body_hash stringlengths 64 64 | body stringlengths 23 109k | docstring stringlengths 1 57k | path stringlengths 4 198 | name stringlengths 1 115 | repository_name stringlengths 7 111 | repository_stars float64 0 191k | lang stringclasses 1
value | body_without_docstring stringlengths 14 108k | unified stringlengths 45 133k |
|---|---|---|---|---|---|---|---|---|---|
c51bf5caf154655e69fbb8b830c3e6f3517a9565ab315e7e2bf1a94388bf4dca | def alignment_error_rate(self, reference, possible=None):
'\n Return the Alignment Error Rate (AER) of an aligned sentence\n with respect to a "gold standard" reference ``AlignedSent``.\n\n Return an error rate between 0.0 (perfect alignment) and 1.0 (no\n alignment).\n\n >>> ... | Return the Alignment Error Rate (AER) of an aligned sentence
with respect to a "gold standard" reference ``AlignedSent``.
Return an error rate between 0.0 (perfect alignment) and 1.0 (no
alignment).
>>> from nltk.align import AlignedSent
>>> s = AlignedSent(["the", "cat"], ["le", "chat"], [(0, 0), (1, 1)])
... | venv/lib/python2.7/site-packages/nltk/align/api.py | alignment_error_rate | sravani-m/Web-Application-Security-Framework | 3 | python | def alignment_error_rate(self, reference, possible=None):
'\n Return the Alignment Error Rate (AER) of an aligned sentence\n with respect to a "gold standard" reference ``AlignedSent``.\n\n Return an error rate between 0.0 (perfect alignment) and 1.0 (no\n alignment).\n\n >>> ... | def alignment_error_rate(self, reference, possible=None):
'\n Return the Alignment Error Rate (AER) of an aligned sentence\n with respect to a "gold standard" reference ``AlignedSent``.\n\n Return an error rate between 0.0 (perfect alignment) and 1.0 (no\n alignment).\n\n >>> ... |
8b5f8336f82d07453244133a22c7ba33da54eb56d9dfe5326c8fc7d8cbbe192d | def __getitem__(self, key):
'\n Look up the alignments that map from a given index or slice.\n '
if (not self._index):
self._build_index()
return self._index.__getitem__(key) | Look up the alignments that map from a given index or slice. | venv/lib/python2.7/site-packages/nltk/align/api.py | __getitem__ | sravani-m/Web-Application-Security-Framework | 3 | python | def __getitem__(self, key):
'\n \n '
if (not self._index):
self._build_index()
return self._index.__getitem__(key) | def __getitem__(self, key):
'\n \n '
if (not self._index):
self._build_index()
return self._index.__getitem__(key)<|docstring|>Look up the alignments that map from a given index or slice.<|endoftext|> |
f67a0c6af96f10b58d8100316589b74c5cb49e23d2bce8c58cb96618d1b325d8 | def invert(self):
'\n Return an Alignment object, being the inverted mapping.\n '
return Alignment((((p[1], p[0]) + p[2:]) for p in self)) | Return an Alignment object, being the inverted mapping. | venv/lib/python2.7/site-packages/nltk/align/api.py | invert | sravani-m/Web-Application-Security-Framework | 3 | python | def invert(self):
'\n \n '
return Alignment((((p[1], p[0]) + p[2:]) for p in self)) | def invert(self):
'\n \n '
return Alignment((((p[1], p[0]) + p[2:]) for p in self))<|docstring|>Return an Alignment object, being the inverted mapping.<|endoftext|> |
93eb14df25bd851b52321d138998768bf6b5be375027687fdeb425de2ff744bc | def range(self, positions=None):
'\n Work out the range of the mapping from the given positions.\n If no positions are specified, compute the range of the entire mapping.\n '
image = set()
if (not self._index):
self._build_index()
if (not positions):
positions = list... | Work out the range of the mapping from the given positions.
If no positions are specified, compute the range of the entire mapping. | venv/lib/python2.7/site-packages/nltk/align/api.py | range | sravani-m/Web-Application-Security-Framework | 3 | python | def range(self, positions=None):
'\n Work out the range of the mapping from the given positions.\n If no positions are specified, compute the range of the entire mapping.\n '
image = set()
if (not self._index):
self._build_index()
if (not positions):
positions = list... | def range(self, positions=None):
'\n Work out the range of the mapping from the given positions.\n If no positions are specified, compute the range of the entire mapping.\n '
image = set()
if (not self._index):
self._build_index()
if (not positions):
positions = list... |
a834a62a6b7e2fb2a50d659c8a4c172f9aea9b6894ab93ac8f38a415e84be66e | def __repr__(self):
'\n Produce a Giza-formatted string representing the alignment.\n '
return ('Alignment(%r)' % sorted(self)) | Produce a Giza-formatted string representing the alignment. | venv/lib/python2.7/site-packages/nltk/align/api.py | __repr__ | sravani-m/Web-Application-Security-Framework | 3 | python | def __repr__(self):
'\n \n '
return ('Alignment(%r)' % sorted(self)) | def __repr__(self):
'\n \n '
return ('Alignment(%r)' % sorted(self))<|docstring|>Produce a Giza-formatted string representing the alignment.<|endoftext|> |
ff2f5fd9d602325dd81e5592657a9d0d0954de2987a24d38ff1ab5d0d9588cb9 | def __str__(self):
'\n Produce a Giza-formatted string representing the alignment.\n '
return ' '.join((('%d-%d' % p[:2]) for p in sorted(self))) | Produce a Giza-formatted string representing the alignment. | venv/lib/python2.7/site-packages/nltk/align/api.py | __str__ | sravani-m/Web-Application-Security-Framework | 3 | python | def __str__(self):
'\n \n '
return ' '.join((('%d-%d' % p[:2]) for p in sorted(self))) | def __str__(self):
'\n \n '
return ' '.join((('%d-%d' % p[:2]) for p in sorted(self)))<|docstring|>Produce a Giza-formatted string representing the alignment.<|endoftext|> |
487eeb5a9ad8701976ebe2bc1b1f48920e666d7a446ce50cd1a656797252b7d0 | def _build_index(self):
'\n Build a list self._index such that self._index[i] is a list\n of the alignments originating from word i.\n '
self._index = [[] for _ in range((self._len + 1))]
for p in self:
self._index[p[0]].append(p) | Build a list self._index such that self._index[i] is a list
of the alignments originating from word i. | venv/lib/python2.7/site-packages/nltk/align/api.py | _build_index | sravani-m/Web-Application-Security-Framework | 3 | python | def _build_index(self):
'\n Build a list self._index such that self._index[i] is a list\n of the alignments originating from word i.\n '
self._index = [[] for _ in range((self._len + 1))]
for p in self:
self._index[p[0]].append(p) | def _build_index(self):
'\n Build a list self._index such that self._index[i] is a list\n of the alignments originating from word i.\n '
self._index = [[] for _ in range((self._len + 1))]
for p in self:
self._index[p[0]].append(p)<|docstring|>Build a list self._index such that s... |
c9777462c471a1c3ce3b7a8cfc324d091295959991be654a17569ceb285215a0 | def _backup_and_load_cache(self):
'Useful for performing evaluation on the slow weights (which typically generalize better)\n '
for group in self.optimizer.param_groups:
for p in group['params']:
param_state = self.state[p]
param_state['backup_params'] = torch.zeros_like(p... | Useful for performing evaluation on the slow weights (which typically generalize better) | pytorch_lightning_spells/optimizers.py | _backup_and_load_cache | veritable-tech/pytorch-lightning-spells | 5 | python | def _backup_and_load_cache(self):
'\n '
for group in self.optimizer.param_groups:
for p in group['params']:
param_state = self.state[p]
param_state['backup_params'] = torch.zeros_like(p.data)
param_state['backup_params'].copy_(p.data)
p.data.copy_(p... | def _backup_and_load_cache(self):
'\n '
for group in self.optimizer.param_groups:
for p in group['params']:
param_state = self.state[p]
param_state['backup_params'] = torch.zeros_like(p.data)
param_state['backup_params'].copy_(p.data)
p.data.copy_(p... |
939264af49ef2ebd0a8e0148387e74686cfb21787ea33c150a74bc2356dcb449 | def step(self, closure=None):
'Performs a single Lookahead optimization step.\n '
loss = self.optimizer.step(closure)
self.step_counter += 1
if (self.step_counter >= self.k):
self.step_counter = 0
for group in self.optimizer.param_groups:
for p in group['params']:
... | Performs a single Lookahead optimization step. | pytorch_lightning_spells/optimizers.py | step | veritable-tech/pytorch-lightning-spells | 5 | python | def step(self, closure=None):
'\n '
loss = self.optimizer.step(closure)
self.step_counter += 1
if (self.step_counter >= self.k):
self.step_counter = 0
for group in self.optimizer.param_groups:
for p in group['params']:
param_state = self.state[p]
... | def step(self, closure=None):
'\n '
loss = self.optimizer.step(closure)
self.step_counter += 1
if (self.step_counter >= self.k):
self.step_counter = 0
for group in self.optimizer.param_groups:
for p in group['params']:
param_state = self.state[p]
... |
eb8e19c310324fa3a5ab0c5086312b4981131391e769fd56b3aca810ec9cf9d1 | @click.command()
def start():
'\n Add filtered datasets.\n '
create_client().consume(callback, consume_routing_key) | Add filtered datasets. | workers/extract/dataset_filter.py | start | open-contracting/pelican-backend | 1 | python | @click.command()
def start():
'\n \n '
create_client().consume(callback, consume_routing_key) | @click.command()
def start():
'\n \n '
create_client().consume(callback, consume_routing_key)<|docstring|>Add filtered datasets.<|endoftext|> |
784e697af8eba437fabd2b81e4707a845a6d0e95c4b284937744ea4b9c413906 | def custom_simclr_contrastive_loss(proj_feat1, proj_feat2, temperature=0.5, seed=SEED):
'\n custom_simclr_contrastive_loss(proj_feat1, proj_feat2)\n Returns contrastive loss, given sets of projected features, with positive\n pairs matched along the batch dimension.\n Required args:\n - proj_feat1 (2D torch Ten... | custom_simclr_contrastive_loss(proj_feat1, proj_feat2)
Returns contrastive loss, given sets of projected features, with positive
pairs matched along the batch dimension.
Required args:
- proj_feat1 (2D torch Tensor): first set of projected features
(batch_size x feat_size)
- proj_feat2 (2D torch Tensor): second set... | tutorials/W3D1_UnsupervisedAndSelfSupervisedLearning/solutions/W3D1_Tutorial1_Solution_8dde8bad.py | custom_simclr_contrastive_loss | haltakov/course-content-dl | 1 | python | def custom_simclr_contrastive_loss(proj_feat1, proj_feat2, temperature=0.5, seed=SEED):
'\n custom_simclr_contrastive_loss(proj_feat1, proj_feat2)\n Returns contrastive loss, given sets of projected features, with positive\n pairs matched along the batch dimension.\n Required args:\n - proj_feat1 (2D torch Ten... | def custom_simclr_contrastive_loss(proj_feat1, proj_feat2, temperature=0.5, seed=SEED):
'\n custom_simclr_contrastive_loss(proj_feat1, proj_feat2)\n Returns contrastive loss, given sets of projected features, with positive\n pairs matched along the batch dimension.\n Required args:\n - proj_feat1 (2D torch Ten... |
39d7bbf4be3e3e81c145c033c47dfbf71c48a7a5085fcbec40da38240bc4c024 | @classmethod
def _validate_sent_datetime(cls, item):
'Validate that sent_datetime of model is less than current time.\n\n Args:\n item: datastore_services.Model. SentEmailModel to validate.\n '
current_datetime = datetime.datetime.utcnow()
if (item.sent_datetime > current_datetime):... | Validate that sent_datetime of model is less than current time.
Args:
item: datastore_services.Model. SentEmailModel to validate. | core/domain/email_validators.py | _validate_sent_datetime | OBITORASU/oppia | 2 | python | @classmethod
def _validate_sent_datetime(cls, item):
'Validate that sent_datetime of model is less than current time.\n\n Args:\n item: datastore_services.Model. SentEmailModel to validate.\n '
current_datetime = datetime.datetime.utcnow()
if (item.sent_datetime > current_datetime):... | @classmethod
def _validate_sent_datetime(cls, item):
'Validate that sent_datetime of model is less than current time.\n\n Args:\n item: datastore_services.Model. SentEmailModel to validate.\n '
current_datetime = datetime.datetime.utcnow()
if (item.sent_datetime > current_datetime):... |
d4a7a605d37058766c8e23204b8bd479409ff099525729d1951ba728574c258c | @classmethod
def _validate_recipient_email(cls, item, field_name_to_external_model_references):
"Validate that recipient email corresponds to email of user obtained\n by using the recipient_id.\n\n Args:\n item: datastore_services.Model. SentEmailModel to validate.\n field_name_t... | Validate that recipient email corresponds to email of user obtained
by using the recipient_id.
Args:
item: datastore_services.Model. SentEmailModel to validate.
field_name_to_external_model_references:
dict(str, (list(base_model_validators.ExternalModelReference))).
A dict keyed by field name. ... | core/domain/email_validators.py | _validate_recipient_email | OBITORASU/oppia | 2 | python | @classmethod
def _validate_recipient_email(cls, item, field_name_to_external_model_references):
"Validate that recipient email corresponds to email of user obtained\n by using the recipient_id.\n\n Args:\n item: datastore_services.Model. SentEmailModel to validate.\n field_name_t... | @classmethod
def _validate_recipient_email(cls, item, field_name_to_external_model_references):
"Validate that recipient email corresponds to email of user obtained\n by using the recipient_id.\n\n Args:\n item: datastore_services.Model. SentEmailModel to validate.\n field_name_t... |
819c3abcf86ba213eccc5dc9b79c43c3ae5f2ab30468a704dd2d662a7e72faca | @classmethod
def _validate_sent_datetime(cls, item):
'Validate that sent_datetime of model is less than current time.\n\n Args:\n item: datastore_services.Model. BulkEmailModel to validate.\n '
current_datetime = datetime.datetime.utcnow()
if (item.sent_datetime > current_datetime):... | Validate that sent_datetime of model is less than current time.
