8aa5d76a64e | [
"num_rows = self._parse_file_data_size(file_path)\npixels = zeros((num_rows, self.num_columns - 1), float32)\nnumbers = zeros((num_rows,), uint8)\nrow = 0\nfor sample_data in super(TrainingSetIO, self).parse(file_path):\n numbers[row] = uint8(sample_data[0])\n pixels[row] = uint8(sample_data[1:])\n row += ... | <|body_start_0|>
num_rows = self._parse_file_data_size(file_path)
pixels = zeros((num_rows, self.num_columns - 1), float32)
numbers = zeros((num_rows,), uint8)
row = 0
for sample_data in super(TrainingSetIO, self).parse(file_path):
numbers[row] = uint8(sample_data[0])... | Parses kaggle input training and test set data for processing For training data input is expected in the form: label, pixel0, pixel1, ... pixelN 1,22,33,...250 9,53,0,...125 ... Where the label column is absent for testing, the format is otherwise identical Pixels can range from 0 -> 255 Labels can range from 0 -> 9 | TrainingSetIO | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TrainingSetIO:
"""Parses kaggle input training and test set data for processing For training data input is expected in the form: label, pixel0, pixel1, ... pixelN 1,22,33,...250 9,53,0,...125 ... Where the label column is absent for testing, the format is otherwise identical Pixels can range from... | stack_v2_sparse_classes_36k_train_002266 | 2,146 | no_license | [
{
"docstring": "Parses the training set for labels (image numbers) and pixel values Generates tuples of integer labels and arrays of pixel values :param file_path: The path to be parsed :return: A tuple of (actual numbers, images). Where actual numbers is an array of the integer value of the associated image. I... | 2 | stack_v2_sparse_classes_30k_train_014683 | Implement the Python class `TrainingSetIO` described below.
Class description:
Parses kaggle input training and test set data for processing For training data input is expected in the form: label, pixel0, pixel1, ... pixelN 1,22,33,...250 9,53,0,...125 ... Where the label column is absent for testing, the format is ot... | Implement the Python class `TrainingSetIO` described below.
Class description:
Parses kaggle input training and test set data for processing For training data input is expected in the form: label, pixel0, pixel1, ... pixelN 1,22,33,...250 9,53,0,...125 ... Where the label column is absent for testing, the format is ot... | 164f8df98b82d6be55e01229feac7f09cd7b3be0 | <|skeleton|>
class TrainingSetIO:
"""Parses kaggle input training and test set data for processing For training data input is expected in the form: label, pixel0, pixel1, ... pixelN 1,22,33,...250 9,53,0,...125 ... Where the label column is absent for testing, the format is otherwise identical Pixels can range from... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TrainingSetIO:
"""Parses kaggle input training and test set data for processing For training data input is expected in the form: label, pixel0, pixel1, ... pixelN 1,22,33,...250 9,53,0,...125 ... Where the label column is absent for testing, the format is otherwise identical Pixels can range from 0 -> 255 Lab... | the_stack_v2_python_sparse | formatted_io/training_set_io.py | barryhennessy/digit_classifier | train | 0 |
eec3ca61ec5b63365ec6b5aaa6c2654bf9720904 | [
"super(EmbeddingCardSuperNet, self).__init__()\nself.cardinality_options = cardinality_options\nself.num_card_options = len(self.cardinality_options)\nself.dim = dim\nself.params_options = nn.Parameter(torch.Tensor([self.dim * curr_card for curr_card in self.cardinality_options]), requires_grad=False)\nself.num_emb... | <|body_start_0|>
super(EmbeddingCardSuperNet, self).__init__()
self.cardinality_options = cardinality_options
self.num_card_options = len(self.cardinality_options)
self.dim = dim
self.params_options = nn.Parameter(torch.Tensor([self.dim * curr_card for curr_card in self.cardinali... | EmbeddingCardSuperNet | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EmbeddingCardSuperNet:
def __init__(self, cardinality_options, dim):
"""Implements an embedding cardinality search supernet. We cannot use the FBNetv2 method of just creating the largest cardinality embedding and then using that becuase then hashed and unhashes embedding indices may be m... | stack_v2_sparse_classes_36k_train_002267 | 6,458 | permissive | [
{
"docstring": "Implements an embedding cardinality search supernet. We cannot use the FBNetv2 method of just creating the largest cardinality embedding and then using that becuase then hashed and unhashes embedding indices may be mapped to the same values. Further, because we will typically be choosing between... | 5 | stack_v2_sparse_classes_30k_train_009554 | Implement the Python class `EmbeddingCardSuperNet` described below.
Class description:
Implement the EmbeddingCardSuperNet class.
Method signatures and docstrings:
- def __init__(self, cardinality_options, dim): Implements an embedding cardinality search supernet. We cannot use the FBNetv2 method of just creating the... | Implement the Python class `EmbeddingCardSuperNet` described below.
Class description:
Implement the EmbeddingCardSuperNet class.
Method signatures and docstrings:
- def __init__(self, cardinality_options, dim): Implements an embedding cardinality search supernet. We cannot use the FBNetv2 method of just creating the... | 39aa5b13d66a3899350cb4e53d87a8cd3c5c198f | <|skeleton|>
class EmbeddingCardSuperNet:
def __init__(self, cardinality_options, dim):
"""Implements an embedding cardinality search supernet. We cannot use the FBNetv2 method of just creating the largest cardinality embedding and then using that becuase then hashed and unhashes embedding indices may be m... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EmbeddingCardSuperNet:
def __init__(self, cardinality_options, dim):
"""Implements an embedding cardinality search supernet. We cannot use the FBNetv2 method of just creating the largest cardinality embedding and then using that becuase then hashed and unhashes embedding indices may be mapped to the s... | the_stack_v2_python_sparse | nas_embedding_card.py | ravikucb/dnas | train | 6 | |
ce0211c5a8cb3561e751a35639df6f56abed625a | [
"filter_lookup = {'published_before': 'published_date__lte', 'published_after': 'published_date__gte', 'title': 'title__icontains', 'number': 'episode_number'}\nfilter_parameters = {}\nfor key, value in params.items():\n filter_parameters.update({filter_lookup[key]: value})\nreturn filter_parameters",
"query_p... | <|body_start_0|>
filter_lookup = {'published_before': 'published_date__lte', 'published_after': 'published_date__gte', 'title': 'title__icontains', 'number': 'episode_number'}
filter_parameters = {}
for key, value in params.items():
filter_parameters.update({filter_lookup[key]: value... | View Set to support creation and retrieval of Podcast Episodes | EpisodeViewSet | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EpisodeViewSet:
"""View Set to support creation and retrieval of Podcast Episodes"""
def _filterify_query_params(params):
"""Method to convert simplified URL query parameters to their appropriate values to be unpacked in a .filter() call :param params: Query parameters passed in the ... | stack_v2_sparse_classes_36k_train_002268 | 6,303 | no_license | [
{
"docstring": "Method to convert simplified URL query parameters to their appropriate values to be unpacked in a .filter() call :param params: Query parameters passed in the request :return: Dictionary of the parameters that can be unpacked in QuerySet's .filter() method",
"name": "_filterify_query_params"... | 2 | stack_v2_sparse_classes_30k_train_004131 | Implement the Python class `EpisodeViewSet` described below.
Class description:
View Set to support creation and retrieval of Podcast Episodes
Method signatures and docstrings:
- def _filterify_query_params(params): Method to convert simplified URL query parameters to their appropriate values to be unpacked in a .fil... | Implement the Python class `EpisodeViewSet` described below.
Class description:
View Set to support creation and retrieval of Podcast Episodes
Method signatures and docstrings:
- def _filterify_query_params(params): Method to convert simplified URL query parameters to their appropriate values to be unpacked in a .fil... | 38a09ce2fe68312338c8cb597a341853901eeaa3 | <|skeleton|>
class EpisodeViewSet:
"""View Set to support creation and retrieval of Podcast Episodes"""
def _filterify_query_params(params):
"""Method to convert simplified URL query parameters to their appropriate values to be unpacked in a .filter() call :param params: Query parameters passed in the ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EpisodeViewSet:
"""View Set to support creation and retrieval of Podcast Episodes"""
def _filterify_query_params(params):
"""Method to convert simplified URL query parameters to their appropriate values to be unpacked in a .filter() call :param params: Query parameters passed in the request :retu... | the_stack_v2_python_sparse | apps/podcast/views.py | AOV-Team/aov-py-backend | train | 0 |
93c6af025c29077888dda20465fa3c674ecdd5c4 | [
"for col in self.columns:\n if lower(col.type) == 'geometry':\n return col",
"for col in self.columns:\n col = col.column\n if col.is_geomref():\n return col"
] | <|body_start_0|>
for col in self.columns:
if lower(col.type) == 'geometry':
return col
<|end_body_0|>
<|body_start_1|>
for col in self.columns:
col = col.column
if col.is_geomref():
return col
<|end_body_1|>
| Describes a physical table in our database. These should *never* be instantiated manually. They are automatically created by :meth:`~.tasks.TableTask.output`. The unique key is :attr:~.meta.OBSTable.id:. .. py:attribute:: id The unique identifier for this table. Is always qualified by the module name of the class that ... | OBSTable | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OBSTable:
"""Describes a physical table in our database. These should *never* be instantiated manually. They are automatically created by :meth:`~.tasks.TableTask.output`. The unique key is :attr:~.meta.OBSTable.id:. .. py:attribute:: id The unique identifier for this table. Is always qualified b... | stack_v2_sparse_classes_36k_train_002269 | 38,974 | permissive | [
{
"docstring": "Return the column geometry column for this table, if it has one. Returns None if there is none.",
"name": "geom_column",
"signature": "def geom_column(self)"
},
{
"docstring": "Return the geomref column for this table, if it has one. Returns None if there is none.",
"name": "... | 2 | stack_v2_sparse_classes_30k_val_000792 | Implement the Python class `OBSTable` described below.
Class description:
Describes a physical table in our database. These should *never* be instantiated manually. They are automatically created by :meth:`~.tasks.TableTask.output`. The unique key is :attr:~.meta.OBSTable.id:. .. py:attribute:: id The unique identifie... | Implement the Python class `OBSTable` described below.
Class description:
Describes a physical table in our database. These should *never* be instantiated manually. They are automatically created by :meth:`~.tasks.TableTask.output`. The unique key is :attr:~.meta.OBSTable.id:. .. py:attribute:: id The unique identifie... | a32325382500f23b8a607e4e02cc0ec111360869 | <|skeleton|>
class OBSTable:
"""Describes a physical table in our database. These should *never* be instantiated manually. They are automatically created by :meth:`~.tasks.TableTask.output`. The unique key is :attr:~.meta.OBSTable.id:. .. py:attribute:: id The unique identifier for this table. Is always qualified b... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class OBSTable:
"""Describes a physical table in our database. These should *never* be instantiated manually. They are automatically created by :meth:`~.tasks.TableTask.output`. The unique key is :attr:~.meta.OBSTable.id:. .. py:attribute:: id The unique identifier for this table. Is always qualified by the module ... | the_stack_v2_python_sparse | tasks/meta.py | CartoDB/bigmetadata | train | 45 |
b756604d267a19ea6b386f7d8b889b9a131ef5d2 | [
"user = request.user\ntry:\n product = Product.objects.get(pk=product_pk)\n wishlist, _ = WishList.objects.get_or_create(owner=user)\n wishlist.add(product)\n return Response(err_result(SUCCESS_CODE, u'关注成功').msg)\nexcept Exception as e:\n logging.exception(e)\n return Response(err_result(SYSTEM_E... | <|body_start_0|>
user = request.user
try:
product = Product.objects.get(pk=product_pk)
wishlist, _ = WishList.objects.get_or_create(owner=user)
wishlist.add(product)
return Response(err_result(SUCCESS_CODE, u'关注成功').msg)
except Exception as e:
... | AppMyFavProduct | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AppMyFavProduct:
def post(self, request, product_pk, *args, **kwargs):
"""添加商品到我的关注 :param request: :param product_pk: 商品id :param args: :param kwargs: :return:"""
<|body_0|>
def delete(self, request, product_pk, format=None):
"""从我的关注里删除关注商品 :param request: :param p... | stack_v2_sparse_classes_36k_train_002270 | 4,827 | no_license | [
{
"docstring": "添加商品到我的关注 :param request: :param product_pk: 商品id :param args: :param kwargs: :return:",
"name": "post",
"signature": "def post(self, request, product_pk, *args, **kwargs)"
},
{
"docstring": "从我的关注里删除关注商品 :param request: :param product_pk：商品id :param format: :return: SUCCESS_CODE... | 2 | null | Implement the Python class `AppMyFavProduct` described below.
