blob_id stringlengths 40 40 | bodies listlengths 2 6 | bodies_text stringlengths 196 7.73k | class_docstring stringlengths 0 700 | class_name stringlengths 1 86 | detected_licenses listlengths 0 45 | format_version stringclasses 1
value | full_text stringlengths 378 8.64k | id stringlengths 44 44 | length_bytes int64 505 50k | license_type stringclasses 2
values | methods listlengths 2 6 | n_methods int64 2 6 | original_id stringlengths 38 40 ⌀ | prompt stringlengths 153 4.88k | prompted_full_text stringlengths 565 12.5k | revision_id stringlengths 40 40 | skeleton stringlengths 162 5.05k | snapshot_name stringclasses 1
value | snapshot_source_dir stringclasses 1
value | snapshot_total_rows int64 75.8k 75.8k | solution stringlengths 242 8.3k | source stringclasses 1
value | source_path stringlengths 4 177 | source_repo stringlengths 6 110 | split stringclasses 1
value | star_events_count int64 0 209k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
eef931d2963599de3cceb805614f7fc79c9b8a86 | [
"i = 0\nfor j in range(1, len(nums)):\n if nums[j] != nums[j - 1]:\n nums[i + 1] = nums[j]\n i += 1\n j += 1\nreturn i + 1",
"i = 0\nfor num in nums[1:]:\n if nums[i] != num:\n i += 1\n nums[i] = num\nreturn i + 1"
] | <|body_start_0|>
i = 0
for j in range(1, len(nums)):
if nums[j] != nums[j - 1]:
nums[i + 1] = nums[j]
i += 1
j += 1
return i + 1
<|end_body_0|>
<|body_start_1|>
i = 0
for num in nums[1:]:
if nums[i] != num:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def removeDuplicatesV1(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def removeDuplicates(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
i = 0
for j in range(1, l... | stack_v2_sparse_classes_75kplus_train_066200 | 587 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "removeDuplicatesV1",
"signature": "def removeDuplicatesV1(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "removeDuplicates",
"signature": "def removeDuplicates(self, nums)"
}
] | 2 | stack_v2_sparse_classes_30k_train_001731 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def removeDuplicatesV1(self, nums): :type nums: List[int] :rtype: int
- def removeDuplicates(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 removeDuplicatesV1(self, nums): :type nums: List[int] :rtype: int
- def removeDuplicates(self, nums): :type nums: List[int] :rtype: int
<|skeleton|>
class Solution:
def... | 057ed5c6fe19268f36a1d5051d27b07aae0b63e0 | <|skeleton|>
class Solution:
def removeDuplicatesV1(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def removeDuplicates(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def removeDuplicatesV1(self, nums):
""":type nums: List[int] :rtype: int"""
i = 0
for j in range(1, len(nums)):
if nums[j] != nums[j - 1]:
nums[i + 1] = nums[j]
i += 1
j += 1
return i + 1
def removeDuplicate... | the_stack_v2_python_sparse | 2020/2020-01/23/eugene.py | wavetogether/wave_algorithm_challenge | train | 3 | |
687f63423d7be487d2047d7ce4d0d016350369ce | [
"self._logger = logging.getLogger(__name__)\nself.temp_file = str(uuid.uuid4()) + '.tar.gz'\nself.source_gzip = os.path.join(temp_folder, self.temp_file)",
"if not (os.path.exists(source_dir_path) and os.access(source_dir_path, os.R_OK)):\n raise MLOpsException('Path: {} does not exist or not readable'.format(... | <|body_start_0|>
self._logger = logging.getLogger(__name__)
self.temp_file = str(uuid.uuid4()) + '.tar.gz'
self.source_gzip = os.path.join(temp_folder, self.temp_file)
<|end_body_0|>
<|body_start_1|>
if not (os.path.exists(source_dir_path) and os.access(source_dir_path, os.R_OK)):
... | Provides API to pack a folder as tar gz archive. This is an internal class which should not be exposed to users of MLOps. | DirectoryPack | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DirectoryPack:
"""Provides API to pack a folder as tar gz archive. This is an internal class which should not be exposed to users of MLOps."""
def __init__(self, temp_folder='/tmp'):
"""Perform initialization of the DirectoryPack. :param temp_folder: folder to save a tar gz file :ret... | stack_v2_sparse_classes_75kplus_train_066201 | 2,096 | permissive | [
{
"docstring": "Perform initialization of the DirectoryPack. :param temp_folder: folder to save a tar gz file :return:",
"name": "__init__",
"signature": "def __init__(self, temp_folder='/tmp')"
},
{
"docstring": "Packs a folder :param source_dir_path: folder to pack :return: path to created tar... | 3 | stack_v2_sparse_classes_30k_test_000386 | Implement the Python class `DirectoryPack` described below.
Class description:
Provides API to pack a folder as tar gz archive. This is an internal class which should not be exposed to users of MLOps.
Method signatures and docstrings:
- def __init__(self, temp_folder='/tmp'): Perform initialization of the DirectoryPa... | Implement the Python class `DirectoryPack` described below.
