blob_id stringlengths 40 40 | bodies listlengths 2 6 | bodies_text stringlengths 196 6.73k | class_docstring stringlengths 0 700 | class_name stringlengths 1 86 | detected_licenses listlengths 0 45 | format_version stringclasses 1
value | full_text stringlengths 438 7.52k | id stringlengths 40 40 | length_bytes int64 506 50k | license_type stringclasses 2
values | methods listlengths 2 6 | n_methods int64 2 6 | original_id stringlengths 38 40 ⌀ | prompt stringlengths 153 4.25k | prompted_full_text stringlengths 645 10.7k | revision_id stringlengths 40 40 | skeleton stringlengths 162 4.34k | snapshot_name stringclasses 1
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value | source_path stringlengths 4 177 | source_repo stringlengths 6 110 | split stringclasses 1
value | star_events_count int64 0 209k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
99c8c384b081271c6a6599b17906b01e1fa62678 | [
"actor_ids = Infraction.objects.order_by().values_list('actor').distinct()\nactors = User.objects.filter(id__in=actor_ids)\nreturn ((a.id, a.username) for a in actors)",
"if not self.value():\n return None\nreturn queryset.filter(actor__id=self.value())"
] | <|body_start_0|>
actor_ids = Infraction.objects.order_by().values_list('actor').distinct()
actors = User.objects.filter(id__in=actor_ids)
return ((a.id, a.username) for a in actors)
<|end_body_0|>
<|body_start_1|>
if not self.value():
return None
return queryset.filt... | Actor Filter for Infraction Admin list page. | InfractionActorFilter | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InfractionActorFilter:
"""Actor Filter for Infraction Admin list page."""
def lookups(self, request: HttpRequest, model: NominationAdmin) -> Iterable[tuple[int, str]]:
"""Selectable values for viewer to filter by."""
<|body_0|>
def queryset(self, request: HttpRequest, qu... | stack_v2_sparse_classes_36k_train_010300 | 14,240 | permissive | [
{
"docstring": "Selectable values for viewer to filter by.",
"name": "lookups",
"signature": "def lookups(self, request: HttpRequest, model: NominationAdmin) -> Iterable[tuple[int, str]]"
},
{
"docstring": "Query to filter the list of Users against.",
"name": "queryset",
"signature": "de... | 2 | null | Implement the Python class `InfractionActorFilter` described below.
Class description:
Actor Filter for Infraction Admin list page.
Method signatures and docstrings:
- def lookups(self, request: HttpRequest, model: NominationAdmin) -> Iterable[tuple[int, str]]: Selectable values for viewer to filter by.
- def queryse... | Implement the Python class `InfractionActorFilter` described below.
Class description:
Actor Filter for Infraction Admin list page.
Method signatures and docstrings:
- def lookups(self, request: HttpRequest, model: NominationAdmin) -> Iterable[tuple[int, str]]: Selectable values for viewer to filter by.
- def queryse... | cb6326cabee6570a5725702cb2893ae39f752279 | <|skeleton|>
class InfractionActorFilter:
"""Actor Filter for Infraction Admin list page."""
def lookups(self, request: HttpRequest, model: NominationAdmin) -> Iterable[tuple[int, str]]:
"""Selectable values for viewer to filter by."""
<|body_0|>
def queryset(self, request: HttpRequest, qu... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class InfractionActorFilter:
"""Actor Filter for Infraction Admin list page."""
def lookups(self, request: HttpRequest, model: NominationAdmin) -> Iterable[tuple[int, str]]:
"""Selectable values for viewer to filter by."""
actor_ids = Infraction.objects.order_by().values_list('actor').distinct(... | the_stack_v2_python_sparse | pydis_site/apps/api/admin.py | python-discord/site | train | 746 |
ba75b39a7eab16a2f69e24dacad66033d6c364ee | [
"tipocontato = get_a_contacttype(id)\nif not tipocontato:\n api.abort(404)\nelse:\n return tipocontato",
"tipocontato = get_a_contacttype(id)\nif not tipocontato:\n api.abort(404)\nelse:\n data = request.json\n return update_contacttype(tipocontato, data=data)"
] | <|body_start_0|>
tipocontato = get_a_contacttype(id)
if not tipocontato:
api.abort(404)
else:
return tipocontato
<|end_body_0|>
<|body_start_1|>
tipocontato = get_a_contacttype(id)
if not tipocontato:
api.abort(404)
else:
d... | Contato | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Contato:
def get(self, id):
"""Obtem informações de um tipo contato com base no seu id"""
<|body_0|>
def patch(self, id):
"""Atualiza um tipo contato Obs: para inativar, coloque 'ativo': false"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
tipocont... | stack_v2_sparse_classes_36k_train_010301 | 2,623 | no_license | [
{
"docstring": "Obtem informações de um tipo contato com base no seu id",
"name": "get",
"signature": "def get(self, id)"
},
{
"docstring": "Atualiza um tipo contato Obs: para inativar, coloque 'ativo': false",
"name": "patch",
"signature": "def patch(self, id)"
}
] | 2 | stack_v2_sparse_classes_30k_train_002285 | Implement the Python class `Contato` described below.
Class description:
Implement the Contato class.
Method signatures and docstrings:
- def get(self, id): Obtem informações de um tipo contato com base no seu id
- def patch(self, id): Atualiza um tipo contato Obs: para inativar, coloque 'ativo': false | Implement the Python class `Contato` described below.
Class description:
Implement the Contato class.
Method signatures and docstrings:
- def get(self, id): Obtem informações de um tipo contato com base no seu id
- def patch(self, id): Atualiza um tipo contato Obs: para inativar, coloque 'ativo': false
<|skeleton|>
... | a86fcb085af8567a661d47876f8b9f13d7b062a9 | <|skeleton|>
class Contato:
def get(self, id):
"""Obtem informações de um tipo contato com base no seu id"""
<|body_0|>
def patch(self, id):
"""Atualiza um tipo contato Obs: para inativar, coloque 'ativo': false"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Contato:
def get(self, id):
"""Obtem informações de um tipo contato com base no seu id"""
tipocontato = get_a_contacttype(id)
if not tipocontato:
api.abort(404)
else:
return tipocontato
def patch(self, id):
"""Atualiza um tipo contato Obs: p... | the_stack_v2_python_sparse | backend/app/main/controller/tipocontato_controller.py | AnderSilva/ozomali | train | 1 | |
1436eeb94d071103defcddc3abdb7610236b3b02 | [
"if obj.sender:\n serializer = UserSerializer(obj.sender, context=self.context, fields=['id', 'username', 'email', 'name', 'last_name', 'second_last_name', 'photo'])\n return serializer.data",
"if obj.target:\n serializer = NotificationTargetSerializer(obj, context=self.context)\n return serializer.da... | <|body_start_0|>
if obj.sender:
serializer = UserSerializer(obj.sender, context=self.context, fields=['id', 'username', 'email', 'name', 'last_name', 'second_last_name', 'photo'])
return serializer.data
<|end_body_0|>
<|body_start_1|>
if obj.target:
serializer = Noti... | Serializer class for the ```tandlr.notifications.models.Notification``` model. | NotificationSerializer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NotificationSerializer:
"""Serializer class for the ```tandlr.notifications.models.Notification``` model."""
def get_sender(self, obj):
"""Returns the notification's sender serialized with the minimal required fields."""
<|body_0|>
def get_target(self, obj):
"""R... | stack_v2_sparse_classes_36k_train_010302 | 3,769 | permissive | [
{
"docstring": "Returns the notification's sender serialized with the minimal required fields.",
"name": "get_sender",
"signature": "def get_sender(self, obj)"
},
{
"docstring": "Returns the notification's target serialized with the minimal required fields.",
"name": "get_target",
"signa... | 2 | null | Implement the Python class `NotificationSerializer` described below.
Class description:
Serializer class for the ```tandlr.notifications.models.Notification``` model.
Method signatures and docstrings:
- def get_sender(self, obj): Returns the notification's sender serialized with the minimal required fields.
- def get... | Implement the Python class `NotificationSerializer` described below.
Class description:
Serializer class for the ```tandlr.notifications.models.Notification``` model.
Method signatures and docstrings:
- def get_sender(self, obj): Returns the notification's sender serialized with the minimal required fields.
- def get... | 7349ce18f56658d67daedf5e1abb352b5c15a029 | <|skeleton|>
class NotificationSerializer:
"""Serializer class for the ```tandlr.notifications.models.Notification``` model."""
def get_sender(self, obj):
"""Returns the notification's sender serialized with the minimal required fields."""
<|body_0|>
def get_target(self, obj):
"""R... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NotificationSerializer:
"""Serializer class for the ```tandlr.notifications.models.Notification``` model."""
def get_sender(self, obj):
"""Returns the notification's sender serialized with the minimal required fields."""
if obj.sender:
serializer = UserSerializer(obj.sender, c... | the_stack_v2_python_sparse | src/tandlr/notifications/serializers.py | shrmoud/schoolapp | train | 0 |
a269b48ae28189a78ab5a3872f5a97437aa33052 | [
"self.act = eval(act)\nself.actstr = act\nself.n_inpl = n_inpl\nself.n_inpr = n_inpr\nself.n_out = n_out\nwbound = np.sqrt(9.0 / (n_inpl + n_inpr + n_out))\nW_values = rng.uniform(low=-wbound, high=wbound, size=(n_inpl, n_inpr, n_out))\nW_values = np.asarray(W_values, dtype=theano.config.floatX)\nself.W = theano.sh... | <|body_start_0|>
self.act = eval(act)
self.actstr = act
self.n_inpl = n_inpl
self.n_inpr = n_inpr
self.n_out = n_out
wbound = np.sqrt(9.0 / (n_inpl + n_inpr + n_out))
W_values = rng.uniform(low=-wbound, high=wbound, size=(n_inpl, n_inpr, n_out))
W_values =... | Class for a layer with bilinear interaction (n-mode vector-tensor product) on two input vectors with a tensor of parameters. | LayerBilinear | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LayerBilinear:
"""Class for a layer with bilinear interaction (n-mode vector-tensor product) on two input vectors with a tensor of parameters."""
def __init__(self, rng, act, n_inpl, n_inpr, n_out, tag=''):
"""Constructor. :param rng: numpy.random module for number generation. :param... | stack_v2_sparse_classes_36k_train_010303 | 46,645 | permissive | [
{
"docstring": "Constructor. :param rng: numpy.random module for number generation. :param act: name of the activation function ('lin', 'rect', 'tanh' or 'sigm'). :param n_inpl: dimension of the 'left' input. :param n_inpr: dimension of the 'right' input. :param n_out: output dimension. :param tag: name of the ... | 3 | stack_v2_sparse_classes_30k_train_001551 | Implement the Python class `LayerBilinear` described below.
Class description:
Class for a layer with bilinear interaction (n-mode vector-tensor product) on two input vectors with a tensor of parameters.
Method signatures and docstrings:
- def __init__(self, rng, act, n_inpl, n_inpr, n_out, tag=''): Constructor. :par... | Implement the Python class `LayerBilinear` described below.
Class description:
Class for a layer with bilinear interaction (n-mode vector-tensor product) on two input vectors with a tensor of parameters.
Method signatures and docstrings:
- def __init__(self, rng, act, n_inpl, n_inpr, n_out, tag=''): Constructor. :par... | 54b4c07fb9cf39a0fc84f5e384a9fc855f9d016f | <|skeleton|>
class LayerBilinear:
"""Class for a layer with bilinear interaction (n-mode vector-tensor product) on two input vectors with a tensor of parameters."""
def __init__(self, rng, act, n_inpl, n_inpr, n_out, tag=''):
"""Constructor. :param rng: numpy.random module for number generation. :param... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LayerBilinear:
"""Class for a layer with bilinear interaction (n-mode vector-tensor product) on two input vectors with a tensor of parameters."""
def __init__(self, rng, act, n_inpl, n_inpr, n_out, tag=''):
"""Constructor. :param rng: numpy.random module for number generation. :param act: name of... | the_stack_v2_python_sparse | SME/model.py | thjashin/kblearn | train | 3 |
19a9ba593a2291e326679f61412abae28c0f07cc | [
"super().__init__(nup, ndown, cuda)\nself.cusp_weights = None\nself.fc1 = nn.Linear(1, size1, bias=False)\nself.fc2 = nn.Linear(size1, size2, bias=False)\nself.fc3 = nn.Linear(size2, 1, bias=False)\neps = 1e-06\nself.fc1.weight.data *= eps\nself.fc2.weight.data *= eps\nself.fc3.weight.data *= eps\nself.nl_func = ac... | <|body_start_0|>
super().__init__(nup, ndown, cuda)
self.cusp_weights = None
self.fc1 = nn.Linear(1, size1, bias=False)
self.fc2 = nn.Linear(size1, size2, bias=False)
self.fc3 = nn.Linear(size2, 1, bias=False)
eps = 1e-06
self.fc1.weight.data *= eps
self.f... | FullyConnectedJastrowKernel | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FullyConnectedJastrowKernel:
def __init__(self, nup, ndown, cuda, size1=16, size2=8, activation=torch.nn.Sigmoid(), include_cusp_weight=True):
"""Defines a fully connected jastrow factors."""
<|body_0|>
def get_var_weight(self):
"""define the variational weight."""
... | stack_v2_sparse_classes_36k_train_010304 | 3,241 | permissive | [
{
"docstring": "Defines a fully connected jastrow factors.",
"name": "__init__",
"signature": "def __init__(self, nup, ndown, cuda, size1=16, size2=8, activation=torch.nn.Sigmoid(), include_cusp_weight=True)"
},
{
"docstring": "define the variational weight.",
"name": "get_var_weight",
"... | 4 | stack_v2_sparse_classes_30k_train_019225 | Implement the Python class `FullyConnectedJastrowKernel` described below.
Class description:
Implement the FullyConnectedJastrowKernel class.
Method signatures and docstrings:
- def __init__(self, nup, ndown, cuda, size1=16, size2=8, activation=torch.nn.Sigmoid(), include_cusp_weight=True): Defines a fully connected ... | Implement the Python class `FullyConnectedJastrowKernel` described below.
Class description:
Implement the FullyConnectedJastrowKernel class.
Method signatures and docstrings:
- def __init__(self, nup, ndown, cuda, size1=16, size2=8, activation=torch.nn.Sigmoid(), include_cusp_weight=True): Defines a fully connected ... | 439a79e97ee63057e3032d28a1a5ebafd2d5b5e4 | <|skeleton|>
class FullyConnectedJastrowKernel:
def __init__(self, nup, ndown, cuda, size1=16, size2=8, activation=torch.nn.Sigmoid(), include_cusp_weight=True):
"""Defines a fully connected jastrow factors."""
<|body_0|>
def get_var_weight(self):
"""define the variational weight."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FullyConnectedJastrowKernel:
def __init__(self, nup, ndown, cuda, size1=16, size2=8, activation=torch.nn.Sigmoid(), include_cusp_weight=True):
"""Defines a fully connected jastrow factors."""
super().__init__(nup, ndown, cuda)
self.cusp_weights = None
self.fc1 = nn.Linear(1, si... | the_stack_v2_python_sparse | qmctorch/wavefunction/jastrows/elec_elec/kernels/fully_connected_jastrow_kernel.py | NLESC-JCER/QMCTorch | train | 22 | |
eb2c22f454df340957439f442f9b6e0ba02e3157 | [
"super().__init__()\nself.generator = generator_cls(latent_dim, num_channels, img_size, n_residual_blocks, num_filts)\nself.discriminator = discriminator_cls(num_channels)\nself.classifier = clf_cls(num_channels, img_size, n_classes)\nself.generator.apply(weights_init_normal)\nself.discriminator.apply(weights_init_... | <|body_start_0|>
super().__init__()
self.generator = generator_cls(latent_dim, num_channels, img_size, n_residual_blocks, num_filts)
self.discriminator = discriminator_cls(num_channels)
self.classifier = clf_cls(num_channels, img_size, n_classes)
self.generator.apply(weights_init... | Class implementing the Unsupervised Pixel-Level Domain Adaptation with Generative Adversarial Networks References ---------- `Paper <https://arxiv.org/abs/1612.05424>`_ Warnings -------- This Network is designed for training only; if you want to predict from an already trained network, it might be best, to split this n... | PixelDomainAdaptation | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PixelDomainAdaptation:
"""Class implementing the Unsupervised Pixel-Level Domain Adaptation with Generative Adversarial Networks References ---------- `Paper <https://arxiv.org/abs/1612.05424>`_ Warnings -------- This Network is designed for training only; if you want to predict from an already t... | stack_v2_sparse_classes_36k_train_010305 | 6,091 | permissive | [
{
"docstring": "Parameters ---------- img_size : int number of pixels per image side num_channels : int number of image channels latent_dim : int size of latent dimension n_classes : int number of classes n_residual_blocks : int number of residual blocks to include num_filts : int number of filters per convolut... | 2 | null | Implement the Python class `PixelDomainAdaptation` described below.
Class description:
Class implementing the Unsupervised Pixel-Level Domain Adaptation with Generative Adversarial Networks References ---------- `Paper <https://arxiv.org/abs/1612.05424>`_ Warnings -------- This Network is designed for training only; i... | Implement the Python class `PixelDomainAdaptation` described below.
Class description:
Class implementing the Unsupervised Pixel-Level Domain Adaptation with Generative Adversarial Networks References ---------- `Paper <https://arxiv.org/abs/1612.05424>`_ Warnings -------- This Network is designed for training only; i... | 1078f5030b8aac2bf022daf5fa14d66f74c3c893 | <|skeleton|>
class PixelDomainAdaptation:
"""Class implementing the Unsupervised Pixel-Level Domain Adaptation with Generative Adversarial Networks References ---------- `Paper <https://arxiv.org/abs/1612.05424>`_ Warnings -------- This Network is designed for training only; if you want to predict from an already t... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PixelDomainAdaptation:
"""Class implementing the Unsupervised Pixel-Level Domain Adaptation with Generative Adversarial Networks References ---------- `Paper <https://arxiv.org/abs/1612.05424>`_ Warnings -------- This Network is designed for training only; if you want to predict from an already trained networ... | the_stack_v2_python_sparse | dlutils/models/gans/pixel_da/pixel_da.py | justusschock/dl-utils | train | 15 |
b1ce921dea63c8dbb9ebbc5a2bb43e0112deb5b3 | [
"if hasattr(self, 'order'):\n order = self.order\n pivot, pvar = ((1,) + (0,) * (self.number_of_variables - 1), 0)\n for var in range(1, self.number_of_variables):\n vindex = (0,) * var + (1,) + (0,) * (self.number_of_variables - var - 1)\n if order.cmp(pivot, vindex) < 0:\n pivot,... | <|body_start_0|>
if hasattr(self, 'order'):
order = self.order
pivot, pvar = ((1,) + (0,) * (self.number_of_variables - 1), 0)
for var in range(1, self.number_of_variables):
vindex = (0,) * var + (1,) + (0,) * (self.number_of_variables - var - 1)
... | Provide nest/unnest pair to convert a multivar polynomial to a univar polynomial of polynomial coefficient and opposite direction. | NestProvider | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NestProvider:
"""Provide nest/unnest pair to convert a multivar polynomial to a univar polynomial of polynomial coefficient and opposite direction."""
def leading_variable(self):
"""Return the position of the leading variable (the leading term among all total degree one terms). The l... | stack_v2_sparse_classes_36k_train_010306 | 24,835 | no_license | [
{
"docstring": "Return the position of the leading variable (the leading term among all total degree one terms). The leading term varies with term orders, so does the result. The term order can be specified via the attribute 'order'.",
"name": "leading_variable",
"signature": "def leading_variable(self)... | 3 | null | Implement the Python class `NestProvider` described below.
Class description:
Provide nest/unnest pair to convert a multivar polynomial to a univar polynomial of polynomial coefficient and opposite direction.
Method signatures and docstrings:
- def leading_variable(self): Return the position of the leading variable (... | Implement the Python class `NestProvider` described below.
Class description:
Provide nest/unnest pair to convert a multivar polynomial to a univar polynomial of polynomial coefficient and opposite direction.
Method signatures and docstrings:
- def leading_variable(self): Return the position of the leading variable (... | a48ae9efcf0d9ad1485c2e9863c948a7f1b20311 | <|skeleton|>
class NestProvider:
"""Provide nest/unnest pair to convert a multivar polynomial to a univar polynomial of polynomial coefficient and opposite direction."""
def leading_variable(self):
"""Return the position of the leading variable (the leading term among all total degree one terms). The l... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NestProvider:
"""Provide nest/unnest pair to convert a multivar polynomial to a univar polynomial of polynomial coefficient and opposite direction."""
def leading_variable(self):
"""Return the position of the leading variable (the leading term among all total degree one terms). The leading term v... | the_stack_v2_python_sparse | nzmath/poly/multiutil.py | turkeydonkey/nzmath3 | train | 2 |
15ed22f7fffd066270fb8d0534cc859287a9c769 | [
"super().__init__(x, y)\nself.fill_color = QtCore.Qt.lightGray\nself.line_color = QtCore.Qt.darkGray\nself.dx = random.randint(1, 3) * random.choice([-1, 1])\nself.dy = random.randint(1, 3) * random.choice([-1, 1])",
"self.x += self.dx\nself.y += self.dy\nif self.x < 0 or self.x > w:\n self.dx *= -1\nif self.y... | <|body_start_0|>
super().__init__(x, y)
self.fill_color = QtCore.Qt.lightGray
self.line_color = QtCore.Qt.darkGray
self.dx = random.randint(1, 3) * random.choice([-1, 1])
self.dy = random.randint(1, 3) * random.choice([-1, 1])
<|end_body_0|>
<|body_start_1|>
self.x += se... | Class to represent a Dodo bird. | Dodo | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Dodo:
"""Class to represent a Dodo bird."""
def __init__(self, x, y):
"""Create a new Dodo with the given x and y values. :param int x: The x-coordinate; default is zero. :param int y: The y-coordinate; default is zero."""
<|body_0|>
def move(self, w, h):
"""A Do... | stack_v2_sparse_classes_36k_train_010307 | 13,878 | no_license | [
{
"docstring": "Create a new Dodo with the given x and y values. :param int x: The x-coordinate; default is zero. :param int y: The y-coordinate; default is zero.",
"name": "__init__",
"signature": "def __init__(self, x, y)"
},
{
"docstring": "A Dodo bird flies in straight lines and bounces off ... | 2 | stack_v2_sparse_classes_30k_train_004827 | Implement the Python class `Dodo` described below.
Class description:
Class to represent a Dodo bird.
Method signatures and docstrings:
- def __init__(self, x, y): Create a new Dodo with the given x and y values. :param int x: The x-coordinate; default is zero. :param int y: The y-coordinate; default is zero.
- def m... | Implement the Python class `Dodo` described below.
Class description:
Class to represent a Dodo bird.
Method signatures and docstrings:
- def __init__(self, x, y): Create a new Dodo with the given x and y values. :param int x: The x-coordinate; default is zero. :param int y: The y-coordinate; default is zero.
- def m... | 0e3470085083012f893adb22aa46d46039016965 | <|skeleton|>
class Dodo:
"""Class to represent a Dodo bird."""
def __init__(self, x, y):
"""Create a new Dodo with the given x and y values. :param int x: The x-coordinate; default is zero. :param int y: The y-coordinate; default is zero."""
<|body_0|>
def move(self, w, h):
"""A Do... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Dodo:
"""Class to represent a Dodo bird."""
def __init__(self, x, y):
"""Create a new Dodo with the given x and y values. :param int x: The x-coordinate; default is zero. :param int y: The y-coordinate; default is zero."""
super().__init__(x, y)
self.fill_color = QtCore.Qt.lightGr... | the_stack_v2_python_sparse | CS_210 (Introduction to Programming)/Labs/Lab34_AviaryApp.py | JacobOrner/USAFA | train | 0 |
ca809099a2db6f2598cc95337667951ef8095c00 | [
"now_time = datetime.datetime.now().strftime('%Y-%m-%d %H-%M-%S')\nmylogs.log_info('-----------------------test_7operate_monitor---------------------------')\nmylogs.log_info('Start to execute test set env and launch ota at {}'.format(now_time))",
"user.click_connect_btn()\nsp(2)\nuser.click_download_and_install_... | <|body_start_0|>
now_time = datetime.datetime.now().strftime('%Y-%m-%d %H-%M-%S')
mylogs.log_info('-----------------------test_7operate_monitor---------------------------')
mylogs.log_info('Start to execute test set env and launch ota at {}'.format(now_time))
<|end_body_0|>
<|body_start_1|>
... | TestOtaSmokeClass | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestOtaSmokeClass:
def setup_class(self):
"""Execute one time before run all cases"""
<|body_0|>
def test_operate_monitor(self):
"""Todo://1.connet,download,install 2.take screen shot"""
<|body_1|>
def teardown_class(self):
"""Execute one time af... | stack_v2_sparse_classes_36k_train_010308 | 3,731 | permissive | [
{
"docstring": "Execute one time before run all cases",
"name": "setup_class",
"signature": "def setup_class(self)"
},
{
"docstring": "Todo://1.connet,download,install 2.take screen shot",
"name": "test_operate_monitor",
"signature": "def test_operate_monitor(self)"
},
{
"docstri... | 3 | stack_v2_sparse_classes_30k_train_000137 | Implement the Python class `TestOtaSmokeClass` described below.
Class description:
Implement the TestOtaSmokeClass class.
Method signatures and docstrings:
- def setup_class(self): Execute one time before run all cases
- def test_operate_monitor(self): Todo://1.connet,download,install 2.take screen shot
- def teardow... | Implement the Python class `TestOtaSmokeClass` described below.
Class description:
Implement the TestOtaSmokeClass class.
Method signatures and docstrings:
- def setup_class(self): Execute one time before run all cases
- def test_operate_monitor(self): Todo://1.connet,download,install 2.take screen shot
- def teardow... | e4afa8944785c1dc1dc80550073858d03a77d629 | <|skeleton|>
class TestOtaSmokeClass:
def setup_class(self):
"""Execute one time before run all cases"""
<|body_0|>
def test_operate_monitor(self):
"""Todo://1.connet,download,install 2.take screen shot"""
<|body_1|>
def teardown_class(self):
"""Execute one time af... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestOtaSmokeClass:
def setup_class(self):
"""Execute one time before run all cases"""
now_time = datetime.datetime.now().strftime('%Y-%m-%d %H-%M-%S')
mylogs.log_info('-----------------------test_7operate_monitor---------------------------')
mylogs.log_info('Start to execute te... | the_stack_v2_python_sparse | testcases/smoke/dongfeng/test_dongfeng_smoke/test_7operate_monitor.py | uniquelover/ota_smoke_auto | train | 0 | |
d4ba1cd917884ee1503fe147fe6bb3ed9493e61f | [
"if not root:\n return 'n'\ns = ''\nstack = [root]\nwhile stack:\n root = stack.pop(0)\n if root:\n s += str(root.val)\n stack.append(root.left)\n stack.append(root.right)\n else:\n s += 'n'\n s += ' '\nreturn s",
"if not data:\n return None\ntree = data.split()\nif t... | <|body_start_0|>
if not root:
return 'n'
s = ''
stack = [root]
while stack:
root = stack.pop(0)
if root:
s += str(root.val)
stack.append(root.left)
stack.append(root.right)
else:
... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|>
<|body_... | stack_v2_sparse_classes_36k_train_010309 | 2,353 | no_license | [
{
"docstring": "Encodes a tree to a single string. :type root: TreeNode :rtype: str",
"name": "serialize",
"signature": "def serialize(self, root)"
},
{
"docstring": "Decodes your encoded data to tree. :type data: str :rtype: TreeNode",
"name": "deserialize",
"signature": "def deserializ... | 2 | stack_v2_sparse_classes_30k_train_019055 | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | ce29ea836bd20841d69972180273e4d4ec11514d | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
if not root:
return 'n'
s = ''
stack = [root]
while stack:
root = stack.pop(0)
if root:
s += str(root.val)
... | the_stack_v2_python_sparse | 37.py | NeilWangziyu/JZOffer | train | 1 | |
6fd479b4ad064a3851a7abe08fe12bea95a3690a | [
"if logger is None:\n logger = InferLogger(args.log_path)\noutput_data_dir = None\nmodel_path = args.model_file\nparam_path = args.params_file\ncfg = CommonFunc.get_framework_config(model_path, args)\nif args.input_data_file is not None:\n input_data_map = np.load(args.input_data_file, allow_pickle=True).item... | <|body_start_0|>
if logger is None:
logger = InferLogger(args.log_path)
output_data_dir = None
model_path = args.model_file
param_path = args.params_file
cfg = CommonFunc.get_framework_config(model_path, args)
if args.input_data_file is not None:
i... | functions for model easy infer | EasyInfer | [
"Apache-2.0",
"LicenseRef-scancode-proprietary-license",
"MPL-1.0",
"OpenSSL",
"LGPL-3.0-only",
"LicenseRef-scancode-warranty-disclaimer",
"BSD-3-Clause-Open-MPI",
"MIT",
"MPL-2.0-no-copyleft-exception",
"NTP",
"BSD-3-Clause",
"GPL-1.0-or-later",
"0BSD",
"MPL-2.0",
"LicenseRef-scancode-f... | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EasyInfer:
"""functions for model easy infer"""
def easy_infer(args, logger=None):
"""model easy infer"""
<|body_0|>
def ms_dynamic_input_infer(args, logger=None):
"""conduct dynamic shape mindspore lite model infer"""
<|body_1|>
<|end_skeleton|>
<|body... | stack_v2_sparse_classes_36k_train_010310 | 3,725 | permissive | [
{
"docstring": "model easy infer",
"name": "easy_infer",
"signature": "def easy_infer(args, logger=None)"
},
{
"docstring": "conduct dynamic shape mindspore lite model infer",
"name": "ms_dynamic_input_infer",
"signature": "def ms_dynamic_input_infer(args, logger=None)"
}
] | 2 | null | Implement the Python class `EasyInfer` described below.
Class description:
functions for model easy infer
Method signatures and docstrings:
- def easy_infer(args, logger=None): model easy infer
- def ms_dynamic_input_infer(args, logger=None): conduct dynamic shape mindspore lite model infer | Implement the Python class `EasyInfer` described below.
Class description:
functions for model easy infer
Method signatures and docstrings:
- def easy_infer(args, logger=None): model easy infer
- def ms_dynamic_input_infer(args, logger=None): conduct dynamic shape mindspore lite model infer
<|skeleton|>
class EasyIn... | 54acb15d435533c815ee1bd9f6dc0b56b4d4cf83 | <|skeleton|>
class EasyInfer:
"""functions for model easy infer"""
def easy_infer(args, logger=None):
"""model easy infer"""
<|body_0|>
def ms_dynamic_input_infer(args, logger=None):
"""conduct dynamic shape mindspore lite model infer"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EasyInfer:
"""functions for model easy infer"""
def easy_infer(args, logger=None):
"""model easy infer"""
if logger is None:
logger = InferLogger(args.log_path)
output_data_dir = None
model_path = args.model_file
param_path = args.params_file
cf... | the_stack_v2_python_sparse | mindspore/lite/tools/mslite_bench/mslite_bench/tools/easy_infer.py | mindspore-ai/mindspore | train | 4,178 |
0c60df827ef68aa87cf300f137aaa9d9d6725dcc | [
"self.disk_to_overwrite = disk_to_overwrite\nself.src_disk = src_disk\nself.target_location = target_location",
"if dictionary is None:\n return None\ndisk_to_overwrite = cohesity_management_sdk.models.virtual_disk_id.VirtualDiskId.from_dictionary(dictionary.get('diskToOverwrite')) if dictionary.get('diskToOve... | <|body_start_0|>
self.disk_to_overwrite = disk_to_overwrite
self.src_disk = src_disk
self.target_location = target_location
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
disk_to_overwrite = cohesity_management_sdk.models.virtual_disk_id.VirtualDi... | Implementation of the 'RecoverVirtualDiskParams_VirtualDiskMapping' model. TODO: type description here. Attributes: disk_to_overwrite (VirtualDiskId): If the user is overwriting a destination disk, then this will capture the target disk info. NOTE: If this is specified, then power_off_vm_before_recovery must be true. s... | RecoverVirtualDiskParams_VirtualDiskMapping | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RecoverVirtualDiskParams_VirtualDiskMapping:
"""Implementation of the 'RecoverVirtualDiskParams_VirtualDiskMapping' model. TODO: type description here. Attributes: disk_to_overwrite (VirtualDiskId): If the user is overwriting a destination disk, then this will capture the target disk info. NOTE: ... | stack_v2_sparse_classes_36k_train_010311 | 2,838 | permissive | [
{
"docstring": "Constructor for the RecoverVirtualDiskParams_VirtualDiskMapping class",
"name": "__init__",
"signature": "def __init__(self, disk_to_overwrite=None, src_disk=None, target_location=None)"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: dictionary (dict... | 2 | stack_v2_sparse_classes_30k_val_000173 | Implement the Python class `RecoverVirtualDiskParams_VirtualDiskMapping` described below.
Class description:
Implementation of the 'RecoverVirtualDiskParams_VirtualDiskMapping' model. TODO: type description here. Attributes: disk_to_overwrite (VirtualDiskId): If the user is overwriting a destination disk, then this wi... | Implement the Python class `RecoverVirtualDiskParams_VirtualDiskMapping` described below.
Class description:
Implementation of the 'RecoverVirtualDiskParams_VirtualDiskMapping' model. TODO: type description here. Attributes: disk_to_overwrite (VirtualDiskId): If the user is overwriting a destination disk, then this wi... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class RecoverVirtualDiskParams_VirtualDiskMapping:
"""Implementation of the 'RecoverVirtualDiskParams_VirtualDiskMapping' model. TODO: type description here. Attributes: disk_to_overwrite (VirtualDiskId): If the user is overwriting a destination disk, then this will capture the target disk info. NOTE: ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RecoverVirtualDiskParams_VirtualDiskMapping:
"""Implementation of the 'RecoverVirtualDiskParams_VirtualDiskMapping' model. TODO: type description here. Attributes: disk_to_overwrite (VirtualDiskId): If the user is overwriting a destination disk, then this will capture the target disk info. NOTE: If this is sp... | the_stack_v2_python_sparse | cohesity_management_sdk/models/recover_virtual_disk_params_virtual_disk_mapping.py | cohesity/management-sdk-python | train | 24 |
1dcb1be470b8860874d5189c7bc3e8f42a43472a | [
"super().__init__(**kwargs)\nself._index = idx\nself.setTitle(f'ROI{idx}')",
"image = data.image.masked_mean\nx, y, w, h = getattr(getattr(data.roi, f'geom{self._index}'), 'geometry')\nif w < 0 or h < 0:\n return\nself.setImage(image[y:y + h, x:x + w])"
] | <|body_start_0|>
super().__init__(**kwargs)
self._index = idx
self.setTitle(f'ROI{idx}')
<|end_body_0|>
<|body_start_1|>
image = data.image.masked_mean
x, y, w, h = getattr(getattr(data.roi, f'geom{self._index}'), 'geometry')
if w < 0 or h < 0:
return
... | RoiImageView class. Widget for displaying the ROI for the assembled image. | RoiImageView | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RoiImageView:
"""RoiImageView class. Widget for displaying the ROI for the assembled image."""
def __init__(self, idx, **kwargs):
"""Initialization."""