Args:
item: datastore_services.Model. BulkEmailModel to validate. | core/domain/email_validators.py | _validate_sent_datetime | OBITORASU/oppia | 2 | python | @classmethod
def _validate_sent_datetime(cls, item):
'Validate that sent_datetime of model is less than current time.\n\n Args:\n item: datastore_services.Model. BulkEmailModel to validate.\n '
current_datetime = datetime.datetime.utcnow()
if (item.sent_datetime > current_datetime):... | @classmethod
def _validate_sent_datetime(cls, item):
'Validate that sent_datetime of model is less than current time.\n\n Args:\n item: datastore_services.Model. BulkEmailModel to validate.\n '
current_datetime = datetime.datetime.utcnow()
if (item.sent_datetime > current_datetime):... |
92880c7feb47f97d25fab83e99c4cd562fe67d5c3dc239773c94be545b1912c0 | @classmethod
def _validate_sender_email(cls, item, field_name_to_external_model_references):
"Validate that sender email corresponds to email of user obtained\n by using the sender_id.\n\n Args:\n item: datastore_services.Model. BulkEmailModel to validate.\n field_name_to_externa... | Validate that sender email corresponds to email of user obtained
by using the sender_id.
Args:
item: datastore_services.Model. BulkEmailModel to validate.
field_name_to_external_model_references:
dict(str, (list(base_model_validators.ExternalModelReference))).
A dict keyed by field name. The fi... | core/domain/email_validators.py | _validate_sender_email | OBITORASU/oppia | 2 | python | @classmethod
def _validate_sender_email(cls, item, field_name_to_external_model_references):
"Validate that sender email corresponds to email of user obtained\n by using the sender_id.\n\n Args:\n item: datastore_services.Model. BulkEmailModel to validate.\n field_name_to_externa... | @classmethod
def _validate_sender_email(cls, item, field_name_to_external_model_references):
"Validate that sender email corresponds to email of user obtained\n by using the sender_id.\n\n Args:\n item: datastore_services.Model. BulkEmailModel to validate.\n field_name_to_externa... |
f6776da2a019e7491fd0341192fb89fffce0173c0b4c73f5fd3d0782f3c1ab60 | @classmethod
def _validate_reply_to_id_length(cls, item):
'Validate that reply_to_id length is less than or equal to\n REPLY_TO_ID_LENGTH.\n\n Args:\n item: datastore_services.Model. GeneralFeedbackEmailReplyToIdModel\n to validate.\n '
if (len(item.reply_to_id) > ... | Validate that reply_to_id length is less than or equal to
REPLY_TO_ID_LENGTH.
Args:
item: datastore_services.Model. GeneralFeedbackEmailReplyToIdModel
to validate. | core/domain/email_validators.py | _validate_reply_to_id_length | OBITORASU/oppia | 2 | python | @classmethod
def _validate_reply_to_id_length(cls, item):
'Validate that reply_to_id length is less than or equal to\n REPLY_TO_ID_LENGTH.\n\n Args:\n item: datastore_services.Model. GeneralFeedbackEmailReplyToIdModel\n to validate.\n '
if (len(item.reply_to_id) > ... | @classmethod
def _validate_reply_to_id_length(cls, item):
'Validate that reply_to_id length is less than or equal to\n REPLY_TO_ID_LENGTH.\n\n Args:\n item: datastore_services.Model. GeneralFeedbackEmailReplyToIdModel\n to validate.\n '
if (len(item.reply_to_id) > ... |
053db00e697f92b2c69ab86dd4994446ba7d5ff78702fe1859ff28c551c81d51 | def __init__(self, params: List[Tensor], max_trust_radius: float=1000, initial_trust_radius: float=0.05, eta: float=0.15, gtol: float=1e-05, **kwargs) -> None:
' Trust Region Newton Conjugate Gradient\n\n Uses the Conjugate Gradient Algorithm to find the solution of the\n trust region sub-prob... | Trust Region Newton Conjugate Gradient
Uses the Conjugate Gradient Algorithm to find the solution of the
trust region sub-problem
For more details see chapter 7.2 of
"Numerical Optimization, Nocedal and Wright"
Arguments:
params (iterable): A list or iterable of tensors that will be
optimized
max_tru... | torchtrustncg/trust_region_newton_cg.py | __init__ | vchoutas/torch-trust-ncg | 14 | python | def __init__(self, params: List[Tensor], max_trust_radius: float=1000, initial_trust_radius: float=0.05, eta: float=0.15, gtol: float=1e-05, **kwargs) -> None:
' Trust Region Newton Conjugate Gradient\n\n Uses the Conjugate Gradient Algorithm to find the solution of the\n trust region sub-prob... | def __init__(self, params: List[Tensor], max_trust_radius: float=1000, initial_trust_radius: float=0.05, eta: float=0.15, gtol: float=1e-05, **kwargs) -> None:
' Trust Region Newton Conjugate Gradient\n\n Uses the Conjugate Gradient Algorithm to find the solution of the\n trust region sub-prob... |
e63a400e6a84a3d92af43a9cf9ac7ed8c5292154ac87152900ccd8d7933fed08 | def _gather_flat_grad(self) -> Tensor:
' Concatenates all gradients into a single gradient vector\n '
views = []
for p in self._params:
if (p.grad is None):
view = p.data.new(p.data.numel()).zero_()
elif p.grad.data.is_sparse:
view = p.grad.to_dense().view((- 1... | Concatenates all gradients into a single gradient vector | torchtrustncg/trust_region_newton_cg.py | _gather_flat_grad | vchoutas/torch-trust-ncg | 14 | python | def _gather_flat_grad(self) -> Tensor:
' \n '
views = []
for p in self._params:
if (p.grad is None):
view = p.data.new(p.data.numel()).zero_()
elif p.grad.data.is_sparse:
view = p.grad.to_dense().view((- 1))
else:
view = p.grad.view((- 1))
... | def _gather_flat_grad(self) -> Tensor:
' \n '
views = []
for p in self._params:
if (p.grad is None):
view = p.data.new(p.data.numel()).zero_()
elif p.grad.data.is_sparse:
view = p.grad.to_dense().view((- 1))
else:
view = p.grad.view((- 1))
... |
6c5dd050e60598777b1053a2f93107dfa2086d537bb18f5c42488a0532ab4580 | @torch.no_grad()
def _improvement_ratio(self, p, start_loss, gradient, closure):
' Calculates the ratio of the actual to the expected improvement\n\n Arguments:\n p (torch.tensor): The update vector for the parameters\n start_loss (torch.tensor): The value of the loss functi... | Calculates the ratio of the actual to the expected improvement
Arguments:
p (torch.tensor): The update vector for the parameters
start_loss (torch.tensor): The value of the loss function
before applying the optimization step
gradient (torch.tensor): The flattened gradient vector of the
para... | torchtrustncg/trust_region_newton_cg.py | _improvement_ratio | vchoutas/torch-trust-ncg | 14 | python | @torch.no_grad()
def _improvement_ratio(self, p, start_loss, gradient, closure):
' Calculates the ratio of the actual to the expected improvement\n\n Arguments:\n p (torch.tensor): The update vector for the parameters\n start_loss (torch.tensor): The value of the loss functi... | @torch.no_grad()
def _improvement_ratio(self, p, start_loss, gradient, closure):
' Calculates the ratio of the actual to the expected improvement\n\n Arguments:\n p (torch.tensor): The update vector for the parameters\n start_loss (torch.tensor): The value of the loss functi... |
1bfb82b9598199891f9399a1d6dbd55f7d00cf0ac735ed1d61d2b3ca9797cffb | @torch.no_grad()
def _quad_model(self, p: Tensor, loss: float, gradient: Tensor, hess_vp: Tensor) -> float:
' Returns the value of the local quadratic approximation\n '
return ((loss + torch.flatten((gradient * p)).sum(dim=(- 1))) + (0.5 * torch.flatten((hess_vp * p)).sum(dim=(- 1)))) | Returns the value of the local quadratic approximation | torchtrustncg/trust_region_newton_cg.py | _quad_model | vchoutas/torch-trust-ncg | 14 | python | @torch.no_grad()
def _quad_model(self, p: Tensor, loss: float, gradient: Tensor, hess_vp: Tensor) -> float:
' \n '
return ((loss + torch.flatten((gradient * p)).sum(dim=(- 1))) + (0.5 * torch.flatten((hess_vp * p)).sum(dim=(- 1)))) | @torch.no_grad()
def _quad_model(self, p: Tensor, loss: float, gradient: Tensor, hess_vp: Tensor) -> float:
' \n '
return ((loss + torch.flatten((gradient * p)).sum(dim=(- 1))) + (0.5 * torch.flatten((hess_vp * p)).sum(dim=(- 1))))<|docstring|>Returns the value of the local quadratic approximation<|endof... |
af437de8906c547bf65d26f7ae13ffe8981b31f4328ea9adb87bdbd152e98920 | @torch.no_grad()
def calc_boundaries(self, iterate: Tensor, direction: Tensor, trust_radius: float) -> Tuple[(Tensor, Tensor)]:
' Calculates the offset to the boundaries of the trust region\n '
a = torch.sum((direction ** 2), dim=(- 1))
b = (2 * torch.sum((direction * iterate), dim=(- 1)))
c = (t... | Calculates the offset to the boundaries of the trust region | torchtrustncg/trust_region_newton_cg.py | calc_boundaries | vchoutas/torch-trust-ncg | 14 | python | @torch.no_grad()
def calc_boundaries(self, iterate: Tensor, direction: Tensor, trust_radius: float) -> Tuple[(Tensor, Tensor)]:
' \n '
a = torch.sum((direction ** 2), dim=(- 1))
b = (2 * torch.sum((direction * iterate), dim=(- 1)))
c = (torch.sum((iterate ** 2), dim=(- 1)) - (trust_radius ** 2))
... | @torch.no_grad()
def calc_boundaries(self, iterate: Tensor, direction: Tensor, trust_radius: float) -> Tuple[(Tensor, Tensor)]:
' \n '
a = torch.sum((direction ** 2), dim=(- 1))
b = (2 * torch.sum((direction * iterate), dim=(- 1)))
c = (torch.sum((iterate ** 2), dim=(- 1)) - (trust_radius ** 2))
... |
4b5766d811ceceed7aec88418f86bb09fbbfe6d2f47437a75ce3f314e5e387c3 | @torch.no_grad()
def _solve_trust_reg_subproblem(self, loss: float, flat_grad: Tensor, trust_radius: float) -> Tuple[(Tensor, bool)]:
' Solves the quadratic subproblem in the trust region\n '
iterate = torch.zeros_like(flat_grad, requires_grad=False)
residual = flat_grad.detach()
direction = (- r... | Solves the quadratic subproblem in the trust region | torchtrustncg/trust_region_newton_cg.py | _solve_trust_reg_subproblem | vchoutas/torch-trust-ncg | 14 | python | @torch.no_grad()
def _solve_trust_reg_subproblem(self, loss: float, flat_grad: Tensor, trust_radius: float) -> Tuple[(Tensor, bool)]:
' \n '
iterate = torch.zeros_like(flat_grad, requires_grad=False)
residual = flat_grad.detach()
direction = (- residual)
jac_mag = torch.norm(flat_grad).item()... | @torch.no_grad()
def _solve_trust_reg_subproblem(self, loss: float, flat_grad: Tensor, trust_radius: float) -> Tuple[(Tensor, bool)]:
' \n '
iterate = torch.zeros_like(flat_grad, requires_grad=False)
residual = flat_grad.detach()
direction = (- residual)
jac_mag = torch.norm(flat_grad).item()... |
7f229ace083ef439d236e0e7c4f6ca2734fe834a095fde6e5d2f077df9aad0c1 | def __init__(self, input_size, projection_layer_size=150, kernel_heights=(3, 5), feature_map_increase=75, cnn_depth=3, output_projection_layer_size=300, activation=nn.LeakyReLU, dp=0, normalize_output=True):
'\n :param input_size: Time step size.\n :param projection_layer_size: Size of projection_laye... | :param input_size: Time step size.
:param projection_layer_size: Size of projection_layer.
:param kernel_heights: Kernel height of the filters.
:param feature_map_increase: Number of filters of each convolutional layer.
:param cnn_depth: Number of convolutional layers per kernel height.
:param output_projection_layer_s... | pytorch_wrapper/modules/sequence_dense_cnn.py | __init__ | christosvar/pytorch-wrapper | 111 | python | def __init__(self, input_size, projection_layer_size=150, kernel_heights=(3, 5), feature_map_increase=75, cnn_depth=3, output_projection_layer_size=300, activation=nn.LeakyReLU, dp=0, normalize_output=True):
'\n :param input_size: Time step size.\n :param projection_layer_size: Size of projection_laye... | def __init__(self, input_size, projection_layer_size=150, kernel_heights=(3, 5), feature_map_increase=75, cnn_depth=3, output_projection_layer_size=300, activation=nn.LeakyReLU, dp=0, normalize_output=True):
'\n :param input_size: Time step size.\n :param projection_layer_size: Size of projection_laye... |
f349b46b1c7c41313e2ed3803a63489b5ebf60f516164f73ae281e33c2b0477d | def forward(self, batch_sequences):
'\n :param batch_sequences: 3D Tensor (batch_size, sequence_length, time_step_size).\n :return: 3D Tensor (batch_size, sequence_length, output_projection_layer_size).\n '
batch_sequences = batch_sequences.transpose(1, 2)
output = [batch_sequences]
... | :param batch_sequences: 3D Tensor (batch_size, sequence_length, time_step_size).