Class description:
Provides API to pack a folder as tar gz archive. This is an internal class which should not be exposed to users of MLOps.
Method signatures and docstrings:
- def __init__(self, temp_folder='/tmp'): Perform initialization of the DirectoryPa... | 738356ce6d5e691a5d813acafa3f0ff730e76136 | <|skeleton|>
class DirectoryPack:
"""Provides API to pack a folder as tar gz archive. This is an internal class which should not be exposed to users of MLOps."""
def __init__(self, temp_folder='/tmp'):
"""Perform initialization of the DirectoryPack. :param temp_folder: folder to save a tar gz file :ret... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DirectoryPack:
"""Provides API to pack a folder as tar gz archive. This is an internal class which should not be exposed to users of MLOps."""
def __init__(self, temp_folder='/tmp'):
"""Perform initialization of the DirectoryPack. :param temp_folder: folder to save a tar gz file :return:"""
... | the_stack_v2_python_sparse | mlops/parallelm/mlops/packer.py | theromis/mlpiper | train | 0 |
a161139a64886902e8f007b34a46617d2614aaa5 | [
"self.file_name = file_name\nself.header = None\nself.data = None\nself.model = None\nself._read_file()",
"with open(self.file_name, 'rb') as f:\n new_test = struct.unpack('<l', f.read(8)[4:])[0]\nf.close()\nwith open(self.file_name, 'rb') as f:\n old_test = struct.unpack('<h', f.read(6)[4:])[0]\nf.close()\... | <|body_start_0|>
self.file_name = file_name
self.header = None
self.data = None
self.model = None
self._read_file()
<|end_body_0|>
<|body_start_1|>
with open(self.file_name, 'rb') as f:
new_test = struct.unpack('<l', f.read(8)[4:])[0]
f.close()
... | A class that holds the information from one file output by a D&P Instruments Model 103F MicroFT or Model 202 TurboFT. Attributes: file_name - The data file name. header - A DpHeader instance holding the header information. data - A DpData instance holding the radiometric information. | DpFile | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DpFile:
"""A class that holds the information from one file output by a D&P Instruments Model 103F MicroFT or Model 202 TurboFT. Attributes: file_name - The data file name. header - A DpHeader instance holding the header information. data - A DpData instance holding the radiometric information.""... | stack_v2_sparse_classes_75kplus_train_066202 | 5,404 | no_license | [
{
"docstring": "DpFile instance constructor. Arguments: file_name - The filename for the data file.",
"name": "__init__",
"signature": "def __init__(self, file_name)"
},
{
"docstring": "Read the data file.",
"name": "_read_file",
"signature": "def _read_file(self)"
},
{
"docstrin... | 4 | stack_v2_sparse_classes_30k_train_044215 | Implement the Python class `DpFile` described below.
Class description:
A class that holds the information from one file output by a D&P Instruments Model 103F MicroFT or Model 202 TurboFT. Attributes: file_name - The data file name. header - A DpHeader instance holding the header information. data - A DpData instance... | Implement the Python class `DpFile` described below.
Class description:
A class that holds the information from one file output by a D&P Instruments Model 103F MicroFT or Model 202 TurboFT. Attributes: file_name - The data file name. header - A DpHeader instance holding the header information. data - A DpData instance... | 743167940f700374755ea273b90da66befae1ba4 | <|skeleton|>
class DpFile:
"""A class that holds the information from one file output by a D&P Instruments Model 103F MicroFT or Model 202 TurboFT. Attributes: file_name - The data file name. header - A DpHeader instance holding the header information. data - A DpData instance holding the radiometric information.""... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DpFile:
"""A class that holds the information from one file output by a D&P Instruments Model 103F MicroFT or Model 202 TurboFT. Attributes: file_name - The data file name. header - A DpHeader instance holding the header information. data - A DpData instance holding the radiometric information."""
def __... | the_stack_v2_python_sparse | tes/models/dp_models/dp_file.py | max19951001/TES | train | 0 |
91bc08739a94ee07872811b6f25477d7b6f76648 | [
"if value < 5:\n raise serializers.ValidationError('amount must be at least 5$')\nreturn value",
"amount = data['amount']\nresponse = stripe.Charge.create(amount=amount, currency='usd', source=data['stripeToken'], description='Donation')\ndatabase_amount = amount * 10\nif response.paid:\n return Donation.ob... | <|body_start_0|>
if value < 5:
raise serializers.ValidationError('amount must be at least 5$')
return value
<|end_body_0|>
<|body_start_1|>
amount = data['amount']
response = stripe.Charge.create(amount=amount, currency='usd', source=data['stripeToken'], description='Donatio... | Donation create serializer. | DonationCreateSerializer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DonationCreateSerializer:
"""Donation create serializer."""
def validate_amount(self, value):
"""Ammount validator."""