<|body_0|>
def updateF(self, data):
"""Override."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_010312 | 7,391 | permissive | [
{
"docstring": "Initialization.",
"name": "__init__",
"signature": "def __init__(self, idx, **kwargs)"
},
{
"docstring": "Override.",
"name": "updateF",
"signature": "def updateF(self, data)"
}
] | 2 | stack_v2_sparse_classes_30k_train_011300 | Implement the Python class `RoiImageView` described below.
Class description:
RoiImageView class. Widget for displaying the ROI for the assembled image.
Method signatures and docstrings:
- def __init__(self, idx, **kwargs): Initialization.
- def updateF(self, data): Override. | Implement the Python class `RoiImageView` described below.
Class description:
RoiImageView class. Widget for displaying the ROI for the assembled image.
Method signatures and docstrings:
- def __init__(self, idx, **kwargs): Initialization.
- def updateF(self, data): Override.
<|skeleton|>
class RoiImageView:
"""... | a6ee28040b15ae8d110570bd9f3c37e5a3e70fc0 | <|skeleton|>
class RoiImageView:
"""RoiImageView class. Widget for displaying the ROI for the assembled image."""
def __init__(self, idx, **kwargs):
"""Initialization."""
<|body_0|>
def updateF(self, data):
"""Override."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RoiImageView:
"""RoiImageView class. Widget for displaying the ROI for the assembled image."""
def __init__(self, idx, **kwargs):
"""Initialization."""
super().__init__(**kwargs)
self._index = idx
self.setTitle(f'ROI{idx}')
def updateF(self, data):
"""Override... | the_stack_v2_python_sparse | extra_foam/gui/plot_widgets/image_views.py | European-XFEL/EXtra-foam | train | 8 |
9990115b8e8732f451610a6d64d92f93b7725dab | [
"ndict = {}\nfor i in range(len(nums)):\n dif = target - nums[i]\n if dif in ndict.values():\n return [i, ndict.keys()[ndict.values().index(dif)]]\n ndict[i] = nums[i]\nreturn []",
"hasht = {k: v for v, k in enumerate(nums)}\nfor i, el in enumerate(nums):\n res = target - el\n if hasht.get(r... | <|body_start_0|>
ndict = {}
for i in range(len(nums)):
dif = target - nums[i]
if dif in ndict.values():
return [i, ndict.keys()[ndict.values().index(dif)]]
ndict[i] = nums[i]
return []
<|end_body_0|>
<|body_start_1|>
hasht = {k: v for ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def twoSum(self, nums, target):
""":type nums: List[int] :type target: int :rtype: List[int]"""
<|body_0|>
def twoSumDictv2(self, nums, target):
""":type nums: List[int] :type target: int :rtype: List[int]"""
<|body_1|>
def twoSumBruteF(self, n... | stack_v2_sparse_classes_36k_train_010313 | 1,571 | no_license | [
{
"docstring": ":type nums: List[int] :type target: int :rtype: List[int]",
"name": "twoSum",
"signature": "def twoSum(self, nums, target)"
},
{
"docstring": ":type nums: List[int] :type target: int :rtype: List[int]",
"name": "twoSumDictv2",
"signature": "def twoSumDictv2(self, nums, ta... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def twoSum(self, nums, target): :type nums: List[int] :type target: int :rtype: List[int]
- def twoSumDictv2(self, nums, target): :type nums: List[int] :type target: int :rtype: ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def twoSum(self, nums, target): :type nums: List[int] :type target: int :rtype: List[int]
- def twoSumDictv2(self, nums, target): :type nums: List[int] :type target: int :rtype: ... | b3a2013d1c3c7a5a16727dbc2ecbc934a01a3979 | <|skeleton|>
class Solution:
def twoSum(self, nums, target):
""":type nums: List[int] :type target: int :rtype: List[int]"""
<|body_0|>
def twoSumDictv2(self, nums, target):
""":type nums: List[int] :type target: int :rtype: List[int]"""
<|body_1|>
def twoSumBruteF(self, n... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def twoSum(self, nums, target):
""":type nums: List[int] :type target: int :rtype: List[int]"""
ndict = {}
for i in range(len(nums)):
dif = target - nums[i]
if dif in ndict.values():
return [i, ndict.keys()[ndict.values().index(dif)]]
... | the_stack_v2_python_sparse | LeetcodePython/TwoSum1.py | DianaLuca/Algorithms | train | 1 | |
e3f2162dc73b1e34d958149db47aef6156d983a0 | [
"try:\n name = cls(value).name\nexcept ValueError:\n return '{}({:#x} = ?)'.format(cls.__name__, value)\nelse:\n assert name.startswith('TPM_ALG_')\n return name[8:]",
"if self == TpmAlgId.TPM_ALG_SHA1:\n return hashlib.sha1(data).digest()\nif self == TpmAlgId.TPM_ALG_SHA256:\n return hashlib.sh... | <|body_start_0|>
try:
name = cls(value).name
except ValueError:
return '{}({:#x} = ?)'.format(cls.__name__, value)
else:
assert name.startswith('TPM_ALG_')
return name[8:]
<|end_body_0|>
<|body_start_1|>
if self == TpmAlgId.TPM_ALG_SHA1:
... | TPM_ALG_ID constants | TpmAlgId | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TpmAlgId:
"""TPM_ALG_ID constants"""
def get_name(cls, value):
"""Get the algorithm from the ID value"""
<|body_0|>
def digest(self, data):
"""Compute the digest of the data"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
try:
name =... | stack_v2_sparse_classes_36k_train_010314 | 27,705 | permissive | [
{
"docstring": "Get the algorithm from the ID value",
"name": "get_name",
"signature": "def get_name(cls, value)"
},
{
"docstring": "Compute the digest of the data",
"name": "digest",
"signature": "def digest(self, data)"
}
] | 2 | null | Implement the Python class `TpmAlgId` described below.
Class description:
TPM_ALG_ID constants
Method signatures and docstrings:
- def get_name(cls, value): Get the algorithm from the ID value
- def digest(self, data): Compute the digest of the data | Implement the Python class `TpmAlgId` described below.
Class description:
TPM_ALG_ID constants
Method signatures and docstrings:
- def get_name(cls, value): Get the algorithm from the ID value
- def digest(self, data): Compute the digest of the data
<|skeleton|>
class TpmAlgId:
"""TPM_ALG_ID constants"""
de... | a846ce38894f749082405d9a86fcf13d0bf5b992 | <|skeleton|>
class TpmAlgId:
"""TPM_ALG_ID constants"""
def get_name(cls, value):
"""Get the algorithm from the ID value"""
<|body_0|>
def digest(self, data):
"""Compute the digest of the data"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TpmAlgId:
"""TPM_ALG_ID constants"""
def get_name(cls, value):
"""Get the algorithm from the ID value"""
try:
name = cls(value).name
except ValueError:
return '{}({:#x} = ?)'.format(cls.__name__, value)
else:
assert name.startswith('TPM_... | the_stack_v2_python_sparse | python/crypto/tpm_decode_bios_measurements.py | fishilico/shared | train | 35 |
47136e7f2cefb379a4bce939d371d98ccf55f6c5 | [
"self.terms = GetText(node.getElementsByTagName('Q')[0])\nparams = node.getElementsByTagName('PARAM')\nfor param in params:\n name = param.getAttribute('name')\n if name == 'num':\n self.size = param.getAttribute('value')\n elif name == 'start':\n self.start = param.getAttribute('value')\nele... | <|body_start_0|>
self.terms = GetText(node.getElementsByTagName('Q')[0])
params = node.getElementsByTagName('PARAM')
for param in params:
name = param.getAttribute('name')
if name == 'num':
self.size = param.getAttribute('value')
elif name == '... | A wrapper around the XML of a search response | Response | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Response:
"""A wrapper around the XML of a search response"""
def __init__(self, node):
"""Construct a wrapper around an XML search response. Exposes the following properties: terms : the requested search terms size: the requested number of search results start: the requested start i... | stack_v2_sparse_classes_36k_train_010315 | 20,975 | no_license | [
{
"docstring": "Construct a wrapper around an XML search response. Exposes the following properties: terms : the requested search terms size: the requested number of search results start: the requested start index (offset 0) first: the index (offset 1) of the first result in the response last: the index (offset... | 2 | null | Implement the Python class `Response` described below.
Class description:
A wrapper around the XML of a search response
Method signatures and docstrings:
- def __init__(self, node): Construct a wrapper around an XML search response. Exposes the following properties: terms : the requested search terms size: the reques... | Implement the Python class `Response` described below.
Class description:
A wrapper around the XML of a search response
Method signatures and docstrings:
- def __init__(self, node): Construct a wrapper around an XML search response. Exposes the following properties: terms : the requested search terms size: the reques... | 99ad033be03779e9680ce8024cdd7a4bdc5a58bd | <|skeleton|>
class Response:
"""A wrapper around the XML of a search response"""
def __init__(self, node):
"""Construct a wrapper around an XML search response. Exposes the following properties: terms : the requested search terms size: the requested number of search results start: the requested start i... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Response:
"""A wrapper around the XML of a search response"""
def __init__(self, node):
"""Construct a wrapper around an XML search response. Exposes the following properties: terms : the requested search terms size: the requested number of search results start: the requested start index (offset ... | the_stack_v2_python_sparse | pubConvGoogle | maximilianh/pubMunch | train | 43 |
698d2ccebcaf0dd43f5dc301eafefd5b2bb6dcb2 | [
"res = ''\ns = longUrl\nfor i in range(len(s)):\n res += str(ord(s[i]) + 1) + '*'\nreturn res",
"s = shortUrl\ntemp = ''\ns = s.split('*')\nfor i in range(len(s)):\n if len(s[i]) != 0:\n temp += str(chr(int(s[i]) - 1))\nreturn temp"
] | <|body_start_0|>
res = ''
s = longUrl
for i in range(len(s)):
res += str(ord(s[i]) + 1) + '*'
return res
<|end_body_0|>
<|body_start_1|>
s = shortUrl
temp = ''
s = s.split('*')
for i in range(len(s)):
if len(s[i]) != 0:
... | Codec | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def encode(self, longUrl: str) -> str:
"""Encodes a URL to a shortened URL."""
<|body_0|>
def decode(self, shortUrl: str) -> str:
"""Decodes a shortened URL to its original URL."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
res = ''
... | stack_v2_sparse_classes_36k_train_010316 | 1,433 | permissive | [
{
"docstring": "Encodes a URL to a shortened URL.",
"name": "encode",
"signature": "def encode(self, longUrl: str) -> str"
},
{
"docstring": "Decodes a shortened URL to its original URL.",
"name": "decode",
"signature": "def decode(self, shortUrl: str) -> str"
}
] | 2 | null | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def encode(self, longUrl: str) -> str: Encodes a URL to a shortened URL.
- def decode(self, shortUrl: str) -> str: Decodes a shortened URL to its original URL. | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def encode(self, longUrl: str) -> str: Encodes a URL to a shortened URL.
- def decode(self, shortUrl: str) -> str: Decodes a shortened URL to its original URL.
<|skeleton|>
class Code... | 68dac358a6d4dabd41d47dbd4addb2ec50e0ca11 | <|skeleton|>
class Codec:
def encode(self, longUrl: str) -> str:
"""Encodes a URL to a shortened URL."""
<|body_0|>
def decode(self, shortUrl: str) -> str:
"""Decodes a shortened URL to its original URL."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Codec:
def encode(self, longUrl: str) -> str:
"""Encodes a URL to a shortened URL."""
res = ''
s = longUrl
for i in range(len(s)):
res += str(ord(s[i]) + 1) + '*'
return res
def decode(self, shortUrl: str) -> str:
"""Decodes a shortened URL to i... | the_stack_v2_python_sparse | encode_and_decode_tiny_url.py | erjan/coding_exercises | train | 5 | |
f6fc5676c7d9015c28ead1d3ba4348b2cc19fd59 | [
"self.name = name\nself.parameters = parameters\nself.annotations = annotations\nself.provisioner = provisioner\nself.api_version = api_version\nself.default_storage_class = str(default_storage_class).lower()\nself.kubeconfig = kubeconfig\nself.mount_options = mount_options\nself.reclaim_policy = reclaim_policy\nse... | <|body_start_0|>
self.name = name
self.parameters = parameters
self.annotations = annotations
self.provisioner = provisioner
self.api_version = api_version
self.default_storage_class = str(default_storage_class).lower()
self.kubeconfig = kubeconfig
self.mo... | Handle service options | StorageClassConfig | [
"LicenseRef-scancode-warranty-disclaimer",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StorageClassConfig:
"""Handle service options"""
def __init__(self, name, provisioner, parameters=None, annotations=None, default_storage_class='false', api_version='v1', kubeconfig='/etc/origin/master/admin.kubeconfig', mount_options=None, reclaim_policy=None):
"""constructor for ha... | stack_v2_sparse_classes_36k_train_010317 | 3,122 | permissive | [
{
"docstring": "constructor for handling storageclass options",
"name": "__init__",
"signature": "def __init__(self, name, provisioner, parameters=None, annotations=None, default_storage_class='false', api_version='v1', kubeconfig='/etc/origin/master/admin.kubeconfig', mount_options=None, reclaim_policy... | 2 | null | Implement the Python class `StorageClassConfig` described below.
Class description:
Handle service options
Method signatures and docstrings:
- def __init__(self, name, provisioner, parameters=None, annotations=None, default_storage_class='false', api_version='v1', kubeconfig='/etc/origin/master/admin.kubeconfig', mou... | Implement the Python class `StorageClassConfig` described below.
Class description:
Handle service options
Method signatures and docstrings:
- def __init__(self, name, provisioner, parameters=None, annotations=None, default_storage_class='false', api_version='v1', kubeconfig='/etc/origin/master/admin.kubeconfig', mou... | e342f6659a4ef1a188ff403e2fc6b06ac6d119c7 | <|skeleton|>
class StorageClassConfig:
"""Handle service options"""
def __init__(self, name, provisioner, parameters=None, annotations=None, default_storage_class='false', api_version='v1', kubeconfig='/etc/origin/master/admin.kubeconfig', mount_options=None, reclaim_policy=None):
"""constructor for ha... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class StorageClassConfig:
"""Handle service options"""
def __init__(self, name, provisioner, parameters=None, annotations=None, default_storage_class='false', api_version='v1', kubeconfig='/etc/origin/master/admin.kubeconfig', mount_options=None, reclaim_policy=None):
"""constructor for handling storag... | the_stack_v2_python_sparse | openshift/installer/vendored/openshift-ansible-3.11.28-1/roles/lib_openshift/src/lib/storageclass.py | openshift/openshift-tools | train | 170 |
6ccaa1fbba33f9a0bbcb608307505b1b45f8a05f | [
"N = len(nums) - 1\ndp = [sys.maxsize] * N\nif N <= 0:\n return 0\nfor i in range(N - 1, -1, -1):\n cur = nums[i]\n if cur == 0:\n continue\n if cur + i < N:\n for j in range(cur, 0, -1):\n if dp[i + j] != sys.maxsize:\n dp[i] = min(dp[i], dp[i + j] + 1)\n else... | <|body_start_0|>
N = len(nums) - 1
dp = [sys.maxsize] * N
if N <= 0:
return 0
for i in range(N - 1, -1, -1):
cur = nums[i]
if cur == 0:
continue
if cur + i < N:
for j in range(cur, 0, -1):
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def jump(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def jump2(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
N = len(nums) - 1
dp = [sys.maxsize] * N
i... | stack_v2_sparse_classes_36k_train_010318 | 1,613 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "jump",
"signature": "def jump(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "jump2",
"signature": "def jump2(self, nums)"
}
] | 2 | stack_v2_sparse_classes_30k_train_020370 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def jump(self, nums): :type nums: List[int] :rtype: int
- def jump2(self, nums): :type nums: List[int] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def jump(self, nums): :type nums: List[int] :rtype: int
- def jump2(self, nums): :type nums: List[int] :rtype: int
<|skeleton|>
class Solution:
def jump(self, nums):
... | b77130a0133cd40990c4d7096db5e388de67cbf2 | <|skeleton|>
class Solution:
def jump(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def jump2(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def jump(self, nums):
""":type nums: List[int] :rtype: int"""
N = len(nums) - 1
dp = [sys.maxsize] * N
if N <= 0:
return 0
for i in range(N - 1, -1, -1):
cur = nums[i]
if cur == 0:
continue
if cur... | the_stack_v2_python_sparse | 45.JumpGame.py | flavorfan/MyLeetCode | train | 0 | |
b145369efa61701f6f9138a9519b412ff67d40a0 | [
"number_of_nodes = 4\nflights = [[0, 1, 100], [1, 2, 100], [2, 0, 100], [1, 3, 600], [2, 3, 200]]\nsource = 0\ndestination = 3\nallowed_stops = 1\nresult = find_cheapest_price(number_of_nodes, flights, source, destination, allowed_stops)\nself.assertEqual(result, 700)",
"number_of_nodes = 4\nflights = [[0, 1, 100... | <|body_start_0|>
number_of_nodes = 4
flights = [[0, 1, 100], [1, 2, 100], [2, 0, 100], [1, 3, 600], [2, 3, 200]]
source = 0
destination = 3
allowed_stops = 1
result = find_cheapest_price(number_of_nodes, flights, source, destination, allowed_stops)
self.assertEqua... | TestFindCheapestPrice | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestFindCheapestPrice:
def test_finds_cheapest_flight_in_list_of_flights(self):
"""Finds the cheapest flight within allowed stops using a list of flights and prices"""
<|body_0|>
def test_returns_negative_one_if_no_route_is_found(self):
"""Returns -1 if no flight rou... | stack_v2_sparse_classes_36k_train_010319 | 1,067 | permissive | [
{
"docstring": "Finds the cheapest flight within allowed stops using a list of flights and prices",
"name": "test_finds_cheapest_flight_in_list_of_flights",
"signature": "def test_finds_cheapest_flight_in_list_of_flights(self)"
},
{
"docstring": "Returns -1 if no flight route can be found in lis... | 2 | null | Implement the Python class `TestFindCheapestPrice` described below.
Class description:
Implement the TestFindCheapestPrice class.
Method signatures and docstrings:
- def test_finds_cheapest_flight_in_list_of_flights(self): Finds the cheapest flight within allowed stops using a list of flights and prices
- def test_re... | Implement the Python class `TestFindCheapestPrice` described below.
Class description:
Implement the TestFindCheapestPrice class.
Method signatures and docstrings:
- def test_finds_cheapest_flight_in_list_of_flights(self): Finds the cheapest flight within allowed stops using a list of flights and prices
- def test_re... | 27ffb6b32d6d18d279c51cfa45bf305a409be5c2 | <|skeleton|>
class TestFindCheapestPrice:
def test_finds_cheapest_flight_in_list_of_flights(self):
"""Finds the cheapest flight within allowed stops using a list of flights and prices"""
<|body_0|>
def test_returns_negative_one_if_no_route_is_found(self):
"""Returns -1 if no flight rou... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestFindCheapestPrice:
def test_finds_cheapest_flight_in_list_of_flights(self):
"""Finds the cheapest flight within allowed stops using a list of flights and prices"""
number_of_nodes = 4
flights = [[0, 1, 100], [1, 2, 100], [2, 0, 100], [1, 3, 600], [2, 3, 200]]
source = 0
... | the_stack_v2_python_sparse | src/leetcode/medium/find-cheapest-flight-within-k-flights/test_find_cheapest_flight_within_k_flights.py | nwthomas/code-challenges | train | 2 | |
4114bb93515e6adbe8553b56ed93467b547d65aa | [
"try:\n code = settings.API_ERROR_CODE[message]\nexcept KeyError:\n logger.error('API: System error when get the code of message \"%(message)s\"' % {'message': message})\n code = -1\nreturn code",
"errors = self.errors\nnew_errors = {'errors': []}\nfor key, value in errors.items():\n if key == 'non_fi... | <|body_start_0|>
try:
code = settings.API_ERROR_CODE[message]
except KeyError:
logger.error('API: System error when get the code of message "%(message)s"' % {'message': message})
code = -1
return code
<|end_body_0|>
<|body_start_1|>
errors = self.erro... | CustomSerializer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CustomSerializer:
def get_api_code(message):
"""根据 message 获得相应的 API 错误代码"""
<|body_0|>
def process_errors(self):
"""对 API 错误信息进行处理后输出, 主要为整理格式"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
try:
code = settings.API_ERROR_CODE[message]
... | stack_v2_sparse_classes_36k_train_010320 | 1,467 | no_license | [
{
"docstring": "根据 message 获得相应的 API 错误代码",
"name": "get_api_code",
"signature": "def get_api_code(message)"
},
{
"docstring": "对 API 错误信息进行处理后输出, 主要为整理格式",
"name": "process_errors",
"signature": "def process_errors(self)"
}
] | 2 | null | Implement the Python class `CustomSerializer` described below.
Class description:
Implement the CustomSerializer class.
Method signatures and docstrings:
- def get_api_code(message): 根据 message 获得相应的 API 错误代码
- def process_errors(self): 对 API 错误信息进行处理后输出, 主要为整理格式 | Implement the Python class `CustomSerializer` described below.
Class description:
Implement the CustomSerializer class.
Method signatures and docstrings:
- def get_api_code(message): 根据 message 获得相应的 API 错误代码
- def process_errors(self): 对 API 错误信息进行处理后输出, 主要为整理格式
<|skeleton|>
class CustomSerializer:
def get_api... | d52681a84bc75615dcfd7a373e579833e1ebece8 | <|skeleton|>
class CustomSerializer:
def get_api_code(message):
"""根据 message 获得相应的 API 错误代码"""
<|body_0|>
def process_errors(self):
"""对 API 错误信息进行处理后输出, 主要为整理格式"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CustomSerializer:
def get_api_code(message):
"""根据 message 获得相应的 API 错误代码"""
try:
code = settings.API_ERROR_CODE[message]
except KeyError:
logger.error('API: System error when get the code of message "%(message)s"' % {'message': message})
code = -1
... | the_stack_v2_python_sparse | citi/libs/api/serializers.py | doraemonext/citi | train | 0 | |
b6093be8a755231bb6ddcbdd6dd0d520a00da5be | [
"table = {}\nbatch_size = start_batch_size\nfor _ in Notifier(pbar)(range(max_iters)):\n info = self.get_memory_utilization(batch_size, method=method, inputs=inputs, targets=targets, n=n, frequency=frequency, time_threshold=time_threshold, tail_size=tail_size, std_threshold=std_threshold)\n table[batch_size] ... | <|body_start_0|>
table = {}
batch_size = start_batch_size
for _ in Notifier(pbar)(range(max_iters)):
info = self.get_memory_utilization(batch_size, method=method, inputs=inputs, targets=targets, n=n, frequency=frequency, time_threshold=time_threshold, tail_size=tail_size, std_thresho... | Compute optimal batch size for training/inference to maximize GPU memory usage. Works by using `train`/`predict` with different batch sizes, and measuring how much memory is taken. Then, we solve the system of `measured_memory = batch_size * item_size + model_size + eps` equations for both `item_size` and `model_size`.... | OptimalBatchSizeMixin | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OptimalBatchSizeMixin:
"""Compute optimal batch size for training/inference to maximize GPU memory usage. Works by using `train`/`predict` with different batch sizes, and measuring how much memory is taken. Then, we solve the system of `measured_memory = batch_size * item_size + model_size + eps`... | stack_v2_sparse_classes_36k_train_010321 | 26,643 | permissive | [
{
"docstring": "Compute memory usage for multiple batch sizes.",
"name": "compute_optimal_batch_size",
"signature": "def compute_optimal_batch_size(self, method='train', max_memory=90, inputs=None, targets=None, pbar='n', start_batch_size=4, delta_batch_size=4, max_batch_size=128, max_iters=16, n=20, fr... | 3 | null | Implement the Python class `OptimalBatchSizeMixin` described below.
Class description:
Compute optimal batch size for training/inference to maximize GPU memory usage. Works by using `train`/`predict` with different batch sizes, and measuring how much memory is taken. Then, we solve the system of `measured_memory = bat... | Implement the Python class `OptimalBatchSizeMixin` described below.
Class description:
Compute optimal batch size for training/inference to maximize GPU memory usage. Works by using `train`/`predict` with different batch sizes, and measuring how much memory is taken. Then, we solve the system of `measured_memory = bat... | bcc2c723976cb5780d7b2876f2c2df74c186d343 | <|skeleton|>
class OptimalBatchSizeMixin:
"""Compute optimal batch size for training/inference to maximize GPU memory usage. Works by using `train`/`predict` with different batch sizes, and measuring how much memory is taken. Then, we solve the system of `measured_memory = batch_size * item_size + model_size + eps`... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class OptimalBatchSizeMixin:
"""Compute optimal batch size for training/inference to maximize GPU memory usage. Works by using `train`/`predict` with different batch sizes, and measuring how much memory is taken. Then, we solve the system of `measured_memory = batch_size * item_size + model_size + eps` equations fo... | the_stack_v2_python_sparse | batchflow/models/torch/base_mixins.py | analysiscenter/batchflow | train | 110 |
5109d6ebed0e8b17a1640b293a7dd4b9a065b036 | [
"datafile_empty = self.get_file('empty.csv')\nschema_empty = [('col_A', int), ('col_B', int), ('col_C', str), ('col_D', float), ('col_E', float), ('col_F', str)]\nframe = self.context.frame.import_csv(datafile_empty, schema=schema_empty)\nself.assertEqual(frame.count(), 0)\nnull2 = frame.copy()\nself.assertEqual(nu... | <|body_start_0|>
datafile_empty = self.get_file('empty.csv')
schema_empty = [('col_A', int), ('col_B', int), ('col_C', str), ('col_D', float), ('col_E', float), ('col_F', str)]
frame = self.context.frame.import_csv(datafile_empty, schema=schema_empty)
self.assertEqual(frame.count(), 0)
... | FileLoadTest | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FileLoadTest:
def test_import_empty(self):
"""Import an empty file."""
<|body_0|>
def test_import_whitespace(self):
"""Build frame with complex quoting and whitespace"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
datafile_empty = self.get_file('em... | stack_v2_sparse_classes_36k_train_010322 | 2,116 | permissive | [
{
"docstring": "Import an empty file.",
"name": "test_import_empty",
"signature": "def test_import_empty(self)"
},
{
"docstring": "Build frame with complex quoting and whitespace",
"name": "test_import_whitespace",
"signature": "def test_import_whitespace(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_004293 | Implement the Python class `FileLoadTest` described below.
Class description:
Implement the FileLoadTest class.
Method signatures and docstrings:
- def test_import_empty(self): Import an empty file.
- def test_import_whitespace(self): Build frame with complex quoting and whitespace | Implement the Python class `FileLoadTest` described below.
Class description:
Implement the FileLoadTest class.
Method signatures and docstrings:
- def test_import_empty(self): Import an empty file.
- def test_import_whitespace(self): Build frame with complex quoting and whitespace
<|skeleton|>
class FileLoadTest:
... | 5548fc925b5c278263cbdebbd9e8c7593320c2f4 | <|skeleton|>
class FileLoadTest:
def test_import_empty(self):
"""Import an empty file."""
<|body_0|>
def test_import_whitespace(self):
"""Build frame with complex quoting and whitespace"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FileLoadTest:
def test_import_empty(self):
"""Import an empty file."""
datafile_empty = self.get_file('empty.csv')
schema_empty = [('col_A', int), ('col_B', int), ('col_C', str), ('col_D', float), ('col_E', float), ('col_F', str)]
frame = self.context.frame.import_csv(datafile_... | the_stack_v2_python_sparse | regression-tests/sparktkregtests/testcases/frames/file_load_test.py | trustedanalytics/spark-tk | train | 35 | |
8cdd55ac5fb149ae51e040031990baa69caceb4f | [
"A.sort()\nmn = min(A)\nmx = max(A)\nret = mx - mn\nfor i in range(len(A) - 1):\n cur_mx = max(mx - K, A[i] + K)\n cur_mn = min(mn + K, A[i + 1] - K)\n ret = min(ret, cur_mx - cur_mn)\nreturn ret",
"mini = min(A)\nmaxa = max(A)\nB = []\nmax_upper_diff = 0\nmax_lower_diff = 0\nupper = max(mini + K, maxa -... | <|body_start_0|>
A.sort()
mn = min(A)
mx = max(A)
ret = mx - mn
for i in range(len(A) - 1):
cur_mx = max(mx - K, A[i] + K)
cur_mn = min(mn + K, A[i + 1] - K)
ret = min(ret, cur_mx - cur_mn)
return ret
<|end_body_0|>
<|body_start_1|>
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def smallestRangeII(self, A: List[int], K: int) -> int:
"""Say A[i] is the largest i that goes up. A[i+1] would be the smallest goes down Then A[0] + K, A[i] + K, A[i+1] - K, A[A.length - 1] - K"""
<|body_0|>
def smallestRangeII_error(self, A: List[int], K: int) ->... | stack_v2_sparse_classes_36k_train_010323 | 1,926 | no_license | [
{
"docstring": "Say A[i] is the largest i that goes up. A[i+1] would be the smallest goes down Then A[0] + K, A[i] + K, A[i+1] - K, A[A.length - 1] - K",
"name": "smallestRangeII",
"signature": "def smallestRangeII(self, A: List[int], K: int) -> int"
},
{
"docstring": "find the min max is not en... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def smallestRangeII(self, A: List[int], K: int) -> int: Say A[i] is the largest i that goes up. A[i+1] would be the smallest goes down Then A[0] + K, A[i] + K, A[i+1] - K, A[A.le... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def smallestRangeII(self, A: List[int], K: int) -> int: Say A[i] is the largest i that goes up. A[i+1] would be the smallest goes down Then A[0] + K, A[i] + K, A[i+1] - K, A[A.le... | 929dde1723fb2f54870c8a9badc80fc23e8400d3 | <|skeleton|>
class Solution:
def smallestRangeII(self, A: List[int], K: int) -> int:
"""Say A[i] is the largest i that goes up. A[i+1] would be the smallest goes down Then A[0] + K, A[i] + K, A[i+1] - K, A[A.length - 1] - K"""
<|body_0|>
def smallestRangeII_error(self, A: List[int], K: int) ->... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def smallestRangeII(self, A: List[int], K: int) -> int:
"""Say A[i] is the largest i that goes up. A[i+1] would be the smallest goes down Then A[0] + K, A[i] + K, A[i+1] - K, A[A.length - 1] - K"""
A.sort()
mn = min(A)
mx = max(A)
ret = mx - mn
for i i... | the_stack_v2_python_sparse | _algorithms_challenges/leetcode/LeetCode/910 Smallest Range II.py | syurskyi/Algorithms_and_Data_Structure | train | 4 | |
5234a2e733c2b76f6f965f4182d2c06044eb665e | [
"super(SELayer, self).__init__()\nself.avg_pool = ops.AdaptiveAvgPool2d(1)\nhidden_dim = _make_divisible(channel // reduction, 8)\nself.fc = Sequential(ops.Linear(channel, hidden_dim, use_bias=False), ops.Relu(inplace=True), ops.Linear(hidden_dim, channel, use_bias=False), ops.Hsigmoid())",
"b, c, _, _ = x.shape\... | <|body_start_0|>
super(SELayer, self).__init__()
self.avg_pool = ops.AdaptiveAvgPool2d(1)
hidden_dim = _make_divisible(channel // reduction, 8)
self.fc = Sequential(ops.Linear(channel, hidden_dim, use_bias=False), ops.Relu(inplace=True), ops.Linear(hidden_dim, channel, use_bias=False), o... | This is the class of Squeeze-and-Excite layer for MobileNetV3. | SELayer | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SELayer:
"""This is the class of Squeeze-and-Excite layer for MobileNetV3."""
def __init__(self, channel, reduction=4):
"""Init SELayer."""
<|body_0|>
def __call__(self, x):
"""Forward compute of SELayer."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_010324 | 9,288 | permissive | [
{
"docstring": "Init SELayer.",
"name": "__init__",
"signature": "def __init__(self, channel, reduction=4)"
},
{
"docstring": "Forward compute of SELayer.",
"name": "__call__",
"signature": "def __call__(self, x)"
}
] | 2 | null | Implement the Python class `SELayer` described below.
Class description:
This is the class of Squeeze-and-Excite layer for MobileNetV3.
Method signatures and docstrings:
- def __init__(self, channel, reduction=4): Init SELayer.
- def __call__(self, x): Forward compute of SELayer. | Implement the Python class `SELayer` described below.
Class description:
This is the class of Squeeze-and-Excite layer for MobileNetV3.
Method signatures and docstrings:
- def __init__(self, channel, reduction=4): Init SELayer.
- def __call__(self, x): Forward compute of SELayer.
<|skeleton|>
class SELayer:
"""T... | e4ef3a1c92d19d1d08c3ef0e2156b6fecefdbe04 | <|skeleton|>
class SELayer:
"""This is the class of Squeeze-and-Excite layer for MobileNetV3."""
def __init__(self, channel, reduction=4):
"""Init SELayer."""