:return: 3D Tensor (batch_size, sequence_length, output_projection_layer_size). | pytorch_wrapper/modules/sequence_dense_cnn.py | forward | christosvar/pytorch-wrapper | 111 | python | def forward(self, batch_sequences):
'\n :param batch_sequences: 3D Tensor (batch_size, sequence_length, time_step_size).\n :return: 3D Tensor (batch_size, sequence_length, output_projection_layer_size).\n '
batch_sequences = batch_sequences.transpose(1, 2)
output = [batch_sequences]
... | def forward(self, batch_sequences):
'\n :param batch_sequences: 3D Tensor (batch_size, sequence_length, time_step_size).\n :return: 3D Tensor (batch_size, sequence_length, output_projection_layer_size).\n '
batch_sequences = batch_sequences.transpose(1, 2)
output = [batch_sequences]
... |
28baf8fd535bb242ab93100856dee5c0d2790c7a9ec5621c2d531de47339ba3d | def absorb(self, victim):
"\n Absorb one tree into another - note that this can't exceed the maximum size of the\n species.\n "
self.size = min((self.size + victim.size), self.species.max_size) | Absorb one tree into another - note that this can't exceed the maximum size of the
species. | forest/tree.py | absorb | DaveTCode/ProceduralForest | 3 | python | def absorb(self, victim):
"\n Absorb one tree into another - note that this can't exceed the maximum size of the\n species.\n "
self.size = min((self.size + victim.size), self.species.max_size) | def absorb(self, victim):
"\n Absorb one tree into another - note that this can't exceed the maximum size of the\n species.\n "
self.size = min((self.size + victim.size), self.species.max_size)<|docstring|>Absorb one tree into another - note that this can't exceed the maximum size o... |
5395cd0377aa86aadeb1c5f60fc59a27f4bb808b80871f93b29e892295539113 | def grow(self):
'\n Increase the size of the tree by the amount specified in the species.\n '
self.size = min((self.size + self.species.growth_rate), self.species.max_size) | Increase the size of the tree by the amount specified in the species. | forest/tree.py | grow | DaveTCode/ProceduralForest | 3 | python | def grow(self):
'\n \n '
self.size = min((self.size + self.species.growth_rate), self.species.max_size) | def grow(self):
'\n \n '
self.size = min((self.size + self.species.growth_rate), self.species.max_size)<|docstring|>Increase the size of the tree by the amount specified in the species.<|endoftext|> |
e3df56faceb3bfaa273d11ab39e70b0a497dbe6ff7f4bf7354a6f158213e8d5b | def is_mature(self):
'\n Some actions only occur when a tree is fully mature. This checks for that by comparing\n the size to the species maximum size.\n '
return (self.size == self.species.max_size) | Some actions only occur when a tree is fully mature. This checks for that by comparing
the size to the species maximum size. | forest/tree.py | is_mature | DaveTCode/ProceduralForest | 3 | python | def is_mature(self):
'\n Some actions only occur when a tree is fully mature. This checks for that by comparing\n the size to the species maximum size.\n '
return (self.size == self.species.max_size) | def is_mature(self):
'\n Some actions only occur when a tree is fully mature. This checks for that by comparing\n the size to the species maximum size.\n '
return (self.size == self.species.max_size)<|docstring|>Some actions only occur when a tree is fully mature. This checks for th... |
b3b0704d8d580d7ca3e0c08e8e3eb7e463b8ed0323d07864353ce616bbc27d66 | def overlapping(self, tree):
'\n Check whether this tree overlaps another tree - assumes circular tree.\n '
d = math.sqrt((math.pow((tree.x - self.x), 2) + math.pow((tree.y - self.y), 2)))
return (d <= (tree.size + self.size)) | Check whether this tree overlaps another tree - assumes circular tree. | forest/tree.py | overlapping | DaveTCode/ProceduralForest | 3 | python | def overlapping(self, tree):
'\n \n '
d = math.sqrt((math.pow((tree.x - self.x), 2) + math.pow((tree.y - self.y), 2)))
return (d <= (tree.size + self.size)) | def overlapping(self, tree):
'\n \n '
d = math.sqrt((math.pow((tree.x - self.x), 2) + math.pow((tree.y - self.y), 2)))
return (d <= (tree.size + self.size))<|docstring|>Check whether this tree overlaps another tree - assumes circular tree.<|endoftext|> |
a70cb22e9eb643cd7c792dbd64ba4b4a5519ed7f8001823b51a574fcdb8fbb3e | def contains_point(self, x, y):
'\n Check whether a point is within this tree.\n '
d = math.sqrt((math.pow((self.x - x), 2) + math.pow((self.y - y), 2)))
return (d <= self.size) | Check whether a point is within this tree. | forest/tree.py | contains_point | DaveTCode/ProceduralForest | 3 | python | def contains_point(self, x, y):
'\n \n '
d = math.sqrt((math.pow((self.x - x), 2) + math.pow((self.y - y), 2)))
return (d <= self.size) | def contains_point(self, x, y):
'\n \n '
d = math.sqrt((math.pow((self.x - x), 2) + math.pow((self.y - y), 2)))
return (d <= self.size)<|docstring|>Check whether a point is within this tree.<|endoftext|> |
10fd4af263e65544d94552ea64635c75ae4944ecefcdc7d4388535c244052ce9 | @pytest.mark.parametrize('config, expected', [pytest.param({'_attr_': 'list', '_eval_': 'partial', '_args_': [[1]]}, (lambda : [1]))])
def test_parser_default_parser(config, expected):
'Test default parse.'
parser = fromconfig.parser.DefaultParser()
parsed = parser(config)
if callable(expected):
... | Test default parse. | tests/unit/parser/test_parser_default.py | test_parser_default_parser | Mbompr/fromconfig | 19 | python | @pytest.mark.parametrize('config, expected', [pytest.param({'_attr_': 'list', '_eval_': 'partial', '_args_': [[1]]}, (lambda : [1]))])
def test_parser_default_parser(config, expected):
parser = fromconfig.parser.DefaultParser()
parsed = parser(config)
if callable(expected):
assert (fromconfig.f... | @pytest.mark.parametrize('config, expected', [pytest.param({'_attr_': 'list', '_eval_': 'partial', '_args_': [[1]]}, (lambda : [1]))])
def test_parser_default_parser(config, expected):
parser = fromconfig.parser.DefaultParser()
parsed = parser(config)
if callable(expected):
assert (fromconfig.f... |
ec63490f0642c392cf7cb8e99f26132580f0ad479cca70fbbf895617e6e92f82 | def __init__(__self__, *, dns_prefix: pulumi.Input[str], name: pulumi.Input[str], count: Optional[pulumi.Input[int]]=None, vm_size: Optional[pulumi.Input[Union[(str, 'ContainerServiceVMSizeTypes')]]]=None):
"\n Profile for container service agent pool\n :param pulumi.Input[str] dns_prefix: DNS prefix ... | Profile for container service agent pool
:param pulumi.Input[str] dns_prefix: DNS prefix to be used to create FQDN for this agent pool
:param pulumi.Input[str] name: Unique name of the agent pool profile within the context of the subscription and resource group
:param pulumi.Input[int] count: No. of agents (VMs) that w... | sdk/python/pulumi_azure_native/containerservice/v20151101preview/_inputs.py | __init__ | pulumi-bot/pulumi-azure-native | 31 | python | def __init__(__self__, *, dns_prefix: pulumi.Input[str], name: pulumi.Input[str], count: Optional[pulumi.Input[int]]=None, vm_size: Optional[pulumi.Input[Union[(str, 'ContainerServiceVMSizeTypes')]]]=None):
"\n Profile for container service agent pool\n :param pulumi.Input[str] dns_prefix: DNS prefix ... | def __init__(__self__, *, dns_prefix: pulumi.Input[str], name: pulumi.Input[str], count: Optional[pulumi.Input[int]]=None, vm_size: Optional[pulumi.Input[Union[(str, 'ContainerServiceVMSizeTypes')]]]=None):
"\n Profile for container service agent pool\n :param pulumi.Input[str] dns_prefix: DNS prefix ... |
f9b94fe8e4adfa8d37551818b83cbef195b65e1613dd16f0e31c7b5f7f3e157e | @property
@pulumi.getter(name='dnsPrefix')
def dns_prefix(self) -> pulumi.Input[str]:
'\n DNS prefix to be used to create FQDN for this agent pool\n '
return pulumi.get(self, 'dns_prefix') | DNS prefix to be used to create FQDN for this agent pool | sdk/python/pulumi_azure_native/containerservice/v20151101preview/_inputs.py | dns_prefix | pulumi-bot/pulumi-azure-native | 31 | python | @property
@pulumi.getter(name='dnsPrefix')
def dns_prefix(self) -> pulumi.Input[str]:
'\n \n '
return pulumi.get(self, 'dns_prefix') | @property
@pulumi.getter(name='dnsPrefix')
def dns_prefix(self) -> pulumi.Input[str]:
'\n \n '
return pulumi.get(self, 'dns_prefix')<|docstring|>DNS prefix to be used to create FQDN for this agent pool<|endoftext|> |
010b38f1633b9bf430457540e76910d06c832627199fc62a8289df31875d1973 | @property
@pulumi.getter
def name(self) -> pulumi.Input[str]:
'\n Unique name of the agent pool profile within the context of the subscription and resource group\n '
return pulumi.get(self, 'name') | Unique name of the agent pool profile within the context of the subscription and resource group | sdk/python/pulumi_azure_native/containerservice/v20151101preview/_inputs.py | name | pulumi-bot/pulumi-azure-native | 31 | python | @property
@pulumi.getter
def name(self) -> pulumi.Input[str]:
'\n \n '
return pulumi.get(self, 'name') | @property
@pulumi.getter
def name(self) -> pulumi.Input[str]:
'\n \n '
return pulumi.get(self, 'name')<|docstring|>Unique name of the agent pool profile within the context of the subscription and resource group<|endoftext|> |
04526ffb1ce57f60d58ca419bfa1e0261f02b4c8ddc89dd18875b57128a3d2f8 | @property
@pulumi.getter
def count(self) -> Optional[pulumi.Input[int]]:
'\n No. of agents (VMs) that will host docker containers\n '
return pulumi.get(self, 'count') | No. of agents (VMs) that will host docker containers | sdk/python/pulumi_azure_native/containerservice/v20151101preview/_inputs.py | count | pulumi-bot/pulumi-azure-native | 31 | python | @property
@pulumi.getter
def count(self) -> Optional[pulumi.Input[int]]:
'\n \n '
return pulumi.get(self, 'count') | @property
@pulumi.getter
def count(self) -> Optional[pulumi.Input[int]]:
'\n \n '
return pulumi.get(self, 'count')<|docstring|>No. of agents (VMs) that will host docker containers<|endoftext|> |
1e84c8d4f0cd5bfde069a73d60e71655897c20ddf9f5b285fcf0936f7c0bb40c | @property
@pulumi.getter(name='vmSize')
def vm_size(self) -> Optional[pulumi.Input[Union[(str, 'ContainerServiceVMSizeTypes')]]]:
'\n Size of agent VMs\n '
return pulumi.get(self, 'vm_size') | Size of agent VMs | sdk/python/pulumi_azure_native/containerservice/v20151101preview/_inputs.py | vm_size | pulumi-bot/pulumi-azure-native | 31 | python | @property
@pulumi.getter(name='vmSize')
def vm_size(self) -> Optional[pulumi.Input[Union[(str, 'ContainerServiceVMSizeTypes')]]]:
'\n \n '
return pulumi.get(self, 'vm_size') | @property
@pulumi.getter(name='vmSize')
def vm_size(self) -> Optional[pulumi.Input[Union[(str, 'ContainerServiceVMSizeTypes')]]]:
'\n \n '
return pulumi.get(self, 'vm_size')<|docstring|>Size of agent VMs<|endoftext|> |
9546bed620f777a14ce8d02de3a909ebdfdc4f5657b5966c67573d66cb668549 | def __init__(__self__, *, vm_diagnostics: Optional[pulumi.Input['ContainerServiceVMDiagnosticsArgs']]=None):
"\n :param pulumi.Input['ContainerServiceVMDiagnosticsArgs'] vm_diagnostics: Profile for container service VM diagnostic agent\n "
if (vm_diagnostics is not None):
pulumi.set(__self... | :param pulumi.Input['ContainerServiceVMDiagnosticsArgs'] vm_diagnostics: Profile for container service VM diagnostic agent | sdk/python/pulumi_azure_native/containerservice/v20151101preview/_inputs.py | __init__ | pulumi-bot/pulumi-azure-native | 31 | python | def __init__(__self__, *, vm_diagnostics: Optional[pulumi.Input['ContainerServiceVMDiagnosticsArgs']]=None):
"\n \n "
if (vm_diagnostics is not None):
pulumi.set(__self__, 'vm_diagnostics', vm_diagnostics) | def __init__(__self__, *, vm_diagnostics: Optional[pulumi.Input['ContainerServiceVMDiagnosticsArgs']]=None):
"\n \n "
if (vm_diagnostics is not None):
pulumi.set(__self__, 'vm_diagnostics', vm_diagnostics)<|docstring|>:param pulumi.Input['ContainerServiceVMDiagnosticsArgs'] vm_diagnostics:... |
12df4900ac49c29af95616f0fd321128627533f869ebc337c33ea7655ec2359d | @property
@pulumi.getter(name='vmDiagnostics')