<|body_0|>
def create(self, data):
"""Handle creation."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if value < 5:
... | stack_v2_sparse_classes_75kplus_train_066203 | 1,445 | no_license | [
{
"docstring": "Ammount validator.",
"name": "validate_amount",
"signature": "def validate_amount(self, value)"
},
{
"docstring": "Handle creation.",
"name": "create",
"signature": "def create(self, data)"
}
] | 2 | stack_v2_sparse_classes_30k_train_053939 | Implement the Python class `DonationCreateSerializer` described below.
Class description:
Donation create serializer.
Method signatures and docstrings:
- def validate_amount(self, value): Ammount validator.
- def create(self, data): Handle creation. | Implement the Python class `DonationCreateSerializer` described below.
Class description:
Donation create serializer.
Method signatures and docstrings:
- def validate_amount(self, value): Ammount validator.
- def create(self, data): Handle creation.
<|skeleton|>
class DonationCreateSerializer:
"""Donation create... | e2f4557e2a85405838c6c9f65f1cb8a5f60a35ba | <|skeleton|>
class DonationCreateSerializer:
"""Donation create serializer."""
def validate_amount(self, value):
"""Ammount validator."""
<|body_0|>
def create(self, data):
"""Handle creation."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DonationCreateSerializer:
"""Donation create serializer."""
def validate_amount(self, value):
"""Ammount validator."""
if value < 5:
raise serializers.ValidationError('amount must be at least 5$')
return value
def create(self, data):
"""Handle creation."""... | the_stack_v2_python_sparse | apps/donations/serializers/donations.py | HebertFerrer/WebMaster-back-end | train | 0 |
2b8151df1079058e084a00ba1af3fbba603dcd48 | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn UsedInsight()",
"from .entity import Entity\nfrom .resource_reference import ResourceReference\nfrom .resource_visualization import ResourceVisualization\nfrom .usage_details import UsageDetails\nfrom .entity import Entity\nfrom .resou... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return UsedInsight()
<|end_body_0|>
<|body_start_1|>
from .entity import Entity
from .resource_reference import ResourceReference
from .resource_visualization import ResourceVisualizati... | UsedInsight | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UsedInsight:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> UsedInsight:
"""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: Us... | stack_v2_sparse_classes_75kplus_train_066204 | 3,435 | 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: UsedInsight",
"name": "create_from_discriminator_value",
"signature": "def create_from_discriminator_value(p... | 3 | null | Implement the Python class `UsedInsight` described below.
Class description:
Implement the UsedInsight class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> UsedInsight: Creates a new instance of the appropriate class based on discriminator value Args:... | Implement the Python class `UsedInsight` described below.
Class description:
Implement the UsedInsight class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> UsedInsight: Creates a new instance of the appropriate class based on discriminator value Args:... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class UsedInsight:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> UsedInsight:
"""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: Us... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class UsedInsight:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> UsedInsight:
"""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: UsedInsight"""
... | the_stack_v2_python_sparse | msgraph/generated/models/used_insight.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
914c8c5a7fd4554c904087a1b77542ed94136e9e | [
"if not correo:\n raise ValueError(_('The Email must be set'))\ncorreo = self.normalize_email(correo)\nuser = self.model(correo=correo, **extra_fields)\nuser.set_password(password)\nuser.save()\nreturn user",
"extra_fields.setdefault('is_staff', True)\nextra_fields.setdefault('is_superuser', True)\nextra_field... | <|body_start_0|>
if not correo:
raise ValueError(_('The Email must be set'))
correo = self.normalize_email(correo)
user = self.model(correo=correo, **extra_fields)
user.set_password(password)
user.save()
return user
<|end_body_0|>
<|body_start_1|>
ext... | Custom user model manager where email is the unique identifiers for authentication instead of usernames. | CustomUserManager | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CustomUserManager:
"""Custom user model manager where email is the unique identifiers for authentication instead of usernames."""
def create_user(self, correo, password, **extra_fields):
"""Create and save a User with the given email and password."""
<|body_0|>
def creat... | stack_v2_sparse_classes_75kplus_train_066205 | 4,069 | no_license | [
{
"docstring": "Create and save a User with the given email and password.",
"name": "create_user",
"signature": "def create_user(self, correo, password, **extra_fields)"
},
{
"docstring": "Create and save a SuperUser with the given email and password.",
"name": "create_superuser",
"signa... | 2 | stack_v2_sparse_classes_30k_train_039257 | Implement the Python class `CustomUserManager` described below.
Class description:
Custom user model manager where email is the unique identifiers for authentication instead of usernames.
Method signatures and docstrings:
- def create_user(self, correo, password, **extra_fields): Create and save a User with the given... | Implement the Python class `CustomUserManager` described below.
Class description:
Custom user model manager where email is the unique identifiers for authentication instead of usernames.
Method signatures and docstrings:
- def create_user(self, correo, password, **extra_fields): Create and save a User with the given... | 8dda723b08355ca5e83a0bdc9b4d920cbde28b5a | <|skeleton|>
class CustomUserManager:
"""Custom user model manager where email is the unique identifiers for authentication instead of usernames."""
def create_user(self, correo, password, **extra_fields):
"""Create and save a User with the given email and password."""