<|body_0|>
def __call__(self, x):
"""Forward compute of SELayer."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SELayer:
"""This is the class of Squeeze-and-Excite layer for MobileNetV3."""
def __init__(self, channel, reduction=4):
"""Init SELayer."""
super(SELayer, self).__init__()
self.avg_pool = ops.AdaptiveAvgPool2d(1)
hidden_dim = _make_divisible(channel // reduction, 8)
... | the_stack_v2_python_sparse | zeus/networks/mobilenetv3.py | huawei-noah/xingtian | train | 308 |
5f59f185f20f6372044506753631cdd6adc94a27 | [
"for num in nums:\n num = abs(num)\n if nums[num] < 0:\n return num\n else:\n nums[num] = -nums[num]",
"store = [0] * len(nums)\nfor i, num in enumerate(nums):\n if store[num] == num:\n return num\n else:\n store[num] = num"
] | <|body_start_0|>
for num in nums:
num = abs(num)
if nums[num] < 0:
return num
else:
nums[num] = -nums[num]
<|end_body_0|>
<|body_start_1|>
store = [0] * len(nums)
for i, num in enumerate(nums):
if store[num] == num:... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findDuplicate(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def findDuplicate(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
for num in nums:
num = abs(nu... | stack_v2_sparse_classes_36k_train_010325 | 1,159 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "findDuplicate",
"signature": "def findDuplicate(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "findDuplicate",
"signature": "def findDuplicate(self, nums)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findDuplicate(self, nums): :type nums: List[int] :rtype: int
- def findDuplicate(self, nums): :type nums: List[int] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findDuplicate(self, nums): :type nums: List[int] :rtype: int
- def findDuplicate(self, nums): :type nums: List[int] :rtype: int
<|skeleton|>
class Solution:
def findDup... | 844f502da4d6fb9cd69cf0a1ef71da3385a4d2b4 | <|skeleton|>
class Solution:
def findDuplicate(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def findDuplicate(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def findDuplicate(self, nums):
""":type nums: List[int] :rtype: int"""
for num in nums:
num = abs(num)
if nums[num] < 0:
return num
else:
nums[num] = -nums[num]
def findDuplicate(self, nums):
""":type nu... | the_stack_v2_python_sparse | 287-find_the_duplicate_num.py | stevestar888/leetcode-problems | train | 2 | |
dc9242ee420a6691b8c50ddae8286278cdeb2eab | [
"if file_format[0] != '.':\n file_format = '.' + file_format\nurl = 'http://www.uniprot.org/uniprot/'\nreq = ''.join([url, accession, file_format])\ntry:\n data = urlopen(req)\n return data.read().decode()\nexcept HTTPError:\n print('Entry :', accession, 'not found.')\n return None",
"result = cls.... | <|body_start_0|>
if file_format[0] != '.':
file_format = '.' + file_format
url = 'http://www.uniprot.org/uniprot/'
req = ''.join([url, accession, file_format])
try:
data = urlopen(req)
return data.read().decode()
except HTTPError:
p... | Tools for querying the UniProt database. | UniProtTools | [
"LicenseRef-scancode-other-permissive"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UniProtTools:
"""Tools for querying the UniProt database."""
def get_uniprot(cls, accession, file_format='.fasta'):
"""Retrieve UniProt data for a given accession."""
<|body_0|>
def get_gene_id(cls, accession):
"""Retrieve the gene id for a given accession."""
... | stack_v2_sparse_classes_36k_train_010326 | 9,507 | permissive | [
{
"docstring": "Retrieve UniProt data for a given accession.",
"name": "get_uniprot",
"signature": "def get_uniprot(cls, accession, file_format='.fasta')"
},
{
"docstring": "Retrieve the gene id for a given accession.",
"name": "get_gene_id",
"signature": "def get_gene_id(cls, accession)... | 3 | stack_v2_sparse_classes_30k_train_020486 | Implement the Python class `UniProtTools` described below.
Class description:
Tools for querying the UniProt database.
Method signatures and docstrings:
- def get_uniprot(cls, accession, file_format='.fasta'): Retrieve UniProt data for a given accession.
- def get_gene_id(cls, accession): Retrieve the gene id for a g... | Implement the Python class `UniProtTools` described below.
Class description:
Tools for querying the UniProt database.
Method signatures and docstrings:
- def get_uniprot(cls, accession, file_format='.fasta'): Retrieve UniProt data for a given accession.
- def get_gene_id(cls, accession): Retrieve the gene id for a g... | bedb36eafe681401c11d562f8d7117aad3d758d7 | <|skeleton|>
class UniProtTools:
"""Tools for querying the UniProt database."""
def get_uniprot(cls, accession, file_format='.fasta'):
"""Retrieve UniProt data for a given accession."""
<|body_0|>
def get_gene_id(cls, accession):
"""Retrieve the gene id for a given accession."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UniProtTools:
"""Tools for querying the UniProt database."""
def get_uniprot(cls, accession, file_format='.fasta'):
"""Retrieve UniProt data for a given accession."""
if file_format[0] != '.':
file_format = '.' + file_format
url = 'http://www.uniprot.org/uniprot/'
... | the_stack_v2_python_sparse | omin/utils/network_tools.py | dmpio/omin | train | 0 |
d0e7540c4b72a7e0197f5ff8bacc0abc628e30b6 | [
"self.master_config = master_config\nself.data_dict = data_dict\nself.base_path = base_path\nself.logger = logger",
"candidate_util = CandidateUtil()\ncandidate_id = candidate_util.get_candidate_id(candidate)\nexperiment_config = self.master_config.get('experiment_config', {})\nvis_value = experiment_config.get('... | <|body_start_0|>
self.master_config = master_config
self.data_dict = data_dict
self.base_path = base_path
self.logger = logger
<|end_body_0|>
<|body_start_1|>
candidate_util = CandidateUtil()
candidate_id = candidate_util.get_candidate_id(candidate)
experiment_co... | Class to aid in handling the configuration and visualize() calling for potentially multiple Network Visualizers. While this class is itself a NetworkVisualizer, we do not enter this in the NetworkVisualizerFactory to avoid a dependency tangle. | NetworkMultiVisualizer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NetworkMultiVisualizer:
"""Class to aid in handling the configuration and visualize() calling for potentially multiple Network Visualizers. While this class is itself a NetworkVisualizer, we do not enter this in the NetworkVisualizerFactory to avoid a dependency tangle."""
def __init__(self,... | stack_v2_sparse_classes_36k_train_010327 | 3,719 | no_license | [
{
"docstring": "Constructor. :param master_config: The master config for the experiment from which all other sub-configs can be obtained. :param data_dict: The data dictionary used in the evaluator. This is often needed by domains in order that the model is built with the correct dimensionality :param base_path... | 2 | stack_v2_sparse_classes_30k_train_013116 | Implement the Python class `NetworkMultiVisualizer` described below.
Class description:
Class to aid in handling the configuration and visualize() calling for potentially multiple Network Visualizers. While this class is itself a NetworkVisualizer, we do not enter this in the NetworkVisualizerFactory to avoid a depend... | Implement the Python class `NetworkMultiVisualizer` described below.
Class description:
Class to aid in handling the configuration and visualize() calling for potentially multiple Network Visualizers. While this class is itself a NetworkVisualizer, we do not enter this in the NetworkVisualizerFactory to avoid a depend... | 99c2f401d6c4b203ee439ed607985a918d0c3c7e | <|skeleton|>
class NetworkMultiVisualizer:
"""Class to aid in handling the configuration and visualize() calling for potentially multiple Network Visualizers. While this class is itself a NetworkVisualizer, we do not enter this in the NetworkVisualizerFactory to avoid a dependency tangle."""
def __init__(self,... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NetworkMultiVisualizer:
"""Class to aid in handling the configuration and visualize() calling for potentially multiple Network Visualizers. While this class is itself a NetworkVisualizer, we do not enter this in the NetworkVisualizerFactory to avoid a dependency tangle."""
def __init__(self, master_confi... | the_stack_v2_python_sparse | experimenthost/networkvisualization/network_multi_visualizer.py | Cognizant-CDB-AIA-BAI-AI-OI/LEAF-ENN-Training-V2 | train | 0 |
dd776d138b4b885ab9550fe7ff3008b7bf7836da | [
"ExterQual_Mapping = {'NaN': 0, 'Po': 1, 'Fa': 2, 'TA': 3, 'Gd': 4, 'Ex': 5}\nfeature_df = train[['ExterQual']]\ntrain['ExterQual'] = feature_df.fillna('NaN').applymap(lambda x: ExterQual_Mapping[x])",
"ExterCond_Mapping = {'NaN': 0, 'Po': 1, 'Fa': 2, 'TA': 3, 'Gd': 4, 'Ex': 5}\nfeature_df = train[['ExterCond']]\... | <|body_start_0|>
ExterQual_Mapping = {'NaN': 0, 'Po': 1, 'Fa': 2, 'TA': 3, 'Gd': 4, 'Ex': 5}
feature_df = train[['ExterQual']]
train['ExterQual'] = feature_df.fillna('NaN').applymap(lambda x: ExterQual_Mapping[x])
<|end_body_0|>
<|body_start_1|>
ExterCond_Mapping = {'NaN': 0, 'Po': 1, '... | Exterior feature exploration | ExteriorFeatures | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ExteriorFeatures:
"""Exterior feature exploration"""
def relabel_exterQual(self, train):
"""Re-label ExterQual"""
<|body_0|>
def relabel_exterCond(self, train):
"""Re-label ExterCond"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
ExterQual_Mapp... | stack_v2_sparse_classes_36k_train_010328 | 1,007 | no_license | [
{
"docstring": "Re-label ExterQual",
"name": "relabel_exterQual",
"signature": "def relabel_exterQual(self, train)"
},
{
"docstring": "Re-label ExterCond",
"name": "relabel_exterCond",
"signature": "def relabel_exterCond(self, train)"
}
] | 2 | stack_v2_sparse_classes_30k_test_000274 | Implement the Python class `ExteriorFeatures` described below.
Class description:
Exterior feature exploration
Method signatures and docstrings:
- def relabel_exterQual(self, train): Re-label ExterQual
- def relabel_exterCond(self, train): Re-label ExterCond | Implement the Python class `ExteriorFeatures` described below.
Class description:
Exterior feature exploration
Method signatures and docstrings:
- def relabel_exterQual(self, train): Re-label ExterQual
- def relabel_exterCond(self, train): Re-label ExterCond
<|skeleton|>
class ExteriorFeatures:
"""Exterior featu... | 4fc530d790d359c1a47fad3f8c49ee581cd3656a | <|skeleton|>
class ExteriorFeatures:
"""Exterior feature exploration"""
def relabel_exterQual(self, train):
"""Re-label ExterQual"""
<|body_0|>
def relabel_exterCond(self, train):
"""Re-label ExterCond"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ExteriorFeatures:
"""Exterior feature exploration"""
def relabel_exterQual(self, train):
"""Re-label ExterQual"""
ExterQual_Mapping = {'NaN': 0, 'Po': 1, 'Fa': 2, 'TA': 3, 'Gd': 4, 'Ex': 5}
feature_df = train[['ExterQual']]
train['ExterQual'] = feature_df.fillna('NaN').app... | the_stack_v2_python_sparse | preprocess/exploringData/missingValues/exterior_features.py | aaaYaaa2/ds_house_price | train | 0 |
7d8bcc90da196daed4347703bb92eaf7eb87ca4c | [
"try:\n print_file = io.StringIO()\n python_vinfo = sys.version_info\n if python_vinfo.major == 3 and python_vinfo.minor < 10:\n traceback.print_exception(etype=type(e), value=e, tb=tb, file=print_file)\n else:\n traceback.print_exception(type(e), value=e, tb=tb, file=print_file)\n prin... | <|body_start_0|>
try:
print_file = io.StringIO()
python_vinfo = sys.version_info
if python_vinfo.major == 3 and python_vinfo.minor < 10:
traceback.print_exception(etype=type(e), value=e, tb=tb, file=print_file)
else:
traceback.print... | SerializedException | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SerializedException:
def from_exception(e: Exception, tb: types.TracebackType) -> 'SerializedException':
"""Best effort attempt to serialize Exception. Because this will be used to communicate from a subprocess to its parent, we want to surface as much information as possible. It is not ... | stack_v2_sparse_classes_36k_train_010329 | 19,762 | permissive | [
{
"docstring": "Best effort attempt to serialize Exception. Because this will be used to communicate from a subprocess to its parent, we want to surface as much information as possible. It is not possible to serialize a traceback because it is too intertwined with the runtime; however what we really want is the... | 2 | null | Implement the Python class `SerializedException` described below.
Class description:
Implement the SerializedException class.
Method signatures and docstrings:
- def from_exception(e: Exception, tb: types.TracebackType) -> 'SerializedException': Best effort attempt to serialize Exception. Because this will be used to... | Implement the Python class `SerializedException` described below.
Class description:
Implement the SerializedException class.
Method signatures and docstrings:
- def from_exception(e: Exception, tb: types.TracebackType) -> 'SerializedException': Best effort attempt to serialize Exception. Because this will be used to... | df4da9bdff11a2f948d5bd4ac83da7922e6f44f4 | <|skeleton|>
class SerializedException:
def from_exception(e: Exception, tb: types.TracebackType) -> 'SerializedException':
"""Best effort attempt to serialize Exception. Because this will be used to communicate from a subprocess to its parent, we want to surface as much information as possible. It is not ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SerializedException:
def from_exception(e: Exception, tb: types.TracebackType) -> 'SerializedException':
"""Best effort attempt to serialize Exception. Because this will be used to communicate from a subprocess to its parent, we want to surface as much information as possible. It is not possible to se... | the_stack_v2_python_sparse | components/_impl/workers/subprocess_rpc.py | pytorch/benchmark | train | 685 | |
8786429ced04caeb1476ce424aa4a2a514574b10 | [
"bboxW = bbox[2] - bbox[0]\nbboxH = bbox[3] - bbox[1]\nbboxA = bboxW * bboxH\nlog.debug('bbox area %s' % bboxA)\npoint = Image.open(icon)\ntileImg = Image.new('RGBA', (width, height), (0, 0, 0, 0))\nfor station in stations:\n if station.checkDates('2006-01-01', '2006-12-31'):\n point = Image.open(icon + '... | <|body_start_0|>
bboxW = bbox[2] - bbox[0]
bboxH = bbox[3] - bbox[1]
bboxA = bboxW * bboxH
log.debug('bbox area %s' % bboxA)
point = Image.open(icon)
tileImg = Image.new('RGBA', (width, height), (0, 0, 0, 0))
for station in stations:
if station.checkDa... | PointRenderer | [
"BSD-3-Clause",
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PointRenderer:
def renderPoint(self, bbox, stations, width, height, cmap, icon):
"""Creates an RGBA PNG with each station within given BBox represented by an icon."""
<|body_0|>
def txt2img(self, label, fontname='courB08.pil', imgformat='PNG', fgcolor=(0, 0, 0), bgcolor=(255... | stack_v2_sparse_classes_36k_train_010330 | 2,968 | permissive | [
{
"docstring": "Creates an RGBA PNG with each station within given BBox represented by an icon.",
"name": "renderPoint",
"signature": "def renderPoint(self, bbox, stations, width, height, cmap, icon)"
},
{
"docstring": "Render text as image.",
"name": "txt2img",
"signature": "def txt2img... | 2 | stack_v2_sparse_classes_30k_train_006407 | Implement the Python class `PointRenderer` described below.
Class description:
Implement the PointRenderer class.
Method signatures and docstrings:
- def renderPoint(self, bbox, stations, width, height, cmap, icon): Creates an RGBA PNG with each station within given BBox represented by an icon.
- def txt2img(self, la... | Implement the Python class `PointRenderer` described below.
Class description:
Implement the PointRenderer class.
Method signatures and docstrings:
- def renderPoint(self, bbox, stations, width, height, cmap, icon): Creates an RGBA PNG with each station within given BBox represented by an icon.
- def txt2img(self, la... | db9ed729c886b271ce85355b97e39243081e8246 | <|skeleton|>
class PointRenderer:
def renderPoint(self, bbox, stations, width, height, cmap, icon):
"""Creates an RGBA PNG with each station within given BBox represented by an icon."""
<|body_0|>
def txt2img(self, label, fontname='courB08.pil', imgformat='PNG', fgcolor=(0, 0, 0), bgcolor=(255... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PointRenderer:
def renderPoint(self, bbox, stations, width, height, cmap, icon):
"""Creates an RGBA PNG with each station within given BBox represented by an icon."""
bboxW = bbox[2] - bbox[0]
bboxH = bbox[3] - bbox[1]
bboxA = bboxW * bboxH
log.debug('bbox area %s' % bb... | the_stack_v2_python_sparse | cows/service/imps/pointrenderer.py | cedadev/cows | train | 2 | |
046d76758e1b005faef5dcfa3d772c11ab50a958 | [
"self.horizontal_line = [ShapePoint(start_end_points[0]), ShapePoint(start_end_points[1])]\nself.colors = colors or list()\nself.bins = bins\ncolumn_count = 2\ncolumns_width = (0.8, 0.2)\nself.text = text\nself.text_scale = 0.6\nself.start_dots_values = start_dots_values\nself.default_color = 'red'\nself.customers,... | <|body_start_0|>
self.horizontal_line = [ShapePoint(start_end_points[0]), ShapePoint(start_end_points[1])]
self.colors = colors or list()
self.bins = bins
column_count = 2
columns_width = (0.8, 0.2)
self.text = text
self.text_scale = 0.6
self.start_dots_va... | Overridden Table class. Custom text and dots were added. | CustomersTable | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CustomersTable:
"""Overridden Table class. Custom text and dots were added."""
def __init__(self, start_end_points: Tuple[tuple, tuple], row_count: int=0, row_height: Union[int, float]=0.5, visible_row_count: int=0, colors: list=None, bins: Union[int, float]=0, text: str='', start_dots_value... | stack_v2_sparse_classes_36k_train_010331 | 9,066 | no_license | [
{
"docstring": "Class initialization. Args: start_end_points (Tuple[tuple, tuple]): Left top and right top points. ((x1,y1), (x2,y2)). row_count (int, optional): Table row count. Defaults to 0. row_height (Union[int, float], optional): Table row height. Defaults to 0.2. visible_row_count (int, optional): Table ... | 2 | stack_v2_sparse_classes_30k_train_013844 | Implement the Python class `CustomersTable` described below.
Class description:
Overridden Table class. Custom text and dots were added.
Method signatures and docstrings:
- def __init__(self, start_end_points: Tuple[tuple, tuple], row_count: int=0, row_height: Union[int, float]=0.5, visible_row_count: int=0, colors: ... | Implement the Python class `CustomersTable` described below.
Class description:
Overridden Table class. Custom text and dots were added.
Method signatures and docstrings:
- def __init__(self, start_end_points: Tuple[tuple, tuple], row_count: int=0, row_height: Union[int, float]=0.5, visible_row_count: int=0, colors: ... | 290bf56ef888283a0225939ed8b1f87445e506d0 | <|skeleton|>
class CustomersTable:
"""Overridden Table class. Custom text and dots were added."""
def __init__(self, start_end_points: Tuple[tuple, tuple], row_count: int=0, row_height: Union[int, float]=0.5, visible_row_count: int=0, colors: list=None, bins: Union[int, float]=0, text: str='', start_dots_value... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CustomersTable:
"""Overridden Table class. Custom text and dots were added."""
def __init__(self, start_end_points: Tuple[tuple, tuple], row_count: int=0, row_height: Union[int, float]=0.5, visible_row_count: int=0, colors: list=None, bins: Union[int, float]=0, text: str='', start_dots_values: list=None)... | the_stack_v2_python_sparse | classes/table.py | mohovkm/habr_manim | train | 0 |
abd8a666d60903ee2bd83234adbe3c032cf415d8 | [
"self.app_name = app\nself.env = env\nself.region = region\nself.prop_path = prop_path\nself.properties = get_properties(properties_file=prop_path, env=env, region=region)",
"remove_all_lambda_permissions(app_name=self.app_name, env=self.env, region=self.region)\ntriggers = self.properties['lambda_triggers']\nLOG... | <|body_start_0|>
self.app_name = app
self.env = env
self.region = region
self.prop_path = prop_path
self.properties = get_properties(properties_file=prop_path, env=env, region=region)
<|end_body_0|>
<|body_start_1|>
remove_all_lambda_permissions(app_name=self.app_name, e... | Manipulate Lambda events. | LambdaEvent | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LambdaEvent:
"""Manipulate Lambda events."""
def __init__(self, app=None, env=None, region=None, prop_path=None):
"""Lambda event object. Args: app (str): Application name env (str): Environment/Account region (str): AWS Region prop_path (str): Path of environment property file"""
... | stack_v2_sparse_classes_36k_train_010332 | 3,903 | permissive | [
{
"docstring": "Lambda event object. Args: app (str): Application name env (str): Environment/Account region (str): AWS Region prop_path (str): Path of environment property file",
"name": "__init__",
"signature": "def __init__(self, app=None, env=None, region=None, prop_path=None)"
},
{
"docstri... | 2 | null | Implement the Python class `LambdaEvent` described below.
Class description:
Manipulate Lambda events.
Method signatures and docstrings:
- def __init__(self, app=None, env=None, region=None, prop_path=None): Lambda event object. Args: app (str): Application name env (str): Environment/Account region (str): AWS Region... | Implement the Python class `LambdaEvent` described below.
Class description:
Manipulate Lambda events.
Method signatures and docstrings:
- def __init__(self, app=None, env=None, region=None, prop_path=None): Lambda event object. Args: app (str): Application name env (str): Environment/Account region (str): AWS Region... | d88001ea0e33fcd09707b81b5c4ed40e5e21fb59 | <|skeleton|>
class LambdaEvent:
"""Manipulate Lambda events."""
def __init__(self, app=None, env=None, region=None, prop_path=None):
"""Lambda event object. Args: app (str): Application name env (str): Environment/Account region (str): AWS Region prop_path (str): Path of environment property file"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LambdaEvent:
"""Manipulate Lambda events."""
def __init__(self, app=None, env=None, region=None, prop_path=None):
"""Lambda event object. Args: app (str): Application name env (str): Environment/Account region (str): AWS Region prop_path (str): Path of environment property file"""
self.ap... | the_stack_v2_python_sparse | src/foremast/awslambda/awslambdaevent.py | foremast/foremast | train | 151 |
7a20a1e69fcd84fea4ff95beff0f39bc000358f9 | [
"super(QCOWFile, self).__init__(resolver_context, path_spec)\nself._parent_qcow_files = []\nself._sub_file_objects = []",
"super(QCOWFile, self)._Close()\nfor qcow_file in self._parent_qcow_files:\n qcow_file.close()\nself._parent_qcow_files = []\nself._sub_file_objects = []",
"if not path_spec.HasParent():\... | <|body_start_0|>
super(QCOWFile, self).__init__(resolver_context, path_spec)
self._parent_qcow_files = []
self._sub_file_objects = []
<|end_body_0|>
<|body_start_1|>
super(QCOWFile, self)._Close()
for qcow_file in self._parent_qcow_files:
qcow_file.close()
se... | File input/output (IO) object using pyqcow. | QCOWFile | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class QCOWFile:
"""File input/output (IO) object using pyqcow."""
def __init__(self, resolver_context, path_spec):
"""Initializes a file input/output (IO) object. Args: resolver_context (Context): resolver context. path_spec (PathSpec): a path specification."""
<|body_0|>
def ... | stack_v2_sparse_classes_36k_train_010333 | 4,074 | permissive | [
{
"docstring": "Initializes a file input/output (IO) object. Args: resolver_context (Context): resolver context. path_spec (PathSpec): a path specification.",
"name": "__init__",
"signature": "def __init__(self, resolver_context, path_spec)"
},
{
"docstring": "Closes the file-like object.",
... | 5 | null | Implement the Python class `QCOWFile` described below.
Class description:
File input/output (IO) object using pyqcow.
Method signatures and docstrings:
- def __init__(self, resolver_context, path_spec): Initializes a file input/output (IO) object. Args: resolver_context (Context): resolver context. path_spec (PathSpe... | Implement the Python class `QCOWFile` described below.
Class description:
File input/output (IO) object using pyqcow.
Method signatures and docstrings:
- def __init__(self, resolver_context, path_spec): Initializes a file input/output (IO) object. Args: resolver_context (Context): resolver context. path_spec (PathSpe... | 28756d910e951a22c5f0b2bcf5184f055a19d544 | <|skeleton|>
class QCOWFile:
"""File input/output (IO) object using pyqcow."""
def __init__(self, resolver_context, path_spec):
"""Initializes a file input/output (IO) object. Args: resolver_context (Context): resolver context. path_spec (PathSpec): a path specification."""
<|body_0|>
def ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class QCOWFile:
"""File input/output (IO) object using pyqcow."""
def __init__(self, resolver_context, path_spec):
"""Initializes a file input/output (IO) object. Args: resolver_context (Context): resolver context. path_spec (PathSpec): a path specification."""
super(QCOWFile, self).__init__(re... | the_stack_v2_python_sparse | dfvfs/file_io/qcow_file_io.py | log2timeline/dfvfs | train | 197 |
d33dacbaccd9541df099a93fba4afe1967e55b9d | [
"clientObject = clientModel.factory.create('ns0:load_case')\nclearAtributes(clientObject)\nclientObject.no = no\nclientObject.name = name\nclientObject.to_solve = True\nclientObject.analysis_type = AnalysisType.ANALYSIS_TYPE_STATIC.name\nclientObject.static_analysis_settings = 1\nclientObject.action_category = 'Per... | <|body_start_0|>
clientObject = clientModel.factory.create('ns0:load_case')
clearAtributes(clientObject)
clientObject.no = no
clientObject.name = name
clientObject.to_solve = True
clientObject.analysis_type = AnalysisType.ANALYSIS_TYPE_STATIC.name
clientObject.sta... | LoadCase | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LoadCase:
def __init__(self, no: int=1, name: str='Self-weight', self_weight=[True, 0.0, 0.0, 10.0], comment: str='Comment', params: dict={}):
"""Creates a default load case with no further options. Analysis type is static by default. Static analysis settings defaults to 1. Action catego... | stack_v2_sparse_classes_36k_train_010334 | 7,905 | permissive | [
{
"docstring": "Creates a default load case with no further options. Analysis type is static by default. Static analysis settings defaults to 1. Action category is Permanent | G by default.",
"name": "__init__",
"signature": "def __init__(self, no: int=1, name: str='Self-weight', self_weight=[True, 0.0,... | 2 | stack_v2_sparse_classes_30k_train_011521 | Implement the Python class `LoadCase` described below.
Class description:
Implement the LoadCase class.
Method signatures and docstrings:
- def __init__(self, no: int=1, name: str='Self-weight', self_weight=[True, 0.0, 0.0, 10.0], comment: str='Comment', params: dict={}): Creates a default load case with no further o... | Implement the Python class `LoadCase` described below.
Class description:
Implement the LoadCase class.
Method signatures and docstrings:
- def __init__(self, no: int=1, name: str='Self-weight', self_weight=[True, 0.0, 0.0, 10.0], comment: str='Comment', params: dict={}): Creates a default load case with no further o... | 4bd0d744007bdc27d86d6ce535a507cdc81552ca | <|skeleton|>
class LoadCase:
def __init__(self, no: int=1, name: str='Self-weight', self_weight=[True, 0.0, 0.0, 10.0], comment: str='Comment', params: dict={}):
"""Creates a default load case with no further options. Analysis type is static by default. Static analysis settings defaults to 1. Action catego... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LoadCase:
def __init__(self, no: int=1, name: str='Self-weight', self_weight=[True, 0.0, 0.0, 10.0], comment: str='Comment', params: dict={}):
"""Creates a default load case with no further options. Analysis type is static by default. Static analysis settings defaults to 1. Action category is Permanen... | the_stack_v2_python_sparse | RFEM/LoadCasesAndCombinations/loadCase.py | r0m30d4c/DlubalRFEM6 | train | 1 | |
532a27a4eaf4b99ff116957218a6905674767f5d | [
"self.net = net\nself.img_size = img_size\nself.isCuda = isCuda\nself.opt = torch.optim.Adam(self.net.parameters(), lr=lr)\nif self.isCuda:\n self.net.cuda()",
"self.data = data_torch.FaceDataset('D:/celeba/train_data/{}/'.format(self.img_size))\nself.loader = data.DataLoader(dataset=self.data, batch_size=batc... | <|body_start_0|>
self.net = net
self.img_size = img_size
self.isCuda = isCuda
self.opt = torch.optim.Adam(self.net.parameters(), lr=lr)
if self.isCuda:
self.net.cuda()
<|end_body_0|>
<|body_start_1|>
self.data = data_torch.FaceDataset('D:/celeba/train_data/{}... | Trainer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Trainer:
def __init__(self, net, img_size, lr=0.001, isCuda=False):
""":param net: 传入网络 :param size: 传入网络训练的图大小,相当于选择训练集 :param batch: 传入训练的批次大小"""
<|body_0|>
def train(self, batch, isLoad=False, isSave=False):
""":param batch: 训练的批次 :return: 训练网络"""
<|body_1... | stack_v2_sparse_classes_36k_train_010335 | 5,050 | no_license | [
{
"docstring": ":param net: 传入网络 :param size: 传入网络训练的图大小,相当于选择训练集 :param batch: 传入训练的批次大小",
"name": "__init__",
"signature": "def __init__(self, net, img_size, lr=0.001, isCuda=False)"
},
{
"docstring": ":param batch: 训练的批次 :return: 训练网络",
"name": "train",
"signature": "def train(self, b... | 3 | stack_v2_sparse_classes_30k_train_007319 | Implement the Python class `Trainer` described below.
Class description:
Implement the Trainer class.
Method signatures and docstrings:
- def __init__(self, net, img_size, lr=0.001, isCuda=False): :param net: 传入网络 :param size: 传入网络训练的图大小,相当于选择训练集 :param batch: 传入训练的批次大小
- def train(self, batch, isLoad=False, isSave=F... | Implement the Python class `Trainer` described below.
Class description:
Implement the Trainer class.
Method signatures and docstrings:
- def __init__(self, net, img_size, lr=0.001, isCuda=False): :param net: 传入网络 :param size: 传入网络训练的图大小,相当于选择训练集 :param batch: 传入训练的批次大小
- def train(self, batch, isLoad=False, isSave=F... | 1e33b81003e23f5c2e69293edee1f01fca5b7263 | <|skeleton|>
class Trainer:
def __init__(self, net, img_size, lr=0.001, isCuda=False):
""":param net: 传入网络 :param size: 传入网络训练的图大小,相当于选择训练集 :param batch: 传入训练的批次大小"""
<|body_0|>
def train(self, batch, isLoad=False, isSave=False):
""":param batch: 训练的批次 :return: 训练网络"""
<|body_1... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Trainer:
def __init__(self, net, img_size, lr=0.001, isCuda=False):
""":param net: 传入网络 :param size: 传入网络训练的图大小,相当于选择训练集 :param batch: 传入训练的批次大小"""
self.net = net
self.img_size = img_size
self.isCuda = isCuda
self.opt = torch.optim.Adam(self.net.parameters(), lr=lr)
... | the_stack_v2_python_sparse | Mtcnn_Step/Step/step3_Net_and_train/trainer2.py | zh3389/MTCNN | train | 5 | |
fb41e4efa4c4fcc14d26743bdc0ca7ca7df7f855 | [
"self.debug = debug\nself.message = message\nself.errors = validation_errors\nif self.debug:\n print('ParserError - init' + lineno())",
"if self.debug:\n print('to_hash ' + lineno())\nhash = {}\nhash[self.message] = self.errors\nreturn hash",
"if self.debug:\n print('to_string' + lineno())\nprint()\nre... | <|body_start_0|>
self.debug = debug
self.message = message
self.errors = validation_errors
if self.debug:
print('ParserError - init' + lineno())
<|end_body_0|>
<|body_start_1|>
if self.debug:
print('to_hash ' + lineno())
hash = {}
hash[sel... | Parser error | ParserError | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ParserError:
"""Parser error"""
def __init__(self, message, validation_errors='None', debug=False):
"""Initialize :param message: :param validation_errors: :param debug:"""
<|body_0|>
def to_hash(self):
"""Convert to hash :return:"""
<|body_1|>
def t... | stack_v2_sparse_classes_36k_train_010336 | 1,208 | permissive | [
{
"docstring": "Initialize :param message: :param validation_errors: :param debug:",
"name": "__init__",
"signature": "def __init__(self, message, validation_errors='None', debug=False)"
},
{
"docstring": "Convert to hash :return:",
"name": "to_hash",
"signature": "def to_hash(self)"
}... | 3 | null | Implement the Python class `ParserError` described below.
Class description:
Parser error
Method signatures and docstrings:
- def __init__(self, message, validation_errors='None', debug=False): Initialize :param message: :param validation_errors: :param debug:
- def to_hash(self): Convert to hash :return:
- def to_st... | Implement the Python class `ParserError` described below.
Class description:
Parser error
Method signatures and docstrings:
- def __init__(self, message, validation_errors='None', debug=False): Initialize :param message: :param validation_errors: :param debug:
- def to_hash(self): Convert to hash :return:
- def to_st... | a9d0335a532acdb4070e5537155b03b34915b73e | <|skeleton|>
class ParserError:
"""Parser error"""
def __init__(self, message, validation_errors='None', debug=False):
"""Initialize :param message: :param validation_errors: :param debug:"""
<|body_0|>
def to_hash(self):
"""Convert to hash :return:"""
<|body_1|>
def t... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ParserError:
"""Parser error"""
def __init__(self, message, validation_errors='None', debug=False):
"""Initialize :param message: :param validation_errors: :param debug:"""
self.debug = debug
self.message = message
self.errors = validation_errors
if self.debug:
... | the_stack_v2_python_sparse | terraform_model/parser/ParserError.py | rubelw/terraform-validator | train | 7 |
7e3c1e4b6f542e219c60bd052f7d288bc9794a6c | [
"client = MongoClient()\ndb = client['database']\nself.assertEqual(((4, 4, 4), (0, 0, 0)), import_data(db, '', 'products.csv', 'customers.csv', 'rentals.csv'))\ndrop_all(db)",
"client = MongoClient()\ndb = client['database']\nproduct = db['product']\ncustomer = db['customer']\nrentals = db['rentals']\nself.assert... | <|body_start_0|>
client = MongoClient()
db = client['database']
self.assertEqual(((4, 4, 4), (0, 0, 0)), import_data(db, '', 'products.csv', 'customers.csv', 'rentals.csv'))
drop_all(db)
<|end_body_0|>
<|body_start_1|>
client = MongoClient()
db = client['database']
... | Unittest functions for testing database.py | TestDatabase | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestDatabase:
"""Unittest functions for testing database.py"""
def test_import_data(self):
"""Test for import_data function from database.py"""
<|body_0|>
def test_add_data(self):
"""Test for add_data function from database.py"""
<|body_1|>
def test_... | stack_v2_sparse_classes_36k_train_010337 | 3,507 | no_license | [
{
"docstring": "Test for import_data function from database.py",
"name": "test_import_data",
"signature": "def test_import_data(self)"
},
{
"docstring": "Test for add_data function from database.py",
"name": "test_add_data",
"signature": "def test_add_data(self)"
},
{
"docstring"... | 6 | null | Implement the Python class `TestDatabase` described below.
Class description:
Unittest functions for testing database.py
Method signatures and docstrings:
- def test_import_data(self): Test for import_data function from database.py
- def test_add_data(self): Test for add_data function from database.py
- def test_csv_... | Implement the Python class `TestDatabase` described below.