Class description:
Implement the AppMyFavProduct class.
Method signatures and docstrings:
- def post(self, request, product_pk, *args, **kwargs): 添加商品到我的关注 :param request: :param product_pk: 商品id :param args: :param kwargs: :return:
- def delete(self, requ... | Implement the Python class `AppMyFavProduct` described below.
Class description:
Implement the AppMyFavProduct class.
Method signatures and docstrings:
- def post(self, request, product_pk, *args, **kwargs): 添加商品到我的关注 :param request: :param product_pk: 商品id :param args: :param kwargs: :return:
- def delete(self, requ... | 3d6198c2a1abc97fa9286408f52c1f5153883b7a | <|skeleton|>
class AppMyFavProduct:
def post(self, request, product_pk, *args, **kwargs):
"""添加商品到我的关注 :param request: :param product_pk: 商品id :param args: :param kwargs: :return:"""
<|body_0|>
def delete(self, request, product_pk, format=None):
"""从我的关注里删除关注商品 :param request: :param p... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AppMyFavProduct:
def post(self, request, product_pk, *args, **kwargs):
"""添加商品到我的关注 :param request: :param product_pk: 商品id :param args: :param kwargs: :return:"""
user = request.user
try:
product = Product.objects.get(pk=product_pk)
wishlist, _ = WishList.objec... | the_stack_v2_python_sparse | stars/apps/api/wishlists/views.py | lisongwei15931/stars | train | 0 | |
abccc51c178ec1f9a5e8af8e5c085c6faa882866 | [
"self.aoi = aoi\nself.ds = ds\nself.mask_value = mask_value\nself.fill_value = fill_value",
"import geopandas as gpd\nfrom downscale import utils\ngdf = gpd.read_file(self.aoi)\nshapes = [(geom, self.mask_value) for geom in gdf.geometry]\nds = self.ds.ds\ncoords = ds.coords\nreturn utils.rasterize(shapes, coords=... | <|body_start_0|>
self.aoi = aoi
self.ds = ds
self.mask_value = mask_value
self.fill_value = fill_value
<|end_body_0|>
<|body_start_1|>
import geopandas as gpd
from downscale import utils
gdf = gpd.read_file(self.aoi)
shapes = [(geom, self.mask_value) for ... | Mask | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Mask:
def __init__(self, aoi, ds, mask_value=1, fill_value=0, *args, **kwargs):
"""make a mask from a shapefile which is already in the CRS and domain of the input ds. ARGUMENTS: --------- aoi = [str] full read path of a shapefile with .shp extension ds = [downscale.Dataset] instance of ... | stack_v2_sparse_classes_36k_train_002271 | 6,957 | permissive | [
{
"docstring": "make a mask from a shapefile which is already in the CRS and domain of the input ds. ARGUMENTS: --------- aoi = [str] full read path of a shapefile with .shp extension ds = [downscale.Dataset] instance of file in a downscale.Dataset object mask_value = [int] value to use for masked areas. defaul... | 4 | null | Implement the Python class `Mask` described below.
Class description:
Implement the Mask class.
Method signatures and docstrings:
- def __init__(self, aoi, ds, mask_value=1, fill_value=0, *args, **kwargs): make a mask from a shapefile which is already in the CRS and domain of the input ds. ARGUMENTS: --------- aoi = ... | Implement the Python class `Mask` described below.
Class description:
Implement the Mask class.
Method signatures and docstrings:
- def __init__(self, aoi, ds, mask_value=1, fill_value=0, *args, **kwargs): make a mask from a shapefile which is already in the CRS and domain of the input ds. ARGUMENTS: --------- aoi = ... | 3fe8ea1774cf82149d19561ce5f19b25e6cba6fb | <|skeleton|>
class Mask:
def __init__(self, aoi, ds, mask_value=1, fill_value=0, *args, **kwargs):
"""make a mask from a shapefile which is already in the CRS and domain of the input ds. ARGUMENTS: --------- aoi = [str] full read path of a shapefile with .shp extension ds = [downscale.Dataset] instance of ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Mask:
def __init__(self, aoi, ds, mask_value=1, fill_value=0, *args, **kwargs):
"""make a mask from a shapefile which is already in the CRS and domain of the input ds. ARGUMENTS: --------- aoi = [str] full read path of a shapefile with .shp extension ds = [downscale.Dataset] instance of file in a down... | the_stack_v2_python_sparse | downscale/dataset.py | yusheng-wang/downscale | train | 0 | |
3e5f1255c2276781a1a4f553bef9fa53919a388e | [
"s, e, i, r, c, m = xs\nif isinstance(parameters, Parameters):\n beta = parameters['beta'].value\n gamma = parameters['gamma'].value\n sigma = parameters['sigma'].value\n eta = parameters['eta'].value\n epsilon = parameters['sigma'].value\n T_quarantine = parameters['T'].value\nelif isinstance(par... | <|body_start_0|>
s, e, i, r, c, m = xs
if isinstance(parameters, Parameters):
beta = parameters['beta'].value
gamma = parameters['gamma'].value
sigma = parameters['sigma'].value
eta = parameters['eta'].value
epsilon = parameters['sigma'].value
... | SEIR Model from https://www.medrxiv.org/content/10.1101/2020.03.04.20031104v1.full.pdf with cumulative cases (C) and cumulative fatalities (M) | SEIRCM | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SEIRCM:
"""SEIR Model from https://www.medrxiv.org/content/10.1101/2020.03.04.20031104v1.full.pdf with cumulative cases (C) and cumulative fatalities (M)"""
def calibrate(cls, xs: tuple, t: float, parameters: Union[Parameters, tuple]) -> tuple:
"""SEIRCM model derivatives at t. :para... | stack_v2_sparse_classes_36k_train_002272 | 29,649 | permissive | [
{
"docstring": "SEIRCM model derivatives at t. :param xs: variables that we are solving for i.e. [S]usceptible, [E]xposed, [I]nfected, [R]emoved, [C]ases, [M]ortality :param t: time parameter :param parameters: parameters of the model (not including initial conditions) i.e. beta, gamma, sigma, eta, epsilon :ret... | 2 | null | Implement the Python class `SEIRCM` described below.
Class description:
SEIR Model from https://www.medrxiv.org/content/10.1101/2020.03.04.20031104v1.full.pdf with cumulative cases (C) and cumulative fatalities (M)
Method signatures and docstrings:
- def calibrate(cls, xs: tuple, t: float, parameters: Union[Parameter... | Implement the Python class `SEIRCM` described below.
Class description:
SEIR Model from https://www.medrxiv.org/content/10.1101/2020.03.04.20031104v1.full.pdf with cumulative cases (C) and cumulative fatalities (M)
Method signatures and docstrings:
- def calibrate(cls, xs: tuple, t: float, parameters: Union[Parameter... | 4cf8ec75c4d85b16ec08371c46cc1a9ede9d72a2 | <|skeleton|>
class SEIRCM:
"""SEIR Model from https://www.medrxiv.org/content/10.1101/2020.03.04.20031104v1.full.pdf with cumulative cases (C) and cumulative fatalities (M)"""
def calibrate(cls, xs: tuple, t: float, parameters: Union[Parameters, tuple]) -> tuple:
"""SEIRCM model derivatives at t. :para... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SEIRCM:
"""SEIR Model from https://www.medrxiv.org/content/10.1101/2020.03.04.20031104v1.full.pdf with cumulative cases (C) and cumulative fatalities (M)"""
def calibrate(cls, xs: tuple, t: float, parameters: Union[Parameters, tuple]) -> tuple:
"""SEIRCM model derivatives at t. :param xs: variabl... | the_stack_v2_python_sparse | gs_quant/models/epidemiology.py | goldmansachs/gs-quant | train | 2,088 |
ba8cbde3934a244f362fc11ce2e8584d80fe25b9 | [
"super(SimulatedExecutionHandler, self).__init__(data_handler.events, False)\nself.data_handler = data_handler\nself.transaction_cost = transaction_cost",
"symbol = order_event.symbol\nquantity = order_event.quantity\naction = params.action_dict[order_event.direction, order_event.trade_type]\nprice_id = [params.P... | <|body_start_0|>
super(SimulatedExecutionHandler, self).__init__(data_handler.events, False)
self.data_handler = data_handler
self.transaction_cost = transaction_cost
<|end_body_0|>
<|body_start_1|>
symbol = order_event.symbol
quantity = order_event.quantity
action = par... | Simulated Execution Handler Class The simulated execution handler simply converts all order objects into their equivalent fill objects automatically without latency, slippage or fill-ratio issues. This allows a straightforward 'first go' test of any strategy, before implementation with a more sophisticated execution ha... | SimulatedExecutionHandler | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SimulatedExecutionHandler:
"""Simulated Execution Handler Class The simulated execution handler simply converts all order objects into their equivalent fill objects automatically without latency, slippage or fill-ratio issues. This allows a straightforward 'first go' test of any strategy, before ... | stack_v2_sparse_classes_36k_train_002273 | 2,574 | permissive | [
{
"docstring": "Initialize parameters of the simulated execution handler object.",
"name": "__init__",
"signature": "def __init__(self, data_handler, transaction_cost=0.0005)"
},
{
"docstring": "Implementation of abstract base class method.",
"name": "execute_order",
"signature": "def ex... | 2 | stack_v2_sparse_classes_30k_train_015693 | Implement the Python class `SimulatedExecutionHandler` described below.
Class description:
Simulated Execution Handler Class The simulated execution handler simply converts all order objects into their equivalent fill objects automatically without latency, slippage or fill-ratio issues. This allows a straightforward '... | Implement the Python class `SimulatedExecutionHandler` described below.
Class description:
Simulated Execution Handler Class The simulated execution handler simply converts all order objects into their equivalent fill objects automatically without latency, slippage or fill-ratio issues. This allows a straightforward '... | e2e9d638c68947d24f1260d35a3527dd84c2523f | <|skeleton|>
class SimulatedExecutionHandler:
"""Simulated Execution Handler Class The simulated execution handler simply converts all order objects into their equivalent fill objects automatically without latency, slippage or fill-ratio issues. This allows a straightforward 'first go' test of any strategy, before ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SimulatedExecutionHandler:
"""Simulated Execution Handler Class The simulated execution handler simply converts all order objects into their equivalent fill objects automatically without latency, slippage or fill-ratio issues. This allows a straightforward 'first go' test of any strategy, before implementatio... | the_stack_v2_python_sparse | odin/handlers/execution_handler/simulated_execution_handler.py | stjordanis/Odin | train | 0 |
56419470d2309cdc2c9a6843be95b3ef0ad43c15 | [
"self.count_dict = {}\nself.count_dict.setdefault('product_errors', 0)\nself.count_dict.setdefault('customer_errors', 0)\nself.count_dict.setdefault('rentals_errors', 0)\nself.count_dict.setdefault('product_count_before', 0)\nself.count_dict.setdefault('product_count_after', 0)\nself.count_dict.setdefault('customer... | <|body_start_0|>
self.count_dict = {}
self.count_dict.setdefault('product_errors', 0)
self.count_dict.setdefault('customer_errors', 0)
self.count_dict.setdefault('rentals_errors', 0)
self.count_dict.setdefault('product_count_before', 0)
self.count_dict.setdefault('product... | This class contains the methods to import all the .csv info | ImportData | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ImportData:
"""This class contains the methods to import all the .csv info"""
def __init__(self):
"""Initiates the dictionary items"""
<|body_0|>
def import_all(self):
"""Imports everything without timing"""
<|body_1|>
def import_stats(self):
... | stack_v2_sparse_classes_36k_train_002274 | 10,744 | no_license | [
{
"docstring": "Initiates the dictionary items",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Imports everything without timing",
"name": "import_all",
"signature": "def import_all(self)"
},
{
"docstring": "This function returns the statistical data on... | 6 | null | Implement the Python class `ImportData` described below.