def vm_diagnostics(self) -> Optional[pulumi.Input['ContainerServiceVMDiagnosticsArgs']]:
'\n Profile for container service VM diagnostic agent\n '
return pulumi.get(self, 'vm_diagnostics') | Profile for container service VM diagnostic agent | sdk/python/pulumi_azure_native/containerservice/v20151101preview/_inputs.py | vm_diagnostics | pulumi-bot/pulumi-azure-native | 31 | python | @property
@pulumi.getter(name='vmDiagnostics')
def vm_diagnostics(self) -> Optional[pulumi.Input['ContainerServiceVMDiagnosticsArgs']]:
'\n \n '
return pulumi.get(self, 'vm_diagnostics') | @property
@pulumi.getter(name='vmDiagnostics')
def vm_diagnostics(self) -> Optional[pulumi.Input['ContainerServiceVMDiagnosticsArgs']]:
'\n \n '
return pulumi.get(self, 'vm_diagnostics')<|docstring|>Profile for container service VM diagnostic agent<|endoftext|> |
53c4601c9c894473b259e4e7c3e7ed27560ed203a57ad3a3b4911c852d3847e8 | def __init__(__self__, *, admin_username: pulumi.Input[str], ssh: pulumi.Input['ContainerServiceSshConfigurationArgs']):
"\n Profile for Linux VM\n :param pulumi.Input[str] admin_username: The administrator username to use for all Linux VMs\n :param pulumi.Input['ContainerServiceSshConfiguratio... | Profile for Linux VM
:param pulumi.Input[str] admin_username: The administrator username to use for all Linux VMs
:param pulumi.Input['ContainerServiceSshConfigurationArgs'] ssh: Specifies the ssh key configuration for Linux VMs | sdk/python/pulumi_azure_native/containerservice/v20151101preview/_inputs.py | __init__ | pulumi-bot/pulumi-azure-native | 31 | python | def __init__(__self__, *, admin_username: pulumi.Input[str], ssh: pulumi.Input['ContainerServiceSshConfigurationArgs']):
"\n Profile for Linux VM\n :param pulumi.Input[str] admin_username: The administrator username to use for all Linux VMs\n :param pulumi.Input['ContainerServiceSshConfiguratio... | def __init__(__self__, *, admin_username: pulumi.Input[str], ssh: pulumi.Input['ContainerServiceSshConfigurationArgs']):
"\n Profile for Linux VM\n :param pulumi.Input[str] admin_username: The administrator username to use for all Linux VMs\n :param pulumi.Input['ContainerServiceSshConfiguratio... |
46b5cde415d4e26ae09075ce569f7174af65184eeb1228dbc4d083dbf812a5a2 | @property
@pulumi.getter(name='adminUsername')
def admin_username(self) -> pulumi.Input[str]:
'\n The administrator username to use for all Linux VMs\n '
return pulumi.get(self, 'admin_username') | The administrator username to use for all Linux VMs | sdk/python/pulumi_azure_native/containerservice/v20151101preview/_inputs.py | admin_username | pulumi-bot/pulumi-azure-native | 31 | python | @property
@pulumi.getter(name='adminUsername')
def admin_username(self) -> pulumi.Input[str]:
'\n \n '
return pulumi.get(self, 'admin_username') | @property
@pulumi.getter(name='adminUsername')
def admin_username(self) -> pulumi.Input[str]:
'\n \n '
return pulumi.get(self, 'admin_username')<|docstring|>The administrator username to use for all Linux VMs<|endoftext|> |
203d09ba55ed754a12c84755b74df592fd4d910d4d9fa22933e1cd1a863f88b9 | @property
@pulumi.getter
def ssh(self) -> pulumi.Input['ContainerServiceSshConfigurationArgs']:
'\n Specifies the ssh key configuration for Linux VMs\n '
return pulumi.get(self, 'ssh') | Specifies the ssh key configuration for Linux VMs | sdk/python/pulumi_azure_native/containerservice/v20151101preview/_inputs.py | ssh | pulumi-bot/pulumi-azure-native | 31 | python | @property
@pulumi.getter
def ssh(self) -> pulumi.Input['ContainerServiceSshConfigurationArgs']:
'\n \n '
return pulumi.get(self, 'ssh') | @property
@pulumi.getter
def ssh(self) -> pulumi.Input['ContainerServiceSshConfigurationArgs']:
'\n \n '
return pulumi.get(self, 'ssh')<|docstring|>Specifies the ssh key configuration for Linux VMs<|endoftext|> |
8e77e867ddc7a92cd069409061790139ccf9b9cc010ec1352c230d0eb195dd6f | def __init__(__self__, *, dns_prefix: pulumi.Input[str], count: Optional[pulumi.Input[int]]=None):
'\n Profile for container service master\n :param pulumi.Input[str] dns_prefix: DNS prefix to be used to create FQDN for master\n :param pulumi.Input[int] count: Number of masters (VMs) in the con... | Profile for container service master
:param pulumi.Input[str] dns_prefix: DNS prefix to be used to create FQDN for master
:param pulumi.Input[int] count: Number of masters (VMs) in the container cluster | sdk/python/pulumi_azure_native/containerservice/v20151101preview/_inputs.py | __init__ | pulumi-bot/pulumi-azure-native | 31 | python | def __init__(__self__, *, dns_prefix: pulumi.Input[str], count: Optional[pulumi.Input[int]]=None):
'\n Profile for container service master\n :param pulumi.Input[str] dns_prefix: DNS prefix to be used to create FQDN for master\n :param pulumi.Input[int] count: Number of masters (VMs) in the con... | def __init__(__self__, *, dns_prefix: pulumi.Input[str], count: Optional[pulumi.Input[int]]=None):
'\n Profile for container service master\n :param pulumi.Input[str] dns_prefix: DNS prefix to be used to create FQDN for master\n :param pulumi.Input[int] count: Number of masters (VMs) in the con... |
87e550ff3cbc2a7ba8e147e95bcc9e97d62b736da36ebb3b471ddaf222f6b1c7 | @property
@pulumi.getter(name='dnsPrefix')
def dns_prefix(self) -> pulumi.Input[str]:
'\n DNS prefix to be used to create FQDN for master\n '
return pulumi.get(self, 'dns_prefix') | DNS prefix to be used to create FQDN for master | sdk/python/pulumi_azure_native/containerservice/v20151101preview/_inputs.py | dns_prefix | pulumi-bot/pulumi-azure-native | 31 | python | @property
@pulumi.getter(name='dnsPrefix')
def dns_prefix(self) -> pulumi.Input[str]:
'\n \n '
return pulumi.get(self, 'dns_prefix') | @property
@pulumi.getter(name='dnsPrefix')
def dns_prefix(self) -> pulumi.Input[str]:
'\n \n '
return pulumi.get(self, 'dns_prefix')<|docstring|>DNS prefix to be used to create FQDN for master<|endoftext|> |
3412b0b23bfdd558ccdb2250452d14c5864693ba3e712d786781822434d0cf35 | @property
@pulumi.getter
def count(self) -> Optional[pulumi.Input[int]]:
'\n Number of masters (VMs) in the container cluster\n '
return pulumi.get(self, 'count') | Number of masters (VMs) in the container cluster | sdk/python/pulumi_azure_native/containerservice/v20151101preview/_inputs.py | count | pulumi-bot/pulumi-azure-native | 31 | python | @property
@pulumi.getter
def count(self) -> Optional[pulumi.Input[int]]:
'\n \n '
return pulumi.get(self, 'count') | @property
@pulumi.getter
def count(self) -> Optional[pulumi.Input[int]]:
'\n \n '
return pulumi.get(self, 'count')<|docstring|>Number of masters (VMs) in the container cluster<|endoftext|> |
bdd94d0c1cb1a9b523d609d2f0f1026344ca4450290c9eabaa69c308c533d4c1 | def __init__(__self__, *, orchestrator_type: Optional[pulumi.Input['ContainerServiceOchestratorTypes']]=None):
"\n Profile for Orchestrator\n :param pulumi.Input['ContainerServiceOchestratorTypes'] orchestrator_type: Specifies what orchestrator will be used to manage container cluster resources.\n ... | Profile for Orchestrator
:param pulumi.Input['ContainerServiceOchestratorTypes'] orchestrator_type: Specifies what orchestrator will be used to manage container cluster resources. | sdk/python/pulumi_azure_native/containerservice/v20151101preview/_inputs.py | __init__ | pulumi-bot/pulumi-azure-native | 31 | python | def __init__(__self__, *, orchestrator_type: Optional[pulumi.Input['ContainerServiceOchestratorTypes']]=None):
"\n Profile for Orchestrator\n :param pulumi.Input['ContainerServiceOchestratorTypes'] orchestrator_type: Specifies what orchestrator will be used to manage container cluster resources.\n ... | def __init__(__self__, *, orchestrator_type: Optional[pulumi.Input['ContainerServiceOchestratorTypes']]=None):
"\n Profile for Orchestrator\n :param pulumi.Input['ContainerServiceOchestratorTypes'] orchestrator_type: Specifies what orchestrator will be used to manage container cluster resources.\n ... |
8fff61dbf719cde6bad3d73590111ad47f3fa172dbc7e16c2a52b02bd0d0d852 | @property
@pulumi.getter(name='orchestratorType')
def orchestrator_type(self) -> Optional[pulumi.Input['ContainerServiceOchestratorTypes']]:
'\n Specifies what orchestrator will be used to manage container cluster resources.\n '
return pulumi.get(self, 'orchestrator_type') | Specifies what orchestrator will be used to manage container cluster resources. | sdk/python/pulumi_azure_native/containerservice/v20151101preview/_inputs.py | orchestrator_type | pulumi-bot/pulumi-azure-native | 31 | python | @property
@pulumi.getter(name='orchestratorType')
def orchestrator_type(self) -> Optional[pulumi.Input['ContainerServiceOchestratorTypes']]:
'\n \n '
return pulumi.get(self, 'orchestrator_type') | @property
@pulumi.getter(name='orchestratorType')
def orchestrator_type(self) -> Optional[pulumi.Input['ContainerServiceOchestratorTypes']]:
'\n \n '
return pulumi.get(self, 'orchestrator_type')<|docstring|>Specifies what orchestrator will be used to manage container cluster resources.<|endoftext|... |
00a713891d07c6b8da7c91b9f5c54755fb0b36853a8b3a6be5704448156db4db | def __init__(__self__, *, public_keys: Optional[pulumi.Input[Sequence[pulumi.Input['ContainerServiceSshPublicKeyArgs']]]]=None):
"\n SSH configuration for Linux based VMs running on Azure\n :param pulumi.Input[Sequence[pulumi.Input['ContainerServiceSshPublicKeyArgs']]] public_keys: Gets or sets the li... | SSH configuration for Linux based VMs running on Azure
:param pulumi.Input[Sequence[pulumi.Input['ContainerServiceSshPublicKeyArgs']]] public_keys: Gets or sets the list of SSH public keys used to authenticate with Linux based VMs | sdk/python/pulumi_azure_native/containerservice/v20151101preview/_inputs.py | __init__ | pulumi-bot/pulumi-azure-native | 31 | python | def __init__(__self__, *, public_keys: Optional[pulumi.Input[Sequence[pulumi.Input['ContainerServiceSshPublicKeyArgs']]]]=None):
"\n SSH configuration for Linux based VMs running on Azure\n :param pulumi.Input[Sequence[pulumi.Input['ContainerServiceSshPublicKeyArgs']]] public_keys: Gets or sets the li... | def __init__(__self__, *, public_keys: Optional[pulumi.Input[Sequence[pulumi.Input['ContainerServiceSshPublicKeyArgs']]]]=None):
"\n SSH configuration for Linux based VMs running on Azure\n :param pulumi.Input[Sequence[pulumi.Input['ContainerServiceSshPublicKeyArgs']]] public_keys: Gets or sets the li... |
0ce7662055523de20e322876dc257050b47523268bf007a87d8c086901bde566 | @property
@pulumi.getter(name='publicKeys')
def public_keys(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['ContainerServiceSshPublicKeyArgs']]]]:
'\n Gets or sets the list of SSH public keys used to authenticate with Linux based VMs\n '
return pulumi.get(self, 'public_keys') | Gets or sets the list of SSH public keys used to authenticate with Linux based VMs | sdk/python/pulumi_azure_native/containerservice/v20151101preview/_inputs.py | public_keys | pulumi-bot/pulumi-azure-native | 31 | python | @property
@pulumi.getter(name='publicKeys')
def public_keys(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['ContainerServiceSshPublicKeyArgs']]]]:
'\n \n '
return pulumi.get(self, 'public_keys') | @property
@pulumi.getter(name='publicKeys')
def public_keys(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['ContainerServiceSshPublicKeyArgs']]]]:
'\n \n '
return pulumi.get(self, 'public_keys')<|docstring|>Gets or sets the list of SSH public keys used to authenticate with Linux based VMs<|e... |
433c33fe0a5e0f47e63e5b1c79ed01ad14be737057a5baf797abbfca283e2df9 | def __init__(__self__, *, key_data: pulumi.Input[str]):
'\n Contains information about SSH certificate public key data.\n :param pulumi.Input[str] key_data: Gets or sets Certificate public key used to authenticate with VM through SSH. The certificate must be in Pem format with or without headers.\n ... | Contains information about SSH certificate public key data.