Class description:
Unittest functions for testing database.py
Method signatures and docstrings:
- def test_import_data(self): Test for import_data function from database.py
- def test_add_data(self): Test for add_data function from database.py
- def test_csv_... | 5dac60f39e3909ff05b26721d602ed20f14d6be3 | <|skeleton|>
class TestDatabase:
"""Unittest functions for testing database.py"""
def test_import_data(self):
"""Test for import_data function from database.py"""
<|body_0|>
def test_add_data(self):
"""Test for add_data function from database.py"""
<|body_1|>
def test_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestDatabase:
"""Unittest functions for testing database.py"""
def test_import_data(self):
"""Test for import_data function from database.py"""
client = MongoClient()
db = client['database']
self.assertEqual(((4, 4, 4), (0, 0, 0)), import_data(db, '', 'products.csv', 'cust... | the_stack_v2_python_sparse | students/njschafi/Lesson05/assignment/test_database.py | JavaRod/SP_Python220B_2019 | train | 1 |
a71e730a60260c3af1028e7376343b29e1c17e46 | [
"if not email:\n raise ValueError('Email is needed')\nemail = self.normalize_email(email)\nuser = self.model(email=email, **extra_fields)\nuser.set_password(password)\nuser.save(using=self._db)\nreturn user",
"extra_fields.setdefault('is_staff', False)\nextra_fields.setdefault('is_superuser', False)\nextra_fie... | <|body_start_0|>
if not email:
raise ValueError('Email is needed')
email = self.normalize_email(email)
user = self.model(email=email, **extra_fields)
user.set_password(password)
user.save(using=self._db)
return user
<|end_body_0|>
<|body_start_1|>
ext... | overrides BaseUserManager class for default django random password and normalize_email functionality | ScfUserManager | [
"Apache-2.0",
"GPL-3.0-only",
"BSD-3-Clause",
"AGPL-3.0-only",
"GPL-1.0-or-later",
"Python-2.0",
"BSD-2-Clause",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ScfUserManager:
"""overrides BaseUserManager class for default django random password and normalize_email functionality"""
def _create_user(self, email, password, **extra_fields):
"""Creates and saves a User with the given email and password."""
<|body_0|>
def create_use... | stack_v2_sparse_classes_36k_train_010338 | 2,740 | permissive | [
{
"docstring": "Creates and saves a User with the given email and password.",
"name": "_create_user",
"signature": "def _create_user(self, email, password, **extra_fields)"
},
{
"docstring": "create normal user",
"name": "create_user",
"signature": "def create_user(self, email, password,... | 4 | null | Implement the Python class `ScfUserManager` described below.
Class description:
overrides BaseUserManager class for default django random password and normalize_email functionality
Method signatures and docstrings:
- def _create_user(self, email, password, **extra_fields): Creates and saves a User with the given emai... | Implement the Python class `ScfUserManager` described below.
Class description:
overrides BaseUserManager class for default django random password and normalize_email functionality
Method signatures and docstrings:
- def _create_user(self, email, password, **extra_fields): Creates and saves a User with the given emai... | 4df3f46e35eb8fcab796be27fc1cc7fa7ed561f3 | <|skeleton|>
class ScfUserManager:
"""overrides BaseUserManager class for default django random password and normalize_email functionality"""
def _create_user(self, email, password, **extra_fields):
"""Creates and saves a User with the given email and password."""
<|body_0|>
def create_use... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ScfUserManager:
"""overrides BaseUserManager class for default django random password and normalize_email functionality"""
def _create_user(self, email, password, **extra_fields):
"""Creates and saves a User with the given email and password."""
if not email:
raise ValueError(... | the_stack_v2_python_sparse | SCRM/ums/managers.py | aricent/secure-cloud-native-fabric | train | 2 |
69af30d67b25d4adfa14de6e4d932ab1bae5b846 | [
"counts = collections.defaultdict(int)\nfor v in nums:\n counts[v] += 1\n if len(counts.keys()) == 3:\n rmks = []\n for k in counts.keys():\n counts[k] -= 1\n if counts[k] == 0:\n rmks.append(k)\n for k in rmks:\n counts.pop(k)\nreturn list(... | <|body_start_0|>
counts = collections.defaultdict(int)
for v in nums:
counts[v] += 1
if len(counts.keys()) == 3:
rmks = []
for k in counts.keys():
counts[k] -= 1
if counts[k] == 0:
rmk... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def majorityElement(self, nums):
"""每次去除3个不一样的数字，最后剩下的数字中一定包含出现次数超过1/3的数字。 1. 假设出现次数超过1/3的数字是X，假设最后剩下的数字中不包含它，那么即使前面 每次去掉的三个数字中都包含一个X，它出现的次数也只有N//3，与题意矛盾。 2. 最后最多剩下2个数字， 再分别遍历一次 :param nums: :return:"""
<|body_0|>
def majorityElement2(self, nums):
"""Very f... | stack_v2_sparse_classes_36k_train_010339 | 2,062 | permissive | [
{
"docstring": "每次去除3个不一样的数字，最后剩下的数字中一定包含出现次数超过1/3的数字。 1. 假设出现次数超过1/3的数字是X，假设最后剩下的数字中不包含它，那么即使前面 每次去掉的三个数字中都包含一个X，它出现的次数也只有N//3，与题意矛盾。 2. 最后最多剩下2个数字， 再分别遍历一次 :param nums: :return:",
"name": "majorityElement",
"signature": "def majorityElement(self, nums)"
},
{
"docstring": "Very fast, but not O(... | 2 | stack_v2_sparse_classes_30k_train_018048 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def majorityElement(self, nums): 每次去除3个不一样的数字，最后剩下的数字中一定包含出现次数超过1/3的数字。 1. 假设出现次数超过1/3的数字是X，假设最后剩下的数字中不包含它，那么即使前面 每次去掉的三个数字中都包含一个X，它出现的次数也只有N//3，与题意矛盾。 2. 最后最多剩下2个数字， 再分别遍历一次 :pa... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def majorityElement(self, nums): 每次去除3个不一样的数字，最后剩下的数字中一定包含出现次数超过1/3的数字。 1. 假设出现次数超过1/3的数字是X，假设最后剩下的数字中不包含它，那么即使前面 每次去掉的三个数字中都包含一个X，它出现的次数也只有N//3，与题意矛盾。 2. 最后最多剩下2个数字， 再分别遍历一次 :pa... | 2830c7e2ada8dfd3dcdda7c06846116d4f944a27 | <|skeleton|>
class Solution:
def majorityElement(self, nums):
"""每次去除3个不一样的数字，最后剩下的数字中一定包含出现次数超过1/3的数字。 1. 假设出现次数超过1/3的数字是X，假设最后剩下的数字中不包含它，那么即使前面 每次去掉的三个数字中都包含一个X，它出现的次数也只有N//3，与题意矛盾。 2. 最后最多剩下2个数字， 再分别遍历一次 :param nums: :return:"""
<|body_0|>
def majorityElement2(self, nums):
"""Very f... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def majorityElement(self, nums):
"""每次去除3个不一样的数字，最后剩下的数字中一定包含出现次数超过1/3的数字。 1. 假设出现次数超过1/3的数字是X，假设最后剩下的数字中不包含它，那么即使前面 每次去掉的三个数字中都包含一个X，它出现的次数也只有N//3，与题意矛盾。 2. 最后最多剩下2个数字， 再分别遍历一次 :param nums: :return:"""
counts = collections.defaultdict(int)
for v in nums:
counts[v... | the_stack_v2_python_sparse | leetcode/medium/Major_Element_II.py | shhuan/algorithms | train | 0 | |
f1326a96f183025268d5f01182b82121f8126419 | [
"from pywallet.controller import Controller\nsuper(AliasForm, self).__init__(**kwargs)\nself.address = '0x' + account.address.hex()\ntry:\n self.alias = Controller.get_address_alias(self.address)\nexcept KeyError:\n self.alias = ''",
"title = 'Update your alias'\ncontent = cls(account)\ndialog = MDDialog(ti... | <|body_start_0|>
from pywallet.controller import Controller
super(AliasForm, self).__init__(**kwargs)
self.address = '0x' + account.address.hex()
try:
self.alias = Controller.get_address_alias(self.address)
except KeyError:
self.alias = ''
<|end_body_0|>
... | AliasForm | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AliasForm:
def __init__(self, account, **kwargs):
"""Setups the current alias for the given account."""
<|body_0|>
def create_alias_dialog(cls, account):
"""Creates the update alias dialog."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
from pywall... | stack_v2_sparse_classes_36k_train_010340 | 1,310 | permissive | [
{
"docstring": "Setups the current alias for the given account.",
"name": "__init__",
"signature": "def __init__(self, account, **kwargs)"
},
{
"docstring": "Creates the update alias dialog.",
"name": "create_alias_dialog",
"signature": "def create_alias_dialog(cls, account)"
}
] | 2 | stack_v2_sparse_classes_30k_train_008306 | Implement the Python class `AliasForm` described below.
Class description:
Implement the AliasForm class.
Method signatures and docstrings:
- def __init__(self, account, **kwargs): Setups the current alias for the given account.
- def create_alias_dialog(cls, account): Creates the update alias dialog. | Implement the Python class `AliasForm` described below.
Class description:
Implement the AliasForm class.
Method signatures and docstrings:
- def __init__(self, account, **kwargs): Setups the current alias for the given account.
- def create_alias_dialog(cls, account): Creates the update alias dialog.
<|skeleton|>
c... | 97c665a63d0dbab181657100bb42c4b5cc8270b1 | <|skeleton|>
class AliasForm:
def __init__(self, account, **kwargs):
"""Setups the current alias for the given account."""
<|body_0|>
def create_alias_dialog(cls, account):
"""Creates the update alias dialog."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AliasForm:
def __init__(self, account, **kwargs):
"""Setups the current alias for the given account."""
from pywallet.controller import Controller
super(AliasForm, self).__init__(**kwargs)
self.address = '0x' + account.address.hex()
try:
self.alias = Control... | the_stack_v2_python_sparse | src/pywallet/aliasform.py | AndreMiras/PyWallet | train | 71 | |
27e2db0f96453751978fe2b1455273cfe2e8b1f6 | [
"add_input_output_information(self, input_names, output_name, output_shape)\nself.window_size = np.ascontiguousarray(window_size, dtype=np.uintp)\nself.input_shape = np.ascontiguousarray(image_shape, dtype=np.uintp)\nself.stride = np.ascontiguousarray(strides, dtype=np.uintp)\nself.pad_top = pad_top\nself.pad_left ... | <|body_start_0|>
add_input_output_information(self, input_names, output_name, output_shape)
self.window_size = np.ascontiguousarray(window_size, dtype=np.uintp)
self.input_shape = np.ascontiguousarray(image_shape, dtype=np.uintp)
self.stride = np.ascontiguousarray(strides, dtype=np.uintp... | DeepzonoPool | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DeepzonoPool:
def __init__(self, image_shape, window_size, strides, pad_top, pad_left, pad_bottom, pad_right, input_names, output_name, output_shape, is_maxpool):
"""Arguments --------- image_shape : numpy.ndarray 1D array of shape [height, width, channels] window_size : numpy.ndarray 1D... | stack_v2_sparse_classes_36k_train_010341 | 34,420 | permissive | [
{
"docstring": "Arguments --------- image_shape : numpy.ndarray 1D array of shape [height, width, channels] window_size : numpy.ndarray 1D array of shape [height, width] representing the window's size in these directions strides : numpy.ndarray 1D array of shape [height, width] representing the stride in these ... | 2 | stack_v2_sparse_classes_30k_train_021160 | Implement the Python class `DeepzonoPool` described below.
Class description:
Implement the DeepzonoPool class.
Method signatures and docstrings:
- def __init__(self, image_shape, window_size, strides, pad_top, pad_left, pad_bottom, pad_right, input_names, output_name, output_shape, is_maxpool): Arguments --------- i... | Implement the Python class `DeepzonoPool` described below.
Class description:
Implement the DeepzonoPool class.
Method signatures and docstrings:
- def __init__(self, image_shape, window_size, strides, pad_top, pad_left, pad_bottom, pad_right, input_names, output_name, output_shape, is_maxpool): Arguments --------- i... | 8771d3158b2c64a360d5bdfd4433490863257dd6 | <|skeleton|>
class DeepzonoPool:
def __init__(self, image_shape, window_size, strides, pad_top, pad_left, pad_bottom, pad_right, input_names, output_name, output_shape, is_maxpool):
"""Arguments --------- image_shape : numpy.ndarray 1D array of shape [height, width, channels] window_size : numpy.ndarray 1D... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DeepzonoPool:
def __init__(self, image_shape, window_size, strides, pad_top, pad_left, pad_bottom, pad_right, input_names, output_name, output_shape, is_maxpool):
"""Arguments --------- image_shape : numpy.ndarray 1D array of shape [height, width, channels] window_size : numpy.ndarray 1D array of shap... | the_stack_v2_python_sparse | tf_verify/deepzono_nodes.py | eth-sri/eran | train | 306 | |
9cfb684630fd561a1d06f476701dba6620760258 | [
"if self._locked:\n raise AlreadyLockedException('File %s is already locked' % self._filename)\nstart_time = time.time()\nvalidate_file(self._filename)\ntry:\n self._fh = open(self._filename, self._mode)\nexcept IOError as e:\n if e.errno in (errno.EPERM, errno.EACCES):\n self._fh = open(self._filen... | <|body_start_0|>
if self._locked:
raise AlreadyLockedException('File %s is already locked' % self._filename)
start_time = time.time()
validate_file(self._filename)
try:
self._fh = open(self._filename, self._mode)
except IOError as e:
if e.errno... | Open, lock, and unlock a file using fcntl.lockf. | _FcntlOpener | [
"LicenseRef-scancode-unknown-license-reference",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class _FcntlOpener:
"""Open, lock, and unlock a file using fcntl.lockf."""
def open_and_lock(self, timeout, delay):
"""Open the file and lock it. Args: timeout: float, How long to try to lock for. delay: float, How long to wait between retries Raises: AlreadyLockedException: if the lock is... | stack_v2_sparse_classes_36k_train_010342 | 11,504 | permissive | [
{
"docstring": "Open the file and lock it. Args: timeout: float, How long to try to lock for. delay: float, How long to wait between retries Raises: AlreadyLockedException: if the lock is already acquired. IOError: if the open fails. CredentialsFileSymbolicLinkError if the file is a symbolic link.",
"name":... | 2 | null | Implement the Python class `_FcntlOpener` described below.
Class description:
Open, lock, and unlock a file using fcntl.lockf.
Method signatures and docstrings:
- def open_and_lock(self, timeout, delay): Open the file and lock it. Args: timeout: float, How long to try to lock for. delay: float, How long to wait betwe... | Implement the Python class `_FcntlOpener` described below.
Class description:
Open, lock, and unlock a file using fcntl.lockf.
Method signatures and docstrings:
- def open_and_lock(self, timeout, delay): Open the file and lock it. Args: timeout: float, How long to try to lock for. delay: float, How long to wait betwe... | 53102de187a48ac2cfc241fef54dcbc29c453a8e | <|skeleton|>
class _FcntlOpener:
"""Open, lock, and unlock a file using fcntl.lockf."""
def open_and_lock(self, timeout, delay):
"""Open the file and lock it. Args: timeout: float, How long to try to lock for. delay: float, How long to wait between retries Raises: AlreadyLockedException: if the lock is... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class _FcntlOpener:
"""Open, lock, and unlock a file using fcntl.lockf."""
def open_and_lock(self, timeout, delay):
"""Open the file and lock it. Args: timeout: float, How long to try to lock for. delay: float, How long to wait between retries Raises: AlreadyLockedException: if the lock is already acqu... | the_stack_v2_python_sparse | third_party/gae_ts_mon/gae_ts_mon/third_party/oauth2client/locked_file.py | catapult-project/catapult | train | 2,032 |
70ff8e149ff472e3cf813a317403512e988eac57 | [
"try:\n subject = Subject.objects.get(pk=pk)\n serializer = SubjectSerializer(subject, context={'request': request})\n return Response(serializer.data)\nexcept Exception as ex:\n return HttpResponseServerError(ex)",
"subjects = Subject.objects.all().order_by('label')\nserializer = SubjectSerializer(su... | <|body_start_0|>
try:
subject = Subject.objects.get(pk=pk)
serializer = SubjectSerializer(subject, context={'request': request})
return Response(serializer.data)
except Exception as ex:
return HttpResponseServerError(ex)
<|end_body_0|>
<|body_start_1|>
... | Journey Subjects | SubjectViewSet | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SubjectViewSet:
"""Journey Subjects"""
def retrieve(self, request, pk=None):
"""Handle GET requests for single subject returns: Response -- JSON serialized subject"""
<|body_0|>
def list(self, request):
"""Handle GET requests to get all subjects Returns: Response... | stack_v2_sparse_classes_36k_train_010343 | 1,370 | no_license | [
{
"docstring": "Handle GET requests for single subject returns: Response -- JSON serialized subject",
"name": "retrieve",
"signature": "def retrieve(self, request, pk=None)"
},
{
"docstring": "Handle GET requests to get all subjects Returns: Response -- JSON serialized list of subjects",
"na... | 2 | stack_v2_sparse_classes_30k_train_002281 | Implement the Python class `SubjectViewSet` described below.
Class description:
Journey Subjects
Method signatures and docstrings:
- def retrieve(self, request, pk=None): Handle GET requests for single subject returns: Response -- JSON serialized subject
- def list(self, request): Handle GET requests to get all subje... | Implement the Python class `SubjectViewSet` described below.
Class description:
Journey Subjects
Method signatures and docstrings:
- def retrieve(self, request, pk=None): Handle GET requests for single subject returns: Response -- JSON serialized subject
- def list(self, request): Handle GET requests to get all subje... | bd996853f6bd9a95d15115248300e6d801c0dc47 | <|skeleton|>
class SubjectViewSet:
"""Journey Subjects"""
def retrieve(self, request, pk=None):
"""Handle GET requests for single subject returns: Response -- JSON serialized subject"""
<|body_0|>
def list(self, request):
"""Handle GET requests to get all subjects Returns: Response... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SubjectViewSet:
"""Journey Subjects"""
def retrieve(self, request, pk=None):
"""Handle GET requests for single subject returns: Response -- JSON serialized subject"""
try:
subject = Subject.objects.get(pk=pk)
serializer = SubjectSerializer(subject, context={'reques... | the_stack_v2_python_sparse | capstoneapi/views/subject.py | jeaninebeckle/backend-capstone-api | train | 0 |
2cf2edd25c0f87c671c3af1bca5be7385563ec60 | [
"super().__init__()\nself.vocab_size = vocab_size\nself.embed_size = embed_size\nself.lstm_size = lstm_size\nself.output_size = output_size\nself.lstm_layers = lstm_layers\nself.dropout = dropout\nself.embedding = nn.Embedding(num_embeddings=vocab_size, embedding_dim=embed_size)\nself.lstm = nn.LSTM(embed_size, lst... | <|body_start_0|>
super().__init__()
self.vocab_size = vocab_size
self.embed_size = embed_size
self.lstm_size = lstm_size
self.output_size = output_size
self.lstm_layers = lstm_layers
self.dropout = dropout
self.embedding = nn.Embedding(num_embeddings=vocab... | TextClassifier | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TextClassifier:
def __init__(self, vocab_size, embed_size, lstm_size, output_size, lstm_layers=1, dropout=0.1):
"""Initialize the model by setting up the layers. Parameters ---------- vocab_size : The vocabulary size. embed_size : The embedding layer size. embedding_dim lstm_size : The L... | stack_v2_sparse_classes_36k_train_010344 | 11,718 | no_license | [
{
"docstring": "Initialize the model by setting up the layers. Parameters ---------- vocab_size : The vocabulary size. embed_size : The embedding layer size. embedding_dim lstm_size : The LSTM layer size. hidden_dim output_size : The output size. lstm_layers : The number of LSTM layers. n_layers dropout : The d... | 3 | stack_v2_sparse_classes_30k_train_000262 | Implement the Python class `TextClassifier` described below.
Class description:
Implement the TextClassifier class.
Method signatures and docstrings:
- def __init__(self, vocab_size, embed_size, lstm_size, output_size, lstm_layers=1, dropout=0.1): Initialize the model by setting up the layers. Parameters ---------- v... | Implement the Python class `TextClassifier` described below.
Class description:
Implement the TextClassifier class.
Method signatures and docstrings:
- def __init__(self, vocab_size, embed_size, lstm_size, output_size, lstm_layers=1, dropout=0.1): Initialize the model by setting up the layers. Parameters ---------- v... | 0cdabea4afb58af71b909fbde7a9260eaa2b7849 | <|skeleton|>
class TextClassifier:
def __init__(self, vocab_size, embed_size, lstm_size, output_size, lstm_layers=1, dropout=0.1):
"""Initialize the model by setting up the layers. Parameters ---------- vocab_size : The vocabulary size. embed_size : The embedding layer size. embedding_dim lstm_size : The L... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TextClassifier:
def __init__(self, vocab_size, embed_size, lstm_size, output_size, lstm_layers=1, dropout=0.1):
"""Initialize the model by setting up the layers. Parameters ---------- vocab_size : The vocabulary size. embed_size : The embedding layer size. embedding_dim lstm_size : The LSTM layer size... | the_stack_v2_python_sparse | trial_calculations_2/LSTMs.py | ThesisNegatif/Thesis | train | 2 | |
a25fdc277578b2111e1eb7828565387d18c757b4 | [
"expr = expr.replace(' ', '').replace(',', '.')\nself.app = app\nif expr.count('=') > 1:\n raise InvalidEquacaoException(\"Há mais que um '=' na equação\")\nelif expr.count('=') == 0:\n expr += '=0'\nterm, term2 = expr.split('=')\nself.first = Expressao(term)\nself.last = Expressao(term2)",
"if self.first !... | <|body_start_0|>
expr = expr.replace(' ', '').replace(',', '.')
self.app = app
if expr.count('=') > 1:
raise InvalidEquacaoException("Há mais que um '=' na equação")
elif expr.count('=') == 0:
expr += '=0'
term, term2 = expr.split('=')
self.first =... | Classe que representa a equação do segundo grau. | Equacao | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Equacao:
"""Classe que representa a equação do segundo grau."""
def __init__(self, app, expr):
"""Construtor da classe. Faz as primeiras verificações da equação. cria as instancias das expressões dadas, caso seja dado apenas uma, inicializa a outra com o valor 0."""
<|body_0|... | stack_v2_sparse_classes_36k_train_010345 | 2,803 | no_license | [
{
"docstring": "Construtor da classe. Faz as primeiras verificações da equação. cria as instancias das expressões dadas, caso seja dado apenas uma, inicializa a outra com o valor 0.",
"name": "__init__",
"signature": "def __init__(self, app, expr)"
},
{
"docstring": "Faz a segunda verificação, c... | 5 | stack_v2_sparse_classes_30k_train_019114 | Implement the Python class `Equacao` described below.
Class description:
Classe que representa a equação do segundo grau.
Method signatures and docstrings:
- def __init__(self, app, expr): Construtor da classe. Faz as primeiras verificações da equação. cria as instancias das expressões dadas, caso seja dado apenas um... | Implement the Python class `Equacao` described below.
Class description:
Classe que representa a equação do segundo grau.
Method signatures and docstrings:
- def __init__(self, app, expr): Construtor da classe. Faz as primeiras verificações da equação. cria as instancias das expressões dadas, caso seja dado apenas um... | f17de5dcfe057df28e956213737a95321693e848 | <|skeleton|>
class Equacao:
"""Classe que representa a equação do segundo grau."""
def __init__(self, app, expr):
"""Construtor da classe. Faz as primeiras verificações da equação. cria as instancias das expressões dadas, caso seja dado apenas uma, inicializa a outra com o valor 0."""
<|body_0|... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Equacao:
"""Classe que representa a equação do segundo grau."""
def __init__(self, app, expr):
"""Construtor da classe. Faz as primeiras verificações da equação. cria as instancias das expressões dadas, caso seja dado apenas uma, inicializa a outra com o valor 0."""
expr = expr.replace(' ... | the_stack_v2_python_sparse | equacao_resolver/equacao.py | rafael146/workufal | train | 0 |
01b1959a87e5d0745caeceb32d6188b53395ae79 | [
"print('Enter the values for filters you want to apply (Press enter to skip)')\nfor key in self.FILTERS:\n while True:\n value = SelectFiles.validate(input(self.FILTERS[key]['description']), key)\n if value == '':\n break\n elif not isinstance(value, bool):\n self.FILTE... | <|body_start_0|>
print('Enter the values for filters you want to apply (Press enter to skip)')
for key in self.FILTERS:
while True:
value = SelectFiles.validate(input(self.FILTERS[key]['description']), key)
if value == '':
break
... | Class containing method to select and filter files at a path. It contains different filters based on which, the files can be filtered | SelectFiles | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SelectFiles:
"""Class containing method to select and filter files at a path. It contains different filters based on which, the files can be filtered"""
def __init__(self):
"""Takes in arguments from the user for filtering files"""
<|body_0|>
def list_all_files(path):
... | stack_v2_sparse_classes_36k_train_010346 | 8,019 | permissive | [
{
"docstring": "Takes in arguments from the user for filtering files",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Returns a Dict object of all the files present at the path argument.",
"name": "list_all_files",
"signature": "def list_all_files(path)"
},
... | 5 | stack_v2_sparse_classes_30k_test_000014 | Implement the Python class `SelectFiles` described below.
Class description:
Class containing method to select and filter files at a path. It contains different filters based on which, the files can be filtered
Method signatures and docstrings:
- def __init__(self): Takes in arguments from the user for filtering file... | Implement the Python class `SelectFiles` described below.
Class description:
Class containing method to select and filter files at a path. It contains different filters based on which, the files can be filtered
Method signatures and docstrings:
- def __init__(self): Takes in arguments from the user for filtering file... | 31fd3fb1233f39ea2252a7a44160ff8a2140f7bd | <|skeleton|>
class SelectFiles:
"""Class containing method to select and filter files at a path. It contains different filters based on which, the files can be filtered"""
def __init__(self):
"""Takes in arguments from the user for filtering files"""
<|body_0|>
def list_all_files(path):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SelectFiles:
"""Class containing method to select and filter files at a path. It contains different filters based on which, the files can be filtered"""
def __init__(self):
"""Takes in arguments from the user for filtering files"""
print('Enter the values for filters you want to apply (Pr... | the_stack_v2_python_sparse | Python/Bulk_File_Renamer/utils.py | HarshCasper/Rotten-Scripts | train | 1,474 |
c1fb96d281ff340126642b38e421cb45381803dd | [
"config = current_app.cea_config\ndashboards = cea.plots.read_dashboards(config, current_app.plot_cache)\nout = []\nfor d in dashboards:\n out.append(dashboard_to_dict(d))\nreturn out",
"form = api.payload\nconfig = current_app.cea_config\nif 'grid' in form['layout']:\n types = [[2] + [1] * 4, [1] * 6, [1] ... | <|body_start_0|>
config = current_app.cea_config
dashboards = cea.plots.read_dashboards(config, current_app.plot_cache)
out = []
for d in dashboards:
out.append(dashboard_to_dict(d))
return out
<|end_body_0|>
<|body_start_1|>
form = api.payload
config... | Dashboards | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Dashboards:
def get(self):
"""Get list of Dashboards"""
<|body_0|>
def post(self):
"""Create Dashboard"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
config = current_app.cea_config
dashboards = cea.plots.read_dashboards(config, current_app... | stack_v2_sparse_classes_36k_train_010347 | 9,106 | permissive | [
{
"docstring": "Get list of Dashboards",
"name": "get",
"signature": "def get(self)"
},
{
"docstring": "Create Dashboard",
"name": "post",
"signature": "def post(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_017597 | Implement the Python class `Dashboards` described below.
Class description:
Implement the Dashboards class.
Method signatures and docstrings:
- def get(self): Get list of Dashboards
- def post(self): Create Dashboard | Implement the Python class `Dashboards` described below.
Class description:
Implement the Dashboards class.
Method signatures and docstrings:
- def get(self): Get list of Dashboards
- def post(self): Create Dashboard
<|skeleton|>
class Dashboards:
def get(self):
"""Get list of Dashboards"""
<|bo... | b84bcefdfdfc2bc0e009b5284b74391a957995ac | <|skeleton|>
class Dashboards:
def get(self):
"""Get list of Dashboards"""
<|body_0|>
def post(self):
"""Create Dashboard"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Dashboards:
def get(self):
"""Get list of Dashboards"""
config = current_app.cea_config
dashboards = cea.plots.read_dashboards(config, current_app.plot_cache)
out = []
for d in dashboards:
out.append(dashboard_to_dict(d))
return out
def post(sel... | the_stack_v2_python_sparse | cea/interfaces/dashboard/api/dashboard.py | architecture-building-systems/CityEnergyAnalyst | train | 166 | |
949909c103bfbcd9b9b0f1250e66cc2695491108 | [
"if RedisPool.__pool == None:\n RedisPool()\nreturn RedisPool.__pool",
"if RedisPool.__pool != None:\n logger.info('Using redis pool singleton')\nelse:\n try:\n RedisPool.__pool = redis.ConnectionPool(host=REDIS_HOST, port=int(REDIS_PORT), db=0, decode_responses=True)\n except Exception as e:\n... | <|body_start_0|>
if RedisPool.__pool == None:
RedisPool()
return RedisPool.__pool
<|end_body_0|>
<|body_start_1|>
if RedisPool.__pool != None:
logger.info('Using redis pool singleton')
else:
try:
RedisPool.__pool = redis.ConnectionPool... | RedisPool | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RedisPool:
def getPool():
"""Static access method."""
<|body_0|>
def __init__(self):
"""Virtually private constructor."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if RedisPool.__pool == None:
RedisPool()
return RedisPool.__po... | stack_v2_sparse_classes_36k_train_010348 | 2,420 | permissive | [
{
"docstring": "Static access method.",
"name": "getPool",
"signature": "def getPool()"
},
{
"docstring": "Virtually private constructor.",
"name": "__init__",
"signature": "def __init__(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_015223 | Implement the Python class `RedisPool` described below.
Class description:
Implement the RedisPool class.
Method signatures and docstrings:
- def getPool(): Static access method.
- def __init__(self): Virtually private constructor. | Implement the Python class `RedisPool` described below.
Class description:
Implement the RedisPool class.
Method signatures and docstrings:
- def getPool(): Static access method.
- def __init__(self): Virtually private constructor.
<|skeleton|>
class RedisPool:
def getPool():
"""Static access method."""... | 7da0de453163130e116611f0ed750414d6d5c107 | <|skeleton|>
class RedisPool:
def getPool():
"""Static access method."""
<|body_0|>
def __init__(self):
"""Virtually private constructor."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RedisPool:
def getPool():
"""Static access method."""
if RedisPool.__pool == None:
RedisPool()
return RedisPool.__pool
def __init__(self):
"""Virtually private constructor."""
if RedisPool.__pool != None:
logger.info('Using redis pool single... | the_stack_v2_python_sparse | gamechangerml/api/utils/redisdriver.py | iamjoshbinder/gamechanger-ml | train | 0 | |
952285a1e4b540700db6b28055fcb686b15938a5 | [
"output_schema = CMOutput()\njson_testdata = get_json_testdata('marshmallow.json')\nout = output_schema.load(data=json_testdata)\nself.assertGreater(len(out), 0)",
"output_schema = CMOutput()\njson_testdata = get_json_testdata('test.json')\nout = output_schema.load(data=json_testdata)\nself.assertGreater(len(out)... | <|body_start_0|>
output_schema = CMOutput()
json_testdata = get_json_testdata('marshmallow.json')
out = output_schema.load(data=json_testdata)
self.assertGreater(len(out), 0)
<|end_body_0|>
<|body_start_1|>
output_schema = CMOutput()
json_testdata = get_json_testdata('te... | TestSchema | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestSchema:
def testLoad(self):
"""Test the load and the validation of json"""
<|body_0|>
def testLongLoad(self):
"""Test the load and the validation of long json"""
<|body_1|>
def testEmptyLoad(self):
"""Test the load and the validation of empty... | stack_v2_sparse_classes_36k_train_010349 | 3,351 | permissive | [
{
"docstring": "Test the load and the validation of json",
"name": "testLoad",
"signature": "def testLoad(self)"
},
{
"docstring": "Test the load and the validation of long json",
"name": "testLongLoad",
"signature": "def testLongLoad(self)"
},
{
"docstring": "Test the load and t... | 3 | null | Implement the Python class `TestSchema` described below.
Class description:
Implement the TestSchema class.
Method signatures and docstrings:
- def testLoad(self): Test the load and the validation of json
- def testLongLoad(self): Test the load and the validation of long json
- def testEmptyLoad(self): Test the load ... | Implement the Python class `TestSchema` described below.
Class description:
Implement the TestSchema class.
Method signatures and docstrings:
- def testLoad(self): Test the load and the validation of json
- def testLongLoad(self): Test the load and the validation of long json
- def testEmptyLoad(self): Test the load ... | bb336e434afcc11463b53880558d9c314f309c0e | <|skeleton|>
class TestSchema:
def testLoad(self):
"""Test the load and the validation of json"""
<|body_0|>
def testLongLoad(self):
"""Test the load and the validation of long json"""
<|body_1|>
def testEmptyLoad(self):
"""Test the load and the validation of empty... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestSchema:
def testLoad(self):
"""Test the load and the validation of json"""
output_schema = CMOutput()
json_testdata = get_json_testdata('marshmallow.json')
out = output_schema.load(data=json_testdata)
self.assertGreater(len(out), 0)
def testLongLoad(self):
... | the_stack_v2_python_sparse | cm/base/BaseCM/test.py | sfrias/enermaps | train | 0 | |
ecabc9886fa79310e177369c541ac253b6e8315e | [
"quick = head\nslow = head\nwhile quick.next:\n quick = quick.next.next\n slow = slow.next\n if quick == slow:\n return True\n if not quick:\n return False\nreturn False",
"if not head:\n print('null')\n return\nif not self.checkLoop(head):\n print('null')\n return\nelse:\n ... | <|body_start_0|>
quick = head
slow = head
while quick.next:
quick = quick.next.next
slow = slow.next
if quick == slow:
return True
if not quick:
return False
return False
<|end_body_0|>
<|body_start_1|>
... | 判断链表中环的入口节点解决方案 | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
"""判断链表中环的入口节点解决方案"""
def checkLoop(self, head):
"""检查是否存在环"""
<|body_0|>
def EntryNodeOfLoop(self, head):
"""获取链表环的入口节点"""
<|body_1|>
def EntryNodeOfLoop2(self, head):
"""获取链表环的入口节点——减少了计算环长度步骤和控制双指针间隔的步骤（2x-x=n）"""
<|body_... | stack_v2_sparse_classes_36k_train_010350 | 5,548 | no_license | [
{
"docstring": "检查是否存在环",
"name": "checkLoop",
"signature": "def checkLoop(self, head)"
},
{
"docstring": "获取链表环的入口节点",
"name": "EntryNodeOfLoop",
"signature": "def EntryNodeOfLoop(self, head)"
},
{
"docstring": "获取链表环的入口节点——减少了计算环长度步骤和控制双指针间隔的步骤（2x-x=n）",
"name": "EntryNodeO... | 3 | null | Implement the Python class `Solution` described below.