Class description:
This class contains the methods to import all the .csv info
Method signatures and docstrings:
- def __init__(self): Initiates the dictionary items
- def import_all(self): Imports everything without timing
- def import_stats(self): This functi... | Implement the Python class `ImportData` described below.
Class description:
This class contains the methods to import all the .csv info
Method signatures and docstrings:
- def __init__(self): Initiates the dictionary items
- def import_all(self): Imports everything without timing
- def import_stats(self): This functi... | 5dac60f39e3909ff05b26721d602ed20f14d6be3 | <|skeleton|>
class ImportData:
"""This class contains the methods to import all the .csv info"""
def __init__(self):
"""Initiates the dictionary items"""
<|body_0|>
def import_all(self):
"""Imports everything without timing"""
<|body_1|>
def import_stats(self):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ImportData:
"""This class contains the methods to import all the .csv info"""
def __init__(self):
"""Initiates the dictionary items"""
self.count_dict = {}
self.count_dict.setdefault('product_errors', 0)
self.count_dict.setdefault('customer_errors', 0)
self.count_d... | the_stack_v2_python_sparse | students/dfspray/Lesson10/src/database.py | JavaRod/SP_Python220B_2019 | train | 1 |
7241ba88f8186037afd1cb47c55f5b36ea68ad1a | [
"self.s_socket = socket.socket(socket.AF_INET, socket.SOCK_STREAM)\nself.h_name = socket.gethostname()\nself.p_number = 9994\nself.s_socket.bind((self.h_name, self.p_number))\nself.s_socket.listen(5)\nself.log = LogManager.get_logger()\nif self.log:\n self.log.log_info('ServerConnection', '__init__', 'opening a ... | <|body_start_0|>
self.s_socket = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
self.h_name = socket.gethostname()
self.p_number = 9994
self.s_socket.bind((self.h_name, self.p_number))
self.s_socket.listen(5)
self.log = LogManager.get_logger()
if self.log:
... | ServerConnection | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ServerConnection:
def __init__(self):
"""Description: Initialization function for ServerConnection Class. It creates a socket at server end to handle the client request on specific port. Argument : None Return Type : None"""
<|body_0|>
def accept_connection(self):
""... | stack_v2_sparse_classes_36k_train_002275 | 4,005 | no_license | [
{
"docstring": "Description: Initialization function for ServerConnection Class. It creates a socket at server end to handle the client request on specific port. Argument : None Return Type : None",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Description: Function to... | 3 | stack_v2_sparse_classes_30k_test_000550 | Implement the Python class `ServerConnection` described below.
Class description:
Implement the ServerConnection class.
Method signatures and docstrings:
- def __init__(self): Description: Initialization function for ServerConnection Class. It creates a socket at server end to handle the client request on specific po... | Implement the Python class `ServerConnection` described below.
Class description:
Implement the ServerConnection class.
Method signatures and docstrings:
- def __init__(self): Description: Initialization function for ServerConnection Class. It creates a socket at server end to handle the client request on specific po... | 0a16a9905a3b0689e3186c76089a99000a4c649d | <|skeleton|>
class ServerConnection:
def __init__(self):
"""Description: Initialization function for ServerConnection Class. It creates a socket at server end to handle the client request on specific port. Argument : None Return Type : None"""
<|body_0|>
def accept_connection(self):
""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ServerConnection:
def __init__(self):
"""Description: Initialization function for ServerConnection Class. It creates a socket at server end to handle the client request on specific port. Argument : None Return Type : None"""
self.s_socket = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
... | the_stack_v2_python_sparse | com/itt/tds/comm/ServerConnection.py | mukultaneja/TaskDistributionSystem | train | 0 | |
19b97710650aff1a53fec93a6d1730a3c3a164aa | [
"new_list = ListNode(0)\ncur = new_list\nwhile l1 and l2:\n if l1.val < l2.val:\n cur.next = l1\n cur = cur.next\n l1 = l1.next\n else:\n cur.next = l2\n cur = cur.next\n l2 = l2.next\nif l1:\n cur.next = l1\nif l2:\n cur.next = l2\nreturn new_list.next",
"if ... | <|body_start_0|>
new_list = ListNode(0)
cur = new_list
while l1 and l2:
if l1.val < l2.val:
cur.next = l1
cur = cur.next
l1 = l1.next
else:
cur.next = l2
cur = cur.next
l2 = l2... | ListNodeOperator | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ListNodeOperator:
def mergeTwoListNode(self, l1, l2):
"""方法一：迭代法"""
<|body_0|>
def mergeTwoListNode(self, l1, l2):
"""方法二: 递归"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
new_list = ListNode(0)
cur = new_list
while l1 and l2:
... | stack_v2_sparse_classes_36k_train_002276 | 1,144 | no_license | [
{
"docstring": "方法一：迭代法",
"name": "mergeTwoListNode",
"signature": "def mergeTwoListNode(self, l1, l2)"
},
{
"docstring": "方法二: 递归",
"name": "mergeTwoListNode",
"signature": "def mergeTwoListNode(self, l1, l2)"
}
] | 2 | stack_v2_sparse_classes_30k_train_016280 | Implement the Python class `ListNodeOperator` described below.
Class description:
Implement the ListNodeOperator class.
Method signatures and docstrings:
- def mergeTwoListNode(self, l1, l2): 方法一：迭代法
- def mergeTwoListNode(self, l1, l2): 方法二: 递归 | Implement the Python class `ListNodeOperator` described below.
Class description:
Implement the ListNodeOperator class.
Method signatures and docstrings:
- def mergeTwoListNode(self, l1, l2): 方法一：迭代法
- def mergeTwoListNode(self, l1, l2): 方法二: 递归
<|skeleton|>
class ListNodeOperator:
def mergeTwoListNode(self, l1... | 417a5412398a29bd3ad5a996ea008327947a5245 | <|skeleton|>
class ListNodeOperator:
def mergeTwoListNode(self, l1, l2):
"""方法一：迭代法"""
<|body_0|>
def mergeTwoListNode(self, l1, l2):
"""方法二: 递归"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ListNodeOperator:
def mergeTwoListNode(self, l1, l2):
"""方法一：迭代法"""
new_list = ListNode(0)
cur = new_list
while l1 and l2:
if l1.val < l2.val:
cur.next = l1
cur = cur.next
l1 = l1.next
else:
... | the_stack_v2_python_sparse | treeAndLink/21.合并两个有序链表.py | lujiely/DataStructureAlgorithm_python | train | 0 | |
207076fd8ab3146cfe118ccec53b72566d9f2ea9 | [
"rootSet = cmds.ls(sl=True)\nsubSets = cmds.sets(rootSet, q=True)\nsetTable = {}\nfor subSet in subSets:\n setMems = cmds.sets(subSet, q=True)\n setTable[subSet] = setMems\nreturn setTable",
"for set in info.keys():\n if info[set] == None:\n continue\n existsObjLs = []\n for obj in info[set]... | <|body_start_0|>
rootSet = cmds.ls(sl=True)
subSets = cmds.sets(rootSet, q=True)
setTable = {}
for subSet in subSets:
setMems = cmds.sets(subSet, q=True)
setTable[subSet] = setMems
return setTable
<|end_body_0|>
<|body_start_1|>
for set in info.ke... | Set information class. Save set information and create set from saved information. | SetInfo | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SetInfo:
"""Set information class. Save set information and create set from saved information."""
def getSelSetInfo(self):
"""Get selected set and subset information."""
<|body_0|>
def createSet(self, info):
"""Create set with information."""
<|body_1|>
... | stack_v2_sparse_classes_36k_train_002277 | 5,415 | no_license | [
{
"docstring": "Get selected set and subset information.",
"name": "getSelSetInfo",
"signature": "def getSelSetInfo(self)"
},
{
"docstring": "Create set with information.",
"name": "createSet",
"signature": "def createSet(self, info)"
}
] | 2 | null | Implement the Python class `SetInfo` described below.
Class description:
Set information class. Save set information and create set from saved information.
Method signatures and docstrings:
- def getSelSetInfo(self): Get selected set and subset information.
- def createSet(self, info): Create set with information. | Implement the Python class `SetInfo` described below.
Class description:
Set information class. Save set information and create set from saved information.
Method signatures and docstrings:
- def getSelSetInfo(self): Get selected set and subset information.
- def createSet(self, info): Create set with information.
<... | bd98679cbab869a0c96eac34cb2f199dfbf8fee8 | <|skeleton|>
class SetInfo:
"""Set information class. Save set information and create set from saved information."""
def getSelSetInfo(self):
"""Get selected set and subset information."""
<|body_0|>
def createSet(self, info):
"""Create set with information."""
<|body_1|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SetInfo:
"""Set information class. Save set information and create set from saved information."""
def getSelSetInfo(self):
"""Get selected set and subset information."""
rootSet = cmds.ls(sl=True)
subSets = cmds.sets(rootSet, q=True)
setTable = {}
for subSet in sub... | the_stack_v2_python_sparse | python/tak_saveSceneInfo.py | jasonbrackman/scripts | train | 0 |
fb966322b9d5f78d5e116d502db6e94c96fc455a | [
"try:\n params = request._serialize()\n headers = request.headers\n body = self.call('DescribeMaterialList', params, headers=headers)\n response = json.loads(body)\n model = models.DescribeMaterialListResponse()\n model._deserialize(response['Response'])\n return model\nexcept Exception as e:\n... | <|body_start_0|>
try:
params = request._serialize()
headers = request.headers
body = self.call('DescribeMaterialList', params, headers=headers)
response = json.loads(body)
model = models.DescribeMaterialListResponse()
model._deserialize(res... | FacefusionClient | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FacefusionClient:
def DescribeMaterialList(self, request):
"""通常通过腾讯云人脸融合的控制台可以查看到素材相关的参数数据，可以满足使用。本接口返回活动的素材数据，包括素材状态等。用于用户通过Api查看素材相关数据，方便使用。 :param request: Request instance for DescribeMaterialList. :type request: :class:`tencentcloud.facefusion.v20181201.models.DescribeMaterialListR... | stack_v2_sparse_classes_36k_train_002278 | 5,785 | permissive | [
{
"docstring": "通常通过腾讯云人脸融合的控制台可以查看到素材相关的参数数据，可以满足使用。本接口返回活动的素材数据，包括素材状态等。用于用户通过Api查看素材相关数据，方便使用。 :param request: Request instance for DescribeMaterialList. :type request: :class:`tencentcloud.facefusion.v20181201.models.DescribeMaterialListRequest` :rtype: :class:`tencentcloud.facefusion.v20181201.models.Descr... | 4 | stack_v2_sparse_classes_30k_train_004465 | Implement the Python class `FacefusionClient` described below.
Class description:
Implement the FacefusionClient class.
Method signatures and docstrings:
- def DescribeMaterialList(self, request): 通常通过腾讯云人脸融合的控制台可以查看到素材相关的参数数据，可以满足使用。本接口返回活动的素材数据，包括素材状态等。用于用户通过Api查看素材相关数据，方便使用。 :param request: Request instance for De... | Implement the Python class `FacefusionClient` described below.