<|body_0|>
def creat... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CustomUserManager:
"""Custom user model manager where email is the unique identifiers for authentication instead of usernames."""
def create_user(self, correo, password, **extra_fields):
"""Create and save a User with the given email and password."""
if not correo:
raise Value... | the_stack_v2_python_sparse | mysite/users/models.py | iPoe/Mascotas-App | train | 0 |
e125e655a8febcb816ca069eaaa3bbd2076ae4e7 | [
"super(Conv1dGenerated, self).__init__()\nself.in_channels = in_channels\nself.out_channels = out_channels\nself.kernel_size = kernel_size\nself.groups = groups\nself.stride = stride\nself.padding = padding\nself.dilation = dilation\nself.bottleneck = nn.Linear(E_1, E_2) if E_1 is not None else nn.Parameter(torch.r... | <|body_start_0|>
super(Conv1dGenerated, self).__init__()
self.in_channels = in_channels
self.out_channels = out_channels
self.kernel_size = kernel_size
self.groups = groups
self.stride = stride
self.padding = padding
self.dilation = dilation
self.b... | 1D convolution with a kernel generated by a linear transformation of the instrument embedding | Conv1dGenerated | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Conv1dGenerated:
"""1D convolution with a kernel generated by a linear transformation of the instrument embedding"""
def __init__(self, E_1, E_2, in_channels, out_channels, kernel_size, stride=1, padding=0, dilation=1, groups=1, bias=False):
"""Arguments: E_1 {int} -- Dimension of th... | stack_v2_sparse_classes_75kplus_train_066206 | 37,269 | no_license | [
{
"docstring": "Arguments: E_1 {int} -- Dimension of the instrument embedding E_2 {int} -- Dimension of the instrument embedding bottleneck in_channels {int} -- Number of channels of the input out_channels {int} -- Number of channels of the output kernel_size {int} -- Kernel size of the convolution Keyword Argu... | 2 | stack_v2_sparse_classes_30k_train_018364 | Implement the Python class `Conv1dGenerated` described below.
Class description:
1D convolution with a kernel generated by a linear transformation of the instrument embedding
Method signatures and docstrings:
- def __init__(self, E_1, E_2, in_channels, out_channels, kernel_size, stride=1, padding=0, dilation=1, group... | Implement the Python class `Conv1dGenerated` described below.
Class description:
1D convolution with a kernel generated by a linear transformation of the instrument embedding
Method signatures and docstrings:
- def __init__(self, E_1, E_2, in_channels, out_channels, kernel_size, stride=1, padding=0, dilation=1, group... | 7e55a422588c1d1e00f35a3d3a3ff896cce59e18 | <|skeleton|>
class Conv1dGenerated:
"""1D convolution with a kernel generated by a linear transformation of the instrument embedding"""
def __init__(self, E_1, E_2, in_channels, out_channels, kernel_size, stride=1, padding=0, dilation=1, groups=1, bias=False):
"""Arguments: E_1 {int} -- Dimension of th... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Conv1dGenerated:
"""1D convolution with a kernel generated by a linear transformation of the instrument embedding"""
def __init__(self, E_1, E_2, in_channels, out_channels, kernel_size, stride=1, padding=0, dilation=1, groups=1, bias=False):
"""Arguments: E_1 {int} -- Dimension of the instrument ... | the_stack_v2_python_sparse | generated/test_pfnet_research_meta_tasnet.py | jansel/pytorch-jit-paritybench | train | 35 |
5bf2f1e93d75a95c089a90df65252a0d1d048a6d | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn EnrollmentTroubleshootingEvent()",
"from .device_enrollment_failure_reason import DeviceEnrollmentFailureReason\nfrom .device_enrollment_type import DeviceEnrollmentType\nfrom .device_management_troubleshooting_event import DeviceManag... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return EnrollmentTroubleshootingEvent()
<|end_body_0|>
<|body_start_1|>
from .device_enrollment_failure_reason import DeviceEnrollmentFailureReason
from .device_enrollment_type import DeviceEnr... | Event representing an enrollment failure. | EnrollmentTroubleshootingEvent | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EnrollmentTroubleshootingEvent:
"""Event representing an enrollment failure."""
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> EnrollmentTroubleshootingEvent:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_nod... | stack_v2_sparse_classes_75kplus_train_066207 | 4,636 | 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: EnrollmentTroubleshootingEvent",
"name": "create_from_discriminator_value",
"signature": "def create_from_di... | 3 | null | Implement the Python class `EnrollmentTroubleshootingEvent` described below.
Class description:
Event representing an enrollment failure.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> EnrollmentTroubleshootingEvent: Creates a new instance of the appro... | Implement the Python class `EnrollmentTroubleshootingEvent` described below.
Class description:
Event representing an enrollment failure.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> EnrollmentTroubleshootingEvent: Creates a new instance of the appro... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class EnrollmentTroubleshootingEvent:
"""Event representing an enrollment failure."""