:param pulumi.Input[str] key_data: Gets or sets Certificate public key used to authenticate with VM through SSH. The certificate must be in Pem format with or without headers. | sdk/python/pulumi_azure_native/containerservice/v20151101preview/_inputs.py | __init__ | pulumi-bot/pulumi-azure-native | 31 | python | def __init__(__self__, *, key_data: pulumi.Input[str]):
'\n Contains information about SSH certificate public key data.\n :param pulumi.Input[str] key_data: Gets or sets Certificate public key used to authenticate with VM through SSH. The certificate must be in Pem format with or without headers.\n ... | def __init__(__self__, *, key_data: pulumi.Input[str]):
'\n Contains information about SSH certificate public key data.\n :param pulumi.Input[str] key_data: Gets or sets Certificate public key used to authenticate with VM through SSH. The certificate must be in Pem format with or without headers.\n ... |
b6f85d688131e88acfa16bdab0ff7e9c9cc183e0dd58def349b530862720939e | @property
@pulumi.getter(name='keyData')
def key_data(self) -> pulumi.Input[str]:
'\n Gets or sets Certificate public key used to authenticate with VM through SSH. The certificate must be in Pem format with or without headers.\n '
return pulumi.get(self, 'key_data') | Gets or sets Certificate public key used to authenticate with VM through SSH. The certificate must be in Pem format with or without headers. | sdk/python/pulumi_azure_native/containerservice/v20151101preview/_inputs.py | key_data | pulumi-bot/pulumi-azure-native | 31 | python | @property
@pulumi.getter(name='keyData')
def key_data(self) -> pulumi.Input[str]:
'\n \n '
return pulumi.get(self, 'key_data') | @property
@pulumi.getter(name='keyData')
def key_data(self) -> pulumi.Input[str]:
'\n \n '
return pulumi.get(self, 'key_data')<|docstring|>Gets or sets Certificate public key used to authenticate with VM through SSH. The certificate must be in Pem format with or without headers.<|endoftext|> |
a625b5c43760321410b34064deaaca5d4d1822c1a696da6f30ee402423b027a1 | def __init__(__self__, *, enabled: Optional[pulumi.Input[bool]]=None):
'\n Describes VM Diagnostics.\n :param pulumi.Input[bool] enabled: Gets or sets whether VM Diagnostic Agent should be provisioned on the Virtual Machine.\n '
if (enabled is not None):
pulumi.set(__self__, 'enable... | Describes VM Diagnostics.
:param pulumi.Input[bool] enabled: Gets or sets whether VM Diagnostic Agent should be provisioned on the Virtual Machine. | sdk/python/pulumi_azure_native/containerservice/v20151101preview/_inputs.py | __init__ | pulumi-bot/pulumi-azure-native | 31 | python | def __init__(__self__, *, enabled: Optional[pulumi.Input[bool]]=None):
'\n Describes VM Diagnostics.\n :param pulumi.Input[bool] enabled: Gets or sets whether VM Diagnostic Agent should be provisioned on the Virtual Machine.\n '
if (enabled is not None):
pulumi.set(__self__, 'enable... | def __init__(__self__, *, enabled: Optional[pulumi.Input[bool]]=None):
'\n Describes VM Diagnostics.\n :param pulumi.Input[bool] enabled: Gets or sets whether VM Diagnostic Agent should be provisioned on the Virtual Machine.\n '
if (enabled is not None):
pulumi.set(__self__, 'enable... |
4ccc30c51289648aaf76c0dc17d4bd1c60b702311ed0e919700d698b333e6f22 | @property
@pulumi.getter
def enabled(self) -> Optional[pulumi.Input[bool]]:
'\n Gets or sets whether VM Diagnostic Agent should be provisioned on the Virtual Machine.\n '
return pulumi.get(self, 'enabled') | Gets or sets whether VM Diagnostic Agent should be provisioned on the Virtual Machine. | sdk/python/pulumi_azure_native/containerservice/v20151101preview/_inputs.py | enabled | pulumi-bot/pulumi-azure-native | 31 | python | @property
@pulumi.getter
def enabled(self) -> Optional[pulumi.Input[bool]]:
'\n \n '
return pulumi.get(self, 'enabled') | @property
@pulumi.getter
def enabled(self) -> Optional[pulumi.Input[bool]]:
'\n \n '
return pulumi.get(self, 'enabled')<|docstring|>Gets or sets whether VM Diagnostic Agent should be provisioned on the Virtual Machine.<|endoftext|> |
81b5fbf28bc40172cdb037e3554c5b23540ee72edc60f763e618b67a346df09c | def __init__(__self__, *, admin_password: pulumi.Input[str], admin_username: pulumi.Input[str]):
'\n Profile for Windows jumpbox\n :param pulumi.Input[str] admin_password: The administrator password to use for Windows jumpbox\n :param pulumi.Input[str] admin_username: The administrator username... | Profile for Windows jumpbox
:param pulumi.Input[str] admin_password: The administrator password to use for Windows jumpbox
:param pulumi.Input[str] admin_username: The administrator username to use for Windows jumpbox | sdk/python/pulumi_azure_native/containerservice/v20151101preview/_inputs.py | __init__ | pulumi-bot/pulumi-azure-native | 31 | python | def __init__(__self__, *, admin_password: pulumi.Input[str], admin_username: pulumi.Input[str]):
'\n Profile for Windows jumpbox\n :param pulumi.Input[str] admin_password: The administrator password to use for Windows jumpbox\n :param pulumi.Input[str] admin_username: The administrator username... | def __init__(__self__, *, admin_password: pulumi.Input[str], admin_username: pulumi.Input[str]):
'\n Profile for Windows jumpbox\n :param pulumi.Input[str] admin_password: The administrator password to use for Windows jumpbox\n :param pulumi.Input[str] admin_username: The administrator username... |
a8c8d245c44dd4c954371302b8234d21c327ab5977f04382af0d3ffca8e516cb | @property
@pulumi.getter(name='adminPassword')
def admin_password(self) -> pulumi.Input[str]:
'\n The administrator password to use for Windows jumpbox\n '
return pulumi.get(self, 'admin_password') | The administrator password to use for Windows jumpbox | sdk/python/pulumi_azure_native/containerservice/v20151101preview/_inputs.py | admin_password | pulumi-bot/pulumi-azure-native | 31 | python | @property
@pulumi.getter(name='adminPassword')
def admin_password(self) -> pulumi.Input[str]:
'\n \n '
return pulumi.get(self, 'admin_password') | @property
@pulumi.getter(name='adminPassword')
def admin_password(self) -> pulumi.Input[str]:
'\n \n '
return pulumi.get(self, 'admin_password')<|docstring|>The administrator password to use for Windows jumpbox<|endoftext|> |
f1e54a52af8c9472f4600771858bcb3c6117eed9aa625f02877686f385824b2c | @property
@pulumi.getter(name='adminUsername')
def admin_username(self) -> pulumi.Input[str]:
'\n The administrator username to use for Windows jumpbox\n '
return pulumi.get(self, 'admin_username') | The administrator username to use for Windows jumpbox | sdk/python/pulumi_azure_native/containerservice/v20151101preview/_inputs.py | admin_username | pulumi-bot/pulumi-azure-native | 31 | python | @property
@pulumi.getter(name='adminUsername')
def admin_username(self) -> pulumi.Input[str]:
'\n \n '
return pulumi.get(self, 'admin_username') | @property
@pulumi.getter(name='adminUsername')
def admin_username(self) -> pulumi.Input[str]:
'\n \n '
return pulumi.get(self, 'admin_username')<|docstring|>The administrator username to use for Windows jumpbox<|endoftext|> |
a144140dfdabe5a2c7427811384be2fc6c8c9eac667613512275c2d04e197481 | def camelCase_to_underscore(str):
"\n >>> camelCase_to_underscore('camelcase')\n 'camelcase'\n >>> camelCase_to_underscore('camelCase')\n 'camel_case'\n >>> camelCase_to_underscore('camelCamelCase')\n 'camel_camel_case'\n "
return re.sub(pattern, sub, str).lower() | >>> camelCase_to_underscore('camelcase')
'camelcase'
>>> camelCase_to_underscore('camelCase')
'camel_case'
>>> camelCase_to_underscore('camelCamelCase')
'camel_camel_case' | utils/model/gen_uml.py | camelCase_to_underscore | MarianelaSena/gaphor | 0 | python | def camelCase_to_underscore(str):
"\n >>> camelCase_to_underscore('camelcase')\n 'camelcase'\n >>> camelCase_to_underscore('camelCase')\n 'camel_case'\n >>> camelCase_to_underscore('camelCamelCase')\n 'camel_camel_case'\n "
return re.sub(pattern, sub, str).lower() | def camelCase_to_underscore(str):
"\n >>> camelCase_to_underscore('camelcase')\n 'camelcase'\n >>> camelCase_to_underscore('camelCase')\n 'camel_case'\n >>> camelCase_to_underscore('camelCamelCase')\n 'camel_camel_case'\n "
return re.sub(pattern, sub, str).lower()<|docstring|>>>> camelCase_... |
070504d83250001b7a80aeb72e7921162917c3567a3b334eb35b9ed895eb8198 | def parse_association_end(head, tail):
'\n The head association end is enriched with the following attributes:\n\n derived - association is a derived union or not\n name - name of the association end (name of head is found on tail)\n class_name - name of the class this association belongs to... | The head association end is enriched with the following attributes:
derived - association is a derived union or not
name - name of the association end (name of head is found on tail)
class_name - name of the class this association belongs to
opposite_class_name - name of the class at the other end of t... | utils/model/gen_uml.py | parse_association_end | MarianelaSena/gaphor | 0 | python | def parse_association_end(head, tail):
'\n The head association end is enriched with the following attributes:\n\n derived - association is a derived union or not\n name - name of the association end (name of head is found on tail)\n class_name - name of the class this association belongs to... | def parse_association_end(head, tail):
'\n The head association end is enriched with the following attributes:\n\n derived - association is a derived union or not\n name - name of the association end (name of head is found on tail)\n class_name - name of the class this association belongs to... |
982a2777ca2c5de69691285727e7e779f017cc8f26c52bb395b36b2dbd0705d1 | def write_classdef(self, clazz):
'\n Write a class definition (class xx(x): pass).\n First the parent classes are examined. After that its own definition\n is written. It is ensured that class definitions are only written\n once.\n '
if (not clazz.written):
s = ''
... | Write a class definition (class xx(x): pass).
First the parent classes are examined. After that its own definition
is written. It is ensured that class definitions are only written
once. | utils/model/gen_uml.py | write_classdef | MarianelaSena/gaphor | 0 | python | def write_classdef(self, clazz):
'\n Write a class definition (class xx(x): pass).\n First the parent classes are examined. After that its own definition\n is written. It is ensured that class definitions are only written\n once.\n '
if (not clazz.written):
s =
... | def write_classdef(self, clazz):
'\n Write a class definition (class xx(x): pass).\n First the parent classes are examined. After that its own definition\n is written. It is ensured that class definitions are only written\n once.\n '
if (not clazz.written):
s =
... |
e44c6932c14d272ed34ca46e5ea5e217a26ab2160b888cbe5b26a3ec54011a8a | def write_property(self, full_name, value):
'\n Write a property to the file. If the property is overridden, use the\n overridden value. full_name should be like Class.attribute. value is\n free format text.\n '
if (not self.overrides.write_override(self, full_name)):
self.wr... | Write a property to the file. If the property is overridden, use the
overridden value. full_name should be like Class.attribute. value is
free format text. | utils/model/gen_uml.py | write_property | MarianelaSena/gaphor | 0 | python | def write_property(self, full_name, value):
'\n Write a property to the file. If the property is overridden, use the\n overridden value. full_name should be like Class.attribute. value is\n free format text.\n '
if (not self.overrides.write_override(self, full_name)):
self.wr... | def write_property(self, full_name, value):
'\n Write a property to the file. If the property is overridden, use the\n overridden value. full_name should be like Class.attribute. value is\n free format text.\n '
if (not self.overrides.write_override(self, full_name)):
self.wr... |
4f1965477e09f6cc8057382526e8f4cbb5e66ef90988e80e6b7cde3da300706d | def write_attribute(self, a, enumerations={}):
'\n Write a definition for attribute a. Enumerations may be a dict\n of enumerations, indexed by ID. These are used to identify enums.\n '
params = {}
type = a.typeValue
if (type is None):
raise ValueError(('ERROR! type is not s... | Write a definition for attribute a. Enumerations may be a dict
of enumerations, indexed by ID. These are used to identify enums. | utils/model/gen_uml.py | write_attribute | MarianelaSena/gaphor | 0 | python | def write_attribute(self, a, enumerations={}):
'\n Write a definition for attribute a. Enumerations may be a dict\n of enumerations, indexed by ID. These are used to identify enums.\n '
params = {}
type = a.typeValue
if (type is None):
raise ValueError(('ERROR! type is not s... | def write_attribute(self, a, enumerations={}):
'\n Write a definition for attribute a. Enumerations may be a dict\n of enumerations, indexed by ID. These are used to identify enums.\n '
params = {}
type = a.typeValue
if (type is None):
raise ValueError(('ERROR! type is not s... |
7de93cb8597f83961b2cf8deadbe85eb654526a97f94f1b4d081b8740a0db6f1 | def write_association(self, head, tail):
'\n Write an association for head.\n The association should not be a redefine or derived association.\n '
if head.written:
return
assert head.navigable
assert (not head.derived)
assert (not head.redefines)
a = f"association('{... | Write an association for head.
The association should not be a redefine or derived association. | utils/model/gen_uml.py | write_association | MarianelaSena/gaphor | 0 | python | def write_association(self, head, tail):
'\n Write an association for head.\n The association should not be a redefine or derived association.\n '
if head.written:
return
assert head.navigable
assert (not head.derived)
assert (not head.redefines)
a = f"association('{... | def write_association(self, head, tail):
'\n Write an association for head.\n The association should not be a redefine or derived association.\n '
if head.written:
return
assert head.navigable
assert (not head.derived)
assert (not head.redefines)
a = f"association('{... |
5ea054be91a38345d6358e1408388a7f878dc796122a5e0e29e905f470caf4c3 | def write_derivedunion(self, d):
'\n Write a derived union. If there are no subsets a warning\n is issued. The derivedunion is still created though.\n\n Derived unions may be created for associations that were returned\n False by write_association().\n '
subs = ''
for u in... | Write a derived union. If there are no subsets a warning
is issued. The derivedunion is still created though.