Class description:
Implement the FacefusionClient class.
Method signatures and docstrings:
- def DescribeMaterialList(self, request): 通常通过腾讯云人脸融合的控制台可以查看到素材相关的参数数据，可以满足使用。本接口返回活动的素材数据，包括素材状态等。用于用户通过Api查看素材相关数据，方便使用。 :param request: Request instance for De... | 6baf00a5a56ba58b6a1123423e0a1422d17a0201 | <|skeleton|>
class FacefusionClient:
def DescribeMaterialList(self, request):
"""通常通过腾讯云人脸融合的控制台可以查看到素材相关的参数数据，可以满足使用。本接口返回活动的素材数据，包括素材状态等。用于用户通过Api查看素材相关数据，方便使用。 :param request: Request instance for DescribeMaterialList. :type request: :class:`tencentcloud.facefusion.v20181201.models.DescribeMaterialListR... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FacefusionClient:
def DescribeMaterialList(self, request):
"""通常通过腾讯云人脸融合的控制台可以查看到素材相关的参数数据，可以满足使用。本接口返回活动的素材数据，包括素材状态等。用于用户通过Api查看素材相关数据，方便使用。 :param request: Request instance for DescribeMaterialList. :type request: :class:`tencentcloud.facefusion.v20181201.models.DescribeMaterialListRequest` :rtype... | the_stack_v2_python_sparse | tencentcloud/facefusion/v20181201/facefusion_client.py | TencentCloud/tencentcloud-sdk-python | train | 594 | |
f6c57e30a470dbffce4d734f9d22a6ac9e7a5305 | [
"self.kids = [{}]\nself.root = 0\nself.vocabular = set([])",
"flag = key in self.vocabular\ncurr = self.root\nself.vocabular.add(key)\nif flag:\n for ch in key:\n index = self.kids[curr][ch][1]\n self.kids[curr][ch] = [val, index]\n curr = index\nelse:\n curr = self.root\n for ch in ... | <|body_start_0|>
self.kids = [{}]
self.root = 0
self.vocabular = set([])
<|end_body_0|>
<|body_start_1|>
flag = key in self.vocabular
curr = self.root
self.vocabular.add(key)
if flag:
for ch in key:
index = self.kids[curr][ch][1]
... | MapSum | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MapSum:
def __init__(self):
"""Initialize your data structure here."""
<|body_0|>
def insert(self, key, val):
""":type key: str :type val: int :rtype: void"""
<|body_1|>
def sum(self, prefix):
""":type prefix: str :rtype: int"""
<|body_2|... | stack_v2_sparse_classes_36k_train_002279 | 1,449 | no_license | [
{
"docstring": "Initialize your data structure here.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": ":type key: str :type val: int :rtype: void",
"name": "insert",
"signature": "def insert(self, key, val)"
},
{
"docstring": ":type prefix: str :rtype: in... | 3 | stack_v2_sparse_classes_30k_train_006197 | Implement the Python class `MapSum` described below.
Class description:
Implement the MapSum class.
Method signatures and docstrings:
- def __init__(self): Initialize your data structure here.
- def insert(self, key, val): :type key: str :type val: int :rtype: void
- def sum(self, prefix): :type prefix: str :rtype: i... | Implement the Python class `MapSum` described below.
Class description:
Implement the MapSum class.
Method signatures and docstrings:
- def __init__(self): Initialize your data structure here.
- def insert(self, key, val): :type key: str :type val: int :rtype: void
- def sum(self, prefix): :type prefix: str :rtype: i... | c1b083733543e05b9f1e86ddcea1b4c6d0330aaa | <|skeleton|>
class MapSum:
def __init__(self):
"""Initialize your data structure here."""
<|body_0|>
def insert(self, key, val):
""":type key: str :type val: int :rtype: void"""
<|body_1|>
def sum(self, prefix):
""":type prefix: str :rtype: int"""
<|body_2|... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MapSum:
def __init__(self):
"""Initialize your data structure here."""
self.kids = [{}]
self.root = 0
self.vocabular = set([])
def insert(self, key, val):
""":type key: str :type val: int :rtype: void"""
flag = key in self.vocabular
curr = self.root... | the_stack_v2_python_sparse | solved/P677.py | lgdxiaobobo/Leetcoce | train | 0 | |
1df2328a215302f59c356ab06afdfaaa82f1d6fb | [
"super(PhasePlanePointwiseObjective, self).__init__(reference, **kwargs)\nself.thresh = dvdt_thresholds\nif self.thresh[0] < 0.0 or self.thresh[1] > 0.0:\n raise Exception('Start threshold must be above 0 and end threshold must be below 0 (found {})'.format(self.thresh))\nself.num_points = num_points\nself.no_sp... | <|body_start_0|>
super(PhasePlanePointwiseObjective, self).__init__(reference, **kwargs)
self.thresh = dvdt_thresholds
if self.thresh[0] < 0.0 or self.thresh[1] > 0.0:
raise Exception('Start threshold must be above 0 and end threshold must be below 0 (found {})'.format(self.thresh))
... | PhasePlanePointwiseObjective | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PhasePlanePointwiseObjective:
def __init__(self, reference, num_points=100, dvdt_thresholds=(10, -10), no_spike_reference=(-100, 0.0), **kwargs):
"""Creates a phase plane histogram from the reference traces and compares that with the histograms from the simulated traces `reference` -- tr... | stack_v2_sparse_classes_36k_train_002280 | 18,902 | no_license | [
{
"docstring": "Creates a phase plane histogram from the reference traces and compares that with the histograms from the simulated traces `reference` -- traces (in Neo format) that are to be compared against [list(neo.AnalogSignal)] `num_points` -- the number of sample points to interpolate between the loop sta... | 2 | stack_v2_sparse_classes_30k_train_006198 | Implement the Python class `PhasePlanePointwiseObjective` described below.
Class description:
Implement the PhasePlanePointwiseObjective class.
Method signatures and docstrings:
- def __init__(self, reference, num_points=100, dvdt_thresholds=(10, -10), no_spike_reference=(-100, 0.0), **kwargs): Creates a phase plane ... | Implement the Python class `PhasePlanePointwiseObjective` described below.
Class description:
Implement the PhasePlanePointwiseObjective class.
Method signatures and docstrings:
- def __init__(self, reference, num_points=100, dvdt_thresholds=(10, -10), no_spike_reference=(-100, 0.0), **kwargs): Creates a phase plane ... | 30974ebe83da6c55f382312cf588a0d714c23f0c | <|skeleton|>
class PhasePlanePointwiseObjective:
def __init__(self, reference, num_points=100, dvdt_thresholds=(10, -10), no_spike_reference=(-100, 0.0), **kwargs):
"""Creates a phase plane histogram from the reference traces and compares that with the histograms from the simulated traces `reference` -- tr... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PhasePlanePointwiseObjective:
def __init__(self, reference, num_points=100, dvdt_thresholds=(10, -10), no_spike_reference=(-100, 0.0), **kwargs):
"""Creates a phase plane histogram from the reference traces and compares that with the histograms from the simulated traces `reference` -- traces (in Neo f... | the_stack_v2_python_sparse | neurotune/objective/phase_plane.py | tclose/neurotune | train | 0 | |
8fb161cc5cfd4c736d4e3f4c3a0fc683e2e4508c | [
"super(DecoderBlock, self).__init__()\nself.mha1 = MultiHeadAttention(dm, h)\nself.mha2 = MultiHeadAttention(dm, h)\nself.dense_hidden = tf.keras.layers.Dense(hidden, activation='relu')\nself.dense_output = tf.keras.layers.Dense(dm)\nself.layernorm1 = tf.keras.layers.LayerNormalization(epsilon=1e-06)\nself.layernor... | <|body_start_0|>
super(DecoderBlock, self).__init__()
self.mha1 = MultiHeadAttention(dm, h)
self.mha2 = MultiHeadAttention(dm, h)
self.dense_hidden = tf.keras.layers.Dense(hidden, activation='relu')
self.dense_output = tf.keras.layers.Dense(dm)
self.layernorm1 = tf.keras.... | DecodeBlock class creates decoder layer | DecoderBlock | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DecoderBlock:
"""DecodeBlock class creates decoder layer"""
def __init__(self, dm, h, hidden, drop_rate=0.1) -> None:
"""Initializer Arguments: dm {int} -- The output dimensionality h {int} -- The number of head hidden {int} -- The hidden units Keyword Arguments: drop_rate {float} --... | stack_v2_sparse_classes_36k_train_002281 | 2,545 | no_license | [
{
"docstring": "Initializer Arguments: dm {int} -- The output dimensionality h {int} -- The number of head hidden {int} -- The hidden units Keyword Arguments: drop_rate {float} -- Drop rate (default: {0.1})",
"name": "__init__",
"signature": "def __init__(self, dm, h, hidden, drop_rate=0.1) -> None"
}... | 2 | stack_v2_sparse_classes_30k_train_003370 | Implement the Python class `DecoderBlock` described below.
Class description:
DecodeBlock class creates decoder layer
Method signatures and docstrings:
- def __init__(self, dm, h, hidden, drop_rate=0.1) -> None: Initializer Arguments: dm {int} -- The output dimensionality h {int} -- The number of head hidden {int} --... | Implement the Python class `DecoderBlock` described below.
Class description:
DecodeBlock class creates decoder layer
Method signatures and docstrings:
- def __init__(self, dm, h, hidden, drop_rate=0.1) -> None: Initializer Arguments: dm {int} -- The output dimensionality h {int} -- The number of head hidden {int} --... | 2ddae38cc25d914488451b8c30e1234f1fa55ebe | <|skeleton|>
class DecoderBlock:
"""DecodeBlock class creates decoder layer"""
def __init__(self, dm, h, hidden, drop_rate=0.1) -> None:
"""Initializer Arguments: dm {int} -- The output dimensionality h {int} -- The number of head hidden {int} -- The hidden units Keyword Arguments: drop_rate {float} --... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DecoderBlock:
"""DecodeBlock class creates decoder layer"""
def __init__(self, dm, h, hidden, drop_rate=0.1) -> None:
"""Initializer Arguments: dm {int} -- The output dimensionality h {int} -- The number of head hidden {int} -- The hidden units Keyword Arguments: drop_rate {float} -- Drop rate (d... | the_stack_v2_python_sparse | supervised_learning/0x11-attention/8-transformer_decoder_block.py | KoeusIss/holbertonschool-machine_learning | train | 0 |
7d2b8d639e6d7fbf51942b1287bed7e1f83d59c9 | [
"data = {'text': 'test skill'}\nresponse = self.client.post(self.url, data, headers={'Content-Type': 'application/json'})\nself.assertEqual(200, response.status_code)",
"self.skill = Skill.objects.create(text='Test')\nresponse = self.client.get(self.url)\nself.assertEqual(len(response.data['results']['data']), Sk... | <|body_start_0|>
data = {'text': 'test skill'}
response = self.client.post(self.url, data, headers={'Content-Type': 'application/json'})
self.assertEqual(200, response.status_code)
<|end_body_0|>
<|body_start_1|>
self.skill = Skill.objects.create(text='Test')
response = self.cli... | Test cases for skill list call | SkillListTestCase | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SkillListTestCase:
"""Test cases for skill list call"""
def test_add_profession(self):
"""Test to add a skill"""
<|body_0|>
def test_profession(self):
"""Test to verify user created skill"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
data = {'... | stack_v2_sparse_classes_36k_train_002282 | 21,995 | no_license | [
{
"docstring": "Test to add a skill",
"name": "test_add_profession",
"signature": "def test_add_profession(self)"
},
{
"docstring": "Test to verify user created skill",
"name": "test_profession",
"signature": "def test_profession(self)"
}
] | 2 | null | Implement the Python class `SkillListTestCase` described below.