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> EnrollmentTroubleshootingEvent:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_nod... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class EnrollmentTroubleshootingEvent:
"""Event representing an enrollment failure."""
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> EnrollmentTroubleshootingEvent:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse ... | the_stack_v2_python_sparse | msgraph/generated/models/enrollment_troubleshooting_event.py | microsoftgraph/msgraph-sdk-python | train | 135 |
e2d2d36417b139398b4e78c3e833476598b2ba19 | [
"self.send_response(200)\nself.send_header('Content-type', 'text/html')\nself.end_headers()\nself.wfile.write(bytes('<html><head><title>Android Runner HTTP Server</title></head>', 'utf-8'))\nself.wfile.write(bytes('<body>', 'utf-8'))\nself.wfile.write(bytes('<p>The Android Runner web server is running successfully!... | <|body_start_0|>
self.send_response(200)
self.send_header('Content-type', 'text/html')
self.end_headers()
self.wfile.write(bytes('<html><head><title>Android Runner HTTP Server</title></head>', 'utf-8'))
self.wfile.write(bytes('<body>', 'utf-8'))
self.wfile.write(bytes('<p... | StopRunWebserver | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StopRunWebserver:
def do_GET(self):
"""Handles incoming HTTP GET requests by: - Showing a simple webpage telling that the server is running and ready for accepting requests."""
<|body_0|>
def do_POST(self):
"""Handles incoming HTTP POST requests by: 1. writing the HT... | stack_v2_sparse_classes_75kplus_train_066208 | 2,507 | no_license | [
{
"docstring": "Handles incoming HTTP GET requests by: - Showing a simple webpage telling that the server is running and ready for accepting requests.",
"name": "do_GET",
"signature": "def do_GET(self)"
},
{
"docstring": "Handles incoming HTTP POST requests by: 1. writing the HTTP POST request p... | 2 | stack_v2_sparse_classes_30k_train_023910 | Implement the Python class `StopRunWebserver` described below.
Class description:
Implement the StopRunWebserver class.
Method signatures and docstrings:
- def do_GET(self): Handles incoming HTTP GET requests by: - Showing a simple webpage telling that the server is running and ready for accepting requests.
- def do_... | Implement the Python class `StopRunWebserver` described below.
Class description:
Implement the StopRunWebserver class.
Method signatures and docstrings:
- def do_GET(self): Handles incoming HTTP GET requests by: - Showing a simple webpage telling that the server is running and ready for accepting requests.
- def do_... | f0fe5f815064416ed14aadcad90f89b2674947db | <|skeleton|>
class StopRunWebserver:
def do_GET(self):
"""Handles incoming HTTP GET requests by: - Showing a simple webpage telling that the server is running and ready for accepting requests."""
<|body_0|>
def do_POST(self):
"""Handles incoming HTTP POST requests by: 1. writing the HT... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class StopRunWebserver:
def do_GET(self):
"""Handles incoming HTTP GET requests by: - Showing a simple webpage telling that the server is running and ready for accepting requests."""
self.send_response(200)
self.send_header('Content-type', 'text/html')
self.end_headers()
self... | the_stack_v2_python_sparse | AndroidRunner/StopRunWebserver.py | S2-group/android-runner | train | 29 | |
037c756c1c6721da6b1b95bcd77e54c144604b72 | [
"self.anchor = anchor\nself.sentence = sentence\nself.event_domain = event_domain\nself.event_type = event_type\nself.score = 0\nself._allocate_arrays(max_sentence_length, neighbor_distance)",
"int_type = 'int32'\nnum_labels = len(self.event_domain.event_types)\nself.label = np.zeros(num_labels, dtype=int_type)\n... | <|body_start_0|>
self.anchor = anchor
self.sentence = sentence
self.event_domain = event_domain
self.event_type = event_type
self.score = 0
self._allocate_arrays(max_sentence_length, neighbor_distance)
<|end_body_0|>
<|body_start_1|>
int_type = 'int32'
nu... | EventTriggerExample | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EventTriggerExample:
def __init__(self, anchor, sentence, event_domain, max_sentence_length, neighbor_distance, event_type=None):
"""We are given a token, sentence as context, and event_type (present during training) :type anchor: nlplingo.text.text_span.Anchor :type sentence: nlplingo.t... | stack_v2_sparse_classes_75kplus_train_066209 | 36,438 | permissive | [
{
"docstring": "We are given a token, sentence as context, and event_type (present during training) :type anchor: nlplingo.text.text_span.Anchor :type sentence: nlplingo.text.text_span.Sentence :type event_domain: nlplingo.event.event_domain.EventDomain :type params: dict :type event_type: str",
"name": "__... | 2 | stack_v2_sparse_classes_30k_train_019623 | Implement the Python class `EventTriggerExample` described below.
Class description:
Implement the EventTriggerExample class.
Method signatures and docstrings:
- def __init__(self, anchor, sentence, event_domain, max_sentence_length, neighbor_distance, event_type=None): We are given a token, sentence as context, and ... | Implement the Python class `EventTriggerExample` described below.
Class description:
Implement the EventTriggerExample class.