Class description:
判断链表中环的入口节点解决方案
Method signatures and docstrings:
- def checkLoop(self, head): 检查是否存在环
- def EntryNodeOfLoop(self, head): 获取链表环的入口节点
- def EntryNodeOfLoop2(self, head): 获取链表环的入口节点——减少了计算环长度步骤和控制双指针间隔的步骤（2x-x=n） | Implement the Python class `Solution` described below.
Class description:
判断链表中环的入口节点解决方案
Method signatures and docstrings:
- def checkLoop(self, head): 检查是否存在环
- def EntryNodeOfLoop(self, head): 获取链表环的入口节点
- def EntryNodeOfLoop2(self, head): 获取链表环的入口节点——减少了计算环长度步骤和控制双指针间隔的步骤（2x-x=n）
<|skeleton|>
class Solution:
... | 4e4f739402b95691f6c91411da26d7d3bfe042b6 | <|skeleton|>
class Solution:
"""判断链表中环的入口节点解决方案"""
def checkLoop(self, head):
"""检查是否存在环"""
<|body_0|>
def EntryNodeOfLoop(self, head):
"""获取链表环的入口节点"""
<|body_1|>
def EntryNodeOfLoop2(self, head):
"""获取链表环的入口节点——减少了计算环长度步骤和控制双指针间隔的步骤（2x-x=n）"""
<|body_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
"""判断链表中环的入口节点解决方案"""
def checkLoop(self, head):
"""检查是否存在环"""
quick = head
slow = head
while quick.next:
quick = quick.next.next
slow = slow.next
if quick == slow:
return True
if not quick:
... | the_stack_v2_python_sparse | 剑指offer/55、链表中环的入口节点.py | hugechuanqi/Algorithms-and-Data-Structures | train | 3 |
eff6e0b49dee7e51b28edb61300870e80bc9f8e1 | [
"filename = TRUKeywords.download_tru()\nself.assertTrue(path.exists(filename))\nremove(filename)\nfilename = TRUKeywords.download_tru(file_name='tru.zip')\nself.assertTrue(path.exists('tru.zip'))\nremove(filename)\nret_file_path = TRUKeywords.download_tru(file_type='tarball')\nself.assertTrue(path.exists(ret_file_p... | <|body_start_0|>
filename = TRUKeywords.download_tru()
self.assertTrue(path.exists(filename))
remove(filename)
filename = TRUKeywords.download_tru(file_name='tru.zip')
self.assertTrue(path.exists('tru.zip'))
remove(filename)
ret_file_path = TRUKeywords.download_tr... | Unit tests for TRUKeywords | TruTests | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TruTests:
"""Unit tests for TRUKeywords"""
def test_download_latest(self):
"""Test latest versions"""
<|body_0|>
def test_download_specific(self):
"""Test specific versions"""
<|body_1|>
def test_run_tru(self):
"""Test full run and retrieval"... | stack_v2_sparse_classes_36k_train_010351 | 10,750 | no_license | [
{
"docstring": "Test latest versions",
"name": "test_download_latest",
"signature": "def test_download_latest(self)"
},
{
"docstring": "Test specific versions",
"name": "test_download_specific",
"signature": "def test_download_specific(self)"
},
{
"docstring": "Test full run and ... | 3 | stack_v2_sparse_classes_30k_train_002429 | Implement the Python class `TruTests` described below.
Class description:
Unit tests for TRUKeywords
Method signatures and docstrings:
- def test_download_latest(self): Test latest versions
- def test_download_specific(self): Test specific versions
- def test_run_tru(self): Test full run and retrieval | Implement the Python class `TruTests` described below.
Class description:
Unit tests for TRUKeywords
Method signatures and docstrings:
- def test_download_latest(self): Test latest versions
- def test_download_specific(self): Test specific versions
- def test_run_tru(self): Test full run and retrieval
<|skeleton|>
c... | 24a74926170cbdfafa47e972644e2fe5b627d8ff | <|skeleton|>
class TruTests:
"""Unit tests for TRUKeywords"""
def test_download_latest(self):
"""Test latest versions"""
<|body_0|>
def test_download_specific(self):
"""Test specific versions"""
<|body_1|>
def test_run_tru(self):
"""Test full run and retrieval"... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TruTests:
"""Unit tests for TRUKeywords"""
def test_download_latest(self):
"""Test latest versions"""
filename = TRUKeywords.download_tru()
self.assertTrue(path.exists(filename))
remove(filename)
filename = TRUKeywords.download_tru(file_name='tru.zip')
self... | the_stack_v2_python_sparse | robo4.2/fusion/FusionLibrary/keywords/tru.py | richa92/Jenkin_Regression_Testing | train | 0 |
2e7f37a250c9756984f1672ea51b26f386c7e40d | [
"super(Assert, self).__init__(*args, **kw)\nself.func = func\nself.err_msg = err_msg",
"result = self.func(value, *args, **kw)\nmessage = self._build_message(value, result) + (self.err_msg if not result else '')\nreturn ValidationResult(value, result, message)"
] | <|body_start_0|>
super(Assert, self).__init__(*args, **kw)
self.func = func
self.err_msg = err_msg
<|end_body_0|>
<|body_start_1|>
result = self.func(value, *args, **kw)
message = self._build_message(value, result) + (self.err_msg if not result else '')
return Validation... | Generic validator which is using function to validate value. .. code-block:: python validation_expression = Assert(lambda x: isString(x), 'Value is not correct') validation_expression.validate('test_string') # returns ValidationResult object | Assert | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Assert:
"""Generic validator which is using function to validate value. .. code-block:: python validation_expression = Assert(lambda x: isString(x), 'Value is not correct') validation_expression.validate('test_string') # returns ValidationResult object"""
def __init__(self, func, err_msg, *a... | stack_v2_sparse_classes_36k_train_010352 | 16,665 | no_license | [
{
"docstring": ":param func: Validation function. :param string err_msg: Message which will be add when validation fail.",
"name": "__init__",
"signature": "def __init__(self, func, err_msg, *args, **kw)"
},
{
"docstring": "Method checks if specified value meet requirements.",
"name": "valid... | 2 | null | Implement the Python class `Assert` described below.
Class description:
Generic validator which is using function to validate value. .. code-block:: python validation_expression = Assert(lambda x: isString(x), 'Value is not correct') validation_expression.validate('test_string') # returns ValidationResult object
Meth... | Implement the Python class `Assert` described below.
Class description:
Generic validator which is using function to validate value. .. code-block:: python validation_expression = Assert(lambda x: isString(x), 'Value is not correct') validation_expression.validate('test_string') # returns ValidationResult object
Meth... | 75487a40ac2cc5f24f70d011ad6cd3924908f783 | <|skeleton|>
class Assert:
"""Generic validator which is using function to validate value. .. code-block:: python validation_expression = Assert(lambda x: isString(x), 'Value is not correct') validation_expression.validate('test_string') # returns ValidationResult object"""
def __init__(self, func, err_msg, *a... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Assert:
"""Generic validator which is using function to validate value. .. code-block:: python validation_expression = Assert(lambda x: isString(x), 'Value is not correct') validation_expression.validate('test_string') # returns ValidationResult object"""
def __init__(self, func, err_msg, *args, **kw):
... | the_stack_v2_python_sparse | bts_infomodel/ute_common_validator/validator.py | jufei/BtsShell | train | 0 |
f9170b9912c228cfa84c28c689686b5386e0da78 | [
"self.old_username = self.instance.username\nself.old_file_root = self.instance.file_root()\nif User.objects.filter(username__iexact=self.cleaned_data['username']):\n raise forms.ValidationError('A user with that username already exists.')\nreturn self.cleaned_data['username'].lower()",
"new_username = self.cl... | <|body_start_0|>
self.old_username = self.instance.username
self.old_file_root = self.instance.file_root()
if User.objects.filter(username__iexact=self.cleaned_data['username']):
raise forms.ValidationError('A user with that username already exists.')
return self.cleaned_data... | Updating the username filed | UsernameChangeForm | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UsernameChangeForm:
"""Updating the username filed"""
def clean_username(self):
"""Record the original username in case it is needed"""
<|body_0|>
def save(self):
"""Change the media file directory name and photo name if any, to match the new username"""
... | stack_v2_sparse_classes_36k_train_010353 | 26,163 | permissive | [
{
"docstring": "Record the original username in case it is needed",
"name": "clean_username",
"signature": "def clean_username(self)"
},
{
"docstring": "Change the media file directory name and photo name if any, to match the new username",
"name": "save",
"signature": "def save(self)"
... | 2 | stack_v2_sparse_classes_30k_train_020364 | Implement the Python class `UsernameChangeForm` described below.
Class description:
Updating the username filed
Method signatures and docstrings:
- def clean_username(self): Record the original username in case it is needed
- def save(self): Change the media file directory name and photo name if any, to match the new... | Implement the Python class `UsernameChangeForm` described below.
Class description:
Updating the username filed
Method signatures and docstrings:
- def clean_username(self): Record the original username in case it is needed
- def save(self): Change the media file directory name and photo name if any, to match the new... | e7c8ed0b07a4c9a1b4007f6089f59aafa6a3ac57 | <|skeleton|>
class UsernameChangeForm:
"""Updating the username filed"""
def clean_username(self):
"""Record the original username in case it is needed"""
<|body_0|>
def save(self):
"""Change the media file directory name and photo name if any, to match the new username"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UsernameChangeForm:
"""Updating the username filed"""
def clean_username(self):
"""Record the original username in case it is needed"""
self.old_username = self.instance.username
self.old_file_root = self.instance.file_root()
if User.objects.filter(username__iexact=self.cl... | the_stack_v2_python_sparse | physionet-django/user/forms.py | tompollard/physionet-build | train | 0 |
fbe855af2c1ba4df177f09df1d7de8e93c5376b8 | [
"if hasattr(self, '_x'):\n return\nself._x = Int(0)",
"from apysc.type import value_util\nself._initialize_x_if_not_initialized()\nreturn value_util.get_copy(value=self._x)",
"from apysc.type.number_value_interface import NumberValueInterface\nfrom apysc.validation import number_validation\nif not isinstance... | <|body_start_0|>
if hasattr(self, '_x'):
return
self._x = Int(0)
<|end_body_0|>
<|body_start_1|>
from apysc.type import value_util
self._initialize_x_if_not_initialized()
return value_util.get_copy(value=self._x)
<|end_body_1|>
<|body_start_2|>
from apysc.ty... | XInterface | [
"MIT",
"CC-BY-4.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class XInterface:
def _initialize_x_if_not_initialized(self) -> None:
"""Initialize _x attribute if it is not initialized yet."""
<|body_0|>
def x(self) -> Int:
"""Get a x-coordinate. Returns ------- x : Int X-coordinate."""
<|body_1|>
def x(self, value: Int) ... | stack_v2_sparse_classes_36k_train_010354 | 2,964 | permissive | [
{
"docstring": "Initialize _x attribute if it is not initialized yet.",
"name": "_initialize_x_if_not_initialized",
"signature": "def _initialize_x_if_not_initialized(self) -> None"
},
{
"docstring": "Get a x-coordinate. Returns ------- x : Int X-coordinate.",
"name": "x",
"signature": "... | 6 | null | Implement the Python class `XInterface` described below.
Class description:
Implement the XInterface class.
Method signatures and docstrings:
- def _initialize_x_if_not_initialized(self) -> None: Initialize _x attribute if it is not initialized yet.
- def x(self) -> Int: Get a x-coordinate. Returns ------- x : Int X-... | Implement the Python class `XInterface` described below.
Class description:
Implement the XInterface class.
Method signatures and docstrings:
- def _initialize_x_if_not_initialized(self) -> None: Initialize _x attribute if it is not initialized yet.
- def x(self) -> Int: Get a x-coordinate. Returns ------- x : Int X-... | 5c6a4674e2e9684cb2cb1325dc9b070879d4d355 | <|skeleton|>
class XInterface:
def _initialize_x_if_not_initialized(self) -> None:
"""Initialize _x attribute if it is not initialized yet."""
<|body_0|>
def x(self) -> Int:
"""Get a x-coordinate. Returns ------- x : Int X-coordinate."""
<|body_1|>
def x(self, value: Int) ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class XInterface:
def _initialize_x_if_not_initialized(self) -> None:
"""Initialize _x attribute if it is not initialized yet."""
if hasattr(self, '_x'):
return
self._x = Int(0)
def x(self) -> Int:
"""Get a x-coordinate. Returns ------- x : Int X-coordinate."""
... | the_stack_v2_python_sparse | apysc/display/x_interface.py | TrendingTechnology/apysc | train | 0 | |
dee29fa7db02c6dce5694df7a2e2ae9ea9e8f6dd | [
"self.mod_type = mod_type\nself.mval = mval\nself.num_bits = 0\nself.num_preamble_bits = 0\nself.num_pilot_bits = 0\nself.tr_extend_on = tr_extend\nself.fs_base = fs_base\nself.barker_type = barker_type\nself.pilot_sym = pilot_sym\nself._create_pilot_tone()\nself._create_preamble()\nif plot:\n self._plot()",
"... | <|body_start_0|>
self.mod_type = mod_type
self.mval = mval
self.num_bits = 0
self.num_preamble_bits = 0
self.num_pilot_bits = 0
self.tr_extend_on = tr_extend
self.fs_base = fs_base
self.barker_type = barker_type
self.pilot_sym = pilot_sym
s... | PreambleClass | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PreambleClass:
def __init__(self, mod_type='fm0', mval=1, tr_extend=None, fs_base=1, barker_type='barker11', pilot_sym=12, plot=False):
"""Generate a Gen2 reverse link preamble including (optional) pilot tone Args: mod_type : One of ['fm0', 'miller', 'square'] mval : One of [1, 2, 4, 8] ... | stack_v2_sparse_classes_36k_train_010355 | 36,290 | no_license | [
{
"docstring": "Generate a Gen2 reverse link preamble including (optional) pilot tone Args: mod_type : One of ['fm0', 'miller', 'square'] mval : One of [1, 2, 4, 8] tr_extend: True/False = pilot tone enabled/disabled fs_base: samples per BLF plot: True=create plot, False=do not create plot",
"name": "__init... | 5 | stack_v2_sparse_classes_30k_train_004478 | Implement the Python class `PreambleClass` described below.
Class description:
Implement the PreambleClass class.
Method signatures and docstrings:
- def __init__(self, mod_type='fm0', mval=1, tr_extend=None, fs_base=1, barker_type='barker11', pilot_sym=12, plot=False): Generate a Gen2 reverse link preamble including... | Implement the Python class `PreambleClass` described below.
Class description:
Implement the PreambleClass class.
Method signatures and docstrings:
- def __init__(self, mod_type='fm0', mval=1, tr_extend=None, fs_base=1, barker_type='barker11', pilot_sym=12, plot=False): Generate a Gen2 reverse link preamble including... | cc7ea7eae78bcc3709117ede81f89ed23d756e26 | <|skeleton|>
class PreambleClass:
def __init__(self, mod_type='fm0', mval=1, tr_extend=None, fs_base=1, barker_type='barker11', pilot_sym=12, plot=False):
"""Generate a Gen2 reverse link preamble including (optional) pilot tone Args: mod_type : One of ['fm0', 'miller', 'square'] mval : One of [1, 2, 4, 8] ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PreambleClass:
def __init__(self, mod_type='fm0', mval=1, tr_extend=None, fs_base=1, barker_type='barker11', pilot_sym=12, plot=False):
"""Generate a Gen2 reverse link preamble including (optional) pilot tone Args: mod_type : One of ['fm0', 'miller', 'square'] mval : One of [1, 2, 4, 8] tr_extend: Tru... | the_stack_v2_python_sparse | systems_r700/model/src/tag/tag_waveforms.py | NopMicrowave/Impinj_R700_Indy_Reader_Chip_and_Speedway_Reader_Simulation | train | 0 | |
29f3acec0536d9e868f177e29704862b3f6ee06d | [
"super().__init__(verbose=verbose)\nif isinstance(fbp_filter, str):\n fbp_filter = fbp_filter.lower()\nself.fbp_filter = fbp_filter\nself.pad_mode = pad_mode",
"if isinstance(self.fbp_filter, str):\n return super().info() + '(F:' + self.fbp_filter.upper() + ')'\nelif isinstance(self.fbp_filter, np.ndarray):... | <|body_start_0|>
super().__init__(verbose=verbose)
if isinstance(fbp_filter, str):
fbp_filter = fbp_filter.lower()
self.fbp_filter = fbp_filter
self.pad_mode = pad_mode
<|end_body_0|>
<|body_start_1|>
if isinstance(self.fbp_filter, str):
return super().in... | Implementation of the Filtered Back-Projection (FBP) algorithm. | FBP | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FBP:
"""Implementation of the Filtered Back-Projection (FBP) algorithm."""
def __init__(self, verbose: bool=False, regularizer: Union[Sequence[BaseRegularizer], BaseRegularizer, None]=None, data_term: Union[str, DataFidelityBase]='l2', fbp_filter: Union[str, NDArrayFloat, filters.Filter]='ra... | stack_v2_sparse_classes_36k_train_010356 | 35,110 | permissive | [
{
"docstring": "Initialize the Filtered Back-Projection (FBP) algorithm. Parameters ---------- verbose : bool, optional Turn on verbose output. The default is False. regularizer : Sequence[BaseRegularizer] | BaseRegularizer | None, optional NOT USED, only exposed for compatibility reasons. data_term : Union[str... | 3 | stack_v2_sparse_classes_30k_train_010426 | Implement the Python class `FBP` described below.
Class description:
Implementation of the Filtered Back-Projection (FBP) algorithm.
Method signatures and docstrings:
- def __init__(self, verbose: bool=False, regularizer: Union[Sequence[BaseRegularizer], BaseRegularizer, None]=None, data_term: Union[str, DataFidelity... | Implement the Python class `FBP` described below.
Class description:
Implementation of the Filtered Back-Projection (FBP) algorithm.
Method signatures and docstrings:
- def __init__(self, verbose: bool=False, regularizer: Union[Sequence[BaseRegularizer], BaseRegularizer, None]=None, data_term: Union[str, DataFidelity... | 66ea08345fe7f7e15f561e66cba5d5b7d02169dd | <|skeleton|>
class FBP:
"""Implementation of the Filtered Back-Projection (FBP) algorithm."""
def __init__(self, verbose: bool=False, regularizer: Union[Sequence[BaseRegularizer], BaseRegularizer, None]=None, data_term: Union[str, DataFidelityBase]='l2', fbp_filter: Union[str, NDArrayFloat, filters.Filter]='ra... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FBP:
"""Implementation of the Filtered Back-Projection (FBP) algorithm."""
def __init__(self, verbose: bool=False, regularizer: Union[Sequence[BaseRegularizer], BaseRegularizer, None]=None, data_term: Union[str, DataFidelityBase]='l2', fbp_filter: Union[str, NDArrayFloat, filters.Filter]='ramp', pad_mode... | the_stack_v2_python_sparse | corrct/solvers.py | cicwi/PyCorrectedEmissionCT | train | 5 |
5b4aec72b768dc96f5310aea98c1d8e0897e3970 | [
"super().__init__()\nself.postnet = nn.LayerList()\nfor layer in six.moves.range(n_layers - 1):\n ichans = odim if layer == 0 else n_chans\n ochans = odim if layer == n_layers - 1 else n_chans\n if use_batch_norm:\n self.postnet.append(nn.Sequential(nn.Conv1D(ichans, ochans, n_filts, stride=1, paddi... | <|body_start_0|>
super().__init__()
self.postnet = nn.LayerList()
for layer in six.moves.range(n_layers - 1):
ichans = odim if layer == 0 else n_chans
ochans = odim if layer == n_layers - 1 else n_chans
if use_batch_norm:
self.postnet.append(nn... | Postnet module for Spectrogram prediction network. This is a module of Postnet in Spectrogram prediction network, which described in `Natural TTS Synthesis by Conditioning WaveNet on Mel Spectrogram Predictions`_. The Postnet predicts refines the predicted Mel-filterbank of the decoder, which helps to compensate the de... | Postnet | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Postnet:
"""Postnet module for Spectrogram prediction network. This is a module of Postnet in Spectrogram prediction network, which described in `Natural TTS Synthesis by Conditioning WaveNet on Mel Spectrogram Predictions`_. The Postnet predicts refines the predicted Mel-filterbank of the decode... | stack_v2_sparse_classes_36k_train_010357 | 6,559 | permissive | [
{
"docstring": "Initialize postnet module. Parameters ---------- idim : int Dimension of the inputs. odim : int Dimension of the outputs. n_layers : int, optional The number of layers. n_filts : int, optional The number of filter size. n_units : int, optional The number of filter channels. use_batch_norm : bool... | 2 | null | Implement the Python class `Postnet` described below.
Class description:
Postnet module for Spectrogram prediction network. This is a module of Postnet in Spectrogram prediction network, which described in `Natural TTS Synthesis by Conditioning WaveNet on Mel Spectrogram Predictions`_. The Postnet predicts refines the... | Implement the Python class `Postnet` described below.
Class description:
Postnet module for Spectrogram prediction network. This is a module of Postnet in Spectrogram prediction network, which described in `Natural TTS Synthesis by Conditioning WaveNet on Mel Spectrogram Predictions`_. The Postnet predicts refines the... | 8705a2a8405e3c63f2174d69880d2b5525a6c9fd | <|skeleton|>
class Postnet:
"""Postnet module for Spectrogram prediction network. This is a module of Postnet in Spectrogram prediction network, which described in `Natural TTS Synthesis by Conditioning WaveNet on Mel Spectrogram Predictions`_. The Postnet predicts refines the predicted Mel-filterbank of the decode... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Postnet:
"""Postnet module for Spectrogram prediction network. This is a module of Postnet in Spectrogram prediction network, which described in `Natural TTS Synthesis by Conditioning WaveNet on Mel Spectrogram Predictions`_. The Postnet predicts refines the predicted Mel-filterbank of the decoder, which help... | the_stack_v2_python_sparse | parakeet/modules/tacotron2/decoder.py | PaddlePaddle/Parakeet | train | 609 |
8f42eb8d9d3d6c628d52930e874ac5f67242d578 | [
"db = DatabaseConnection()\nconn = db.getconnection()\ntry:\n with conn.cursor() as cursor:\n sql = \"SELECT A.user_pref, AST.assertion_type, A.parameters FROM assertions A LEFT JOIN assertions_types AST ON A.assertion_type = AST.id WHERE A.user_pref = '\" + user_pref + \"' ORDER BY A.assertion_type\"\n ... | <|body_start_0|>
db = DatabaseConnection()
conn = db.getconnection()
try:
with conn.cursor() as cursor:
sql = "SELECT A.user_pref, AST.assertion_type, A.parameters FROM assertions A LEFT JOIN assertions_types AST ON A.assertion_type = AST.id WHERE A.user_pref = '" + u... | AssertionModel | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AssertionModel:
def getAssertionByUserPreference(self, user_pref):
""":param user_pref: :returns the assertions by user preference:"""
<|body_0|>
def getLikedPagesAndEvents(self):
""":returns list of LikedPagesAndEvents object:"""
<|body_1|>
def getAsser... | stack_v2_sparse_classes_36k_train_010358 | 4,087 | no_license | [
{
"docstring": ":param user_pref: :returns the assertions by user preference:",
"name": "getAssertionByUserPreference",
"signature": "def getAssertionByUserPreference(self, user_pref)"
},
{
"docstring": ":returns list of LikedPagesAndEvents object:",
"name": "getLikedPagesAndEvents",
"si... | 4 | stack_v2_sparse_classes_30k_train_004102 | Implement the Python class `AssertionModel` described below.
Class description:
Implement the AssertionModel class.
Method signatures and docstrings:
- def getAssertionByUserPreference(self, user_pref): :param user_pref: :returns the assertions by user preference:
- def getLikedPagesAndEvents(self): :returns list of ... | Implement the Python class `AssertionModel` described below.
Class description:
Implement the AssertionModel class.
Method signatures and docstrings:
- def getAssertionByUserPreference(self, user_pref): :param user_pref: :returns the assertions by user preference:
- def getLikedPagesAndEvents(self): :returns list of ... | 44a7dc53f33cb342b087d3c62149437eb655a3c7 | <|skeleton|>
class AssertionModel:
def getAssertionByUserPreference(self, user_pref):
""":param user_pref: :returns the assertions by user preference:"""
<|body_0|>
def getLikedPagesAndEvents(self):
""":returns list of LikedPagesAndEvents object:"""
<|body_1|>
def getAsser... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AssertionModel:
def getAssertionByUserPreference(self, user_pref):
""":param user_pref: :returns the assertions by user preference:"""
db = DatabaseConnection()
conn = db.getconnection()
try:
with conn.cursor() as cursor:
sql = "SELECT A.user_pref, A... | the_stack_v2_python_sparse | StoryGenerator/storygenappv2/storygen/models/AssertionModel.py | hbrosas/Persona-Based-Life-Story-Generation | train | 0 | |
692132eba1fbb4d74c05d078887d8a3901db52d4 | [
"c = Client()\nresp = c.get('/react-example/')\nself.assertIn(b'<div id=\"react_container\"></div>', resp.content)\nself.assertIn(b'<script crossorigin src=\"https://unpkg.com/react@16/umd/react.development.js\"></script>', resp.content)\nself.assertIn(b'<script crossorigin src=\"https://unpkg.com/react-dom@16/umd/... | <|body_start_0|>
c = Client()
resp = c.get('/react-example/')
self.assertIn(b'<div id="react_container"></div>', resp.content)
self.assertIn(b'<script crossorigin src="https://unpkg.com/react@16/umd/react.development.js"></script>', resp.content)
self.assertIn(b'<script crossorig... | Exercise4Test | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Exercise4Test:
def test_view_and_template(self):
"""Test that the view, URLs and template are set up properly by checking the contents of the response."""
<|body_0|>
def test_js_content(self):
"""Test that some expected things are in the JS file."""
<|body_1|... | stack_v2_sparse_classes_36k_train_010359 | 2,702 | permissive | [
{
"docstring": "Test that the view, URLs and template are set up properly by checking the contents of the response.",
"name": "test_view_and_template",
"signature": "def test_view_and_template(self)"
},
{
"docstring": "Test that some expected things are in the JS file.",
"name": "test_js_con... | 2 | null | Implement the Python class `Exercise4Test` described below.
Class description:
Implement the Exercise4Test class.
Method signatures and docstrings:
- def test_view_and_template(self): Test that the view, URLs and template are set up properly by checking the contents of the response.
- def test_js_content(self): Test ... | Implement the Python class `Exercise4Test` described below.
Class description:
Implement the Exercise4Test class.
Method signatures and docstrings:
- def test_view_and_template(self): Test that the view, URLs and template are set up properly by checking the contents of the response.
- def test_js_content(self): Test ... | 52e86a8f93cb38bf70d50e9b8d2c6d7dac416f62 | <|skeleton|>
class Exercise4Test:
def test_view_and_template(self):
"""Test that the view, URLs and template are set up properly by checking the contents of the response."""
<|body_0|>
def test_js_content(self):
"""Test that some expected things are in the JS file."""
<|body_1|... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Exercise4Test:
def test_view_and_template(self):
"""Test that the view, URLs and template are set up properly by checking the contents of the response."""
c = Client()
resp = c.get('/react-example/')
self.assertIn(b'<div id="react_container"></div>', resp.content)
self.... | the_stack_v2_python_sparse | Chapter16/Exercise16.04/bookr/reviews/tests.py | lmoshood/The-Django-Workshop | train | 0 | |
89e34bdb92d7bf94d16257a84928320dde6832a3 | [
"import numpy as np\nimport healpy as hp\nsuper(GSMObserver2016, self).__init__()\nself.gsm = GlobalSkyModel2016(freq_unit='MHz')\nself.observed_sky = None\nself.gsm.generate(1000)\nself._n_pix = hp.get_map_size(self.gsm.generated_map_data)\nself._n_side = hp.npix2nside(self._n_pix)\nself._theta, self._phi = hp.pix... | <|body_start_0|>
import numpy as np
import healpy as hp
super(GSMObserver2016, self).__init__()
self.gsm = GlobalSkyModel2016(freq_unit='MHz')
self.observed_sky = None
self.gsm.generate(1000)
self._n_pix = hp.get_map_size(self.gsm.generated_map_data)
self.... | Observer of the Global Sky Model. Generates the Observed sky, for a given point on Earth. Applies the necessary rotations and coordinate transformations so that the observed 'sky' can be returned, instead of the full galaxy-centered GSM. This class is based on pyephem's Observer(). The GSM bit can be thought of as an '... | pyGSM2016Obs | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class pyGSM2016Obs:
"""Observer of the Global Sky Model. Generates the Observed sky, for a given point on Earth. Applies the necessary rotations and coordinate transformations so that the observed 'sky' can be returned, instead of the full galaxy-centered GSM. This class is based on pyephem's Observer(... | stack_v2_sparse_classes_36k_train_010360 | 21,210 | no_license | [
{
"docstring": "Initialize the Observer object. Calls ephem.Observer.__init__ function and adds on gsm",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Generate the observed sky for the observer, based on the GSM. Parameters ---------- freq: float Frequency of map to ge... | 4 | null | Implement the Python class `pyGSM2016Obs` described below.
Class description:
Observer of the Global Sky Model. Generates the Observed sky, for a given point on Earth. Applies the necessary rotations and coordinate transformations so that the observed 'sky' can be returned, instead of the full galaxy-centered GSM. Thi... | Implement the Python class `pyGSM2016Obs` described below.
Class description:
Observer of the Global Sky Model. Generates the Observed sky, for a given point on Earth. Applies the necessary rotations and coordinate transformations so that the observed 'sky' can be returned, instead of the full galaxy-centered GSM. Thi... | b49777105a76b5ae03555a9f93f116454c8245a9 | <|skeleton|>
class pyGSM2016Obs:
"""Observer of the Global Sky Model. Generates the Observed sky, for a given point on Earth. Applies the necessary rotations and coordinate transformations so that the observed 'sky' can be returned, instead of the full galaxy-centered GSM. This class is based on pyephem's Observer(... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class pyGSM2016Obs:
"""Observer of the Global Sky Model. Generates the Observed sky, for a given point on Earth. Applies the necessary rotations and coordinate transformations so that the observed 'sky' can be returned, instead of the full galaxy-centered GSM. This class is based on pyephem's Observer(). The GSM bi... | the_stack_v2_python_sparse | Astro/pyGSM.py | jizhi/jizhipy | train | 1 |
64d94509752f81351b397f6d53dcdb863a2651b2 | [
"super(MultiHeadAttention, self).__init__()\nself.h = h\nself.dm = dm\nself.depth = self.dm // self.h\nself.Wq = tf.keras.layers.Dense(self.dm)\nself.Wk = tf.keras.layers.Dense(self.dm)\nself.Wv = tf.keras.layers.Dense(self.dm)\nself.linear = tf.keras.layers.Dense(self.dm)",
"batch_size = tf.shape(Q)[0]\nq = self... | <|body_start_0|>
super(MultiHeadAttention, self).__init__()
self.h = h
self.dm = dm
self.depth = self.dm // self.h
self.Wq = tf.keras.layers.Dense(self.dm)
self.Wk = tf.keras.layers.Dense(self.dm)
self.Wv = tf.keras.layers.Dense(self.dm)
self.linear = tf.k... | MultiHeadAttention class perform multi-head attention | MultiHeadAttention | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MultiHeadAttention:
"""MultiHeadAttention class perform multi-head attention"""
def __init__(self, dm, h) -> None:
"""Initializer Arguments: dm {int} -- Is representing the dimensionality of the model h {int} -- Is representing the number of heads"""
<|body_0|>
def call(... | stack_v2_sparse_classes_36k_train_010361 | 2,227 | no_license | [
{
"docstring": "Initializer Arguments: dm {int} -- Is representing the dimensionality of the model h {int} -- Is representing the number of heads",
"name": "__init__",
"signature": "def __init__(self, dm, h) -> None"
},
{
"docstring": "Instance call Arguments: Q {tf.Tensor} -- Is a tensor of sha... | 2 | null | Implement the Python class `MultiHeadAttention` described below.
Class description:
MultiHeadAttention class perform multi-head attention
Method signatures and docstrings:
- def __init__(self, dm, h) -> None: Initializer Arguments: dm {int} -- Is representing the dimensionality of the model h {int} -- Is representing... | Implement the Python class `MultiHeadAttention` described below.
Class description:
MultiHeadAttention class perform multi-head attention
Method signatures and docstrings:
- def __init__(self, dm, h) -> None: Initializer Arguments: dm {int} -- Is representing the dimensionality of the model h {int} -- Is representing... | 2ddae38cc25d914488451b8c30e1234f1fa55ebe | <|skeleton|>
class MultiHeadAttention:
"""MultiHeadAttention class perform multi-head attention"""
def __init__(self, dm, h) -> None:
"""Initializer Arguments: dm {int} -- Is representing the dimensionality of the model h {int} -- Is representing the number of heads"""
<|body_0|>
def call(... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MultiHeadAttention:
"""MultiHeadAttention class perform multi-head attention"""
def __init__(self, dm, h) -> None:
"""Initializer Arguments: dm {int} -- Is representing the dimensionality of the model h {int} -- Is representing the number of heads"""
super(MultiHeadAttention, self).__init... | the_stack_v2_python_sparse | supervised_learning/0x11-attention/6-multihead_attention.py | KoeusIss/holbertonschool-machine_learning | train | 0 |
7602f95cd08a30236f27ac25319a1eefeb5c0ec8 | [
"msg = f'Model object must be of type flopy.mfusg.MfUsg\\nbut received type: {type(model)}.'\nassert isinstance(model, MfUsg), msg\nfilenames = self._prepare_filenames(filenames)\nsuper().__init__(model, ipakcb=ipakcb, stress_period_data=stress_period_data, dtype=dtype, extension=extension, options=options, binary=... | <|body_start_0|>
msg = f'Model object must be of type flopy.mfusg.MfUsg\nbut received type: {type(model)}.'
assert isinstance(model, MfUsg), msg
filenames = self._prepare_filenames(filenames)
super().__init__(model, ipakcb=ipakcb, stress_period_data=stress_period_data, dtype=dtype, exten... | MODFLOW-USG Well Package Class. Parameters ---------- model : model object The model object (of type :class:`flopy.modflow.mf.Modflow`) to which this package will be added. ipakcb : int A flag that is used to determine if cell-by-cell budget data should be saved. If ipakcb is non-zero cell-by-cell budget data will be s... | MfUsgWel | [
"CC0-1.0",
"LicenseRef-scancode-public-domain"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MfUsgWel:
"""MODFLOW-USG Well Package Class. Parameters ---------- model : model object The model object (of type :class:`flopy.modflow.mf.Modflow`) to which this package will be added. ipakcb : int A flag that is used to determine if cell-by-cell budget data should be saved. If ipakcb is non-zer... | stack_v2_sparse_classes_36k_train_010362 | 10,176 | permissive | [
{
"docstring": "Package constructor.",
"name": "__init__",
"signature": "def __init__(self, model, ipakcb=None, stress_period_data=None, cln_stress_period_data=None, dtype=None, cln_dtype=None, extension='wel', options=None, binary=False, unitnumber=None, filenames=None, add_package=True)"
},
{
... | 3 | null | Implement the Python class `MfUsgWel` described below.