Derived unions may be created for associations that were returned
False by write_association(). | utils/model/gen_uml.py | write_derivedunion | MarianelaSena/gaphor | 0 | python | def write_derivedunion(self, d):
'\n Write a derived union. If there are no subsets a warning\n is issued. The derivedunion is still created though.\n\n Derived unions may be created for associations that were returned\n False by write_association().\n '
subs =
for u in d... | def write_derivedunion(self, d):
'\n Write a derived union. If there are no subsets a warning\n is issued. The derivedunion is still created though.\n\n Derived unions may be created for associations that were returned\n False by write_association().\n '
subs =
for u in d... |
35135c6ba384843bffb929b45cce4118bd80117f4836b179d9dd8eda6580098c | def write_redefine(self, r):
'\n Redefines may be created for associations that were returned\n False by write_association().\n '
self.write_property(f'{r.class_name}.{r.name}', ("redefine(%s, '%s', %s, %s)" % (r.class_name, r.name, r.opposite_class_name, r.redefines))) | Redefines may be created for associations that were returned
False by write_association(). | utils/model/gen_uml.py | write_redefine | MarianelaSena/gaphor | 0 | python | def write_redefine(self, r):
'\n Redefines may be created for associations that were returned\n False by write_association().\n '
self.write_property(f'{r.class_name}.{r.name}', ("redefine(%s, '%s', %s, %s)" % (r.class_name, r.name, r.opposite_class_name, r.redefines))) | def write_redefine(self, r):
'\n Redefines may be created for associations that were returned\n False by write_association().\n '
self.write_property(f'{r.class_name}.{r.name}', ("redefine(%s, '%s', %s, %s)" % (r.class_name, r.name, r.opposite_class_name, r.redefines)))<|docstring|>Redefine... |
d2ce16097c0f7345cfc9695eae9f1557be67887cebf85c128e38d0b1590ed91b | def resolve(val, attr):
'Resolve references.\n '
try:
refs = val.references[attr]
except KeyError:
val.references[attr] = None
return
if isinstance(refs, type([])):
unrefs = []
for r in refs:
unrefs.append(all_elements[r])
val.references... | Resolve references. | utils/model/gen_uml.py | resolve | MarianelaSena/gaphor | 0 | python | def resolve(val, attr):
'\n '
try:
refs = val.references[attr]
except KeyError:
val.references[attr] = None
return
if isinstance(refs, type([])):
unrefs = []
for r in refs:
unrefs.append(all_elements[r])
val.references[attr] = unrefs
... | def resolve(val, attr):
'\n '
try:
refs = val.references[attr]
except KeyError:
val.references[attr] = None
return
if isinstance(refs, type([])):
unrefs = []
for r in refs:
unrefs.append(all_elements[r])
val.references[attr] = unrefs
... |
3bbfbb628960ca0d952031868d7320250b3b3edec4549e11e60ca83d29621bca | def read_data(self):
'Reads the json data located in self.data_fname into memory, to\n the attribute self.data.\n '
with open(self.data_fname, 'r') as j:
self.data = json.loads(j.read()) | Reads the json data located in self.data_fname into memory, to
the attribute self.data. | hw5.py | read_data | yaelgat/hw5 | 0 | python | def read_data(self):
'Reads the json data located in self.data_fname into memory, to\n the attribute self.data.\n '
with open(self.data_fname, 'r') as j:
self.data = json.loads(j.read()) | def read_data(self):
'Reads the json data located in self.data_fname into memory, to\n the attribute self.data.\n '
with open(self.data_fname, 'r') as j:
self.data = json.loads(j.read())<|docstring|>Reads the json data located in self.data_fname into memory, to
the attribute self.data.<|en... |
9b5ef0ce19e5ff07df658a2866fbb76b29c923bf05d8e374c6c5ffb9c8c435b4 | def test_parser() -> None:
'Run a merge test with the provided action.'
test_data = parse_path(__file__)
parser(test_data.org, test_data.model, test_data.driver, test_data.path) | Run a merge test with the provided action. | tests/models/openconfig/data/openconfig_vlan/parse/junos/config/test_case.py | test_parser | steinzi/ntc-rosetta | 95 | python | def test_parser() -> None:
test_data = parse_path(__file__)
parser(test_data.org, test_data.model, test_data.driver, test_data.path) | def test_parser() -> None:
test_data = parse_path(__file__)
parser(test_data.org, test_data.model, test_data.driver, test_data.path)<|docstring|>Run a merge test with the provided action.<|endoftext|> |
edde19febba1c53828a7bd818e3b690b25c1b511309f59ecbf4a22a1871fc17d | def is_mobile(text: str) -> bool:
'\n 检查手机号码\n\n :param text:\n :return:\n '
return check_string('^1[3-9]\\d{9}$', text) | 检查手机号码
:param text:
:return: | backend/app/utils/processing_string.py | is_mobile | wu-clan/fastapi_mysql_demo | 0 | python | def is_mobile(text: str) -> bool:
'\n 检查手机号码\n\n :param text:\n :return:\n '
return check_string('^1[3-9]\\d{9}$', text) | def is_mobile(text: str) -> bool:
'\n 检查手机号码\n\n :param text:\n :return:\n '
return check_string('^1[3-9]\\d{9}$', text)<|docstring|>检查手机号码
:param text:
:return:<|endoftext|> |
cbd162f7f5588a3e007844f377606740564ddfe09e4de511c5cab9d111d19f5c | def is_wechat(text: str) -> bool:
'\n 检查微信号\n\n :param text:\n :return:\n '
return check_string('^[a-zA-Z]([-_a-zA-Z0-9]{5,19})+$', text) | 检查微信号
:param text:
:return: | backend/app/utils/processing_string.py | is_wechat | wu-clan/fastapi_mysql_demo | 0 | python | def is_wechat(text: str) -> bool:
'\n 检查微信号\n\n :param text:\n :return:\n '
return check_string('^[a-zA-Z]([-_a-zA-Z0-9]{5,19})+$', text) | def is_wechat(text: str) -> bool:
'\n 检查微信号\n\n :param text:\n :return:\n '
return check_string('^[a-zA-Z]([-_a-zA-Z0-9]{5,19})+$', text)<|docstring|>检查微信号
:param text:
:return:<|endoftext|> |
808cc832b8d25cd480dc189d293ebd1c69be828150834dd9edf5ab34b15c9324 | def is_QQ(text: str) -> bool:
'\n 检查QQ号\n\n :param text:\n :return:\n '
return check_string('^[1-9][0-9]{4,10}$', text) | 检查QQ号
:param text:
:return: | backend/app/utils/processing_string.py | is_QQ | wu-clan/fastapi_mysql_demo | 0 | python | def is_QQ(text: str) -> bool:
'\n 检查QQ号\n\n :param text:\n :return:\n '
return check_string('^[1-9][0-9]{4,10}$', text) | def is_QQ(text: str) -> bool:
'\n 检查QQ号\n\n :param text:\n :return:\n '
return check_string('^[1-9][0-9]{4,10}$', text)<|docstring|>检查QQ号
:param text:
:return:<|endoftext|> |
8bf252a347a073ca831779c129b3a4457af854a87bcf4dc65b9f3ad628e2c8c1 | def appdata_dir():
'Find the path to the application data directory; add an electrum folder and return path.'
if (platform.system() == 'Windows'):
return os.path.join(os.environ['APPDATA'], 'Electrum')
elif (platform.system() == 'Linux'):
return os.path.join(sys.prefix, 'share', 'electrum')
... | Find the path to the application data directory; add an electrum folder and return path. | web/cgi-bin/electrum/lib/util.py | appdata_dir | appealing-alexey/ew | 1 | python | def appdata_dir():
if (platform.system() == 'Windows'):
return os.path.join(os.environ['APPDATA'], 'Electrum')
elif (platform.system() == 'Linux'):
return os.path.join(sys.prefix, 'share', 'electrum')
elif ((platform.system() == 'Darwin') or (platform.system() == 'DragonFly')):
... | def appdata_dir():
if (platform.system() == 'Windows'):
return os.path.join(os.environ['APPDATA'], 'Electrum')
elif (platform.system() == 'Linux'):
return os.path.join(sys.prefix, 'share', 'electrum')
elif ((platform.system() == 'Darwin') or (platform.system() == 'DragonFly')):
... |
47aaaa404f8ce217020099d62ae14a0d20e3c84da02adf1ef160ec77d33016e0 | def local_data_dir():
'Return path to the data folder.'
assert sys.argv
prefix_path = os.path.dirname(sys.argv[0])
local_data = os.path.join(prefix_path, 'data')
return local_data | Return path to the data folder. | web/cgi-bin/electrum/lib/util.py | local_data_dir | appealing-alexey/ew | 1 | python | def local_data_dir():
assert sys.argv
prefix_path = os.path.dirname(sys.argv[0])
local_data = os.path.join(prefix_path, 'data')
return local_data | def local_data_dir():
assert sys.argv
prefix_path = os.path.dirname(sys.argv[0])
local_data = os.path.join(prefix_path, 'data')
return local_data<|docstring|>Return path to the data folder.<|endoftext|> |
eb1bd0571d9977a75262d44ba307146da36e267b97898f76653d172855948014 | def compress_content(self):
'\n Method to change for new implementations\n '
raise NotImplementedError() | Method to change for new implementations | compress_field/base.py | compress_content | valdergallo/django-compress-field | 13 | python | def compress_content(self):
'\n \n '
raise NotImplementedError() | def compress_content(self):
'\n \n '
raise NotImplementedError()<|docstring|>Method to change for new implementations<|endoftext|> |
0d537422e4b85bb1c9262ff289899c7d3e071a6039607d2a77ecc9bef8e8c011 | def intersect_line_and_sphere(endpoint, center, radius):
'Compute distance to intersections of a line and a sphere.\n\n Given a line through the origin (0,0,0) and an |xyz| ``endpoint``,\n and a sphere with the |xyz| ``center`` and scalar ``radius``,\n return the distance from the origin to their two inter... | Compute distance to intersections of a line and a sphere.
Given a line through the origin (0,0,0) and an |xyz| ``endpoint``,
and a sphere with the |xyz| ``center`` and scalar ``radius``,
return the distance from the origin to their two intersections.
If the line is tangent to the sphere, the two intersections will be... | skyfield/geometry.py | intersect_line_and_sphere | Imperator26/python-skyfield | 765 | python | def intersect_line_and_sphere(endpoint, center, radius):
'Compute distance to intersections of a line and a sphere.\n\n Given a line through the origin (0,0,0) and an |xyz| ``endpoint``,\n and a sphere with the |xyz| ``center`` and scalar ``radius``,\n return the distance from the origin to their two inter... | def intersect_line_and_sphere(endpoint, center, radius):
'Compute distance to intersections of a line and a sphere.\n\n Given a line through the origin (0,0,0) and an |xyz| ``endpoint``,\n and a sphere with the |xyz| ``center`` and scalar ``radius``,\n return the distance from the origin to their two inter... |
15e24af4165a83d38fa36e14b5527a5bab34f387c925d083b1362e124ccc35d6 | def dense_patch_slices(image_size, patch_size, scan_interval):
'\n Enumerate all slices defining 2D/3D patches of size `patch_size` from an `image_size` input image.\n\n Args:\n image_size (tuple of int): dimensions of image to iterate over\n patch_size (tuple of int): size of patches to generat... | Enumerate all slices defining 2D/3D patches of size `patch_size` from an `image_size` input image.
Args:
image_size (tuple of int): dimensions of image to iterate over
patch_size (tuple of int): size of patches to generate slices
scan_interval (tuple of int): dense patch sampling interval
Returns:
a l... | contrib/MedicalSeg/medicalseg/core/infer_window.py | dense_patch_slices | sun222/PaddleSeg | 0 | python | def dense_patch_slices(image_size, patch_size, scan_interval):
'\n Enumerate all slices defining 2D/3D patches of size `patch_size` from an `image_size` input image.\n\n Args:\n image_size (tuple of int): dimensions of image to iterate over\n patch_size (tuple of int): size of patches to generat... | def dense_patch_slices(image_size, patch_size, scan_interval):
'\n Enumerate all slices defining 2D/3D patches of size `patch_size` from an `image_size` input image.\n\n Args:\n image_size (tuple of int): dimensions of image to iterate over\n patch_size (tuple of int): size of patches to generat... |
7144d827d1aee22abe2a85031b09ba701ab100076a0d3b9c4d217d6b2acd603a | def sliding_window_inference(inputs, roi_size, sw_batch_size, predictor):
'Use SlidingWindow method to execute inference.\n\n Args:\n inputs (torch Tensor): input image to be processed (assuming NCHW[D])\n roi_size (list, tuple): the window size to execute SlidingWindow inference.\n sw_batch... | Use SlidingWindow method to execute inference.
Args:
inputs (torch Tensor): input image to be processed (assuming NCHW[D])
roi_size (list, tuple): the window size to execute SlidingWindow inference.
sw_batch_size (int): the batch size to run window slices.
predictor (Callable): given input tensor `patc... | contrib/MedicalSeg/medicalseg/core/infer_window.py | sliding_window_inference | sun222/PaddleSeg | 0 | python | def sliding_window_inference(inputs, roi_size, sw_batch_size, predictor):
'Use SlidingWindow method to execute inference.\n\n Args:\n inputs (torch Tensor): input image to be processed (assuming NCHW[D])\n roi_size (list, tuple): the window size to execute SlidingWindow inference.\n sw_batch... | def sliding_window_inference(inputs, roi_size, sw_batch_size, predictor):
'Use SlidingWindow method to execute inference.\n\n Args:\n inputs (torch Tensor): input image to be processed (assuming NCHW[D])\n roi_size (list, tuple): the window size to execute SlidingWindow inference.\n sw_batch... |
7e025e755bf09e59182db5285e8dcd4c7ba5544dc1fa06f4ca4800720b8f564e | def set_size_mode(self, mode: SizeConstraintStr):
'Set the size mode of the layout.\n\n Args:\n mode: size mode for the layout\n\n Raises:\n InvalidParamError: size mode does not exist\n '
if (mode not in SIZE_CONSTRAINT):
raise InvalidParamError(mode, SIZE_CON... | Set the size mode of the layout.