Method signatures and docstrings:
- def __init__(self, anchor, sentence, event_domain, max_sentence_length, neighbor_distance, event_type=None): We are given a token, sentence as context, and ... | 32ff17b1320937faa3d3ebe727032f4b3e7a353d | <|skeleton|>
class EventTriggerExample:
def __init__(self, anchor, sentence, event_domain, max_sentence_length, neighbor_distance, event_type=None):
"""We are given a token, sentence as context, and event_type (present during training) :type anchor: nlplingo.text.text_span.Anchor :type sentence: nlplingo.t... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class EventTriggerExample:
def __init__(self, anchor, sentence, event_domain, max_sentence_length, neighbor_distance, event_type=None):
"""We are given a token, sentence as context, and event_type (present during training) :type anchor: nlplingo.text.text_span.Anchor :type sentence: nlplingo.text.text_span.... | the_stack_v2_python_sparse | nlplingo/sandbox/misc/event_trigger.py | BBN-E/nlplingo | train | 3 | |
b3218b1f63512719bf13a8f67966abd43290d8ef | [
"if model._meta.app_label in UltraTech_APP:\n return self.using\nreturn None",
"if model._meta.app_label in UltraTech_APP:\n return self.using\nreturn None",
"if obj1._meta.app_label in UltraTech_APP or obj2._meta.app_label in UltraTech_APP:\n return True\nreturn None",
"if app_label in UltraTech_APP... | <|body_start_0|>
if model._meta.app_label in UltraTech_APP:
return self.using
return None
<|end_body_0|>
<|body_start_1|>
if model._meta.app_label in UltraTech_APP:
return self.using
return None
<|end_body_1|>
<|body_start_2|>
if obj1._meta.app_label in ... | A router to control all database operations on models in the auth application. | UltraTechRouter | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UltraTechRouter:
"""A router to control all database operations on models in the auth application."""
def db_for_read(self, model, **hints):
"""Attempts to read auth models go to auth_db."""
<|body_0|>
def db_for_write(self, model, **hints):
"""Attempts to write ... | stack_v2_sparse_classes_75kplus_train_066210 | 3,768 | no_license | [
{
"docstring": "Attempts to read auth models go to auth_db.",
"name": "db_for_read",
"signature": "def db_for_read(self, model, **hints)"
},
{
"docstring": "Attempts to write auth models go to auth_db.",
"name": "db_for_write",
"signature": "def db_for_write(self, model, **hints)"
},
... | 4 | stack_v2_sparse_classes_30k_train_054590 | Implement the Python class `UltraTechRouter` described below.
Class description:
A router to control all database operations on models in the auth application.
Method signatures and docstrings:
- def db_for_read(self, model, **hints): Attempts to read auth models go to auth_db.
- def db_for_write(self, model, **hints... | Implement the Python class `UltraTechRouter` described below.
Class description:
A router to control all database operations on models in the auth application.
Method signatures and docstrings:
- def db_for_read(self, model, **hints): Attempts to read auth models go to auth_db.
- def db_for_write(self, model, **hints... | 23d31fbeddcd303a7dc90ac9cfbe2c762d61c61e | <|skeleton|>
class UltraTechRouter:
"""A router to control all database operations on models in the auth application."""
def db_for_read(self, model, **hints):
"""Attempts to read auth models go to auth_db."""
<|body_0|>
def db_for_write(self, model, **hints):
"""Attempts to write ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class UltraTechRouter:
"""A router to control all database operations on models in the auth application."""
def db_for_read(self, model, **hints):
"""Attempts to read auth models go to auth_db."""
if model._meta.app_label in UltraTech_APP:
return self.using
return None
... | the_stack_v2_python_sparse | ultratech_fare/settings/routers.py | KONASANI-0143/Dev | train | 0 |
6347ab4ef1ac777104444b8ba2eb96f9ef280896 | [
"token = request.cookies.get('token')\nif token:\n try:\n uuid = jwt.decode(token, app.config['SECRET_KEY'], algorithms=['HS256'])['user_id']\n user = User.query.filter_by(uuid=uuid).first()\n except:\n return make_response(render_template('login.html'), 419)\n flash('You already autho... | <|body_start_0|>
token = request.cookies.get('token')
if token:
try:
uuid = jwt.decode(token, app.config['SECRET_KEY'], algorithms=['HS256'])['user_id']
user = User.query.filter_by(uuid=uuid).first()
except:
return make_response(ren... | Login resource Сontains login form Authentication is not required and shouldn't be done | Login | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Login:
"""Login resource Сontains login form Authentication is not required and shouldn't be done"""
def get(self):
"""Get method Return "login.html" In case of exception can return main page"""
<|body_0|>
def post(self):
"""Post method Return redirect to "main.h... | stack_v2_sparse_classes_75kplus_train_066211 | 2,820 | no_license | [
{
"docstring": "Get method Return \"login.html\" In case of exception can return main page",
"name": "get",
"signature": "def get(self)"
},
{
"docstring": "Post method Return redirect to \"main.html\" if session joining was successful In case of exception can return login page",
"name": "pos... | 2 | stack_v2_sparse_classes_30k_train_001635 | Implement the Python class `Login` described below.