Class description:
MODFLOW-USG Well Package Class. Parameters ---------- model : model object The model object (of type :class:`flopy.modflow.mf.Modflow`) to which this package will be added. ipakcb : int A flag that is used to determine if cell-by-cell budget dat... | Implement the Python class `MfUsgWel` described below.
Class description:
MODFLOW-USG Well Package Class. Parameters ---------- model : model object The model object (of type :class:`flopy.modflow.mf.Modflow`) to which this package will be added. ipakcb : int A flag that is used to determine if cell-by-cell budget dat... | 22ef330bcfb9259fc23735d6b174d27804b624a0 | <|skeleton|>
class MfUsgWel:
"""MODFLOW-USG Well Package Class. Parameters ---------- model : model object The model object (of type :class:`flopy.modflow.mf.Modflow`) to which this package will be added. ipakcb : int A flag that is used to determine if cell-by-cell budget data should be saved. If ipakcb is non-zer... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MfUsgWel:
"""MODFLOW-USG Well Package Class. Parameters ---------- model : model object The model object (of type :class:`flopy.modflow.mf.Modflow`) to which this package will be added. ipakcb : int A flag that is used to determine if cell-by-cell budget data should be saved. If ipakcb is non-zero cell-by-cel... | the_stack_v2_python_sparse | flopy/mfusg/mfusgwel.py | robinthibaut/flopy | train | 0 |
047db63311d0359ae9ba8de7b5900a2cc655848f | [
"source = yaml.get('source', None)\nself.source: Optional[SourceName] = None if source is None else SourceName(source)\nself.remote: Optional[str] = yaml.get('remote', None)\ngit = yaml.get('git', None)\nself.git_settings: Optional[GitSettings] = None if git is None else GitSettings(git)\nself.branch: Optional[str]... | <|body_start_0|>
source = yaml.get('source', None)
self.source: Optional[SourceName] = None if source is None else SourceName(source)
self.remote: Optional[str] = yaml.get('remote', None)
git = yaml.get('git', None)
self.git_settings: Optional[GitSettings] = None if git is None e... | clowder yaml Defaults model class :ivar Optional[SourceName] source: Default source name :ivar Optional[str] remote: Default remote name :ivar Optional[GitSettings] git_settings: Custom git settings :ivar Optional[str] branch: Default git branch :ivar Optional[str] tag: Default git tag :ivar Optional[str] commit: Defau... | Defaults | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Defaults:
"""clowder yaml Defaults model class :ivar Optional[SourceName] source: Default source name :ivar Optional[str] remote: Default remote name :ivar Optional[GitSettings] git_settings: Custom git settings :ivar Optional[str] branch: Default git branch :ivar Optional[str] tag: Default git t... | stack_v2_sparse_classes_36k_train_010363 | 2,342 | permissive | [
{
"docstring": "Defaults __init__ :param dict yaml: Parsed YAML python object for defaults",
"name": "__init__",
"signature": "def __init__(self, yaml: dict)"
},
{
"docstring": "Return python object representation for saving yaml :return: YAML python object",
"name": "get_yaml",
"signatu... | 2 | stack_v2_sparse_classes_30k_train_005269 | Implement the Python class `Defaults` described below.
Class description:
clowder yaml Defaults model class :ivar Optional[SourceName] source: Default source name :ivar Optional[str] remote: Default remote name :ivar Optional[GitSettings] git_settings: Custom git settings :ivar Optional[str] branch: Default git branch... | Implement the Python class `Defaults` described below.
Class description:
clowder yaml Defaults model class :ivar Optional[SourceName] source: Default source name :ivar Optional[str] remote: Default remote name :ivar Optional[GitSettings] git_settings: Custom git settings :ivar Optional[str] branch: Default git branch... | 1438fc8b1bb7379de66142ffcb0e20b459b59159 | <|skeleton|>
class Defaults:
"""clowder yaml Defaults model class :ivar Optional[SourceName] source: Default source name :ivar Optional[str] remote: Default remote name :ivar Optional[GitSettings] git_settings: Custom git settings :ivar Optional[str] branch: Default git branch :ivar Optional[str] tag: Default git t... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Defaults:
"""clowder yaml Defaults model class :ivar Optional[SourceName] source: Default source name :ivar Optional[str] remote: Default remote name :ivar Optional[GitSettings] git_settings: Custom git settings :ivar Optional[str] branch: Default git branch :ivar Optional[str] tag: Default git tag :ivar Opti... | the_stack_v2_python_sparse | clowder/model/defaults.py | JrGoodle/clowder | train | 17 |
1bfe38249ba97406c12af39807b10ccb13ed1d8f | [
"if not pHead1 or not pHead2:\n return None\nids = []\np1 = pHead1\np2 = pHead2\nwhile p1:\n ids.append(id(p1))\n p1 = p1.next\nwhile p2:\n if id(p2) in ids:\n return p2\n p2 = p2.next\nreturn None",
"if not pHead1 or not pHead2:\n return None\nstack1 = []\nstack2 = []\np1 = pHead1\np2 = ... | <|body_start_0|>
if not pHead1 or not pHead2:
return None
ids = []
p1 = pHead1
p2 = pHead2
while p1:
ids.append(id(p1))
p1 = p1.next
while p2:
if id(p2) in ids:
return p2
p2 = p2.next
retu... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def FindFirstCommonNode(self, pHead1, pHead2):
"""Python特色的解法"""
<|body_0|>
def FindFirstCommonNode2(self, pHead1, pHead2):
"""由于是单向链表，因此若存在公共节点，则两个链表的尾节点一定相同 可以从尾节点开始比较，第一个不相同的节点的next节点就是第一个公共节点"""
<|body_1|>
def FindFirstCommonNode3(self, pHe... | stack_v2_sparse_classes_36k_train_010364 | 3,088 | no_license | [
{
"docstring": "Python特色的解法",
"name": "FindFirstCommonNode",
"signature": "def FindFirstCommonNode(self, pHead1, pHead2)"
},
{
"docstring": "由于是单向链表，因此若存在公共节点，则两个链表的尾节点一定相同 可以从尾节点开始比较，第一个不相同的节点的next节点就是第一个公共节点",
"name": "FindFirstCommonNode2",
"signature": "def FindFirstCommonNode2(self,... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def FindFirstCommonNode(self, pHead1, pHead2): Python特色的解法
- def FindFirstCommonNode2(self, pHead1, pHead2): 由于是单向链表，因此若存在公共节点，则两个链表的尾节点一定相同 可以从尾节点开始比较，第一个不相同的节点的next节点就是第一个公共节点
... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def FindFirstCommonNode(self, pHead1, pHead2): Python特色的解法
- def FindFirstCommonNode2(self, pHead1, pHead2): 由于是单向链表，因此若存在公共节点，则两个链表的尾节点一定相同 可以从尾节点开始比较，第一个不相同的节点的next节点就是第一个公共节点
... | 24dd0fcf44a84126d7c88e3d4622c26262e72863 | <|skeleton|>
class Solution:
def FindFirstCommonNode(self, pHead1, pHead2):
"""Python特色的解法"""
<|body_0|>
def FindFirstCommonNode2(self, pHead1, pHead2):
"""由于是单向链表，因此若存在公共节点，则两个链表的尾节点一定相同 可以从尾节点开始比较，第一个不相同的节点的next节点就是第一个公共节点"""
<|body_1|>
def FindFirstCommonNode3(self, pHe... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def FindFirstCommonNode(self, pHead1, pHead2):
"""Python特色的解法"""
if not pHead1 or not pHead2:
return None
ids = []
p1 = pHead1
p2 = pHead2
while p1:
ids.append(id(p1))
p1 = p1.next
while p2:
if id... | the_stack_v2_python_sparse | 54.两个链表的第一个公共节点.py | costume24/Sword-to-Offer | train | 0 | |
a010d69c47164225eb4103b9030e9501db02118e | [
"assert nums is not None\nnums.sort()\nn = len(nums)\nres = set()\nadict = {}\nfor i in xrange(n - 1):\n for j in xrange(i + 1, n):\n asum = nums[i] + nums[j]\n if asum not in adict:\n adict[asum] = [(i, j)]\n else:\n adict[asum].append((i, j))\nfor i in xrange(n - 4 + ... | <|body_start_0|>
assert nums is not None
nums.sort()
n = len(nums)
res = set()
adict = {}
for i in xrange(n - 1):
for j in xrange(i + 1, n):
asum = nums[i] + nums[j]
if asum not in adict:
adict[asum] = [(i, j... | Given an array S of n integers, are there elements a, b, c, and d in S such that a + b + c + d = target? Find all unique quadruplets in the array which gives the sum of target. Note: Elements in a quadruplet (a,b,c,d) must be in non-descending order. (ie, a+b+c+d) The solution set must not contain duplicate quadruplets... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
"""Given an array S of n integers, are there elements a, b, c, and d in S such that a + b + c + d = target? Find all unique quadruplets in the array which gives the sum of target. Note: Elements in a quadruplet (a,b,c,d) must be in non-descending order. (ie, a+b+c+d) The solution set mu... | stack_v2_sparse_classes_36k_train_010365 | 2,724 | no_license | [
{
"docstring": ":type nums: List[int] :type target: int :rtype: List[List[int]]",
"name": "fourSum_hash",
"signature": "def fourSum_hash(self, nums, target)"
},
{
"docstring": ":type nums: List[int] :type target: int :rtype: List[List[int]]",
"name": "fourSum_Generic",
"signature": "def ... | 2 | stack_v2_sparse_classes_30k_train_018960 | Implement the Python class `Solution` described below.
Class description:
Given an array S of n integers, are there elements a, b, c, and d in S such that a + b + c + d = target? Find all unique quadruplets in the array which gives the sum of target. Note: Elements in a quadruplet (a,b,c,d) must be in non-descending o... | Implement the Python class `Solution` described below.
Class description:
Given an array S of n integers, are there elements a, b, c, and d in S such that a + b + c + d = target? Find all unique quadruplets in the array which gives the sum of target. Note: Elements in a quadruplet (a,b,c,d) must be in non-descending o... | cbe6a7e7f05eccb4f9c5fce8651c0d87e5168516 | <|skeleton|>
class Solution:
"""Given an array S of n integers, are there elements a, b, c, and d in S such that a + b + c + d = target? Find all unique quadruplets in the array which gives the sum of target. Note: Elements in a quadruplet (a,b,c,d) must be in non-descending order. (ie, a+b+c+d) The solution set mu... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
"""Given an array S of n integers, are there elements a, b, c, and d in S such that a + b + c + d = target? Find all unique quadruplets in the array which gives the sum of target. Note: Elements in a quadruplet (a,b,c,d) must be in non-descending order. (ie, a+b+c+d) The solution set must not contai... | the_stack_v2_python_sparse | src/array/leetcode18_4Sum.py | apepkuss/Cracking-Leetcode-in-Python | train | 2 |
95b8145b69bb78f1bdb97ab2afbddb341dde14d1 | [
"cls = kwargs.pop('cls', None)\nerror_map = {401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError}\nerror_map.update(kwargs.pop('error_map', {}))\napi_version = kwargs.pop('api_version', '2021-05-01-preview')\nrequest = build_get_sip_configuration_request(api_version=api_version, tem... | <|body_start_0|>
cls = kwargs.pop('cls', None)
error_map = {401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError}
error_map.update(kwargs.pop('error_map', {}))
api_version = kwargs.pop('api_version', '2021-05-01-preview')
request = build_get_sip_co... | SIPRoutingServiceOperationsMixin | [
"LicenseRef-scancode-generic-cla",
"MIT",
"LGPL-2.1-or-later"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SIPRoutingServiceOperationsMixin:
def get_sip_configuration(self, **kwargs):
"""Gets SIP configuration for resource. Gets SIP configuration for resource. :keyword callable cls: A custom type or function that will be passed the direct response :return: SipConfiguration, or the result of c... | stack_v2_sparse_classes_36k_train_010366 | 8,134 | permissive | [
{
"docstring": "Gets SIP configuration for resource. Gets SIP configuration for resource. :keyword callable cls: A custom type or function that will be passed the direct response :return: SipConfiguration, or the result of cls(response) :rtype: ~azure.communication.phonenumbers.siprouting.models.SipConfiguratio... | 2 | stack_v2_sparse_classes_30k_train_006735 | Implement the Python class `SIPRoutingServiceOperationsMixin` described below.
Class description:
Implement the SIPRoutingServiceOperationsMixin class.
Method signatures and docstrings:
- def get_sip_configuration(self, **kwargs): Gets SIP configuration for resource. Gets SIP configuration for resource. :keyword call... | Implement the Python class `SIPRoutingServiceOperationsMixin` described below.
Class description:
Implement the SIPRoutingServiceOperationsMixin class.
Method signatures and docstrings:
- def get_sip_configuration(self, **kwargs): Gets SIP configuration for resource. Gets SIP configuration for resource. :keyword call... | b23e71b289c71f179b9cf9b8c75b1922833a542a | <|skeleton|>
class SIPRoutingServiceOperationsMixin:
def get_sip_configuration(self, **kwargs):
"""Gets SIP configuration for resource. Gets SIP configuration for resource. :keyword callable cls: A custom type or function that will be passed the direct response :return: SipConfiguration, or the result of c... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SIPRoutingServiceOperationsMixin:
def get_sip_configuration(self, **kwargs):
"""Gets SIP configuration for resource. Gets SIP configuration for resource. :keyword callable cls: A custom type or function that will be passed the direct response :return: SipConfiguration, or the result of cls(response) :... | the_stack_v2_python_sparse | sdk/communication/azure-communication-phonenumbers/azure/communication/phonenumbers/siprouting/_generated/operations/_sip_routing_service_operations.py | kurtzeborn/azure-sdk-for-python | train | 0 | |
8e13433aa32802d85924f63b27a40189790fd67c | [
"self.api = board.apis.uart\nself.initialized = False\nself.baud = baud\nself.data_bits = data_bits\nself.stop_bits = stop_bits\nself.parity = parity or self.PARITY_NONE\nself.uart_number = 0\nself.actual_baud = 0",
"self.baud = baud if baud is not None else self.baud\nself.data_bits = data_bits if data_bits is n... | <|body_start_0|>
self.api = board.apis.uart
self.initialized = False
self.baud = baud
self.data_bits = data_bits
self.stop_bits = stop_bits
self.parity = parity or self.PARITY_NONE
self.uart_number = 0
self.actual_baud = 0
<|end_body_0|>
<|body_start_1|>
... | TODO: description | UART | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UART:
"""TODO: description"""
def __init__(self, board, baud=115200, data_bits=8, stop_bits=1, parity=None, uart_number=0):
"""Args: board -- GreatFET board whose UART lines are to be controlled"""
<|body_0|>
def update_parameters(self, baud=None, data_bits=None, stop_bi... | stack_v2_sparse_classes_36k_train_010367 | 2,821 | permissive | [
{
"docstring": "Args: board -- GreatFET board whose UART lines are to be controlled",
"name": "__init__",
"signature": "def __init__(self, board, baud=115200, data_bits=8, stop_bits=1, parity=None, uart_number=0)"
},
{
"docstring": "Updates the UART parameters for the provided board. This is int... | 4 | null | Implement the Python class `UART` described below.
Class description:
TODO: description
Method signatures and docstrings:
- def __init__(self, board, baud=115200, data_bits=8, stop_bits=1, parity=None, uart_number=0): Args: board -- GreatFET board whose UART lines are to be controlled
- def update_parameters(self, ba... | Implement the Python class `UART` described below.
Class description:
TODO: description
Method signatures and docstrings:
- def __init__(self, board, baud=115200, data_bits=8, stop_bits=1, parity=None, uart_number=0): Args: board -- GreatFET board whose UART lines are to be controlled
- def update_parameters(self, ba... | 2409575d28fc7c9cae44c9085c7457ddfb54f893 | <|skeleton|>
class UART:
"""TODO: description"""
def __init__(self, board, baud=115200, data_bits=8, stop_bits=1, parity=None, uart_number=0):
"""Args: board -- GreatFET board whose UART lines are to be controlled"""
<|body_0|>
def update_parameters(self, baud=None, data_bits=None, stop_bi... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UART:
"""TODO: description"""
def __init__(self, board, baud=115200, data_bits=8, stop_bits=1, parity=None, uart_number=0):
"""Args: board -- GreatFET board whose UART lines are to be controlled"""
self.api = board.apis.uart
self.initialized = False
self.baud = baud
... | the_stack_v2_python_sparse | host/greatfet/interfaces/uart.py | greatscottgadgets/greatfet | train | 273 |
58c0cb36d14e9b9f12af452961dd3e0dbf540586 | [
"allowed_fields = {'process_id', 'output', 'input', 'tags', 'entity', 'entity_id', 'collection', 'collection_id', 'name'}\nnot_allowed_keys = set(model_data.keys()) - allowed_fields\nif not_allowed_keys:\n raise RuntimeError(f\"Not allowed to set {','.join(not_allowed_keys)}.\")\nself._has_permission(user, Proce... | <|body_start_0|>
allowed_fields = {'process_id', 'output', 'input', 'tags', 'entity', 'entity_id', 'collection', 'collection_id', 'name'}
not_allowed_keys = set(model_data.keys()) - allowed_fields
if not_allowed_keys:
raise RuntimeError(f"Not allowed to set {','.join(not_allowed_keys... | Expose the Data model. | ExposeData | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ExposeData:
"""Expose the Data model."""
def can_create(self, user: 'UserType', model_data: dict, data_id: int):
"""Can user update the given model instance. :raises RuntimeError: if user does not have permissions to create the given model."""
<|body_0|>
def can_update(s... | stack_v2_sparse_classes_36k_train_010368 | 13,286 | permissive | [
{
"docstring": "Can user update the given model instance. :raises RuntimeError: if user does not have permissions to create the given model.",
"name": "can_create",
"signature": "def can_create(self, user: 'UserType', model_data: dict, data_id: int)"
},
{
"docstring": "Can user update the given ... | 3 | null | Implement the Python class `ExposeData` described below.
Class description:
Expose the Data model.
Method signatures and docstrings:
- def can_create(self, user: 'UserType', model_data: dict, data_id: int): Can user update the given model instance. :raises RuntimeError: if user does not have permissions to create the... | Implement the Python class `ExposeData` described below.
Class description:
Expose the Data model.
Method signatures and docstrings:
- def can_create(self, user: 'UserType', model_data: dict, data_id: int): Can user update the given model instance. :raises RuntimeError: if user does not have permissions to create the... | 25c0c45235ef37beb45c1af4c917fbbae6282016 | <|skeleton|>
class ExposeData:
"""Expose the Data model."""
def can_create(self, user: 'UserType', model_data: dict, data_id: int):
"""Can user update the given model instance. :raises RuntimeError: if user does not have permissions to create the given model."""
<|body_0|>
def can_update(s... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ExposeData:
"""Expose the Data model."""
def can_create(self, user: 'UserType', model_data: dict, data_id: int):
"""Can user update the given model instance. :raises RuntimeError: if user does not have permissions to create the given model."""
allowed_fields = {'process_id', 'output', 'in... | the_stack_v2_python_sparse | resolwe/flow/managers/listener/permission_plugin.py | genialis/resolwe | train | 35 |
e8645b24f89a25162c401501d9a79fc8da214a54 | [
"self._cache = cache\nself._package = package\nself._service_manager = service_manager",
"self._service_manager.RecordServices()\ntry:\n self._package.mark_install(True, True, False)\n logging.info('Installing...')\n self._cache.commit()\nexcept (apt.cache.FetchFailedException, SystemError) as e:\n lo... | <|body_start_0|>
self._cache = cache
self._package = package
self._service_manager = service_manager
<|end_body_0|>
<|body_start_1|>
self._service_manager.RecordServices()
try:
self._package.mark_install(True, True, False)
logging.info('Installing...')
... | A Debian "install" trigger. | DebInstall | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DebInstall:
"""A Debian "install" trigger."""
def __init__(self, cache, package, service_manager):
"""Constructor. Args: cache: An apt cache. package: A package to be installed. service_manager: A service manager for the application."""
<|body_0|>
def RunTrigger(self):
... | stack_v2_sparse_classes_36k_train_010369 | 10,965 | no_license | [
{
"docstring": "Constructor. Args: cache: An apt cache. package: A package to be installed. service_manager: A service manager for the application.",
"name": "__init__",
"signature": "def __init__(self, cache, package, service_manager)"
},
{
"docstring": "Run a Debian \"install\" trigger. This t... | 2 | stack_v2_sparse_classes_30k_train_021256 | Implement the Python class `DebInstall` described below.
Class description:
A Debian "install" trigger.
Method signatures and docstrings:
- def __init__(self, cache, package, service_manager): Constructor. Args: cache: An apt cache. package: A package to be installed. service_manager: A service manager for the applic... | Implement the Python class `DebInstall` described below.
Class description:
A Debian "install" trigger.
Method signatures and docstrings:
- def __init__(self, cache, package, service_manager): Constructor. Args: cache: An apt cache. package: A package to be installed. service_manager: A service manager for the applic... | 3fa5a9d67eb4eea87d3a54b1af5946cec8b67cca | <|skeleton|>
class DebInstall:
"""A Debian "install" trigger."""
def __init__(self, cache, package, service_manager):
"""Constructor. Args: cache: An apt cache. package: A package to be installed. service_manager: A service manager for the application."""
<|body_0|>
def RunTrigger(self):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DebInstall:
"""A Debian "install" trigger."""
def __init__(self, cache, package, service_manager):
"""Constructor. Args: cache: An apt cache. package: A package to be installed. service_manager: A service manager for the application."""
self._cache = cache
self._package = package
... | the_stack_v2_python_sparse | guest/deb_triggers.py | tojo2000/wheelbarrow | train | 0 |
dea5b347ac137197c39d64d7f2b5ed5fd6881a45 | [
"self.token = random_number_token(length)\nself.valid_until = timezone.now() + timedelta(seconds=valid_secs)\nif commit:\n self.save()",
"_now = timezone.now()\nif self.token is not None and token == self.token and (_now < self.valid_until):\n self.token = None\n self.valid_until = _now\n self.save()\... | <|body_start_0|>
self.token = random_number_token(length)
self.valid_until = timezone.now() + timedelta(seconds=valid_secs)
if commit:
self.save()
<|end_body_0|>
<|body_start_1|>
_now = timezone.now()
if self.token is not None and token == self.token and (_now < self... | Abstract base model for a side-channel :term:`device` attached to a user. This model implements token generation, verification and expiration, so the concrete devices only have to implement delivery. | SideChannelDevice | [
"Unlicense"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SideChannelDevice:
"""Abstract base model for a side-channel :term:`device` attached to a user. This model implements token generation, verification and expiration, so the concrete devices only have to implement delivery."""
def generate_token(self, length=6, valid_secs=300, commit=True):
... | stack_v2_sparse_classes_36k_train_010370 | 13,172 | permissive | [
{
"docstring": "Generates a token of the specified length, then sets it on the model and sets the expiration of the token on the model. Pass 'commit=False' to avoid calling self.save(). :param int length: Number of decimal digits in the generated token. :param int valid_secs: Amount of seconds the token should ... | 2 | stack_v2_sparse_classes_30k_train_012892 | Implement the Python class `SideChannelDevice` described below.
Class description:
Abstract base model for a side-channel :term:`device` attached to a user. This model implements token generation, verification and expiration, so the concrete devices only have to implement delivery.
Method signatures and docstrings:
-... | Implement the Python class `SideChannelDevice` described below.
Class description:
Abstract base model for a side-channel :term:`device` attached to a user. This model implements token generation, verification and expiration, so the concrete devices only have to implement delivery.
Method signatures and docstrings:
-... | d65a039582509a08c56c35f905380fe3ff8507cb | <|skeleton|>
class SideChannelDevice:
"""Abstract base model for a side-channel :term:`device` attached to a user. This model implements token generation, verification and expiration, so the concrete devices only have to implement delivery."""
def generate_token(self, length=6, valid_secs=300, commit=True):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SideChannelDevice:
"""Abstract base model for a side-channel :term:`device` attached to a user. This model implements token generation, verification and expiration, so the concrete devices only have to implement delivery."""
def generate_token(self, length=6, valid_secs=300, commit=True):
"""Gene... | the_stack_v2_python_sparse | src/django_otp/models.py | django-otp/django-otp | train | 460 |
9a41b66cb097b527e50226d6af9fb3571758f1e9 | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn WorkforceIntegration()",
"from .change_tracked_entity import ChangeTrackedEntity\nfrom .workforce_integration_encryption import WorkforceIntegrationEncryption\nfrom .workforce_integration_supported_entities import WorkforceIntegrationS... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return WorkforceIntegration()
<|end_body_0|>
<|body_start_1|>
from .change_tracked_entity import ChangeTrackedEntity
from .workforce_integration_encryption import WorkforceIntegrationEncryption... | WorkforceIntegration | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WorkforceIntegration:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> WorkforceIntegration:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the ... | stack_v2_sparse_classes_36k_train_010371 | 4,400 | permissive | [
{
"docstring": "Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Returns: WorkforceIntegration",
"name": "create_from_discriminator_value",
"signature": "def create_from_discriminato... | 3 | null | Implement the Python class `WorkforceIntegration` described below.
Class description:
Implement the WorkforceIntegration class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> WorkforceIntegration: Creates a new instance of the appropriate class based o... | Implement the Python class `WorkforceIntegration` described below.
Class description:
Implement the WorkforceIntegration class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> WorkforceIntegration: Creates a new instance of the appropriate class based o... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class WorkforceIntegration:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> WorkforceIntegration:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class WorkforceIntegration:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> WorkforceIntegration:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Returns... | the_stack_v2_python_sparse | msgraph/generated/models/workforce_integration.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
74e1a8d745d8263614e8b7e080fedc65d9709b81 | [
"self.years = [year for year in range(year_i, year_f + 1)]\nself.type_AOD = type_AOD\nself.year_i = year_i\nself.year_f = year_f\nself.file = file",
"self.data = pd.read_csv(path + self.file + '.csv')\nself.clean_data()\nself.data = self.data.fillna(-1)\nself.len_data = len(self.data[self.type_AOD])",
"for key ... | <|body_start_0|>
self.years = [year for year in range(year_i, year_f + 1)]
self.type_AOD = type_AOD
self.year_i = year_i
self.year_f = year_f
self.file = file
<|end_body_0|>
<|body_start_1|>
self.data = pd.read_csv(path + self.file + '.csv')
self.clean_data()
... | Clase que contiene los metodos y lectura que se le aplicaran a los datos de MODIS | MODIS_data | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MODIS_data:
"""Clase que contiene los metodos y lectura que se le aplicaran a los datos de MODIS"""
def __init__(self, file, year_i, year_f, type_AOD):
"""Describcion de variables: type_AOD---> columna de AOD que leer file ---> archivo que contiene la informacion del AOD year_i ---> ... | stack_v2_sparse_classes_36k_train_010372 | 2,794 | no_license | [
{
"docstring": "Describcion de variables: type_AOD---> columna de AOD que leer file ---> archivo que contiene la informacion del AOD year_i ---> año en el que inicia el analisis year_f ---> año en el que finaliza el analisis",
"name": "__init__",
"signature": "def __init__(self, file, year_i, year_f, ty... | 5 | stack_v2_sparse_classes_30k_train_014470 | Implement the Python class `MODIS_data` described below.
Class description:
Clase que contiene los metodos y lectura que se le aplicaran a los datos de MODIS
Method signatures and docstrings:
- def __init__(self, file, year_i, year_f, type_AOD): Describcion de variables: type_AOD---> columna de AOD que leer file --->... | Implement the Python class `MODIS_data` described below.
Class description:
Clase que contiene los metodos y lectura que se le aplicaran a los datos de MODIS
Method signatures and docstrings:
- def __init__(self, file, year_i, year_f, type_AOD): Describcion de variables: type_AOD---> columna de AOD que leer file --->... | 43c7c6e6c57e76a0f80a3052a9060161d9b9dd41 | <|skeleton|>
class MODIS_data:
"""Clase que contiene los metodos y lectura que se le aplicaran a los datos de MODIS"""
def __init__(self, file, year_i, year_f, type_AOD):
"""Describcion de variables: type_AOD---> columna de AOD que leer file ---> archivo que contiene la informacion del AOD year_i ---> ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MODIS_data:
"""Clase que contiene los metodos y lectura que se le aplicaran a los datos de MODIS"""
def __init__(self, file, year_i, year_f, type_AOD):
"""Describcion de variables: type_AOD---> columna de AOD que leer file ---> archivo que contiene la informacion del AOD year_i ---> año en el que... | the_stack_v2_python_sparse | Scripts/functions_MODIS.py | iphadra/SIMA | train | 0 |
e0416be9a7b208860b912f07d9a5a0e52a8a25b6 | [
"if not password_file:\n raise RuntimeError('No password file specified')\nif not os.path.exists(password_file):\n raise RuntimeError(f\"password file '{password_file}' does not exist\")\nself.password_file = password_file\nself.newt_base_url = newt_base_url if newt_base_url else _NEWT_BASE_URL\nif not self.n... | <|body_start_0|>
if not password_file:
raise RuntimeError('No password file specified')
if not os.path.exists(password_file):
raise RuntimeError(f"password file '{password_file}' does not exist")
self.password_file = password_file
self.newt_base_url = newt_base_ur... | Newt | [
"Apache-2.0",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Newt:
def __init__(self, password_file, newt_base_url=None, max_retries=0, retry_backoff_factor=0):
"""Constructor that takes path to password file and optional Newt base URL :param password_file: path to password file :param newt_base_url: Newt base URL (default will be _NEWT_BASE_URL)"... | stack_v2_sparse_classes_36k_train_010373 | 5,141 | permissive | [
{
"docstring": "Constructor that takes path to password file and optional Newt base URL :param password_file: path to password file :param newt_base_url: Newt base URL (default will be _NEWT_BASE_URL)",
"name": "__init__",
"signature": "def __init__(self, password_file, newt_base_url=None, max_retries=0... | 6 | stack_v2_sparse_classes_30k_train_010630 | Implement the Python class `Newt` described below.
Class description:
Implement the Newt class.
Method signatures and docstrings:
- def __init__(self, password_file, newt_base_url=None, max_retries=0, retry_backoff_factor=0): Constructor that takes path to password file and optional Newt base URL :param password_file... | Implement the Python class `Newt` described below.
Class description:
Implement the Newt class.
Method signatures and docstrings:
- def __init__(self, password_file, newt_base_url=None, max_retries=0, retry_backoff_factor=0): Constructor that takes path to password file and optional Newt base URL :param password_file... | 842fdc91a31879084906d71a7d0c317e5035a925 | <|skeleton|>
class Newt:
def __init__(self, password_file, newt_base_url=None, max_retries=0, retry_backoff_factor=0):
"""Constructor that takes path to password file and optional Newt base URL :param password_file: path to password file :param newt_base_url: Newt base URL (default will be _NEWT_BASE_URL)"... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Newt:
def __init__(self, password_file, newt_base_url=None, max_retries=0, retry_backoff_factor=0):
"""Constructor that takes path to password file and optional Newt base URL :param password_file: path to password file :param newt_base_url: Newt base URL (default will be _NEWT_BASE_URL)"""
if ... | the_stack_v2_python_sparse | src/decisionengine_modules/NERSC/util/newt.py | HEPCloud/decisionengine_modules | train | 2 | |
bed83aa1055c3d8905a3a360f4de307ca0c0587d | [
"self.sc_middleware = SharedContextMiddleware()\nself.request = MagicMock()\nself.request.GET = {'q': 'a_deal_search_key'}\nself.response = MagicMock()\nself.response.context_data = {'context_var_from_view': 'blah blah blah'}",
"response = self.sc_middleware.process_template_response(self.request, self.response)\... | <|body_start_0|>
self.sc_middleware = SharedContextMiddleware()
self.request = MagicMock()
self.request.GET = {'q': 'a_deal_search_key'}
self.response = MagicMock()
self.response.context_data = {'context_var_from_view': 'blah blah blah'}
<|end_body_0|>
<|body_start_1|>
r... | Testcase for the SharedContextMiddleware class | SharedContextMiddlewareTestCase | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SharedContextMiddlewareTestCase:
"""Testcase for the SharedContextMiddleware class"""
def setUp(self):
"""operations to run before every test"""
<|body_0|>
def test_that_middleware_updates_context_with_categories(self):
"""tests that the response context_data was... | stack_v2_sparse_classes_36k_train_010374 | 2,698 | permissive | [
{
"docstring": "operations to run before every test",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "tests that the response context_data was updated with correct data for categories, cities, advertisers and search.",
"name": "test_that_middleware_updates_context_with_cat... | 3 | null | Implement the Python class `SharedContextMiddlewareTestCase` described below.
Class description:
Testcase for the SharedContextMiddleware class
Method signatures and docstrings:
- def setUp(self): operations to run before every test
- def test_that_middleware_updates_context_with_categories(self): tests that the resp... | Implement the Python class `SharedContextMiddlewareTestCase` described below.