Class description:
Test cases for skill list call
Method signatures and docstrings:
- def test_add_profession(self): Test to add a skill
- def test_profession(self): Test to verify user created skill | Implement the Python class `SkillListTestCase` described below.
Class description:
Test cases for skill list call
Method signatures and docstrings:
- def test_add_profession(self): Test to add a skill
- def test_profession(self): Test to verify user created skill
<|skeleton|>
class SkillListTestCase:
"""Test cas... | f38ea1ff9283416f4b4b1a9eb134344a566856a4 | <|skeleton|>
class SkillListTestCase:
"""Test cases for skill list call"""
def test_add_profession(self):
"""Test to add a skill"""
<|body_0|>
def test_profession(self):
"""Test to verify user created skill"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SkillListTestCase:
"""Test cases for skill list call"""
def test_add_profession(self):
"""Test to add a skill"""
data = {'text': 'test skill'}
response = self.client.post(self.url, data, headers={'Content-Type': 'application/json'})
self.assertEqual(200, response.status_co... | the_stack_v2_python_sparse | userprofile/tests.py | meanwise-eng/meanwise-server | train | 0 |
5e872aaf50142500d7a3573769ca37b9a7cc7d65 | [
"super(ResNetBase, self).__init__()\nself.output_channel_block = [int(output_channel / 4), int(output_channel / 2), output_channel, output_channel]\nself.inplanes = int(output_channel / 8)\nself.conv0_1 = nn.Conv2d(input_channel, int(output_channel / 16), kernel_size=3, stride=1, padding=1, bias=False)\nself.bn0_1 ... | <|body_start_0|>
super(ResNetBase, self).__init__()
self.output_channel_block = [int(output_channel / 4), int(output_channel / 2), output_channel, output_channel]
self.inplanes = int(output_channel / 8)
self.conv0_1 = nn.Conv2d(input_channel, int(output_channel / 16), kernel_size=3, stri... | Base share backbone network | ResNetBase | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ResNetBase:
"""Base share backbone network"""
def __init__(self, input_channel, output_channel, block, layers):
"""Args: input_channel (int): input channel output_channel (int): output channel block (BasicBlock): convolution block layers (list): layers of the block"""
<|body_... | stack_v2_sparse_classes_36k_train_002283 | 11,483 | permissive | [
{
"docstring": "Args: input_channel (int): input channel output_channel (int): output channel block (BasicBlock): convolution block layers (list): layers of the block",
"name": "__init__",
"signature": "def __init__(self, input_channel, output_channel, block, layers)"
},
{
"docstring": "Args: bl... | 3 | stack_v2_sparse_classes_30k_train_013478 | Implement the Python class `ResNetBase` described below.
Class description:
Base share backbone network
Method signatures and docstrings:
- def __init__(self, input_channel, output_channel, block, layers): Args: input_channel (int): input channel output_channel (int): output channel block (BasicBlock): convolution bl... | Implement the Python class `ResNetBase` described below.
Class description:
Base share backbone network
Method signatures and docstrings:
- def __init__(self, input_channel, output_channel, block, layers): Args: input_channel (int): input channel output_channel (int): output channel block (BasicBlock): convolution bl... | fb47a96d1a38f5ce634c6f12d710ed5300cc89fc | <|skeleton|>
class ResNetBase:
"""Base share backbone network"""
def __init__(self, input_channel, output_channel, block, layers):
"""Args: input_channel (int): input channel output_channel (int): output channel block (BasicBlock): convolution block layers (list): layers of the block"""
<|body_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ResNetBase:
"""Base share backbone network"""
def __init__(self, input_channel, output_channel, block, layers):
"""Args: input_channel (int): input channel output_channel (int): output channel block (BasicBlock): convolution block layers (list): layers of the block"""
super(ResNetBase, se... | the_stack_v2_python_sparse | davarocr/davarocr/davar_rcg/models/backbones/ResNetRFL.py | OCRWorld/DAVAR-Lab-OCR | train | 0 |
8b6eec457c1d52828903130dddc183ebff086d99 | [
"try:\n prefix, token = header.split()\nexcept ValueError:\n raise authentication.AuthenticationError('Unable to split prefix and token from Authorization header.')\nif prefix.upper() != 'JWT':\n raise authentication.AuthenticationError(f\"Invalid Authorization header prefix '{prefix}'.\")\nreturn token",
... | <|body_start_0|>
try:
prefix, token = header.split()
except ValueError:
raise authentication.AuthenticationError('Unable to split prefix and token from Authorization header.')
if prefix.upper() != 'JWT':
raise authentication.AuthenticationError(f"Invalid Autho... | Custom Starlette authentication backend for JWT. | JWTAuthenticationBackend | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class JWTAuthenticationBackend:
"""Custom Starlette authentication backend for JWT."""
def get_token_from_header(header: str) -> str:
"""Parse JWT token from header value."""
<|body_0|>
async def authenticate(self, request: Request) -> t.Optional[tuple[authentication.AuthCrede... | stack_v2_sparse_classes_36k_train_002284 | 1,656 | permissive | [
{
"docstring": "Parse JWT token from header value.",
"name": "get_token_from_header",
"signature": "def get_token_from_header(header: str) -> str"
},
{
"docstring": "Handles JWT authentication process.",
"name": "authenticate",
"signature": "async def authenticate(self, request: Request)... | 2 | stack_v2_sparse_classes_30k_train_014349 | Implement the Python class `JWTAuthenticationBackend` described below.
Class description:
Custom Starlette authentication backend for JWT.
Method signatures and docstrings:
- def get_token_from_header(header: str) -> str: Parse JWT token from header value.
- async def authenticate(self, request: Request) -> t.Optiona... | Implement the Python class `JWTAuthenticationBackend` described below.
Class description:
Custom Starlette authentication backend for JWT.
Method signatures and docstrings:
- def get_token_from_header(header: str) -> str: Parse JWT token from header value.
- async def authenticate(self, request: Request) -> t.Optiona... | 1b4b4fe6819352f1f072ce307eee892866a11dcf | <|skeleton|>
class JWTAuthenticationBackend:
"""Custom Starlette authentication backend for JWT."""
def get_token_from_header(header: str) -> str:
"""Parse JWT token from header value."""
<|body_0|>
async def authenticate(self, request: Request) -> t.Optional[tuple[authentication.AuthCrede... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class JWTAuthenticationBackend:
"""Custom Starlette authentication backend for JWT."""
def get_token_from_header(header: str) -> str:
"""Parse JWT token from header value."""
try:
prefix, token = header.split()
except ValueError:
raise authentication.Authenticati... | the_stack_v2_python_sparse | backend/authentication/backend.py | MrGrote/forms-backend | train | 0 |
c6cd01d1695b9d40a3c3ec862bfe86e4da2c1339 | [
"url = utils.urljoin(self.base_path, image_id)\nresp = session.get(url, headers={'Accept': 'application/json'}, endpoint_filter=self.service)\nself.response = resp.json()\nself._translate_response(resp, has_body=True)\nreturn self",
"url = utils.urljoin(self.base_path, image_id)\nattrs_list = json.dumps(attrs_lis... | <|body_start_0|>
url = utils.urljoin(self.base_path, image_id)
resp = session.get(url, headers={'Accept': 'application/json'}, endpoint_filter=self.service)
self.response = resp.json()
self._translate_response(resp, has_body=True)
return self
<|end_body_0|>
<|body_start_1|>
... | Image | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Image:
def get(self, session, image_id):
"""Get a single image's detailed information."""
<|body_0|>
def update(self, session, image_id, attrs_list):
"""Updates a specified image."""
<|body_1|>
def upload(self, session, image_id, image_data):
"""... | stack_v2_sparse_classes_36k_train_002285 | 10,107 | permissive | [
{
"docstring": "Get a single image's detailed information.",
"name": "get",
"signature": "def get(self, session, image_id)"
},
{
"docstring": "Updates a specified image.",
"name": "update",
"signature": "def update(self, session, image_id, attrs_list)"
},
{
"docstring": "Upload d... | 5 | null | Implement the Python class `Image` described below.
Class description:
Implement the Image class.
Method signatures and docstrings:
- def get(self, session, image_id): Get a single image's detailed information.
- def update(self, session, image_id, attrs_list): Updates a specified image.
- def upload(self, session, i... | Implement the Python class `Image` described below.
Class description:
Implement the Image class.
Method signatures and docstrings:
- def get(self, session, image_id): Get a single image's detailed information.
- def update(self, session, image_id, attrs_list): Updates a specified image.
- def upload(self, session, i... | c2dafba850c4e6fb55b5e10de79257bbc9a01af3 | <|skeleton|>
class Image:
def get(self, session, image_id):
"""Get a single image's detailed information."""
<|body_0|>
def update(self, session, image_id, attrs_list):
"""Updates a specified image."""
<|body_1|>
def upload(self, session, image_id, image_data):
"""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Image:
def get(self, session, image_id):
"""Get a single image's detailed information."""
url = utils.urljoin(self.base_path, image_id)
resp = session.get(url, headers={'Accept': 'application/json'}, endpoint_filter=self.service)
self.response = resp.json()
self._transl... | the_stack_v2_python_sparse | ecl/image/v2/image.py | nttcom/eclsdk | train | 5 | |
40988b73704fa81b343adbcd3a503af945f65206 | [
"super(SentimentRNN, self).__init__()\nself.output_size = output_size\nself.n_layers = n_layers\nself.hidden_dim = hidden_dim\nself.embedding = nn.Embedding(vocab_size, embedding_dim)\nself.lstm = nn.LSTM(embedding_dim, hidden_dim, n_layers, dropout=drop_prob, batch_first=True)\nself.dropout = nn.Dropout(0.3)\nself... | <|body_start_0|>
super(SentimentRNN, self).__init__()
self.output_size = output_size
self.n_layers = n_layers
self.hidden_dim = hidden_dim
self.embedding = nn.Embedding(vocab_size, embedding_dim)
self.lstm = nn.LSTM(embedding_dim, hidden_dim, n_layers, dropout=drop_prob, ... | RNN 文本分类 | SentimentRNN | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SentimentRNN:
"""RNN 文本分类"""
def __init__(self, vocab_size, output_size, embedding_dim, hidden_dim, n_layers, drop_prob=0.5):
"""Initialize the model by setting up the layers."""
<|body_0|>
def forward(self, x, hidden):
"""Perform a forward pass of our model on s... | stack_v2_sparse_classes_36k_train_002286 | 8,138 | no_license | [
{
"docstring": "Initialize the model by setting up the layers.",
"name": "__init__",
"signature": "def __init__(self, vocab_size, output_size, embedding_dim, hidden_dim, n_layers, drop_prob=0.5)"
},
{
"docstring": "Perform a forward pass of our model on some input and hidden state.",
"name":... | 3 | stack_v2_sparse_classes_30k_train_014482 | Implement the Python class `SentimentRNN` described below.
Class description:
RNN 文本分类
Method signatures and docstrings:
- def __init__(self, vocab_size, output_size, embedding_dim, hidden_dim, n_layers, drop_prob=0.5): Initialize the model by setting up the layers.
- def forward(self, x, hidden): Perform a forward p... | Implement the Python class `SentimentRNN` described below.
Class description:
RNN 文本分类
Method signatures and docstrings:
- def __init__(self, vocab_size, output_size, embedding_dim, hidden_dim, n_layers, drop_prob=0.5): Initialize the model by setting up the layers.
- def forward(self, x, hidden): Perform a forward p... | 64714414c272149a0f83e9ea846348470d45d33a | <|skeleton|>
class SentimentRNN:
"""RNN 文本分类"""
def __init__(self, vocab_size, output_size, embedding_dim, hidden_dim, n_layers, drop_prob=0.5):
"""Initialize the model by setting up the layers."""