Class description:
Login resource Сontains login form Authentication is not required and shouldn't be done
Method signatures and docstrings:
- def get(self): Get method Return "login.html" In case of exception can return main page
- def post(self): Post method Retur... | Implement the Python class `Login` described below.
Class description:
Login resource Сontains login form Authentication is not required and shouldn't be done
Method signatures and docstrings:
- def get(self): Get method Return "login.html" In case of exception can return main page
- def post(self): Post method Retur... | a09780621357957e5575aba36391bef161b5137d | <|skeleton|>
class Login:
"""Login resource Сontains login form Authentication is not required and shouldn't be done"""
def get(self):
"""Get method Return "login.html" In case of exception can return main page"""
<|body_0|>
def post(self):
"""Post method Return redirect to "main.h... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Login:
"""Login resource Сontains login form Authentication is not required and shouldn't be done"""
def get(self):
"""Get method Return "login.html" In case of exception can return main page"""
token = request.cookies.get('token')
if token:
try:
uuid =... | the_stack_v2_python_sparse | src/resources/login.py | meg4ik/epam_final_project | train | 0 |
8123c2990e6fbfbfc81c9ece296c412ace1c595e | [
"mensajes = getMensajes()\nserialize = self.serializer_class(mensajes, many=True)\nreturn Response(serialize.data, status=status.HTTP_200_OK)",
"serializer = self.serializer_class(data=request.data)\nif serializer.is_valid():\n try:\n createMensaje(request.data)\n return Response(serializer.data,... | <|body_start_0|>
mensajes = getMensajes()
serialize = self.serializer_class(mensajes, many=True)
return Response(serialize.data, status=status.HTTP_200_OK)
<|end_body_0|>
<|body_start_1|>
serializer = self.serializer_class(data=request.data)
if serializer.is_valid():
... | Clase que cocntiene el metodo GET y POST de mensaje Args: APIView Herencia | mensageListView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class mensageListView:
"""Clase que cocntiene el metodo GET y POST de mensaje Args: APIView Herencia"""
def get(self, request, format=None):
"""Metodo GET que retorna la lista de mensajes Args: request ([type]): [description] format ([type], optional): [description]. Defaults to None. Retu... | stack_v2_sparse_classes_75kplus_train_066212 | 8,545 | no_license | [
{
"docstring": "Metodo GET que retorna la lista de mensajes Args: request ([type]): [description] format ([type], optional): [description]. Defaults to None. Returns: HTTP200",
"name": "get",
"signature": "def get(self, request, format=None)"
},
{
"docstring": "Metodo POST que crear un mensaje A... | 2 | null | Implement the Python class `mensageListView` described below.
Class description:
Clase que cocntiene el metodo GET y POST de mensaje Args: APIView Herencia
Method signatures and docstrings:
- def get(self, request, format=None): Metodo GET que retorna la lista de mensajes Args: request ([type]): [description] format ... | Implement the Python class `mensageListView` described below.
Class description:
Clase que cocntiene el metodo GET y POST de mensaje Args: APIView Herencia
Method signatures and docstrings:
- def get(self, request, format=None): Metodo GET que retorna la lista de mensajes Args: request ([type]): [description] format ... | 5edfc0fb9316c899dbd5cd5607989300c75ab4e8 | <|skeleton|>
class mensageListView:
"""Clase que cocntiene el metodo GET y POST de mensaje Args: APIView Herencia"""
def get(self, request, format=None):
"""Metodo GET que retorna la lista de mensajes Args: request ([type]): [description] format ([type], optional): [description]. Defaults to None. Retu... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class mensageListView:
"""Clase que cocntiene el metodo GET y POST de mensaje Args: APIView Herencia"""
def get(self, request, format=None):
"""Metodo GET que retorna la lista de mensajes Args: request ([type]): [description] format ([type], optional): [description]. Defaults to None. Returns: HTTP200"... | the_stack_v2_python_sparse | chat_API/views.py | MartinGalvanCastro/ApoyaFem-API | train | 0 |
a09b03ac37f60e776f3b081d59400252b8f20fc4 | [
"novo_no = No(dado, None, None)\nif self.cabeca is None:\n self.cabeca = novo_no\n self.rabo = novo_no\nelse:\n novo_no.anterior = self.rabo\n novo_no.proximo = None\n self.rabo.proximo = novo_no\n self.rabo = novo_no",
"no_atual = self.cabeca\nwhile no_atual is not None:\n if no_atual.dado =... | <|body_start_0|>
novo_no = No(dado, None, None)
if self.cabeca is None:
self.cabeca = novo_no
self.rabo = novo_no
else:
novo_no.anterior = self.rabo
novo_no.proximo = None
self.rabo.proximo = novo_no
self.rabo = novo_no
<|en... | ListaDuplamenteEncadeada | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ListaDuplamenteEncadeada:
def acrescentar(self, dado):
"""Acrescenta um novo no a lista."""