Args:
mode: size mode for the layout
Raises:
InvalidParamError: size mode does not exist | prettyqt/widgets/layout.py | set_size_mode | phil65/PrettyQt | 7 | python | def set_size_mode(self, mode: SizeConstraintStr):
'Set the size mode of the layout.\n\n Args:\n mode: size mode for the layout\n\n Raises:\n InvalidParamError: size mode does not exist\n '
if (mode not in SIZE_CONSTRAINT):
raise InvalidParamError(mode, SIZE_CON... | def set_size_mode(self, mode: SizeConstraintStr):
'Set the size mode of the layout.\n\n Args:\n mode: size mode for the layout\n\n Raises:\n InvalidParamError: size mode does not exist\n '
if (mode not in SIZE_CONSTRAINT):
raise InvalidParamError(mode, SIZE_CON... |
d31f9d69b1ba200b061aba15d47b93e2628490947fc78c44f2dec7b1995e0502 | def get_size_mode(self) -> SizeConstraintStr:
'Return current size mode.\n\n Returns:\n size mode\n '
return SIZE_CONSTRAINT.inverse[self.sizeConstraint()] | Return current size mode.
Returns:
size mode | prettyqt/widgets/layout.py | get_size_mode | phil65/PrettyQt | 7 | python | def get_size_mode(self) -> SizeConstraintStr:
'Return current size mode.\n\n Returns:\n size mode\n '
return SIZE_CONSTRAINT.inverse[self.sizeConstraint()] | def get_size_mode(self) -> SizeConstraintStr:
'Return current size mode.\n\n Returns:\n size mode\n '
return SIZE_CONSTRAINT.inverse[self.sizeConstraint()]<|docstring|>Return current size mode.
Returns:
size mode<|endoftext|> |
76b93e94c15326eaee0d22da5b39ba7b01a32c590f0f3e9c5cab99fb02edce28 | def set_alignment(self, alignment: constants.AlignmentStr, item: ((QtWidgets.QWidget | QtWidgets.QLayout) | None)=None):
'Set the alignment for widget / layout to alignment.\n\n Returns true if w is found in this layout (not including child layouts).\n\n Args:\n alignment: alignment for the... | Set the alignment for widget / layout to alignment.
Returns true if w is found in this layout (not including child layouts).
Args:
alignment: alignment for the layout
item: set alignment for specific child only
Raises:
InvalidParamError: alignment does not exist | prettyqt/widgets/layout.py | set_alignment | phil65/PrettyQt | 7 | python | def set_alignment(self, alignment: constants.AlignmentStr, item: ((QtWidgets.QWidget | QtWidgets.QLayout) | None)=None):
'Set the alignment for widget / layout to alignment.\n\n Returns true if w is found in this layout (not including child layouts).\n\n Args:\n alignment: alignment for the... | def set_alignment(self, alignment: constants.AlignmentStr, item: ((QtWidgets.QWidget | QtWidgets.QLayout) | None)=None):
'Set the alignment for widget / layout to alignment.\n\n Returns true if w is found in this layout (not including child layouts).\n\n Args:\n alignment: alignment for the... |
89e9670cad8dc02bfb002290bb9053ddff5d4be649e15ce5fce3e07d967054f5 | def _zero_pad_1d(self, embedding: torch.FloatTensor):
'Pads a 1-D tensor with zeros to the right'
batch_size = embedding.size(0)
padding = torch.zeros(batch_size, (self.d - embedding.size((- 1))), device=self.device)
return torch.cat([embedding, padding], dim=(- 1)) | Pads a 1-D tensor with zeros to the right | learning/models/embedder.py | _zero_pad_1d | samlanka/oracle | 2 | python | def _zero_pad_1d(self, embedding: torch.FloatTensor):
batch_size = embedding.size(0)
padding = torch.zeros(batch_size, (self.d - embedding.size((- 1))), device=self.device)
return torch.cat([embedding, padding], dim=(- 1)) | def _zero_pad_1d(self, embedding: torch.FloatTensor):
batch_size = embedding.size(0)
padding = torch.zeros(batch_size, (self.d - embedding.size((- 1))), device=self.device)
return torch.cat([embedding, padding], dim=(- 1))<|docstring|>Pads a 1-D tensor with zeros to the right<|endoftext|> |
006f3ece1f13f59a721fd0ec62c3e5b736202eafdae8009ec827593e80379771 | def build_sampler(cfg):
'Build sampler\n\n Args:\n cfg(mmcv.Config): Sample cfg\n\n Returns:\n obj: sampler\n '
return build(cfg, SAMPLER) | Build sampler
Args:
cfg(mmcv.Config): Sample cfg
Returns:
obj: sampler | davarocr/davarocr/davar_common/datasets/builder.py | build_sampler | CuteyThyme/MultiModal_IE | 0 | python | def build_sampler(cfg):
'Build sampler\n\n Args:\n cfg(mmcv.Config): Sample cfg\n\n Returns:\n obj: sampler\n '
return build(cfg, SAMPLER) | def build_sampler(cfg):
'Build sampler\n\n Args:\n cfg(mmcv.Config): Sample cfg\n\n Returns:\n obj: sampler\n '
return build(cfg, SAMPLER)<|docstring|>Build sampler
Args:
cfg(mmcv.Config): Sample cfg
Returns:
obj: sampler<|endoftext|> |
fd4419092fbfc56643c93f0319762b023aaef718f56698a8b544a20fe807245e | def davar_build_dataloader(dataset, samples_per_gpu=1, workers_per_gpu=1, sampler_type=None, num_gpus=1, dist=True, shuffle=True, seed=None, **kwargs):
'\n\n Args:\n dataset (Dataset): dataset\n samples_per_gpu (int): image numbers on each gpu\n workers_per_gpu (int): workers each gpu\n ... | Args:
dataset (Dataset): dataset
samples_per_gpu (int): image numbers on each gpu
workers_per_gpu (int): workers each gpu
sampler_type (optional | dict): sampler parameter
num_gpus (int): numbers of gpu
dist (boolean): whether to use distributed mode
shuffle (boolean): whether to shuffle the... | davarocr/davarocr/davar_common/datasets/builder.py | davar_build_dataloader | CuteyThyme/MultiModal_IE | 0 | python | def davar_build_dataloader(dataset, samples_per_gpu=1, workers_per_gpu=1, sampler_type=None, num_gpus=1, dist=True, shuffle=True, seed=None, **kwargs):
'\n\n Args:\n dataset (Dataset): dataset\n samples_per_gpu (int): image numbers on each gpu\n workers_per_gpu (int): workers each gpu\n ... | def davar_build_dataloader(dataset, samples_per_gpu=1, workers_per_gpu=1, sampler_type=None, num_gpus=1, dist=True, shuffle=True, seed=None, **kwargs):
'\n\n Args:\n dataset (Dataset): dataset\n samples_per_gpu (int): image numbers on each gpu\n workers_per_gpu (int): workers each gpu\n ... |
4a5b1a6d5b05cb3ad6eb1cdff19d8a03097bb74b681baf5b05f6efe59363088c | def _concat_dataset(cfg, default_args=None):
'\n\n Args:\n cfg (cfg): model config file\n default_args (args): back parameter\n\n Returns:\n concat all the dataset in config file\n\n '
ann_files = cfg['ann_file']
img_prefixes = cfg.get('img_prefix', None)
seg_prefixes = cfg... | Args:
cfg (cfg): model config file
default_args (args): back parameter
Returns:
concat all the dataset in config file | davarocr/davarocr/davar_common/datasets/builder.py | _concat_dataset | CuteyThyme/MultiModal_IE | 0 | python | def _concat_dataset(cfg, default_args=None):
'\n\n Args:\n cfg (cfg): model config file\n default_args (args): back parameter\n\n Returns:\n concat all the dataset in config file\n\n '
ann_files = cfg['ann_file']
img_prefixes = cfg.get('img_prefix', None)
seg_prefixes = cfg... | def _concat_dataset(cfg, default_args=None):
'\n\n Args:\n cfg (cfg): model config file\n default_args (args): back parameter\n\n Returns:\n concat all the dataset in config file\n\n '
ann_files = cfg['ann_file']
img_prefixes = cfg.get('img_prefix', None)
seg_prefixes = cfg... |
b981a01aa03b2e936974b968e8fe503aeb172b77bc960319ddcc2c6ea5be4d44 | def davar_build_dataset(cfg, default_args=None):
'\n\n Args:\n cfg (cfg): model config file\n default_args (args): back parameter\n\n Returns:\n build the dataset for training\n\n '
from mmdet.datasets.dataset_wrappers import ConcatDataset, RepeatDataset, ClassBalancedDataset
f... | Args:
cfg (cfg): model config file
default_args (args): back parameter
Returns:
build the dataset for training | davarocr/davarocr/davar_common/datasets/builder.py | davar_build_dataset | CuteyThyme/MultiModal_IE | 0 | python | def davar_build_dataset(cfg, default_args=None):
'\n\n Args:\n cfg (cfg): model config file\n default_args (args): back parameter\n\n Returns:\n build the dataset for training\n\n '
from mmdet.datasets.dataset_wrappers import ConcatDataset, RepeatDataset, ClassBalancedDataset
f... | def davar_build_dataset(cfg, default_args=None):
'\n\n Args:\n cfg (cfg): model config file\n default_args (args): back parameter\n\n Returns:\n build the dataset for training\n\n '
from mmdet.datasets.dataset_wrappers import ConcatDataset, RepeatDataset, ClassBalancedDataset
f... |
32d53f789b9c7e0328bf9123df7abe572df61c5261d835ad7a192e5cbf800631 | def parameter_align(cfg):
' pipeline parameter alignment\n Args:\n cfg (config): model pipeline config\n\n Returns:\n\n '
align_para = list()
if isinstance(cfg['batch_ratios'], (float, int)):
batch_ratios = [cfg['batch_ratios']]
elif isinstance(cfg['batch_ratios'], (tuple, list))... | pipeline parameter alignment
Args:
cfg (config): model pipeline config
Returns: | davarocr/davarocr/davar_common/datasets/builder.py | parameter_align | CuteyThyme/MultiModal_IE | 0 | python | def parameter_align(cfg):
' pipeline parameter alignment\n Args:\n cfg (config): model pipeline config\n\n Returns:\n\n '
align_para = list()
if isinstance(cfg['batch_ratios'], (float, int)):
batch_ratios = [cfg['batch_ratios']]
elif isinstance(cfg['batch_ratios'], (tuple, list))... | def parameter_align(cfg):
' pipeline parameter alignment\n Args:\n cfg (config): model pipeline config\n\n Returns:\n\n '
align_para = list()
if isinstance(cfg['batch_ratios'], (float, int)):
batch_ratios = [cfg['batch_ratios']]
elif isinstance(cfg['batch_ratios'], (tuple, list))... |
ddf62bf1039713a8e8e0ed94e51404271c2a6307d7be3cbd818cc758af533d83 | def Get_timestamp():
'Return time & date at moment t'
return time.asctime(time.localtime()) | Return time & date at moment t | main.py | Get_timestamp | SlothKun/Shopopop_autonotif | 0 | python | def Get_timestamp():
return time.asctime(time.localtime()) | def Get_timestamp():
return time.asctime(time.localtime())<|docstring|>Return time & date at moment t<|endoftext|> |
e941bdb8e72797a4b22af411301444836679d7e23c30026ae19c121962301154 | def Get_foregroundapp(device):
'Return the foreground app'
return device.shell("dumpsys activity recents | grep 'Recent #0' | cut -d= -f2 | sed 's| .*||' | cut -d '/' -f1").strip() | Return the foreground app | main.py | Get_foregroundapp | SlothKun/Shopopop_autonotif | 0 | python | def Get_foregroundapp(device):
return device.shell("dumpsys activity recents | grep 'Recent #0' | cut -d= -f2 | sed 's| .*||' | cut -d '/' -f1").strip() | def Get_foregroundapp(device):
return device.shell("dumpsys activity recents | grep 'Recent #0' | cut -d= -f2 | sed 's| .*||' | cut -d '/' -f1").strip()<|docstring|>Return the foreground app<|endoftext|> |
15360511ebbbb1716b9f496a4258e1206d1f3a1759204e0e59e00dd6089141cb | def Screen(device):
'Make a screenshot of the screen and save it on the computer'
with open('phonescreen.png', 'wb') as fp:
fp.write(device.screencap()) | Make a screenshot of the screen and save it on the computer | main.py | Screen | SlothKun/Shopopop_autonotif | 0 | python | def Screen(device):
with open('phonescreen.png', 'wb') as fp:
fp.write(device.screencap()) | def Screen(device):
with open('phonescreen.png', 'wb') as fp:
fp.write(device.screencap())<|docstring|>Make a screenshot of the screen and save it on the computer<|endoftext|> |
328a62eef37f9554322215cec5229ff41735ada4723a7508669218f17af3d701 | def Get_refreshcoordinates():
'\n Search the refresh button presence by checking the line at the 2/3 of the top menu\n '
try:
img = Image.open('phonescreen.png')
rgb_img = img.load()
i = 1
pixelstart = rgb_img[(0, 0)]
newpixel = rgb_img[(0, i)]
while (pixels... | Search the refresh button presence by checking the line at the 2/3 of the top menu | main.py | Get_refreshcoordinates | SlothKun/Shopopop_autonotif | 0 | python | def Get_refreshcoordinates():
'\n \n '
try:
img = Image.open('phonescreen.png')
rgb_img = img.load()
i = 1
pixelstart = rgb_img[(0, 0)]
newpixel = rgb_img[(0, i)]
while (pixelstart == newpixel):
newpixel = rgb_img[(0, i)]
i += 1
... | def Get_refreshcoordinates():
'\n \n '
try:
img = Image.open('phonescreen.png')
rgb_img = img.load()
i = 1
pixelstart = rgb_img[(0, 0)]
newpixel = rgb_img[(0, i)]
while (pixelstart == newpixel):
newpixel = rgb_img[(0, i)]
i += 1
... |
c7ccd9bb4e23fca3696d1cfc53eb29cff9033d4cdb973dcd86da90520f580091 | def Get_checkdeliv():
"\n Check screen for the right pixel color corresponding to the delivery's button\n Start from the middle of the screen as the button will always be on the bottom of it\n "
try:
img = Image.open('phonescreen.png')
rgb_img = img.load()
x = int((img.size[0] /... | Check screen for the right pixel color corresponding to the delivery's button
Start from the middle of the screen as the button will always be on the bottom of it | main.py | Get_checkdeliv | SlothKun/Shopopop_autonotif | 0 | python | def Get_checkdeliv():
"\n Check screen for the right pixel color corresponding to the delivery's button\n Start from the middle of the screen as the button will always be on the bottom of it\n "
try:
img = Image.open('phonescreen.png')
rgb_img = img.load()
x = int((img.size[0] /... | def Get_checkdeliv():
"\n Check screen for the right pixel color corresponding to the delivery's button\n Start from the middle of the screen as the button will always be on the bottom of it\n "
try:
img = Image.open('phonescreen.png')
rgb_img = img.load()
x = int((img.size[0] /... |
da679392ce90c154c3aeacdd4265d55c55544d9bf329824fbdc83ff137fbde38 | def transform(item_paths, output_dir, experiment_code, compresslevel=0):
'Read medable csv and writes gen3 json.'