Class description:
Testcase for the SharedContextMiddleware class
Method signatures and docstrings:
- def setUp(self): operations to run before every test
- def test_that_middleware_updates_context_with_categories(self): tests that the resp... | 3704cbe6e69ba3e4c53401d3bbc339208e9ebccd | <|skeleton|>
class SharedContextMiddlewareTestCase:
"""Testcase for the SharedContextMiddleware class"""
def setUp(self):
"""operations to run before every test"""
<|body_0|>
def test_that_middleware_updates_context_with_categories(self):
"""tests that the response context_data was... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SharedContextMiddlewareTestCase:
"""Testcase for the SharedContextMiddleware class"""
def setUp(self):
"""operations to run before every test"""
self.sc_middleware = SharedContextMiddleware()
self.request = MagicMock()
self.request.GET = {'q': 'a_deal_search_key'}
... | the_stack_v2_python_sparse | troupon/middleware/test_middleware.py | morristech/troupon | train | 0 |
4e0006352d5b8dc5f80ebb467d94a86b12073fff | [
"credential, unused_project_id = google.auth.default(scopes=['https://www.googleapis.com/auth/gerritcodereview'])\ncredential.refresh(google.auth.transport.requests.Request())\nreturn 'o=git-{service_account_name}={token}'.format(service_account_name=credential.service_account_email, token=credential.token)",
"tr... | <|body_start_0|>
credential, unused_project_id = google.auth.default(scopes=['https://www.googleapis.com/auth/gerritcodereview'])
credential.refresh(google.auth.transport.requests.Request())
return 'o=git-{service_account_name}={token}'.format(service_account_name=credential.service_account_emai... | A helper class for the gerrit connector. | GerritConnectorHelper | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GerritConnectorHelper:
"""A helper class for the gerrit connector."""
def GetGerritAuthCookie(self) -> str:
"""Get the OAuth cookie of gerrit code review. Returns: An string of the cookie."""
<|body_0|>
def ConvertDataToJson(self, data) -> dict:
"""Convert the da... | stack_v2_sparse_classes_36k_train_010375 | 5,382 | permissive | [
{
"docstring": "Get the OAuth cookie of gerrit code review. Returns: An string of the cookie.",
"name": "GetGerritAuthCookie",
"signature": "def GetGerritAuthCookie(self) -> str"
},
{
"docstring": "Convert the data responded from the Gerrit Rest API to the json type. Args: data: The string from ... | 3 | null | Implement the Python class `GerritConnectorHelper` described below.
Class description:
A helper class for the gerrit connector.
Method signatures and docstrings:
- def GetGerritAuthCookie(self) -> str: Get the OAuth cookie of gerrit code review. Returns: An string of the cookie.
- def ConvertDataToJson(self, data) ->... | Implement the Python class `GerritConnectorHelper` described below.
Class description:
A helper class for the gerrit connector.
Method signatures and docstrings:
- def GetGerritAuthCookie(self) -> str: Get the OAuth cookie of gerrit code review. Returns: An string of the cookie.
- def ConvertDataToJson(self, data) ->... | a1b0fccd68987d8cd9c89710adc3c04b868347ec | <|skeleton|>
class GerritConnectorHelper:
"""A helper class for the gerrit connector."""
def GetGerritAuthCookie(self) -> str:
"""Get the OAuth cookie of gerrit code review. Returns: An string of the cookie."""
<|body_0|>
def ConvertDataToJson(self, data) -> dict:
"""Convert the da... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GerritConnectorHelper:
"""A helper class for the gerrit connector."""
def GetGerritAuthCookie(self) -> str:
"""Get the OAuth cookie of gerrit code review. Returns: An string of the cookie."""
credential, unused_project_id = google.auth.default(scopes=['https://www.googleapis.com/auth/gerr... | the_stack_v2_python_sparse | py/probe_info_service/app_engine/gerrit_connector.py | bridder/factory | train | 0 |
62ead22077b5657537030bbdd1c9a176ae2bf000 | [
"super(BilinearNetworkLayer, self).__init__()\nself.inputs_size = inputs_size\nself.model = nn.ModuleList()\nfor _ in range(num_layers):\n self.model.append(nn.Bilinear(inputs_size, inputs_size, inputs_size))",
"outputs = emb_inputs.detach().requires_grad_()\nfor layer in self.model:\n outputs = layer(emb_i... | <|body_start_0|>
super(BilinearNetworkLayer, self).__init__()
self.inputs_size = inputs_size
self.model = nn.ModuleList()
for _ in range(num_layers):
self.model.append(nn.Bilinear(inputs_size, inputs_size, inputs_size))
<|end_body_0|>
<|body_start_1|>
outputs = emb_i... | Layer class of Bilinear. Bilinear is to calculate interaction in element-wise by nn.Bilinear, which the calculation is: for i-th layer, :math:`x_{i} = (x_{0} * A_{i} * x_{i - 1}) + b_{i} + x_{0}`, where :math:`A_{i}` is the weight of module of shape :math:`(O_{i}, I_{i1}, I_{i2})`. | BilinearNetworkLayer | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BilinearNetworkLayer:
"""Layer class of Bilinear. Bilinear is to calculate interaction in element-wise by nn.Bilinear, which the calculation is: for i-th layer, :math:`x_{i} = (x_{0} * A_{i} * x_{i - 1}) + b_{i} + x_{0}`, where :math:`A_{i}` is the weight of module of shape :math:`(O_{i}, I_{i1},... | stack_v2_sparse_classes_36k_train_010376 | 2,600 | permissive | [
{
"docstring": "Initialize BilinearNetworkLayer Args: inputs_size (int): Input size of Bilinear, i.e. size of embedding tensor. num_layers (int): Number of layers of Bilinear Network Attributes: inputs_size (int): Size of inputs, or Product of embed_size and num_fields. model (torch.nn.ModuleList): Module List ... | 2 | stack_v2_sparse_classes_30k_train_021131 | Implement the Python class `BilinearNetworkLayer` described below.
Class description:
Layer class of Bilinear. Bilinear is to calculate interaction in element-wise by nn.Bilinear, which the calculation is: for i-th layer, :math:`x_{i} = (x_{0} * A_{i} * x_{i - 1}) + b_{i} + x_{0}`, where :math:`A_{i}` is the weight of... | Implement the Python class `BilinearNetworkLayer` described below.
Class description:
Layer class of Bilinear. Bilinear is to calculate interaction in element-wise by nn.Bilinear, which the calculation is: for i-th layer, :math:`x_{i} = (x_{0} * A_{i} * x_{i - 1}) + b_{i} + x_{0}`, where :math:`A_{i}` is the weight of... | 07a6a38c7eb44225f2b22f332081f697c3b92894 | <|skeleton|>
class BilinearNetworkLayer:
"""Layer class of Bilinear. Bilinear is to calculate interaction in element-wise by nn.Bilinear, which the calculation is: for i-th layer, :math:`x_{i} = (x_{0} * A_{i} * x_{i - 1}) + b_{i} + x_{0}`, where :math:`A_{i}` is the weight of module of shape :math:`(O_{i}, I_{i1},... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BilinearNetworkLayer:
"""Layer class of Bilinear. Bilinear is to calculate interaction in element-wise by nn.Bilinear, which the calculation is: for i-th layer, :math:`x_{i} = (x_{0} * A_{i} * x_{i - 1}) + b_{i} + x_{0}`, where :math:`A_{i}` is the weight of module of shape :math:`(O_{i}, I_{i1}, I_{i2})`."""... | the_stack_v2_python_sparse | torecsys/layers/ctr/bilinear.py | zwcdp/torecsys | train | 0 |
e79d104ebc2456ebc8816db0762f2e2dc74a2df8 | [
"super().__init__()\nself.mlp = mlp\nself.use_softmax = use_softmax",
"B, C, N = feature.size()\nfeature = feature.view(B, C, N, 1).repeat(1, 1, 1, N)\nif feature.device.type == 'cpu':\n feature = feature - feature.transpose(2, 3).contiguous() + torch.mul(feature, torch.eye(N).view(1, 1, N, N))\nelse:\n fea... | <|body_start_0|>
super().__init__()
self.mlp = mlp
self.use_softmax = use_softmax
<|end_body_0|>
<|body_start_1|>
B, C, N = feature.size()
feature = feature.view(B, C, N, 1).repeat(1, 1, 1, N)
if feature.device.type == 'cpu':
feature = feature - feature.trans... | AFAModule | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AFAModule:
def __init__(self, mlp, use_softmax=False):
""":param mlp: mlp for learning weight mode: transformation or aggregation"""
<|body_0|>
def forward(self, feature: torch.Tensor) -> torch.Tensor:
"""Parameters ---------- features : torch.Tensor (B, C, N, M) or ... | stack_v2_sparse_classes_36k_train_010377 | 12,242 | permissive | [
{
"docstring": ":param mlp: mlp for learning weight mode: transformation or aggregation",
"name": "__init__",
"signature": "def __init__(self, mlp, use_softmax=False)"
},
{
"docstring": "Parameters ---------- features : torch.Tensor (B, C, N, M) or (B, C, N) Returns ------- new_features : torch.... | 2 | stack_v2_sparse_classes_30k_train_014991 | Implement the Python class `AFAModule` described below.
Class description:
Implement the AFAModule class.
Method signatures and docstrings:
- def __init__(self, mlp, use_softmax=False): :param mlp: mlp for learning weight mode: transformation or aggregation
- def forward(self, feature: torch.Tensor) -> torch.Tensor: ... | Implement the Python class `AFAModule` described below.
Class description:
Implement the AFAModule class.
Method signatures and docstrings:
- def __init__(self, mlp, use_softmax=False): :param mlp: mlp for learning weight mode: transformation or aggregation
- def forward(self, feature: torch.Tensor) -> torch.Tensor: ... | 241b3c94112efb2944a27e4cc3eb1d65775edc10 | <|skeleton|>
class AFAModule:
def __init__(self, mlp, use_softmax=False):
""":param mlp: mlp for learning weight mode: transformation or aggregation"""
<|body_0|>
def forward(self, feature: torch.Tensor) -> torch.Tensor:
"""Parameters ---------- features : torch.Tensor (B, C, N, M) or ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AFAModule:
def __init__(self, mlp, use_softmax=False):
""":param mlp: mlp for learning weight mode: transformation or aggregation"""
super().__init__()
self.mlp = mlp
self.use_softmax = use_softmax
def forward(self, feature: torch.Tensor) -> torch.Tensor:
"""Parame... | the_stack_v2_python_sparse | crowd_nav/policy/gipcarl.py | sustech-isus/AEMCARL | train | 0 | |
0bcdf7b7d27e6f6462f5a35ea2ff631bbf095ebe | [
"memo = {}\nfor num in nums1:\n memo[num] = memo.get(num, 0) + 1\nresult = []\nfor num in nums2:\n if num in memo and memo[num] > 0:\n result.append(num)\n memo[num] -= 1\nreturn result",
"nums1.sort()\nnums2.sort()\nresult = []\ni1 = i2 = 0\nwhile i1 < len(nums1) and i2 < len(nums2):\n if ... | <|body_start_0|>
memo = {}
for num in nums1:
memo[num] = memo.get(num, 0) + 1
result = []
for num in nums2:
if num in memo and memo[num] > 0:
result.append(num)
memo[num] -= 1
return result
<|end_body_0|>
<|body_start_1|>
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def intersect_0(self, nums1, nums2):
""":type nums1: List[int] :type nums2: List[int] :rtype: List[int]"""
<|body_0|>
def intersect_1(self, nums1, nums2):
""":type nums1: List[int] :type nums2: List[int] :rtype: List[int]"""
<|body_1|>
<|end_skelet... | stack_v2_sparse_classes_36k_train_010378 | 2,179 | no_license | [
{
"docstring": ":type nums1: List[int] :type nums2: List[int] :rtype: List[int]",
"name": "intersect_0",
"signature": "def intersect_0(self, nums1, nums2)"
},
{
"docstring": ":type nums1: List[int] :type nums2: List[int] :rtype: List[int]",
"name": "intersect_1",
"signature": "def inters... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def intersect_0(self, nums1, nums2): :type nums1: List[int] :type nums2: List[int] :rtype: List[int]
- def intersect_1(self, nums1, nums2): :type nums1: List[int] :type nums2: Li... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def intersect_0(self, nums1, nums2): :type nums1: List[int] :type nums2: List[int] :rtype: List[int]
- def intersect_1(self, nums1, nums2): :type nums1: List[int] :type nums2: Li... | 9ac54720f571a4bea09d0cceb0039381a78df9e8 | <|skeleton|>
class Solution:
def intersect_0(self, nums1, nums2):
""":type nums1: List[int] :type nums2: List[int] :rtype: List[int]"""
<|body_0|>
def intersect_1(self, nums1, nums2):
""":type nums1: List[int] :type nums2: List[int] :rtype: List[int]"""
<|body_1|>
<|end_skelet... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def intersect_0(self, nums1, nums2):
""":type nums1: List[int] :type nums2: List[int] :rtype: List[int]"""
memo = {}
for num in nums1:
memo[num] = memo.get(num, 0) + 1
result = []
for num in nums2:
if num in memo and memo[num] > 0:
... | the_stack_v2_python_sparse | code/350_intersection-of-two-arrays-ii.py | linhdvu14/leetcode-solutions | train | 2 | |
e8aefc791b1d2b255a182bd702708bfe12feb5d8 | [
"parser.add_argument('job_name', metavar='JOB_NAME', help='The unique name to assign to the job.')\nparser.add_argument('--gcs-location', help='The location of the job template to run.', required=True)\nparser.add_argument('--zone', type=arg_parsers.RegexpValidator('\\\\w+-\\\\w+\\\\d-\\\\w', 'must provide a valid ... | <|body_start_0|>
parser.add_argument('job_name', metavar='JOB_NAME', help='The unique name to assign to the job.')
parser.add_argument('--gcs-location', help='The location of the job template to run.', required=True)
parser.add_argument('--zone', type=arg_parsers.RegexpValidator('\\w+-\\w+\\d-\\... | Runs a job from the specified path. | Run | [
"LicenseRef-scancode-unknown-license-reference",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Run:
"""Runs a job from the specified path."""
def Args(parser):
"""Register flags for this command. Args: parser: argparse.ArgumentParser to register arguments with."""
<|body_0|>
def Run(self, args):
"""Runs the command. Args: args: The arguments that were prov... | stack_v2_sparse_classes_36k_train_010379 | 2,918 | permissive | [
{
"docstring": "Register flags for this command. Args: parser: argparse.ArgumentParser to register arguments with.",
"name": "Args",
"signature": "def Args(parser)"
},
{
"docstring": "Runs the command. Args: args: The arguments that were provided to this command invocation. Returns: A Job messag... | 2 | null | Implement the Python class `Run` described below.
Class description:
Runs a job from the specified path.
Method signatures and docstrings:
- def Args(parser): Register flags for this command. Args: parser: argparse.ArgumentParser to register arguments with.
- def Run(self, args): Runs the command. Args: args: The arg... | Implement the Python class `Run` described below.
Class description:
Runs a job from the specified path.
Method signatures and docstrings:
- def Args(parser): Register flags for this command. Args: parser: argparse.ArgumentParser to register arguments with.
- def Run(self, args): Runs the command. Args: args: The arg... | c98b58aeb0994e011df960163541e9379ae7ea06 | <|skeleton|>
class Run:
"""Runs a job from the specified path."""
def Args(parser):
"""Register flags for this command. Args: parser: argparse.ArgumentParser to register arguments with."""
<|body_0|>
def Run(self, args):
"""Runs the command. Args: args: The arguments that were prov... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Run:
"""Runs a job from the specified path."""
def Args(parser):
"""Register flags for this command. Args: parser: argparse.ArgumentParser to register arguments with."""
parser.add_argument('job_name', metavar='JOB_NAME', help='The unique name to assign to the job.')
parser.add_ar... | the_stack_v2_python_sparse | google-cloud-sdk/.install/.backup/lib/surface/dataflow/jobs/run.py | KaranToor/MA450 | train | 1 |
6c0fa090a6cfb14576aa2adc98c69dd5075836d5 | [
"res = deque()\nfor i in range(len(nums)):\n if nums[i] % 2 == 0:\n res.append(nums[i])\n else:\n res.appendleft(nums[i])\nreturn list(res)",
"i, j = (0, len(nums) - 1)\nwhile i < j:\n while i < j and nums[i] & 1 == 1:\n i += 1\n while i < j and nums[j] & 1 == 0:\n j -= 1\n... | <|body_start_0|>
res = deque()
for i in range(len(nums)):
if nums[i] % 2 == 0:
res.append(nums[i])
else:
res.appendleft(nums[i])
return list(res)
<|end_body_0|>
<|body_start_1|>
i, j = (0, len(nums) - 1)
while i < j:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def exchange_1(self, nums: List[int]) -> List[int]:
"""双端队列 时间复杂度 O(N) 空间复杂度 O(N) :param nums: :return:"""
<|body_0|>
def exchange_2(self, nums: List[int]) -> List[int]:
"""双指针 时间复杂度 O(N) 空间复杂度 O(1) :param nums: :return:"""
<|body_1|>
<|end_skeleto... | stack_v2_sparse_classes_36k_train_010380 | 1,516 | no_license | [
{
"docstring": "双端队列 时间复杂度 O(N) 空间复杂度 O(N) :param nums: :return:",
"name": "exchange_1",
"signature": "def exchange_1(self, nums: List[int]) -> List[int]"
},
{
"docstring": "双指针 时间复杂度 O(N) 空间复杂度 O(1) :param nums: :return:",
"name": "exchange_2",
"signature": "def exchange_2(self, nums: L... | 2 | stack_v2_sparse_classes_30k_train_009393 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def exchange_1(self, nums: List[int]) -> List[int]: 双端队列 时间复杂度 O(N) 空间复杂度 O(N) :param nums: :return:
- def exchange_2(self, nums: List[int]) -> List[int]: 双指针 时间复杂度 O(N) 空间复杂度 O(... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def exchange_1(self, nums: List[int]) -> List[int]: 双端队列 时间复杂度 O(N) 空间复杂度 O(N) :param nums: :return:
- def exchange_2(self, nums: List[int]) -> List[int]: 双指针 时间复杂度 O(N) 空间复杂度 O(... | 62419b49000e79962bcdc99cd98afd2fb82ea345 | <|skeleton|>
class Solution:
def exchange_1(self, nums: List[int]) -> List[int]:
"""双端队列 时间复杂度 O(N) 空间复杂度 O(N) :param nums: :return:"""
<|body_0|>
def exchange_2(self, nums: List[int]) -> List[int]:
"""双指针 时间复杂度 O(N) 空间复杂度 O(1) :param nums: :return:"""
<|body_1|>
<|end_skeleto... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def exchange_1(self, nums: List[int]) -> List[int]:
"""双端队列 时间复杂度 O(N) 空间复杂度 O(N) :param nums: :return:"""
res = deque()
for i in range(len(nums)):
if nums[i] % 2 == 0:
res.append(nums[i])
else:
res.appendleft(nums[i])
... | the_stack_v2_python_sparse | 剑指 Offer（第 2 版）/exchange.py | MaoningGuan/LeetCode | train | 3 | |
70ca41daa6d3c92741d6a2fe027d4c8f34b167f8 | [
"if not isinstance(document, Mapping):\n raise ValueError('Document is not a Mapping')\nif isinstance(document, Document):\n doc_id = document.doc_id\n self._next_id = None\nelse:\n doc_id = self._get_next_id()\n\ndef updater(table: dict):\n assert doc_id not in table, 'doc_id ' + str(doc_id) + ' alr... | <|body_start_0|>
if not isinstance(document, Mapping):
raise ValueError('Document is not a Mapping')
if isinstance(document, Document):
doc_id = document.doc_id
self._next_id = None
else:
doc_id = self._get_next_id()
def updater(table: dic... | MyDb | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MyDb:
def insert(self, document):
"""Insert a new document into the table. :param document: the document to insert :returns: the inserted document's ID"""
<|body_0|>
def insert_multiple(self, documents: Iterable[Mapping]) -> List[int]:
"""Insert multiple documents in... | stack_v2_sparse_classes_36k_train_010381 | 3,238 | no_license | [
{
"docstring": "Insert a new document into the table. :param document: the document to insert :returns: the inserted document's ID",
"name": "insert",
"signature": "def insert(self, document)"
},
{
"docstring": "Insert multiple documents into the table. :param documents: a Iterable of documents ... | 2 | null | Implement the Python class `MyDb` described below.
Class description:
Implement the MyDb class.
Method signatures and docstrings:
- def insert(self, document): Insert a new document into the table. :param document: the document to insert :returns: the inserted document's ID
- def insert_multiple(self, documents: Iter... | Implement the Python class `MyDb` described below.
Class description:
Implement the MyDb class.
Method signatures and docstrings:
- def insert(self, document): Insert a new document into the table. :param document: the document to insert :returns: the inserted document's ID
- def insert_multiple(self, documents: Iter... | 095d6587d6620469e0f1803d59a506682714da17 | <|skeleton|>
class MyDb:
def insert(self, document):
"""Insert a new document into the table. :param document: the document to insert :returns: the inserted document's ID"""
<|body_0|>
def insert_multiple(self, documents: Iterable[Mapping]) -> List[int]:
"""Insert multiple documents in... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MyDb:
def insert(self, document):
"""Insert a new document into the table. :param document: the document to insert :returns: the inserted document's ID"""
if not isinstance(document, Mapping):
raise ValueError('Document is not a Mapping')
if isinstance(document, Document):
... | the_stack_v2_python_sparse | _msic/py/tinydb/test_use.py | FXTD-ODYSSEY/MayaScript | train | 45 | |
979e39a1c51c0a72875cfa6144beaa7ea504af40 | [
"if isinstance(value, (ipaddress.IPv4Address, ipaddress.IPv6Address)):\n ip = value\nelse:\n ip = ipaddress.ip_address(value)\nif ip.version != self.version:\n raise FieldValueError(f'IP version mismatch: {ip.version} != {self.version}')\nreturn ip.packed",
"val = ipaddress.ip_address(value)\nif val.vers... | <|body_start_0|>
if isinstance(value, (ipaddress.IPv4Address, ipaddress.IPv6Address)):
ip = value
else:
ip = ipaddress.ip_address(value)
if ip.version != self.version:
raise FieldValueError(f'IP version mismatch: {ip.version} != {self.version}')
return... | Internal IP address value for protocol fields. Args: length: Field size (in bytes). callback: Callback function to be called upon :meth:`self.__call__ <pcapkit.corekit.fields.field._Field.__call__>`. | _IPAddressField | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class _IPAddressField:
"""Internal IP address value for protocol fields. Args: length: Field size (in bytes). callback: Callback function to be called upon :meth:`self.__call__ <pcapkit.corekit.fields.field._Field.__call__>`."""
def pre_process(self, value: '_AT | bytes | int | str', packet: 'dict... | stack_v2_sparse_classes_36k_train_010382 | 8,370 | permissive | [
{
"docstring": "Process field value before packing. Args: value: Field value. packet: Packet data. Returns: Processed field value.",
"name": "pre_process",
"signature": "def pre_process(self, value: '_AT | bytes | int | str', packet: 'dict[str, Any]') -> 'bytes'"
},
{
"docstring": "Process field... | 2 | stack_v2_sparse_classes_30k_train_008212 | Implement the Python class `_IPAddressField` described below.
Class description:
Internal IP address value for protocol fields. Args: length: Field size (in bytes). callback: Callback function to be called upon :meth:`self.__call__ <pcapkit.corekit.fields.field._Field.__call__>`.
Method signatures and docstrings:
- d... | Implement the Python class `_IPAddressField` described below.
Class description:
Internal IP address value for protocol fields. Args: length: Field size (in bytes). callback: Callback function to be called upon :meth:`self.__call__ <pcapkit.corekit.fields.field._Field.__call__>`.
Method signatures and docstrings:
- d... | a6fe49ec58f09e105bec5a00fb66d9b3f22730d9 | <|skeleton|>
class _IPAddressField:
"""Internal IP address value for protocol fields. Args: length: Field size (in bytes). callback: Callback function to be called upon :meth:`self.__call__ <pcapkit.corekit.fields.field._Field.__call__>`."""
def pre_process(self, value: '_AT | bytes | int | str', packet: 'dict... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class _IPAddressField:
"""Internal IP address value for protocol fields. Args: length: Field size (in bytes). callback: Callback function to be called upon :meth:`self.__call__ <pcapkit.corekit.fields.field._Field.__call__>`."""
def pre_process(self, value: '_AT | bytes | int | str', packet: 'dict[str, Any]') ... | the_stack_v2_python_sparse | pcapkit/corekit/fields/ipaddress.py | JarryShaw/PyPCAPKit | train | 204 |
a4a18c37df588cc7d4965486140b62e9b15bba47 | [
"dp = [0] * (n + 1)\nif n <= 2:\n return n\ndp[1] = 1\ndp[2] = 2\nfor i in range(3, n + 1):\n dp[i] = dp[i - 1] + dp[i - 2]\nprint(dp[n])\nreturn dp[n]",
"def rec(n, memo):\n if n in memo:\n return memo[n]\n memo[n] = rec(n - 1, memo) + rec(n - 2, memo)\n return memo[n]\nmemo = {}\nmemo[1] =... | <|body_start_0|>
dp = [0] * (n + 1)
if n <= 2:
return n
dp[1] = 1
dp[2] = 2
for i in range(3, n + 1):
dp[i] = dp[i - 1] + dp[i - 2]
print(dp[n])
return dp[n]
<|end_body_0|>
<|body_start_1|>
def rec(n, memo):
if n in mem... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def climbStairs(self, n):
""":type n: int :rtype: int"""
<|body_0|>
def climbStairs_rec(self, n):
""":type n: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
dp = [0] * (n + 1)
if n <= 2:
return n
... | stack_v2_sparse_classes_36k_train_010383 | 1,740 | no_license | [
{
"docstring": ":type n: int :rtype: int",
"name": "climbStairs",
"signature": "def climbStairs(self, n)"
},
{
"docstring": ":type n: int :rtype: int",
"name": "climbStairs_rec",
"signature": "def climbStairs_rec(self, n)"
}
] | 2 | stack_v2_sparse_classes_30k_train_005402 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def climbStairs(self, n): :type n: int :rtype: int
- def climbStairs_rec(self, n): :type n: int :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def climbStairs(self, n): :type n: int :rtype: int
- def climbStairs_rec(self, n): :type n: int :rtype: int
<|skeleton|>
class Solution:
def climbStairs(self, n):
"... | 2d5fa4cd696d5035ea8859befeadc5cc436959c9 | <|skeleton|>
class Solution:
def climbStairs(self, n):
""":type n: int :rtype: int"""
<|body_0|>
def climbStairs_rec(self, n):
""":type n: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def climbStairs(self, n):
""":type n: int :rtype: int"""
dp = [0] * (n + 1)
if n <= 2:
return n
dp[1] = 1
dp[2] = 2
for i in range(3, n + 1):
dp[i] = dp[i - 1] + dp[i - 2]
print(dp[n])
return dp[n]
def climb... | the_stack_v2_python_sparse | SourceCode/Python/Problem/00070.Climbing Stairs.py | roger6blog/LeetCode | train | 0 | |
dce82b60dd0ac35efad9427b0f7fb5878127c0ed | [
"cmd = 'nova'\nif api_version:\n cmd += ' --os-compute-api-version {0}'.format(api_version)\ncmd += ' list'\nexit_code, stdout, stderr = self.execute_command(cmd, timeout=config.SERVER_LIST_TIMEOUT, check=check)\nif check:\n list_result = output_parser.listing(stdout)\n assert_that(list_result, is_not(empt... | <|body_start_0|>
cmd = 'nova'
if api_version:
cmd += ' --os-compute-api-version {0}'.format(api_version)
cmd += ' list'
exit_code, stdout, stderr = self.execute_command(cmd, timeout=config.SERVER_LIST_TIMEOUT, check=check)
if check:
list_result = output_pa... | CLI nova client steps. | CliNovaSteps | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CliNovaSteps:
"""CLI nova client steps."""
def nova_list(self, api_version=None, check=True):
"""Step to get nova list. Args: api_version (str|None): micro version for nova list command check (bool): flag whether to check result or not Raises: TimeoutExpired|AssertionError: if check ... | stack_v2_sparse_classes_36k_train_010384 | 2,899 | no_license | [
{
"docstring": "Step to get nova list. Args: api_version (str|None): micro version for nova list command check (bool): flag whether to check result or not Raises: TimeoutExpired|AssertionError: if check failed after timeout",
"name": "nova_list",
"signature": "def nova_list(self, api_version=None, check... | 2 | stack_v2_sparse_classes_30k_train_004245 | Implement the Python class `CliNovaSteps` described below.
Class description:
CLI nova client steps.
Method signatures and docstrings:
- def nova_list(self, api_version=None, check=True): Step to get nova list. Args: api_version (str|None): micro version for nova list command check (bool): flag whether to check resul... | Implement the Python class `CliNovaSteps` described below.
Class description:
CLI nova client steps.
Method signatures and docstrings:
- def nova_list(self, api_version=None, check=True): Step to get nova list. Args: api_version (str|None): micro version for nova list command check (bool): flag whether to check resul... | e7583444cd24893ec6ae237b47db7c605b99b0c5 | <|skeleton|>
class CliNovaSteps:
"""CLI nova client steps."""
def nova_list(self, api_version=None, check=True):
"""Step to get nova list. Args: api_version (str|None): micro version for nova list command check (bool): flag whether to check result or not Raises: TimeoutExpired|AssertionError: if check ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CliNovaSteps:
"""CLI nova client steps."""
def nova_list(self, api_version=None, check=True):
"""Step to get nova list. Args: api_version (str|None): micro version for nova list command check (bool): flag whether to check result or not Raises: TimeoutExpired|AssertionError: if check failed after ... | the_stack_v2_python_sparse | stepler/cli_clients/steps/nova.py | Mirantis/stepler | train | 16 |
7cebaa98aa274383b70615d2869af2d0889a37c6 | [
"super(AfterSaleServiceConditionImpliedWarranties, self).__init__(*args, **kwargs)\nself.endpoint = '/after-sales-service-conditions/implied-warranties'\nself.seller_id = None\nself._headers = {'Accept': 'application/vnd.allegro.public.v1+json', 'Content-type': 'application/vnd.allegro.public.v1+json'}",
"self.se... | <|body_start_0|>
super(AfterSaleServiceConditionImpliedWarranties, self).__init__(*args, **kwargs)
self.endpoint = '/after-sales-service-conditions/implied-warranties'
self.seller_id = None
self._headers = {'Accept': 'application/vnd.allegro.public.v1+json', 'Content-type': 'application/... | Manage category tree | AfterSaleServiceConditionImpliedWarranties | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AfterSaleServiceConditionImpliedWarranties:
"""Manage category tree"""
def __init__(self, *args, **kwargs):
"""Initialize the endpoint"""
<|body_0|>
def all(self, seller_id=None):
"""Get a list of categories :param seller_id: The seller's unique id. :type seller_... | stack_v2_sparse_classes_36k_train_010385 | 1,357 | permissive | [
{
"docstring": "Initialize the endpoint",
"name": "__init__",
"signature": "def __init__(self, *args, **kwargs)"
},
{
"docstring": "Get a list of categories :param seller_id: The seller's unique id. :type seller_id: :py:class:`str` :return: The JSON response from API or error or None (if 204) :r... | 2 | stack_v2_sparse_classes_30k_test_000220 | Implement the Python class `AfterSaleServiceConditionImpliedWarranties` described below.
Class description:
Manage category tree
Method signatures and docstrings:
- def __init__(self, *args, **kwargs): Initialize the endpoint
- def all(self, seller_id=None): Get a list of categories :param seller_id: The seller's uni... | Implement the Python class `AfterSaleServiceConditionImpliedWarranties` described below.
Class description:
Manage category tree
Method signatures and docstrings:
- def __init__(self, *args, **kwargs): Initialize the endpoint
- def all(self, seller_id=None): Get a list of categories :param seller_id: The seller's uni... | 112b0f2570fcf3840645dd62f6f7150956e56f9c | <|skeleton|>
class AfterSaleServiceConditionImpliedWarranties:
"""Manage category tree"""
def __init__(self, *args, **kwargs):
"""Initialize the endpoint"""
<|body_0|>
def all(self, seller_id=None):
"""Get a list of categories :param seller_id: The seller's unique id. :type seller_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AfterSaleServiceConditionImpliedWarranties:
"""Manage category tree"""
def __init__(self, *args, **kwargs):
"""Initialize the endpoint"""
super(AfterSaleServiceConditionImpliedWarranties, self).__init__(*args, **kwargs)
self.endpoint = '/after-sales-service-conditions/implied-warr... | the_stack_v2_python_sparse | allegroapi/entities/aftersalesserviceconditionsimpliedwarranties.py | krystianmagdziarz/python-allegro | train | 0 |
e44ca393f1970a08b88b045422a099b883e84ae4 | [
"if not root:\n return ''\narr = []\nqueue = [root]\nwhile queue:\n node = queue.pop(0)\n arr.append(str(node.val) if node else 'null')\n if node:\n queue.append(node.left)\n queue.append(node.right)\nwhile arr[-1] == 'null':\n arr.pop()\nreturn ','.join(arr)",
"if not data:\n retu... | <|body_start_0|>
if not root:
return ''
arr = []
queue = [root]
while queue:
node = queue.pop(0)
arr.append(str(node.val) if node else 'null')
if node:
queue.append(node.left)
queue.append(node.right)
... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|>
<|body_... | stack_v2_sparse_classes_36k_train_010386 | 2,195 | no_license | [
{
"docstring": "Encodes a tree to a single string. :type root: TreeNode :rtype: str",
"name": "serialize",
"signature": "def serialize(self, root)"
},
{
"docstring": "Decodes your encoded data to tree. :type data: str :rtype: TreeNode",
"name": "deserialize",
"signature": "def deserializ... | 2 | null | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | 26fddfdbd09c30376cb0720e13baf0402c3a1e90 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
if not root:
return ''
arr = []
queue = [root]
while queue:
node = queue.pop(0)
arr.append(str(node.val) if node else 'null')
... | the_stack_v2_python_sparse | 2022.2.8start/297.二叉树的序列化与反序列化.py | cosJin/LeetCode | train | 0 | |
587fcc5493081aa26787413f58e6f8e5d8782256 | [
"adm = ProjektAdministration()\nsemester = adm.get_alle_semester()\nreturn semester",
"id = request.args.get('id')\nadm = ProjektAdministration()\nadm.delete_semester(id)",
"adm = ProjektAdministration()\nsemester = Semester.from_dict(api.payload)\nif semester is not None:\n ' Wir verwenden semester des Prop... | <|body_start_0|>
adm = ProjektAdministration()
semester = adm.get_alle_semester()
return semester
<|end_body_0|>
<|body_start_1|>
id = request.args.get('id')
adm = ProjektAdministration()
adm.delete_semester(id)
<|end_body_1|>
<|body_start_2|>
adm = ProjektAdmin... | SemesterOperationen | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SemesterOperationen:
def get(self):
"""Auslesen aller Semester-Objekten. Sollten keine User-Objekte verfügbar sein, so wird eine leere Sequenz zurückgegeben."""