<|body_0|>
def forward(self, x, hidden):
"""Perform a forward pass of our model on s... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SentimentRNN:
"""RNN 文本分类"""
def __init__(self, vocab_size, output_size, embedding_dim, hidden_dim, n_layers, drop_prob=0.5):
"""Initialize the model by setting up the layers."""
super(SentimentRNN, self).__init__()
self.output_size = output_size
self.n_layers = n_layers
... | the_stack_v2_python_sparse | 任务二：基于深度学习（RNN）的文本分类（Pytorch）.py | Zhangbingbin11/xiyu-NLPTrainee | train | 1 |
ec55e7e8567fa0615f54ad5159259e02c2c55149 | [
"recipe = Recipe.get_by_id(recipe_id=recipe_id)\nif recipe is None:\n return ({'message': 'recipe not found'}, HTTPStatus.NOT_FOUND)\ncurrent_user = get_jwt_identity()\nif current_user != recipe.user_id:\n return ({'message': 'Access is not allowed'}, HTTPStatus.FORBIDDEN)\nrecipe.is_publish = True\nrecipe.sa... | <|body_start_0|>
recipe = Recipe.get_by_id(recipe_id=recipe_id)
if recipe is None:
return ({'message': 'recipe not found'}, HTTPStatus.NOT_FOUND)
current_user = get_jwt_identity()
if current_user != recipe.user_id:
return ({'message': 'Access is not allowed'}, HTT... | RecipePublishResource | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RecipePublishResource:
def put(self, recipe_id):
""":param"""
<|body_0|>
def delete(self, recipe_id):
""":param"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
recipe = Recipe.get_by_id(recipe_id=recipe_id)
if recipe is None:
ret... | stack_v2_sparse_classes_36k_train_002287 | 8,070 | no_license | [
{
"docstring": ":param",
"name": "put",
"signature": "def put(self, recipe_id)"
},
{
"docstring": ":param",
"name": "delete",
"signature": "def delete(self, recipe_id)"
}
] | 2 | stack_v2_sparse_classes_30k_train_000843 | Implement the Python class `RecipePublishResource` described below.
Class description:
Implement the RecipePublishResource class.
Method signatures and docstrings:
- def put(self, recipe_id): :param
- def delete(self, recipe_id): :param | Implement the Python class `RecipePublishResource` described below.
Class description:
Implement the RecipePublishResource class.
Method signatures and docstrings:
- def put(self, recipe_id): :param
- def delete(self, recipe_id): :param
<|skeleton|>
class RecipePublishResource:
def put(self, recipe_id):
... | 875b8bc3cc5315efe8ccee8ce9b312056802c49d | <|skeleton|>
class RecipePublishResource:
def put(self, recipe_id):
""":param"""
<|body_0|>
def delete(self, recipe_id):
""":param"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RecipePublishResource:
def put(self, recipe_id):
""":param"""
recipe = Recipe.get_by_id(recipe_id=recipe_id)
if recipe is None:
return ({'message': 'recipe not found'}, HTTPStatus.NOT_FOUND)
current_user = get_jwt_identity()
if current_user != recipe.user_id... | the_stack_v2_python_sparse | resources/recipe.py | ShayanRiyaz/TheDailyCook | train | 1 | |
26106f68a025c363d45a752f79cdeef0b771e8ae | [
"self.frequency = _frequency\nself.two_pi_frequency = 2 * pi * _frequency\nself.amplitude = _amplitude\nself.phase = _phase\nself.voltage_offset = voltage_offset\nself.noise_level = noise_level\nself.signal_log = []",
"test_sig0 = self.amplitude * sin(_t * self.two_pi_frequency + self.phase) + (random.random() * ... | <|body_start_0|>
self.frequency = _frequency
self.two_pi_frequency = 2 * pi * _frequency
self.amplitude = _amplitude
self.phase = _phase
self.voltage_offset = voltage_offset
self.noise_level = noise_level
self.signal_log = []
<|end_body_0|>
<|body_start_1|>
... | ComplexSineSignal | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ComplexSineSignal:
def __init__(self, _amplitude, _frequency, _phase, noise_level=0, voltage_offset=0):
"""The constructor for a sine wave signal. :param _amplitude: the amplitude of the sine wave in volts :param _frequency: the frequency of the sine wave in Hz :param _phase: the phase o... | stack_v2_sparse_classes_36k_train_002288 | 3,002 | no_license | [
{
"docstring": "The constructor for a sine wave signal. :param _amplitude: the amplitude of the sine wave in volts :param _frequency: the frequency of the sine wave in Hz :param _phase: the phase of the sine wave in radians :param noise_level: (optional) the absolute noise level of the sine wave (default 0) :pa... | 2 | stack_v2_sparse_classes_30k_train_012111 | Implement the Python class `ComplexSineSignal` described below.
Class description:
Implement the ComplexSineSignal class.
Method signatures and docstrings:
- def __init__(self, _amplitude, _frequency, _phase, noise_level=0, voltage_offset=0): The constructor for a sine wave signal. :param _amplitude: the amplitude of... | Implement the Python class `ComplexSineSignal` described below.
Class description:
Implement the ComplexSineSignal class.
Method signatures and docstrings:
- def __init__(self, _amplitude, _frequency, _phase, noise_level=0, voltage_offset=0): The constructor for a sine wave signal. :param _amplitude: the amplitude of... | b8061fe79f88c0892b55c2f4488355a8f68cc957 | <|skeleton|>
class ComplexSineSignal:
def __init__(self, _amplitude, _frequency, _phase, noise_level=0, voltage_offset=0):
"""The constructor for a sine wave signal. :param _amplitude: the amplitude of the sine wave in volts :param _frequency: the frequency of the sine wave in Hz :param _phase: the phase o... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ComplexSineSignal:
def __init__(self, _amplitude, _frequency, _phase, noise_level=0, voltage_offset=0):
"""The constructor for a sine wave signal. :param _amplitude: the amplitude of the sine wave in volts :param _frequency: the frequency of the sine wave in Hz :param _phase: the phase of the sine wav... | the_stack_v2_python_sparse | lib/signals/TestSignals.py | kevroy314/PLL-Neural-Network | train | 3 | |
0bd72cb09b7ccf50a08c15a23b3d680baab6f444 | [
"log = logging.getLogger(__name__)\nif cls.LOCAL is not None:\n log.warn('Warning, %s is already configured. Ignoring new configuration.', str(cls))\nelse:\n log.info('Setting FDataMover.LOCAL (use_local_implementation) to: %s' % settings['bccvl.data_mover.use_local_implementation'])\n cls.LOCAL = asbool(s... | <|body_start_0|>
log = logging.getLogger(__name__)
if cls.LOCAL is not None:
log.warn('Warning, %s is already configured. Ignoring new configuration.', str(cls))
else:
log.info('Setting FDataMover.LOCAL (use_local_implementation) to: %s' % settings['bccvl.data_mover.use_l... | FDataMover | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FDataMover:
def configure_from_config(cls, settings):
"""configure the FDataMover (and DataMover) constants"""
<|body_0|>
def new_data_mover(cls, *args, **kwargs):
"""Create a data mover"""
<|body_1|>
def get_data_mover_class(cls, *args, **kwargs):
... | stack_v2_sparse_classes_36k_train_002289 | 10,537 | no_license | [
{
"docstring": "configure the FDataMover (and DataMover) constants",
"name": "configure_from_config",
"signature": "def configure_from_config(cls, settings)"
},
{
"docstring": "Create a data mover",
"name": "new_data_mover",
"signature": "def new_data_mover(cls, *args, **kwargs)"
},
... | 3 | stack_v2_sparse_classes_30k_val_000652 | Implement the Python class `FDataMover` described below.
Class description:
Implement the FDataMover class.
Method signatures and docstrings:
- def configure_from_config(cls, settings): configure the FDataMover (and DataMover) constants
- def new_data_mover(cls, *args, **kwargs): Create a data mover
- def get_data_mo... | Implement the Python class `FDataMover` described below.
Class description:
Implement the FDataMover class.
Method signatures and docstrings:
- def configure_from_config(cls, settings): configure the FDataMover (and DataMover) constants
- def new_data_mover(cls, *args, **kwargs): Create a data mover
- def get_data_mo... | ff41e44b5cf10136082a4d7349f1fdb61239f6c5 | <|skeleton|>
class FDataMover:
def configure_from_config(cls, settings):
"""configure the FDataMover (and DataMover) constants"""
<|body_0|>
def new_data_mover(cls, *args, **kwargs):
"""Create a data mover"""
<|body_1|>
def get_data_mover_class(cls, *args, **kwargs):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FDataMover:
def configure_from_config(cls, settings):
"""configure the FDataMover (and DataMover) constants"""
log = logging.getLogger(__name__)
if cls.LOCAL is not None:
log.warn('Warning, %s is already configured. Ignoring new configuration.', str(cls))
else:
... | the_stack_v2_python_sparse | bccvl_visualiser/models/external_api/data_mover.py | BCCVL/BCCVL_Visualiser | train | 1 | |
73fd11624fa8a24d4153683638eed3bf71697318 | [
"procurement_date_planned = datetime.strptime(procurement.date_planned, DEFAULT_SERVER_DATETIME_FORMAT)\nseller_delay = int(procurement.product_id.seller_delay)\nschedule_date = procurement_date_planned + relativedelta(days=company.po_lead) + relativedelta(days=seller_delay)\nreturn schedule_date",
"procurement_d... | <|body_start_0|>
procurement_date_planned = datetime.strptime(procurement.date_planned, DEFAULT_SERVER_DATETIME_FORMAT)
seller_delay = int(procurement.product_id.seller_delay)
schedule_date = procurement_date_planned + relativedelta(days=company.po_lead) + relativedelta(days=seller_delay)
... | procurement_order | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class procurement_order:
def _get_purchase_schedule_date(self, cr, uid, procurement, company, context=None):
"""Return the datetime value to use as Schedule Date (``date_planned``) for the Purchase Order Lines created to satisfy the given procurement. :param browse_record procurement: the proc... | stack_v2_sparse_classes_36k_train_002290 | 2,336 | no_license | [
{
"docstring": "Return the datetime value to use as Schedule Date (``date_planned``) for the Purchase Order Lines created to satisfy the given procurement. :param browse_record procurement: the procurement for which a PO will be created. :param browse_report company: the company to which the new PO will belong ... | 2 | stack_v2_sparse_classes_30k_train_019509 | Implement the Python class `procurement_order` described below.
Class description:
Implement the procurement_order class.
Method signatures and docstrings:
- def _get_purchase_schedule_date(self, cr, uid, procurement, company, context=None): Return the datetime value to use as Schedule Date (``date_planned``) for the... | Implement the Python class `procurement_order` described below.
Class description:
Implement the procurement_order class.
Method signatures and docstrings:
- def _get_purchase_schedule_date(self, cr, uid, procurement, company, context=None): Return the datetime value to use as Schedule Date (``date_planned``) for the... | faa4d22da620331b55c949dcb773ec2d2d19dab7 | <|skeleton|>
class procurement_order:
def _get_purchase_schedule_date(self, cr, uid, procurement, company, context=None):
"""Return the datetime value to use as Schedule Date (``date_planned``) for the Purchase Order Lines created to satisfy the given procurement. :param browse_record procurement: the proc... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class procurement_order:
def _get_purchase_schedule_date(self, cr, uid, procurement, company, context=None):
"""Return the datetime value to use as Schedule Date (``date_planned``) for the Purchase Order Lines created to satisfy the given procurement. :param browse_record procurement: the procurement for wh... | the_stack_v2_python_sparse | purchase_osv.py | hjainavi/panipat_handloom | train | 0 | |
1e56fd0ad8e80953ff4f7bafbbe7ba6eecc4f9e7 | [
"from gringotts.services import cinder\nfrom gringotts.services import neutron\nfrom gringotts.services import nova\nfrom gringotts.services import trove\nproject_id = acl.get_limited_to_project(request.headers, 'quota_update')\nif project_id:\n raise exception.NotAuthorized\nif data.project_id == wtypes.Unset o... | <|body_start_0|>
from gringotts.services import cinder
from gringotts.services import neutron
from gringotts.services import nova
from gringotts.services import trove
project_id = acl.get_limited_to_project(request.headers, 'quota_update')
if project_id:
raise... | Operations on resources. | QuotasController | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class QuotasController:
"""Operations on resources."""
def put(self, data):
"""Get all resources of specified project_id in all regions."""