file_emitter = emitter('submitted_file', output_dir=output_dir)
with open(item_paths[0], newline='') as csvfile:
reader = csv.DictReader(csvfile)
for row in reader:
i... | Read medable csv and writes gen3 json. | transform/hop/file.py | transform | ohsu-comp-bio/gen3-etl | 1 | python | def transform(item_paths, output_dir, experiment_code, compresslevel=0):
file_emitter = emitter('submitted_file', output_dir=output_dir)
with open(item_paths[0], newline=) as csvfile:
reader = csv.DictReader(csvfile)
for row in reader:
if exclude_row(row):
contin... | def transform(item_paths, output_dir, experiment_code, compresslevel=0):
file_emitter = emitter('submitted_file', output_dir=output_dir)
with open(item_paths[0], newline=) as csvfile:
reader = csv.DictReader(csvfile)
for row in reader:
if exclude_row(row):
contin... |
3dd748ea2b0044be6b00c4c6e6d74429d619a1415f7f8f4bf653af9aa72dd43a | def rest_get(self, suburi):
'REST GET'
return self.rest_client.get(path=suburi) | REST GET | examples/Rest/_restobject.py | rest_get | HewlettPackard/python-ilorest-library-EOL | 27 | python | def rest_get(self, suburi):
return self.rest_client.get(path=suburi) | def rest_get(self, suburi):
return self.rest_client.get(path=suburi)<|docstring|>REST GET<|endoftext|> |
5bfe3f968c9aaf84d432f13130c839602439a4501778d0530eacb0f60cc61ceb | def rest_patch(self, suburi, request_body, optionalpassword=None):
'REST PATCH'
sys.stdout.write((((('PATCH ' + str(request_body)) + ' to ') + suburi) + '\n'))
response = self.rest_client.patch(path=suburi, body=request_body, optionalpassword=optionalpassword)
sys.stdout.write((('PATCH response = ' + st... | REST PATCH | examples/Rest/_restobject.py | rest_patch | HewlettPackard/python-ilorest-library-EOL | 27 | python | def rest_patch(self, suburi, request_body, optionalpassword=None):
sys.stdout.write((((('PATCH ' + str(request_body)) + ' to ') + suburi) + '\n'))
response = self.rest_client.patch(path=suburi, body=request_body, optionalpassword=optionalpassword)
sys.stdout.write((('PATCH response = ' + str(response.s... | def rest_patch(self, suburi, request_body, optionalpassword=None):
sys.stdout.write((((('PATCH ' + str(request_body)) + ' to ') + suburi) + '\n'))
response = self.rest_client.patch(path=suburi, body=request_body, optionalpassword=optionalpassword)
sys.stdout.write((('PATCH response = ' + str(response.s... |
7a68f7be376f498d3d4235432eacc395b20bf2f206ae464b636cd04491967b18 | def rest_put(self, suburi, request_body, optionalpassword=None):
'REST PUT'
sys.stdout.write((((('PUT ' + str(request_body)) + ' to ') + suburi) + '\n'))
response = self.rest_client.put(path=suburi, body=request_body, optionalpassword=optionalpassword)
sys.stdout.write((('PUT response = ' + str(response... | REST PUT | examples/Rest/_restobject.py | rest_put | HewlettPackard/python-ilorest-library-EOL | 27 | python | def rest_put(self, suburi, request_body, optionalpassword=None):
sys.stdout.write((((('PUT ' + str(request_body)) + ' to ') + suburi) + '\n'))
response = self.rest_client.put(path=suburi, body=request_body, optionalpassword=optionalpassword)
sys.stdout.write((('PUT response = ' + str(response.status)) ... | def rest_put(self, suburi, request_body, optionalpassword=None):
sys.stdout.write((((('PUT ' + str(request_body)) + ' to ') + suburi) + '\n'))
response = self.rest_client.put(path=suburi, body=request_body, optionalpassword=optionalpassword)
sys.stdout.write((('PUT response = ' + str(response.status)) ... |
c141d8a3bcd15483e631e50bc90e9532f59d9e3e6f42eaa70d94d46c5b3acd6a | def rest_post(self, suburi, request_body):
'REST POST'
sys.stdout.write((((('POST ' + str(request_body)) + ' to ') + suburi) + '\n'))
response = self.rest_client.post(path=suburi, body=request_body)
sys.stdout.write((('POST response = ' + str(response.status)) + '\n'))
return response | REST POST | examples/Rest/_restobject.py | rest_post | HewlettPackard/python-ilorest-library-EOL | 27 | python | def rest_post(self, suburi, request_body):
sys.stdout.write((((('POST ' + str(request_body)) + ' to ') + suburi) + '\n'))
response = self.rest_client.post(path=suburi, body=request_body)
sys.stdout.write((('POST response = ' + str(response.status)) + '\n'))
return response | def rest_post(self, suburi, request_body):
sys.stdout.write((((('POST ' + str(request_body)) + ' to ') + suburi) + '\n'))
response = self.rest_client.post(path=suburi, body=request_body)
sys.stdout.write((('POST response = ' + str(response.status)) + '\n'))
return response<|docstring|>REST POST<|en... |
c697c89ec1ea15a0b2f318990d61a9599a90f72194aa0ca92cc64abd27602251 | def rest_delete(self, suburi):
'REST DELETE'
sys.stdout.write((('DELETE ' + suburi) + '\n'))
response = self.rest_client.delete(path=suburi)
sys.stdout.write((('DELETE response = ' + str(response.status)) + '\n'))
return response | REST DELETE | examples/Rest/_restobject.py | rest_delete | HewlettPackard/python-ilorest-library-EOL | 27 | python | def rest_delete(self, suburi):
sys.stdout.write((('DELETE ' + suburi) + '\n'))
response = self.rest_client.delete(path=suburi)
sys.stdout.write((('DELETE response = ' + str(response.status)) + '\n'))
return response | def rest_delete(self, suburi):
sys.stdout.write((('DELETE ' + suburi) + '\n'))
response = self.rest_client.delete(path=suburi)
sys.stdout.write((('DELETE response = ' + str(response.status)) + '\n'))
return response<|docstring|>REST DELETE<|endoftext|> |
d7752b9671eab837061798b193d2517d0d8305ad6456f3c2f6297af370bb188d | def __hash__(self):
'\n Return hash(self).\n '
return None | Return hash(self). | nuke_stubs/nuke/nuke_classes/ToolBar.py | __hash__ | sisoe24/Nuke-Python-Stubs | 1 | python | def __hash__(self):
'\n \n '
return None | def __hash__(self):
'\n \n '
return None<|docstring|>Return hash(self).<|endoftext|> |
cf416fac323b173d338cb8363e1aababbccc3f14968a8783bd9f08cc63ba7b0f | def __new__(self, *args, **kwargs):
'\n Create and return a new object. See help(type) for accurate signature.\n '
return None | Create and return a new object. See help(type) for accurate signature. | nuke_stubs/nuke/nuke_classes/ToolBar.py | __new__ | sisoe24/Nuke-Python-Stubs | 1 | python | def __new__(self, *args, **kwargs):
'\n \n '
return None | def __new__(self, *args, **kwargs):
'\n \n '
return None<|docstring|>Create and return a new object. See help(type) for accurate signature.<|endoftext|> |
1d41eb0ac8fb88bfc9e6fd9bd9fb644ca69dadfd2bd3871effb9f205a2c2f4f6 | def addCommand(self, name: str, command: str=None, shortcut: str=None, icon: str=None, tooltip: str=None, index: Number=None, readonly: bool=None):
'\n self.addCommand(name, command, shortcut, icon, tooltip, index, readonly) -> The menu/toolbar item that was added to hold the command.\n Add a new comm... | self.addCommand(name, command, shortcut, icon, tooltip, index, readonly) -> The menu/toolbar item that was added to hold the command.
Add a new command to this menu/toolbar. Note that when invoked, the command is automatically enclosed in an undo group, so that undo/redo functionality works. Optional arguments can be s... | nuke_stubs/nuke/nuke_classes/ToolBar.py | addCommand | sisoe24/Nuke-Python-Stubs | 1 | python | def addCommand(self, name: str, command: str=None, shortcut: str=None, icon: str=None, tooltip: str=None, index: Number=None, readonly: bool=None):
'\n self.addCommand(name, command, shortcut, icon, tooltip, index, readonly) -> The menu/toolbar item that was added to hold the command.\n Add a new comm... | def addCommand(self, name: str, command: str=None, shortcut: str=None, icon: str=None, tooltip: str=None, index: Number=None, readonly: bool=None):
'\n self.addCommand(name, command, shortcut, icon, tooltip, index, readonly) -> The menu/toolbar item that was added to hold the command.\n Add a new comm... |
69f9ce1b7b78d984ed8897544b839b603498b6a89d9cd5507ca53516965ea008 | def addMenu(self, **kwargs):
'\n self.addMenu(**kwargs) -> The submenu that was added.\n Add a new submenu.\n @param **kwargs The following keyword arguments are accepted:\n name The name for the menu/toolbar item\n icon An icon for the me... | self.addMenu(**kwargs) -> The submenu that was added.
Add a new submenu.
@param **kwargs The following keyword arguments are accepted:
name The name for the menu/toolbar item
icon An icon for the menu. Loaded from the nuke search path.
tooltip The tooltip text... | nuke_stubs/nuke/nuke_classes/ToolBar.py | addMenu | sisoe24/Nuke-Python-Stubs | 1 | python | def addMenu(self, **kwargs):
'\n self.addMenu(**kwargs) -> The submenu that was added.\n Add a new submenu.\n @param **kwargs The following keyword arguments are accepted:\n name The name for the menu/toolbar item\n icon An icon for the me... | def addMenu(self, **kwargs):
'\n self.addMenu(**kwargs) -> The submenu that was added.\n Add a new submenu.\n @param **kwargs The following keyword arguments are accepted:\n name The name for the menu/toolbar item\n icon An icon for the me... |
fcc607853e3865a3f7ecfcd2ff72c6f3ddf62b470c223e8cf267d2e06ebe68f6 | def clearMenu(self):
'\n self.clearMenu() \n Clears a menu.\n @param **kwargs The following keyword arguments are accepted:\n name The name for the menu/toolbar item\n @return: true if cleared, false if menu not found \n '
return bool() | self.clearMenu()
Clears a menu.
@param **kwargs The following keyword arguments are accepted:
name The name for the menu/toolbar item
@return: true if cleared, false if menu not found | nuke_stubs/nuke/nuke_classes/ToolBar.py | clearMenu | sisoe24/Nuke-Python-Stubs | 1 | python | def clearMenu(self):
'\n self.clearMenu() \n Clears a menu.\n @param **kwargs The following keyword arguments are accepted:\n name The name for the menu/toolbar item\n @return: true if cleared, false if menu not found \n '
return bool() | def clearMenu(self):
'\n self.clearMenu() \n Clears a menu.\n @param **kwargs The following keyword arguments are accepted:\n name The name for the menu/toolbar item\n @return: true if cleared, false if menu not found \n '
return bool()<|docstring|>... |
df111cc113c04d5cb5ae664f22064c81b3e9b8c9747516f7dd7a9e3fb561b067 | def addSeparator(self, **kwargs):
'\n self.addSeparator(**kwargs) -> The separator that was created.\n Add a separator to this menu/toolbar.\n @param **kwargs The following keyword arguments are accepted:\n index The position to insert the new separator in, in the menu/toolbar.\n ... | self.addSeparator(**kwargs) -> The separator that was created.
Add a separator to this menu/toolbar.
@param **kwargs The following keyword arguments are accepted:
index The position to insert the new separator in, in the menu/toolbar.
@return: The separator that was created. | nuke_stubs/nuke/nuke_classes/ToolBar.py | addSeparator | sisoe24/Nuke-Python-Stubs | 1 | python | def addSeparator(self, **kwargs):
'\n self.addSeparator(**kwargs) -> The separator that was created.\n Add a separator to this menu/toolbar.\n @param **kwargs The following keyword arguments are accepted:\n index The position to insert the new separator in, in the menu/toolbar.\n ... | def addSeparator(self, **kwargs):
'\n self.addSeparator(**kwargs) -> The separator that was created.\n Add a separator to this menu/toolbar.\n @param **kwargs The following keyword arguments are accepted:\n index The position to insert the new separator in, in the menu/toolbar.\n ... |
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