<|body_0|>
def delete(self):
"""Löschen eines bestimmten Semester-Objekts nach id."""
<|body_1|>
... | stack_v2_sparse_classes_36k_train_010387 | 29,521 | no_license | [
{
"docstring": "Auslesen aller Semester-Objekten. Sollten keine User-Objekte verfügbar sein, so wird eine leere Sequenz zurückgegeben.",
"name": "get",
"signature": "def get(self)"
},
{
"docstring": "Löschen eines bestimmten Semester-Objekts nach id.",
"name": "delete",
"signature": "def... | 4 | stack_v2_sparse_classes_30k_train_009898 | Implement the Python class `SemesterOperationen` described below.
Class description:
Implement the SemesterOperationen class.
Method signatures and docstrings:
- def get(self): Auslesen aller Semester-Objekten. Sollten keine User-Objekte verfügbar sein, so wird eine leere Sequenz zurückgegeben.
- def delete(self): Lö... | Implement the Python class `SemesterOperationen` described below.
Class description:
Implement the SemesterOperationen class.
Method signatures and docstrings:
- def get(self): Auslesen aller Semester-Objekten. Sollten keine User-Objekte verfügbar sein, so wird eine leere Sequenz zurückgegeben.
- def delete(self): Lö... | 9014f16fed08956bd28216e1373b60139e5caea1 | <|skeleton|>
class SemesterOperationen:
def get(self):
"""Auslesen aller Semester-Objekten. Sollten keine User-Objekte verfügbar sein, so wird eine leere Sequenz zurückgegeben."""
<|body_0|>
def delete(self):
"""Löschen eines bestimmten Semester-Objekts nach id."""
<|body_1|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SemesterOperationen:
def get(self):
"""Auslesen aller Semester-Objekten. Sollten keine User-Objekte verfügbar sein, so wird eine leere Sequenz zurückgegeben."""
adm = ProjektAdministration()
semester = adm.get_alle_semester()
return semester
def delete(self):
"""Lö... | the_stack_v2_python_sparse | src/main.py | leanderpeter/university_project_selector | train | 3 | |
e1693b454a5a36cbb1ef53743dbad728954c1078 | [
"team.trusted = trusted\nteam.save(update_fields=['trusted'])\nreturn Response({'detail': 'Mapping Team set as {}.'.format('trusted' if trusted else 'untrusted')}, status=status.HTTP_200_OK)",
"team = self.get_object()\nif team.trusted:\n return Response({'detail': 'Mapping team is already trusted.'}, status=s... | <|body_start_0|>
team.trusted = trusted
team.save(update_fields=['trusted'])
return Response({'detail': 'Mapping Team set as {}.'.format('trusted' if trusted else 'untrusted')}, status=status.HTTP_200_OK)
<|end_body_0|>
<|body_start_1|>
team = self.get_object()
if team.trusted:
... | MappingTeamTrustingAPIView | [
"BSD-3-Clause",
"BSD-2-Clause",
"ISC",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MappingTeamTrustingAPIView:
def update_team(self, team, request, trusted):
"""Update 'checked', 'harmful', 'check_user', 'check_date' fields of the changeset and return a 200 response"""
<|body_0|>
def set_trusted(self, request, pk):
"""Set a Mapping Team as trusted.... | stack_v2_sparse_classes_36k_train_010388 | 9,317 | permissive | [
{
"docstring": "Update 'checked', 'harmful', 'check_user', 'check_date' fields of the changeset and return a 200 response",
"name": "update_team",
"signature": "def update_team(self, team, request, trusted)"
},
{
"docstring": "Set a Mapping Team as trusted. You don't need to send data, just make... | 3 | stack_v2_sparse_classes_30k_train_001514 | Implement the Python class `MappingTeamTrustingAPIView` described below.
Class description:
Implement the MappingTeamTrustingAPIView class.
Method signatures and docstrings:
- def update_team(self, team, request, trusted): Update 'checked', 'harmful', 'check_user', 'check_date' fields of the changeset and return a 20... | Implement the Python class `MappingTeamTrustingAPIView` described below.
Class description:
Implement the MappingTeamTrustingAPIView class.
Method signatures and docstrings:
- def update_team(self, team, request, trusted): Update 'checked', 'harmful', 'check_user', 'check_date' fields of the changeset and return a 20... | 603496dce834bf3ecf28cc949da619b837e2873c | <|skeleton|>
class MappingTeamTrustingAPIView:
def update_team(self, team, request, trusted):
"""Update 'checked', 'harmful', 'check_user', 'check_date' fields of the changeset and return a 200 response"""
<|body_0|>
def set_trusted(self, request, pk):
"""Set a Mapping Team as trusted.... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MappingTeamTrustingAPIView:
def update_team(self, team, request, trusted):
"""Update 'checked', 'harmful', 'check_user', 'check_date' fields of the changeset and return a 200 response"""
team.trusted = trusted
team.save(update_fields=['trusted'])
return Response({'detail': 'Map... | the_stack_v2_python_sparse | Backend/osmchadjango/users/views.py | habi/srz-edi | train | 1 | |
4109b0a3748f7d5d98c91fd5f9cadfed173c5270 | [
"self.BATT_SIZE = 50\nself.FULL_CHAR = '+'\nself.EMPTY_CHAR = '.'\nself.empty = empty\nself.full = full\nself.charge = None",
"if self.charge is None:\n return None\nreturn saturate(self.charge, self.empty, self.full, 0, 100)",
"level = self.get_level()\nif level is None:\n return 'Awaiting data...'\nasse... | <|body_start_0|>
self.BATT_SIZE = 50
self.FULL_CHAR = '+'
self.EMPTY_CHAR = '.'
self.empty = empty
self.full = full
self.charge = None
<|end_body_0|>
<|body_start_1|>
if self.charge is None:
return None
return saturate(self.charge, self.empty,... | Represents a battery and defines its analog port and charge limits (eg, full, empty). | Battery | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Battery:
"""Represents a battery and defines its analog port and charge limits (eg, full, empty)."""
def __init__(self, empty=120, full=150):
"""Constructor. @param empty: the raw signal value that indicates empty battery @param full: the raw signal value that indicates full battery"... | stack_v2_sparse_classes_36k_train_010389 | 5,209 | no_license | [
{
"docstring": "Constructor. @param empty: the raw signal value that indicates empty battery @param full: the raw signal value that indicates full battery",
"name": "__init__",
"signature": "def __init__(self, empty=120, full=150)"
},
{
"docstring": "@return: the current charge of the battery as... | 3 | null | Implement the Python class `Battery` described below.
Class description:
Represents a battery and defines its analog port and charge limits (eg, full, empty).
Method signatures and docstrings:
- def __init__(self, empty=120, full=150): Constructor. @param empty: the raw signal value that indicates empty battery @para... | Implement the Python class `Battery` described below.
Class description:
Represents a battery and defines its analog port and charge limits (eg, full, empty).
Method signatures and docstrings:
- def __init__(self, empty=120, full=150): Constructor. @param empty: the raw signal value that indicates empty battery @para... | 52bacd9f58524090e0ab421a47714629249ca273 | <|skeleton|>
class Battery:
"""Represents a battery and defines its analog port and charge limits (eg, full, empty)."""
def __init__(self, empty=120, full=150):
"""Constructor. @param empty: the raw signal value that indicates empty battery @param full: the raw signal value that indicates full battery"... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Battery:
"""Represents a battery and defines its analog port and charge limits (eg, full, empty)."""
def __init__(self, empty=120, full=150):
"""Constructor. @param empty: the raw signal value that indicates empty battery @param full: the raw signal value that indicates full battery"""
se... | the_stack_v2_python_sparse | src/09-10/ubc-tbird-ros-pkg/sb_util/scripts/battery_monitor.py | jpearkes/snowbots | train | 0 |
3e9af28a4872dd2a0eb5fafb9a1795c385c75977 | [
"if not matrix:\n self.dp = None\n return\nm = len(matrix)\nn = len(matrix[0])\ndp = self.dp = [[0 for _ in range(n + 1)] for _ in range(m + 1)]\nfor x in range(1, m + 1):\n for y in range(1, n + 1):\n dp[x][y] = dp[x - 1][y] + dp[x][y - 1] - dp[x - 1][y - 1] + matrix[x - 1][y - 1]",
"if not self.... | <|body_start_0|>
if not matrix:
self.dp = None
return
m = len(matrix)
n = len(matrix[0])
dp = self.dp = [[0 for _ in range(n + 1)] for _ in range(m + 1)]
for x in range(1, m + 1):
for y in range(1, n + 1):
dp[x][y] = dp[x - 1][y... | NumMatrix | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NumMatrix:
def __init__(self, matrix):
"""initialize your data structure here. :type matrix: List[List[int]]"""
<|body_0|>
def sumRegion(self, row1, col1, row2, col2):
"""sum of elements matrix[(row1,col1)..(row2,col2)], inclusive. :type row1: int :type col1: int :ty... | stack_v2_sparse_classes_36k_train_010390 | 1,287 | no_license | [
{
"docstring": "initialize your data structure here. :type matrix: List[List[int]]",
"name": "__init__",
"signature": "def __init__(self, matrix)"
},
{
"docstring": "sum of elements matrix[(row1,col1)..(row2,col2)], inclusive. :type row1: int :type col1: int :type row2: int :type col2: int :rtyp... | 2 | stack_v2_sparse_classes_30k_train_001395 | Implement the Python class `NumMatrix` described below.
Class description:
Implement the NumMatrix class.
Method signatures and docstrings:
- def __init__(self, matrix): initialize your data structure here. :type matrix: List[List[int]]
- def sumRegion(self, row1, col1, row2, col2): sum of elements matrix[(row1,col1)... | Implement the Python class `NumMatrix` described below.
Class description:
Implement the NumMatrix class.
Method signatures and docstrings:
- def __init__(self, matrix): initialize your data structure here. :type matrix: List[List[int]]
- def sumRegion(self, row1, col1, row2, col2): sum of elements matrix[(row1,col1)... | a041962eeab9192799ad7f74b4bbd3e4f74933d0 | <|skeleton|>
class NumMatrix:
def __init__(self, matrix):
"""initialize your data structure here. :type matrix: List[List[int]]"""
<|body_0|>
def sumRegion(self, row1, col1, row2, col2):
"""sum of elements matrix[(row1,col1)..(row2,col2)], inclusive. :type row1: int :type col1: int :ty... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NumMatrix:
def __init__(self, matrix):
"""initialize your data structure here. :type matrix: List[List[int]]"""
if not matrix:
self.dp = None
return
m = len(matrix)
n = len(matrix[0])
dp = self.dp = [[0 for _ in range(n + 1)] for _ in range(m + 1... | the_stack_v2_python_sparse | codes/304. Range Sum Query 2D - Immutable.py | zcgu/leetcode | train | 1 | |
daf7ce02d1a3d3a275d7e2a771f708388619e0df | [
"self.log.info('login from Weibo Sina')\ncode = context.get('code')\nredirect_uri = context.get('redirect_uri')\nif not code or not redirect_uri:\n return None\naccess_token = self.get_token(code, redirect_uri)\nuser_info = self.get_user_info(access_token['access_token'], access_token['uid'])\nemail_list = []\nn... | <|body_start_0|>
self.log.info('login from Weibo Sina')
code = context.get('code')
redirect_uri = context.get('redirect_uri')
if not code or not redirect_uri:
return None
access_token = self.get_token(code, redirect_uri)
user_info = self.get_user_info(access_t... | Sign in with weibo :Example: from client.user.login import WeiboLogin WeiboLogin() .. notes:: | WeiboLogin | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WeiboLogin:
"""Sign in with weibo :Example: from client.user.login import WeiboLogin WeiboLogin() .. notes::"""
def login(self, context):
"""weibo Login :type context: Context :param context: :rtype: dict :return: token and instance of user"""
<|body_0|>
def get_token(se... | stack_v2_sparse_classes_36k_train_010391 | 17,886 | permissive | [
{
"docstring": "weibo Login :type context: Context :param context: :rtype: dict :return: token and instance of user",
"name": "login",
"signature": "def login(self, context)"
},
{
"docstring": "Get weibo access token :type code: str :param code: :type redirect_uri: str :param redirect_uri: :rtyp... | 4 | stack_v2_sparse_classes_30k_train_016664 | Implement the Python class `WeiboLogin` described below.
Class description:
Sign in with weibo :Example: from client.user.login import WeiboLogin WeiboLogin() .. notes::
Method signatures and docstrings:
- def login(self, context): weibo Login :type context: Context :param context: :rtype: dict :return: token and ins... | Implement the Python class `WeiboLogin` described below.
Class description:
Sign in with weibo :Example: from client.user.login import WeiboLogin WeiboLogin() .. notes::
Method signatures and docstrings:
- def login(self, context): weibo Login :type context: Context :param context: :rtype: dict :return: token and ins... | 945c4fd2755f5b0dea11e54eb649eeb37ec93d01 | <|skeleton|>
class WeiboLogin:
"""Sign in with weibo :Example: from client.user.login import WeiboLogin WeiboLogin() .. notes::"""
def login(self, context):
"""weibo Login :type context: Context :param context: :rtype: dict :return: token and instance of user"""
<|body_0|>
def get_token(se... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class WeiboLogin:
"""Sign in with weibo :Example: from client.user.login import WeiboLogin WeiboLogin() .. notes::"""
def login(self, context):
"""weibo Login :type context: Context :param context: :rtype: dict :return: token and instance of user"""
self.log.info('login from Weibo Sina')
... | the_stack_v2_python_sparse | open-hackathon-server/src/hackathon/user/oauth_login.py | kaiyuanshe/open-hackathon | train | 46 |
4c8a321d05ea10be2837e0358786c29c5a538a36 | [
"try:\n response, status = (DistributionCodeService.find_all(), HTTPStatus.OK)\nexcept BusinessException as exception:\n return exception.response()\nreturn (jsonify(response), status)",
"request_json = request.get_json()\nvalid_format, errors = schema_utils.validate(request_json, 'distribution_code')\nif n... | <|body_start_0|>
try:
response, status = (DistributionCodeService.find_all(), HTTPStatus.OK)
except BusinessException as exception:
return exception.response()
return (jsonify(response), status)
<|end_body_0|>
<|body_start_1|>
request_json = request.get_json()
... | Endpoint resource to get and post distribution. | Distributions | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Distributions:
"""Endpoint resource to get and post distribution."""
def get():
"""Return all distributions."""
<|body_0|>
def post():
"""Create a new distribution from the payload."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
try:
... | stack_v2_sparse_classes_36k_train_010392 | 5,455 | permissive | [
{
"docstring": "Return all distributions.",
"name": "get",
"signature": "def get()"
},
{
"docstring": "Create a new distribution from the payload.",
"name": "post",
"signature": "def post()"
}
] | 2 | null | Implement the Python class `Distributions` described below.
Class description:
Endpoint resource to get and post distribution.
Method signatures and docstrings:
- def get(): Return all distributions.
- def post(): Create a new distribution from the payload. | Implement the Python class `Distributions` described below.
Class description:
Endpoint resource to get and post distribution.
Method signatures and docstrings:
- def get(): Return all distributions.
- def post(): Create a new distribution from the payload.
<|skeleton|>
class Distributions:
"""Endpoint resource ... | 0d71d37b0e08d11f6b6d9f59a4b202dfabc98fc1 | <|skeleton|>
class Distributions:
"""Endpoint resource to get and post distribution."""
def get():
"""Return all distributions."""
<|body_0|>
def post():
"""Create a new distribution from the payload."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Distributions:
"""Endpoint resource to get and post distribution."""
def get():
"""Return all distributions."""
try:
response, status = (DistributionCodeService.find_all(), HTTPStatus.OK)
except BusinessException as exception:
return exception.response()
... | the_stack_v2_python_sparse | pay-api/src/pay_api/resources/distributions.py | bcgov/sbc-pay | train | 6 |
c7dcb9f944b98b04eb1d0c37294b000a1c32da57 | [
"for order in self:\n unit = ['', 'Satu', 'Dua', 'Tiga', 'Empat', 'Lima', 'Enam', 'Tujuh', 'Delapan', 'Sembilan', 'Sepuluh', 'Sebelas']\n result = ' '\n total_terbilang = self.total_terbilang\n n = int(amount_total)\n if n >= 0 and n <= 11:\n result = result + unit[n]\n elif n < 20:\n ... | <|body_start_0|>
for order in self:
unit = ['', 'Satu', 'Dua', 'Tiga', 'Empat', 'Lima', 'Enam', 'Tujuh', 'Delapan', 'Sembilan', 'Sepuluh', 'Sebelas']
result = ' '
total_terbilang = self.total_terbilang
n = int(amount_total)
if n >= 0 and n <= 11:
... | inherit sale.order | SaleOrder | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SaleOrder:
"""inherit sale.order"""
def total_terbilang(self, amount_total):
"""function total terbilang"""
<|body_0|>
def write(self, vals):
"""extend function write to add warning if payment term customer is different with sale order"""
<|body_1|>
<|en... | stack_v2_sparse_classes_36k_train_010393 | 5,118 | no_license | [
{
"docstring": "function total terbilang",
"name": "total_terbilang",
"signature": "def total_terbilang(self, amount_total)"
},
{
"docstring": "extend function write to add warning if payment term customer is different with sale order",
"name": "write",
"signature": "def write(self, vals... | 2 | stack_v2_sparse_classes_30k_train_001351 | Implement the Python class `SaleOrder` described below.
Class description:
inherit sale.order
Method signatures and docstrings:
- def total_terbilang(self, amount_total): function total terbilang
- def write(self, vals): extend function write to add warning if payment term customer is different with sale order | Implement the Python class `SaleOrder` described below.
Class description:
inherit sale.order
Method signatures and docstrings:
- def total_terbilang(self, amount_total): function total terbilang
- def write(self, vals): extend function write to add warning if payment term customer is different with sale order
<|ske... | 976928395f3b600275f6ab53445605fe1167c6ba | <|skeleton|>
class SaleOrder:
"""inherit sale.order"""
def total_terbilang(self, amount_total):
"""function total terbilang"""
<|body_0|>
def write(self, vals):
"""extend function write to add warning if payment term customer is different with sale order"""
<|body_1|>
<|en... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SaleOrder:
"""inherit sale.order"""
def total_terbilang(self, amount_total):
"""function total terbilang"""
for order in self:
unit = ['', 'Satu', 'Dua', 'Tiga', 'Empat', 'Lima', 'Enam', 'Tujuh', 'Delapan', 'Sembilan', 'Sepuluh', 'Sebelas']
result = ' '
... | the_stack_v2_python_sparse | pn_sale/models/sale.py | detian08/pennyu | train | 0 |
eee63d2f4aba5b57e557cab0ffb52af98669bc6a | [
"if len(s) != len(t):\n return False\ncache = {}\nresult = [0] * len(s)\ncounter = 0\nfor i in range(len(s)):\n if s[i] not in cache:\n cache[s[i]] = counter\n counter += 1\n result[i] = cache[s[i]]\ncache = {}\ncounter = 0\nfor j in range(len(t)):\n if t[j] not in cache:\n cache[t[... | <|body_start_0|>
if len(s) != len(t):
return False
cache = {}
result = [0] * len(s)
counter = 0
for i in range(len(s)):
if s[i] not in cache:
cache[s[i]] = counter
counter += 1
result[i] = cache[s[i]]
cac... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def isIsomorphic(self, s, t):
""":type s: str :type t: str :rtype: bool"""
<|body_0|>
def isIsomorphic(self, s, t):
""":type s: str :type t: str :rtype: bool"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if len(s) != len(t):
... | stack_v2_sparse_classes_36k_train_010394 | 1,393 | no_license | [
{
"docstring": ":type s: str :type t: str :rtype: bool",
"name": "isIsomorphic",
"signature": "def isIsomorphic(self, s, t)"
},
{
"docstring": ":type s: str :type t: str :rtype: bool",
"name": "isIsomorphic",
"signature": "def isIsomorphic(self, s, t)"
}
] | 2 | stack_v2_sparse_classes_30k_train_007301 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isIsomorphic(self, s, t): :type s: str :type t: str :rtype: bool
- def isIsomorphic(self, s, t): :type s: str :type t: str :rtype: bool | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isIsomorphic(self, s, t): :type s: str :type t: str :rtype: bool
- def isIsomorphic(self, s, t): :type s: str :type t: str :rtype: bool
<|skeleton|>
class Solution:
def... | d75876ae96bcd85c67bbfbf91bbc0f0bc773e97c | <|skeleton|>
class Solution:
def isIsomorphic(self, s, t):
""":type s: str :type t: str :rtype: bool"""
<|body_0|>
def isIsomorphic(self, s, t):
""":type s: str :type t: str :rtype: bool"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def isIsomorphic(self, s, t):
""":type s: str :type t: str :rtype: bool"""
if len(s) != len(t):
return False
cache = {}
result = [0] * len(s)
counter = 0
for i in range(len(s)):
if s[i] not in cache:
cache[s[i]] ... | the_stack_v2_python_sparse | 205. Isomorphic Strings.py | samir-0711/Leetcode-Python | train | 0 | |
e43b33087eb346d2f5693e879f6276d4787e9565 | [
"N = len(nums)\nA = nums\nleft = [0] * (N + 1)\nfor i in range(1, N + 1):\n left[i] = left[i - 1] + A[i - 1]\n\ndef check(val, numsplit):\n i, v, c = (0, 0, 0)\n while i < N + 1:\n c += 1\n j = bisect.bisect_right(left, v + val, i)\n if i == j:\n return False\n i = j\... | <|body_start_0|>
N = len(nums)
A = nums
left = [0] * (N + 1)
for i in range(1, N + 1):
left[i] = left[i - 1] + A[i - 1]
def check(val, numsplit):
i, v, c = (0, 0, 0)
while i < N + 1:
c += 1
j = bisect.bisect_rig... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def splitArray(self, nums, m):
""":type nums: List[int] :type m: int :rtype: int"""
<|body_0|>
def splitArray2(self, nums, m):
""":type nums: List[int] :type m: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
N = len(nums)
... | stack_v2_sparse_classes_36k_train_010395 | 6,363 | permissive | [
{
"docstring": ":type nums: List[int] :type m: int :rtype: int",
"name": "splitArray",
"signature": "def splitArray(self, nums, m)"
},
{
"docstring": ":type nums: List[int] :type m: int :rtype: int",
"name": "splitArray2",
"signature": "def splitArray2(self, nums, m)"
}
] | 2 | stack_v2_sparse_classes_30k_train_012918 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def splitArray(self, nums, m): :type nums: List[int] :type m: int :rtype: int
- def splitArray2(self, nums, m): :type nums: List[int] :type m: int :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def splitArray(self, nums, m): :type nums: List[int] :type m: int :rtype: int
- def splitArray2(self, nums, m): :type nums: List[int] :type m: int :rtype: int
<|skeleton|>
class... | 2830c7e2ada8dfd3dcdda7c06846116d4f944a27 | <|skeleton|>
class Solution:
def splitArray(self, nums, m):
""":type nums: List[int] :type m: int :rtype: int"""
<|body_0|>
def splitArray2(self, nums, m):
""":type nums: List[int] :type m: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def splitArray(self, nums, m):
""":type nums: List[int] :type m: int :rtype: int"""
N = len(nums)
A = nums
left = [0] * (N + 1)
for i in range(1, N + 1):
left[i] = left[i - 1] + A[i - 1]
def check(val, numsplit):
i, v, c = (0, ... | the_stack_v2_python_sparse | leetcode/hard/Split_Array_Largest_Sum.py | shhuan/algorithms | train | 0 | |
9b4d7eefb4fa087cea6fd65d4e67d15cc1000620 | [
"super().__init__(problem, name=name, **kwargs)\nif distance_weight_type not in ['squared', 'uniform']:\n raise ValueError(\"Parameter distance_weight_type must be either 'squared' or 'uniform'.\")\nself._distance_weight_mode = distance_weight_type\nif max_distance < 0.0:\n raise ValueError(\"Parameter max_di... | <|body_start_0|>
super().__init__(problem, name=name, **kwargs)
if distance_weight_type not in ['squared', 'uniform']:
raise ValueError("Parameter distance_weight_type must be either 'squared' or 'uniform'.")
self._distance_weight_mode = distance_weight_type
if max_distance <... | Implementation of the KNN-Averaging algorithm[^quatic21]. [^quatic21]: Klikovits, S., Arcaini, P. (2021). KNN-Averaging for Noisy Multi-objective Optimisation. In: Paiva, A.C.R., Cavalli, A.R., Ventura Martins, P., Pérez-Castillo, R. (eds) Quality of Information and Communications Technology. QUATIC 2021. Communication... | KNNAvg | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class KNNAvg:
"""Implementation of the KNN-Averaging algorithm[^quatic21]. [^quatic21]: Klikovits, S., Arcaini, P. (2021). KNN-Averaging for Noisy Multi-objective Optimisation. In: Paiva, A.C.R., Cavalli, A.R., Ventura Martins, P., Pérez-Castillo, R. (eds) Quality of Information and Communications Tech... | stack_v2_sparse_classes_36k_train_010396 | 4,578 | permissive | [
{
"docstring": "Constructor. Args: problem (`nmoo.wrapped_problem.WrappedProblem`): Noisy problem. For memory optimization reasons, this should be a `nmoo.wrapped_problem.WrappedProblem` as opposed to a pymoo `Problem`. distance_weight_type (str): Either `squared` or `uniform` (the default). max_distance (float... | 2 | stack_v2_sparse_classes_30k_train_001585 | Implement the Python class `KNNAvg` described below.
Class description:
Implementation of the KNN-Averaging algorithm[^quatic21]. [^quatic21]: Klikovits, S., Arcaini, P. (2021). KNN-Averaging for Noisy Multi-objective Optimisation. In: Paiva, A.C.R., Cavalli, A.R., Ventura Martins, P., Pérez-Castillo, R. (eds) Quality... | Implement the Python class `KNNAvg` described below.
Class description:
Implementation of the KNN-Averaging algorithm[^quatic21]. [^quatic21]: Klikovits, S., Arcaini, P. (2021). KNN-Averaging for Noisy Multi-objective Optimisation. In: Paiva, A.C.R., Cavalli, A.R., Ventura Martins, P., Pérez-Castillo, R. (eds) Quality... | bba29af38230040272a90e08571623a3a3a8e96f | <|skeleton|>
class KNNAvg:
"""Implementation of the KNN-Averaging algorithm[^quatic21]. [^quatic21]: Klikovits, S., Arcaini, P. (2021). KNN-Averaging for Noisy Multi-objective Optimisation. In: Paiva, A.C.R., Cavalli, A.R., Ventura Martins, P., Pérez-Castillo, R. (eds) Quality of Information and Communications Tech... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class KNNAvg:
"""Implementation of the KNN-Averaging algorithm[^quatic21]. [^quatic21]: Klikovits, S., Arcaini, P. (2021). KNN-Averaging for Noisy Multi-objective Optimisation. In: Paiva, A.C.R., Cavalli, A.R., Ventura Martins, P., Pérez-Castillo, R. (eds) Quality of Information and Communications Technology. QUATI... | the_stack_v2_python_sparse | nmoo/denoisers/knnavg.py | altaris/noisy-moo | train | 3 |
ad62afe12fac08f8f15d5e451be6d1e5124370b7 | [
"Block.__init__(self, scenario, args)\nif self.language is None:\n raise LoadingException('Language must be defined!')\nself.lexicon = Lexicon()",
"if tnode.gram_verbmod != 'cdn' or re.search('(aby|kdyby)', tnode.formeme):\n return\naconj = tnode.get_deref_attr('wild/conjugated')\nif aconj.afun == 'AuxV':\n... | <|body_start_0|>
Block.__init__(self, scenario, args)
if self.language is None:
raise LoadingException('Language must be defined!')
self.lexicon = Lexicon()
<|end_body_0|>
<|body_start_1|>
if tnode.gram_verbmod != 'cdn' or re.search('(aby|kdyby)', tnode.formeme):
... | Add conditional auxiliary 'by'/'bych'. Arguments: language: the language of the target tree selector: the selector of the target tree | AddAuxVerbConditional | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AddAuxVerbConditional:
"""Add conditional auxiliary 'by'/'bych'. Arguments: language: the language of the target tree selector: the selector of the target tree"""
def __init__(self, scenario, args):
"""Constructor, just checking the argument values"""
<|body_0|>
def proc... | stack_v2_sparse_classes_36k_train_010397 | 1,984 | permissive | [
{
"docstring": "Constructor, just checking the argument values",
"name": "__init__",
"signature": "def __init__(self, scenario, args)"
},
{
"docstring": "Add conditional auxiliary to a node, where appropriate.",
"name": "process_tnode",
"signature": "def process_tnode(self, tnode)"
}
] | 2 | null | Implement the Python class `AddAuxVerbConditional` described below.
Class description:
Add conditional auxiliary 'by'/'bych'. Arguments: language: the language of the target tree selector: the selector of the target tree
Method signatures and docstrings:
- def __init__(self, scenario, args): Constructor, just checkin... | Implement the Python class `AddAuxVerbConditional` described below.
Class description:
Add conditional auxiliary 'by'/'bych'. Arguments: language: the language of the target tree selector: the selector of the target tree
Method signatures and docstrings:
- def __init__(self, scenario, args): Constructor, just checkin... | 73af644ec35c8a1cd0c37cd478c2afc1db717e0b | <|skeleton|>
class AddAuxVerbConditional:
"""Add conditional auxiliary 'by'/'bych'. Arguments: language: the language of the target tree selector: the selector of the target tree"""
def __init__(self, scenario, args):
"""Constructor, just checking the argument values"""
<|body_0|>
def proc... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AddAuxVerbConditional:
"""Add conditional auxiliary 'by'/'bych'. Arguments: language: the language of the target tree selector: the selector of the target tree"""
def __init__(self, scenario, args):
"""Constructor, just checking the argument values"""
Block.__init__(self, scenario, args)
... | the_stack_v2_python_sparse | alex/components/nlg/tectotpl/block/t2a/cs/addauxverbconditional.py | oplatek/alex | train | 0 |
766e00129a6f048fc25fecdfc367691636b504dd | [
"n = len(nums)\nif n < 3:\n return []\nnums = sorted(nums)\nres = []\nfor i in range(n):\n l = i + 1\n h = n - 1\n if i - 1 >= 0 and nums[i] == nums[i - 1]:\n continue\n while l < h:\n cur = nums[l] + nums[h]\n if cur > -nums[i]:\n while h - 1 > l and nums[h] == nums[h... | <|body_start_0|>
n = len(nums)
if n < 3:
return []
nums = sorted(nums)
res = []
for i in range(n):
l = i + 1
h = n - 1
if i - 1 >= 0 and nums[i] == nums[i - 1]:
continue
while l < h:
cur =... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def threeSum(self, nums):
""":type nums: List[int] :rtype: List[List[int]]"""
<|body_0|>
def threeSumClosest(self, nums, target):
""":type nums: List[int] :type target: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
n = le... | stack_v2_sparse_classes_36k_train_010398 | 1,862 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: List[List[int]]",
"name": "threeSum",
"signature": "def threeSum(self, nums)"
},
{
"docstring": ":type nums: List[int] :type target: int :rtype: int",
"name": "threeSumClosest",
"signature": "def threeSumClosest(self, nums, target)"
}
] | 2 | stack_v2_sparse_classes_30k_train_016454 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def threeSum(self, nums): :type nums: List[int] :rtype: List[List[int]]
- def threeSumClosest(self, nums, target): :type nums: List[int] :type target: int :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def threeSum(self, nums): :type nums: List[int] :rtype: List[List[int]]
- def threeSumClosest(self, nums, target): :type nums: List[int] :type target: int :rtype: int
<|skeleton... | 176cc1db3291843fb068f06d0180766dd8c3122c | <|skeleton|>
class Solution:
def threeSum(self, nums):
""":type nums: List[int] :rtype: List[List[int]]"""
<|body_0|>
def threeSumClosest(self, nums, target):
""":type nums: List[int] :type target: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def threeSum(self, nums):
""":type nums: List[int] :rtype: List[List[int]]"""
n = len(nums)
if n < 3:
return []
nums = sorted(nums)
res = []
for i in range(n):
l = i + 1
h = n - 1
if i - 1 >= 0 and nums[i... | the_stack_v2_python_sparse | 2019/array/three_sum_15.py | yehongyu/acode | train | 0 | |
a682f11cdbc20570ac456c882a4631f6fb46f7c3 | [
"from collections import Counter\ncount = Counter(nums)\nfor key, val in count.items():\n if val == 1:\n return key",
"s = set()\nfor num in nums:\n if num in s:\n s.discard(num)\n else:\n s.add(num)\nreturn s.pop()",
"x = nums[0]\nfor num in nums[1:]:\n x ^= num\nreturn x"
] | <|body_start_0|>
from collections import Counter
count = Counter(nums)
for key, val in count.items():
if val == 1:
return key
<|end_body_0|>
<|body_start_1|>
s = set()
for num in nums:
if num in s:
s.discard(num)
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def singleNumber(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def singleNumber(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
def singleNumber(self, nums):
""":type nums: List[int] :rtype: int"""
... | stack_v2_sparse_classes_36k_train_010399 | 1,161 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "singleNumber",
"signature": "def singleNumber(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "singleNumber",
"signature": "def singleNumber(self, nums)"
},
{
"docstring": ":type nums: List[i... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def singleNumber(self, nums): :type nums: List[int] :rtype: int
- def singleNumber(self, nums): :type nums: List[int] :rtype: int
- def singleNumber(self, nums): :type nums: List... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def singleNumber(self, nums): :type nums: List[int] :rtype: int
- def singleNumber(self, nums): :type nums: List[int] :rtype: int
- def singleNumber(self, nums): :type nums: List... | b18786c06417a2781662805a7e0e984ee7fa5240 | <|skeleton|>
class Solution:
def singleNumber(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def singleNumber(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
def singleNumber(self, nums):
""":type nums: List[int] :rtype: int"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def singleNumber(self, nums):
""":type nums: List[int] :rtype: int"""
from collections import Counter
count = Counter(nums)
for key, val in count.items():
if val == 1:
return key
def singleNumber(self, nums):
""":type nums: Lis... | the_stack_v2_python_sparse | data_structures/136. Single Number.py | YuriiPaziuk/leetcode | train | 0 |
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