<|body_0|>
def get(self, project_id=None, user_id=None, region_name=None):
"""Get quota of specified project in specified region.... | stack_v2_sparse_classes_36k_train_002291 | 6,777 | no_license | [
{
"docstring": "Get all resources of specified project_id in all regions.",
"name": "put",
"signature": "def put(self, data)"
},
{
"docstring": "Get quota of specified project in specified region.",
"name": "get",
"signature": "def get(self, project_id=None, user_id=None, region_name=Non... | 2 | stack_v2_sparse_classes_30k_val_000326 | Implement the Python class `QuotasController` described below.
Class description:
Operations on resources.
Method signatures and docstrings:
- def put(self, data): Get all resources of specified project_id in all regions.
- def get(self, project_id=None, user_id=None, region_name=None): Get quota of specified project... | Implement the Python class `QuotasController` described below.
Class description:
Operations on resources.
Method signatures and docstrings:
- def put(self, data): Get all resources of specified project_id in all regions.
- def get(self, project_id=None, user_id=None, region_name=None): Get quota of specified project... | 75f656398c11b0dbddf99bf429994624915c3565 | <|skeleton|>
class QuotasController:
"""Operations on resources."""
def put(self, data):
"""Get all resources of specified project_id in all regions."""
<|body_0|>
def get(self, project_id=None, user_id=None, region_name=None):
"""Get quota of specified project in specified region.... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class QuotasController:
"""Operations on resources."""
def put(self, data):
"""Get all resources of specified project_id in all regions."""
from gringotts.services import cinder
from gringotts.services import neutron
from gringotts.services import nova
from gringotts.ser... | the_stack_v2_python_sparse | gringotts/api/v2/quotas.py | rogeroger-yu/ustack-gringotts | train | 1 |
c57f1160fb160f8e68a0ec2500ffeb2c7f442ab7 | [
"n = len(nums1)\nm = len(nums2)\ni = -1\nj = 0\nans = []\nwhile k:\n ch = []\n if 0 <= i + 1 < n and 0 <= j < m:\n ch.append((nums1[i + 1] + nums2[j], i + 1, 0, nums1[i + 1], nums2[j]))\n if 0 <= j + 1 < m and 0 <= i < n:\n ch.append((nums1[i] + nums2[j + 1], 0, j + 1, nums1[i], nums2[j + 1])... | <|body_start_0|>
n = len(nums1)
m = len(nums2)
i = -1
j = 0
ans = []
while k:
ch = []
if 0 <= i + 1 < n and 0 <= j < m:
ch.append((nums1[i + 1] + nums2[j], i + 1, 0, nums1[i + 1], nums2[j]))
if 0 <= j + 1 < m and 0 <= i ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def kSmallestPairsWA(self, nums1, nums2, k):
""":type nums1: List[int] :type nums2: List[int] :type k: int :rtype: List[List[int]]"""
<|body_0|>
def kSmallestPairs(self, nums1, nums2, k):
""":type nums1: List[int] :type nums2: List[int] :type k: int :rtype:... | stack_v2_sparse_classes_36k_train_002292 | 2,425 | no_license | [
{
"docstring": ":type nums1: List[int] :type nums2: List[int] :type k: int :rtype: List[List[int]]",
"name": "kSmallestPairsWA",
"signature": "def kSmallestPairsWA(self, nums1, nums2, k)"
},
{
"docstring": ":type nums1: List[int] :type nums2: List[int] :type k: int :rtype: List[List[int]]",
... | 2 | stack_v2_sparse_classes_30k_train_003596 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def kSmallestPairsWA(self, nums1, nums2, k): :type nums1: List[int] :type nums2: List[int] :type k: int :rtype: List[List[int]]
- def kSmallestPairs(self, nums1, nums2, k): :type... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def kSmallestPairsWA(self, nums1, nums2, k): :type nums1: List[int] :type nums2: List[int] :type k: int :rtype: List[List[int]]
- def kSmallestPairs(self, nums1, nums2, k): :type... | 02ebe56cd92b9f4baeee132c5077892590018650 | <|skeleton|>
class Solution:
def kSmallestPairsWA(self, nums1, nums2, k):
""":type nums1: List[int] :type nums2: List[int] :type k: int :rtype: List[List[int]]"""
<|body_0|>
def kSmallestPairs(self, nums1, nums2, k):
""":type nums1: List[int] :type nums2: List[int] :type k: int :rtype:... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def kSmallestPairsWA(self, nums1, nums2, k):
""":type nums1: List[int] :type nums2: List[int] :type k: int :rtype: List[List[int]]"""
n = len(nums1)
m = len(nums2)
i = -1
j = 0
ans = []
while k:
ch = []
if 0 <= i + 1 < n... | the_stack_v2_python_sparse | python/leetcode.373.py | CalvinNeo/LeetCode | train | 3 | |
60388b49b2e571ce8a13b0974a1ed0b213ade031 | [
"EPS = 1e-05\npoints = set(map(tuple, points))\nret = float('inf')\nfor p1, p2, p3 in itertools.permutations(points, 3):\n p4 = (p2[0] + p3[0] - p1[0], p2[1] + p3[1] - p1[1])\n if p4 in points:\n v31 = complex(p3[0] - p1[0], p3[1] - p1[1])\n v21 = complex(p2[0] - p1[0], p2[1] - p1[1])\n i... | <|body_start_0|>
EPS = 1e-05
points = set(map(tuple, points))
ret = float('inf')
for p1, p2, p3 in itertools.permutations(points, 3):
p4 = (p2[0] + p3[0] - p1[0], p2[1] + p3[1] - p1[1])
if p4 in points:
v31 = complex(p3[0] - p1[0], p3[1] - p1[1])
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def minAreaFreeRect1(self, points):
""":type points: List[List[int]] :rtype: float"""
<|body_0|>
def minAreaFreeRect2(self, points):
""":type points: List[List[int]] :rtype: float"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
EPS = 1e-05... | stack_v2_sparse_classes_36k_train_002293 | 2,530 | no_license | [
{
"docstring": ":type points: List[List[int]] :rtype: float",
"name": "minAreaFreeRect1",
"signature": "def minAreaFreeRect1(self, points)"
},
{
"docstring": ":type points: List[List[int]] :rtype: float",
"name": "minAreaFreeRect2",
"signature": "def minAreaFreeRect2(self, points)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def minAreaFreeRect1(self, points): :type points: List[List[int]] :rtype: float
- def minAreaFreeRect2(self, points): :type points: List[List[int]] :rtype: float | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def minAreaFreeRect1(self, points): :type points: List[List[int]] :rtype: float
- def minAreaFreeRect2(self, points): :type points: List[List[int]] :rtype: float
<|skeleton|>
cl... | d3e8669f932fc2e22711e8b7590d3365d020e189 | <|skeleton|>
class Solution:
def minAreaFreeRect1(self, points):
""":type points: List[List[int]] :rtype: float"""
<|body_0|>
def minAreaFreeRect2(self, points):
""":type points: List[List[int]] :rtype: float"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def minAreaFreeRect1(self, points):
""":type points: List[List[int]] :rtype: float"""
EPS = 1e-05
points = set(map(tuple, points))
ret = float('inf')
for p1, p2, p3 in itertools.permutations(points, 3):
p4 = (p2[0] + p3[0] - p1[0], p2[1] + p3[1] - ... | the_stack_v2_python_sparse | leetcode/963.py | liuweilin17/algorithm | train | 3 | |
6fd893bd164680229de1f5cf40a2fd1de24361db | [
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')",
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')"
] | <|body_start_0|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!')
<|end_body_0|>
<|body_start_1|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not im... | Set of methods to view possible host configurations. | HostTypeServiceServicer | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HostTypeServiceServicer:
"""Set of methods to view possible host configurations."""
def Get(self, request, context):
"""Returns information about specified host type."""
<|body_0|>
def List(self, request, context):
"""List avaliable host types."""
<|body_... | stack_v2_sparse_classes_36k_train_002294 | 4,759 | permissive | [
{
"docstring": "Returns information about specified host type.",
"name": "Get",
"signature": "def Get(self, request, context)"
},
{
"docstring": "List avaliable host types.",
"name": "List",
"signature": "def List(self, request, context)"
}
] | 2 | null | Implement the Python class `HostTypeServiceServicer` described below.
Class description:
Set of methods to view possible host configurations.
Method signatures and docstrings:
- def Get(self, request, context): Returns information about specified host type.
- def List(self, request, context): List avaliable host type... | Implement the Python class `HostTypeServiceServicer` described below.
Class description:
Set of methods to view possible host configurations.
Method signatures and docstrings:
- def Get(self, request, context): Returns information about specified host type.
- def List(self, request, context): List avaliable host type... | b906a014dd893e2697864e1e48e814a8d9fbc48c | <|skeleton|>
class HostTypeServiceServicer:
"""Set of methods to view possible host configurations."""
def Get(self, request, context):
"""Returns information about specified host type."""
<|body_0|>
def List(self, request, context):
"""List avaliable host types."""
<|body_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class HostTypeServiceServicer:
"""Set of methods to view possible host configurations."""
def Get(self, request, context):
"""Returns information about specified host type."""
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise No... | the_stack_v2_python_sparse | yandex/cloud/compute/v1/host_type_service_pb2_grpc.py | yandex-cloud/python-sdk | train | 63 |
6eb0e3c82c02edc76a91e724b1389aff8f84f610 | [
"title = request.data.get('title', '')\nplugin = request.data.get('plugin', '')\ncondition = unquote(request.data.get('condition', ''))\nplan = request.data.get('plan', 0)\nids = request.data.get('ids', '')\nisupdate = request.data.get('isupdate', '0')\nconn = mongo.MongoConn()\nif plugin:\n targets = []\n fo... | <|body_start_0|>
title = request.data.get('title', '')
plugin = request.data.get('plugin', '')
condition = unquote(request.data.get('condition', ''))
plan = request.data.get('plan', 0)
ids = request.data.get('ids', '')
isupdate = request.data.get('isupdate', '0')
... | 任务 | TaskView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TaskView:
"""任务"""
def post(self, request):
"""添加任务"""
<|body_0|>
def delete(self, request, id=None):
"""删除任务"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
title = request.data.get('title', '')
plugin = request.data.get('plugin', '')
... | stack_v2_sparse_classes_36k_train_002295 | 9,175 | no_license | [
{
"docstring": "添加任务",
"name": "post",
"signature": "def post(self, request)"
},
{
"docstring": "删除任务",
"name": "delete",
"signature": "def delete(self, request, id=None)"
}
] | 2 | null | Implement the Python class `TaskView` described below.
Class description:
任务
Method signatures and docstrings:
- def post(self, request): 添加任务
- def delete(self, request, id=None): 删除任务 | Implement the Python class `TaskView` described below.
Class description:
任务
Method signatures and docstrings:
- def post(self, request): 添加任务
- def delete(self, request, id=None): 删除任务
<|skeleton|>
class TaskView:
"""任务"""
def post(self, request):
"""添加任务"""
<|body_0|>
def delete(self,... | d6e025d7e9d9e3aecfd399c77f376130edd8a2df | <|skeleton|>
class TaskView:
"""任务"""
def post(self, request):
"""添加任务"""
<|body_0|>
def delete(self, request, id=None):
"""删除任务"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TaskView:
"""任务"""
def post(self, request):
"""添加任务"""
title = request.data.get('title', '')
plugin = request.data.get('plugin', '')
condition = unquote(request.data.get('condition', ''))
plan = request.data.get('plan', 0)
ids = request.data.get('ids', '')
... | the_stack_v2_python_sparse | soc_scan/views/task.py | sundw2015/841 | train | 4 |
711f0cc9120543dc7376a6280a2342f95e5c4de4 | [
"from .transformer import Transformer\nfrom .reactor import Reactor\nfrom .macro import Macro, Path\nfrom .unilink import UniLink\nmanager = self._get_manager()\nif isinstance(target, UniLink):\n target = target.get_linked()\ntarget_subpath = None\nif isinstance(target, Inchannel):\n target_subpath = target.s... | <|body_start_0|>
from .transformer import Transformer
from .reactor import Reactor
from .macro import Macro, Path
from .unilink import UniLink
manager = self._get_manager()
if isinstance(target, UniLink):
target = target.get_linked()
target_subpath = N... | Connects the output of workers (transformers and reactors) to cells outputpin.connect(cell) connects an outputpin to a cell outputpin.cell() returns or creates a cell that is connected to the outputpin | OutputPin | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OutputPin:
"""Connects the output of workers (transformers and reactors) to cells outputpin.connect(cell) connects an outputpin to a cell outputpin.cell() returns or creates a cell that is connected to the outputpin"""
def connect(self, target):
"""connects the pin to a target"""
... | stack_v2_sparse_classes_36k_train_002296 | 10,150 | permissive | [
{
"docstring": "connects the pin to a target",
"name": "connect",
"signature": "def connect(self, target)"
},
{
"docstring": "returns or creates a cell that is connected to the pin",
"name": "cell",
"signature": "def cell(self, celltype=None)"
},
{
"docstring": "Returns all cell/... | 3 | stack_v2_sparse_classes_30k_train_014456 | Implement the Python class `OutputPin` described below.
Class description:
Connects the output of workers (transformers and reactors) to cells outputpin.connect(cell) connects an outputpin to a cell outputpin.cell() returns or creates a cell that is connected to the outputpin
Method signatures and docstrings:
- def c... | Implement the Python class `OutputPin` described below.
Class description:
Connects the output of workers (transformers and reactors) to cells outputpin.connect(cell) connects an outputpin to a cell outputpin.cell() returns or creates a cell that is connected to the outputpin
Method signatures and docstrings:
- def c... | 04802149d738c790f0ba8fc9e5188ea2a45ddb7d | <|skeleton|>
class OutputPin:
"""Connects the output of workers (transformers and reactors) to cells outputpin.connect(cell) connects an outputpin to a cell outputpin.cell() returns or creates a cell that is connected to the outputpin"""
def connect(self, target):
"""connects the pin to a target"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class OutputPin:
"""Connects the output of workers (transformers and reactors) to cells outputpin.connect(cell) connects an outputpin to a cell outputpin.cell() returns or creates a cell that is connected to the outputpin"""
def connect(self, target):
"""connects the pin to a target"""
from .tr... | the_stack_v2_python_sparse | seamless/core/worker.py | sjdv1982/seamless | train | 33 |
39e879cfa2b015b70198567b635042493ba6683a | [
"super(OmpdFrameDecorator, self).__init__(fobj)\nself.addr_space = ompd.addr_space\nself.fobj = None\nif isinstance(fobj, gdb.Frame):\n self.fobj = fobj\nelif isinstance(fobj, FrameDecorator):\n self.fobj = fobj.inferior_frame()\nself.curr_task_handle = curr_task_handle",
"name = str(self.fobj.name())\nif s... | <|body_start_0|>
super(OmpdFrameDecorator, self).__init__(fobj)
self.addr_space = ompd.addr_space
self.fobj = None
if isinstance(fobj, gdb.Frame):
self.fobj = fobj
elif isinstance(fobj, FrameDecorator):
self.fobj = fobj.inferior_frame()
self.curr_t... | OmpdFrameDecorator | [
"MIT",
"Apache-2.0",
"LLVM-exception",
"NCSA",
"LicenseRef-scancode-arm-llvm-sga",
"LicenseRef-scancode-generic-cla"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OmpdFrameDecorator:
def __init__(self, fobj, curr_task_handle):
"""Initializes a FrameDecorator with the given GDB Frame object. The global OMPD address space defined in ompd.py is set as well."""
<|body_0|>
def function(self):
"""This appends the name of a frame tha... | stack_v2_sparse_classes_36k_train_002297 | 12,548 | permissive | [
{
"docstring": "Initializes a FrameDecorator with the given GDB Frame object. The global OMPD address space defined in ompd.py is set as well.",
"name": "__init__",
"signature": "def __init__(self, fobj, curr_task_handle)"
},
{
"docstring": "This appends the name of a frame that is printed with ... | 2 | stack_v2_sparse_classes_30k_train_010481 | Implement the Python class `OmpdFrameDecorator` described below.
Class description:
Implement the OmpdFrameDecorator class.
Method signatures and docstrings:
- def __init__(self, fobj, curr_task_handle): Initializes a FrameDecorator with the given GDB Frame object. The global OMPD address space defined in ompd.py is ... | Implement the Python class `OmpdFrameDecorator` described below.
Class description:
Implement the OmpdFrameDecorator class.
Method signatures and docstrings:
- def __init__(self, fobj, curr_task_handle): Initializes a FrameDecorator with the given GDB Frame object. The global OMPD address space defined in ompd.py is ... | 764287f1ad69469cc264bb094e8fcdcfdd0fcdfb | <|skeleton|>
class OmpdFrameDecorator:
def __init__(self, fobj, curr_task_handle):
"""Initializes a FrameDecorator with the given GDB Frame object. The global OMPD address space defined in ompd.py is set as well."""
<|body_0|>
def function(self):
"""This appends the name of a frame tha... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class OmpdFrameDecorator:
def __init__(self, fobj, curr_task_handle):
"""Initializes a FrameDecorator with the given GDB Frame object. The global OMPD address space defined in ompd.py is set as well."""
super(OmpdFrameDecorator, self).__init__(fobj)
self.addr_space = ompd.addr_space
... | the_stack_v2_python_sparse | openmp/libompd/gdb-plugin/ompd/frame_filter.py | smeenai/llvm-project | train | 0 | |
181ddc7bada60c0c8c06021fe5a33d210d56d929 | [
"self.curl = pycurl.Curl()\nfull_url = url if params is None else '%s?%s' % (url, urllib.parse.urlencode(params))\nself.curl.setopt(pycurl.URL, str(full_url))\nif bind is not None:\n self.curl.setopt(pycurl.INTERFACE, str(bind))\nself.curl.setopt(pycurl.FOLLOWLOCATION, allow_redirects)\nif headers is not None:\n... | <|body_start_0|>
self.curl = pycurl.Curl()
full_url = url if params is None else '%s?%s' % (url, urllib.parse.urlencode(params))
self.curl.setopt(pycurl.URL, str(full_url))
if bind is not None:
self.curl.setopt(pycurl.INTERFACE, str(bind))
self.curl.setopt(pycurl.FOLL... | PycURLRunner | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PycURLRunner:
def __init__(self, url, params, bind, timeout, allow_redirects, headers, verify_keys):
"""Constructor"""
<|body_0|>
def __call__(self, json, throw):
"""Fetch the URL"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.curl = pycurl.Cu... | stack_v2_sparse_classes_36k_train_002298 | 7,458 | permissive | [
{
"docstring": "Constructor",
"name": "__init__",
"signature": "def __init__(self, url, params, bind, timeout, allow_redirects, headers, verify_keys)"
},
{
"docstring": "Fetch the URL",
"name": "__call__",
"signature": "def __call__(self, json, throw)"
}
] | 2 | stack_v2_sparse_classes_30k_test_000684 | Implement the Python class `PycURLRunner` described below.
Class description:
Implement the PycURLRunner class.
Method signatures and docstrings:
- def __init__(self, url, params, bind, timeout, allow_redirects, headers, verify_keys): Constructor
- def __call__(self, json, throw): Fetch the URL | Implement the Python class `PycURLRunner` described below.
Class description:
Implement the PycURLRunner class.
Method signatures and docstrings:
- def __init__(self, url, params, bind, timeout, allow_redirects, headers, verify_keys): Constructor
- def __call__(self, json, throw): Fetch the URL
<|skeleton|>
class Py... | f6d04c0455e5be4d490df16ec1acb377f9025d9f | <|skeleton|>
class PycURLRunner:
def __init__(self, url, params, bind, timeout, allow_redirects, headers, verify_keys):
"""Constructor"""
<|body_0|>
def __call__(self, json, throw):
"""Fetch the URL"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PycURLRunner:
def __init__(self, url, params, bind, timeout, allow_redirects, headers, verify_keys):
"""Constructor"""
self.curl = pycurl.Curl()
full_url = url if params is None else '%s?%s' % (url, urllib.parse.urlencode(params))
self.curl.setopt(pycurl.URL, str(full_url))
... | the_stack_v2_python_sparse | python-pscheduler/pscheduler/pscheduler/psurl.py | perfsonar/pscheduler | train | 53 | |
8651b6bd2cbd75d9aba12ad4cab767cf2202e9af | [
"stakeholder_categories = set()\nfor stakeholder_category in self.stakeholdercategory_set.all():\n stakeholder_categories.add(stakeholder_category)\nreturn stakeholder_categories",
"implementations = set()\nfor uic in self.userincasestudy_set.all():\n for implementation in uic.implementation_set.all():\n ... | <|body_start_0|>
stakeholder_categories = set()
for stakeholder_category in self.stakeholdercategory_set.all():
stakeholder_categories.add(stakeholder_category)
return stakeholder_categories
<|end_body_0|>
<|body_start_1|>
implementations = set()
for uic in self.user... | CaseStudy | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CaseStudy:
def stakeholder_categories(self):
"""look for all stakeholder categories created by the users of the casestudy"""
<|body_0|>
def implementations(self):
"""look for all stakeholder categories created by the users of the casestudy"""
<|body_1|>
<|en... | stack_v2_sparse_classes_36k_train_002299 | 3,398 | no_license | [
{
"docstring": "look for all stakeholder categories created by the users of the casestudy",
"name": "stakeholder_categories",
"signature": "def stakeholder_categories(self)"
},
{
"docstring": "look for all stakeholder categories created by the users of the casestudy",
"name": "implementation... | 2 | null | Implement the Python class `CaseStudy` described below.
Class description:
Implement the CaseStudy class.
Method signatures and docstrings:
- def stakeholder_categories(self): look for all stakeholder categories created by the users of the casestudy
- def implementations(self): look for all stakeholder categories cre... | Implement the Python class `CaseStudy` described below.
Class description:
Implement the CaseStudy class.
Method signatures and docstrings:
- def stakeholder_categories(self): look for all stakeholder categories created by the users of the casestudy
- def implementations(self): look for all stakeholder categories cre... | a5ba34f085f0d5af5ea3ded24706ea54ab39e7cb | <|skeleton|>
class CaseStudy:
def stakeholder_categories(self):
"""look for all stakeholder categories created by the users of the casestudy"""
<|body_0|>
def implementations(self):
"""look for all stakeholder categories created by the users of the casestudy"""
<|body_1|>
<|en... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CaseStudy:
def stakeholder_categories(self):
"""look for all stakeholder categories created by the users of the casestudy"""
stakeholder_categories = set()
for stakeholder_category in self.stakeholdercategory_set.all():
stakeholder_categories.add(stakeholder_category)
... | the_stack_v2_python_sparse | repair/apps/login/models/users.py | MaxBo/REPAiR-Web | train | 9 |
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