<|body_0|>
def remover(self, dado):
"""Remove um no da lista."""
<|body_1|>
def mostrar(self):
"""Mostra todos os dados da lista."""
<|body_2|>
<... | stack_v2_sparse_classes_75kplus_train_066213 | 3,743 | permissive | [
{
"docstring": "Acrescenta um novo no a lista.",
"name": "acrescentar",
"signature": "def acrescentar(self, dado)"
},
{
"docstring": "Remove um no da lista.",
"name": "remover",
"signature": "def remover(self, dado)"
},
{
"docstring": "Mostra todos os dados da lista.",
"name"... | 3 | stack_v2_sparse_classes_30k_train_032118 | Implement the Python class `ListaDuplamenteEncadeada` described below.
Class description:
Implement the ListaDuplamenteEncadeada class.
Method signatures and docstrings:
- def acrescentar(self, dado): Acrescenta um novo no a lista.
- def remover(self, dado): Remove um no da lista.
- def mostrar(self): Mostra todos os... | Implement the Python class `ListaDuplamenteEncadeada` described below.
Class description:
Implement the ListaDuplamenteEncadeada class.
Method signatures and docstrings:
- def acrescentar(self, dado): Acrescenta um novo no a lista.
- def remover(self, dado): Remove um no da lista.
- def mostrar(self): Mostra todos os... | 8e656f846f2de4783aa59dbed8ff57b9b4b48c09 | <|skeleton|>
class ListaDuplamenteEncadeada:
def acrescentar(self, dado):
"""Acrescenta um novo no a lista."""
<|body_0|>
def remover(self, dado):
"""Remove um no da lista."""
<|body_1|>
def mostrar(self):
"""Mostra todos os dados da lista."""
<|body_2|>
<... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ListaDuplamenteEncadeada:
def acrescentar(self, dado):
"""Acrescenta um novo no a lista."""
novo_no = No(dado, None, None)
if self.cabeca is None:
self.cabeca = novo_no
self.rabo = novo_no
else:
novo_no.anterior = self.rabo
novo_n... | the_stack_v2_python_sparse | UNP/ref/Python/TADs e Classes/TAD_Listas_Duplamente_Encadeadas.py | ed1rac/AulasEstruturasDados | train | 8 | |
b87f95828974a114651d6da3830cd65aca75cf03 | [
"iris_prefix_found = re.search('^iris', self.metric_name, re.IGNORECASE)\nself.metric_name = self.metric_name if iris_prefix_found else 'iris_{}'.format(self.metric_name)\nself.help_str = '# HELP {} {}'.format(self.metric_name, self.help_str)\nself.type_str = '# TYPE {} {}'.format(self.metric_name, self.type_str)",... | <|body_start_0|>
iris_prefix_found = re.search('^iris', self.metric_name, re.IGNORECASE)
self.metric_name = self.metric_name if iris_prefix_found else 'iris_{}'.format(self.metric_name)
self.help_str = '# HELP {} {}'.format(self.metric_name, self.help_str)
self.type_str = '# TYPE {} {}'.... | The PromStrBuilder is a class that helps transform a MetricResult into a string in .prom file format :param metric_name: the name of the Metric we want to build a prom string from :param metric_result: the MetricResult of the executed metric we want to build a prom string from :param help_str: the help string that desc... | PromStrBuilder | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PromStrBuilder:
"""The PromStrBuilder is a class that helps transform a MetricResult into a string in .prom file format :param metric_name: the name of the Metric we want to build a prom string from :param metric_result: the MetricResult of the executed metric we want to build a prom string from ... | stack_v2_sparse_classes_75kplus_train_066214 | 5,963 | no_license | [
{
"docstring": "Add the iris_ prefix to the metric if it is not in the metric name. Create the help_str and type_str :return: None",
"name": "__post_init__",
"signature": "def __post_init__(self) -> None"
},
{
"docstring": "Create the prom string from the metric we executed :return: the metric r... | 3 | stack_v2_sparse_classes_30k_train_010353 | Implement the Python class `PromStrBuilder` described below.
Class description:
The PromStrBuilder is a class that helps transform a MetricResult into a string in .prom file format :param metric_name: the name of the Metric we want to build a prom string from :param metric_result: the MetricResult of the executed metr... | Implement the Python class `PromStrBuilder` described below.
Class description:
The PromStrBuilder is a class that helps transform a MetricResult into a string in .prom file format :param metric_name: the name of the Metric we want to build a prom string from :param metric_result: the MetricResult of the executed metr... | e66651af2c4e106d8c05999ac1137a4b9a58f29f | <|skeleton|>
class PromStrBuilder:
"""The PromStrBuilder is a class that helps transform a MetricResult into a string in .prom file format :param metric_name: the name of the Metric we want to build a prom string from :param metric_result: the MetricResult of the executed metric we want to build a prom string from ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PromStrBuilder:
"""The PromStrBuilder is a class that helps transform a MetricResult into a string in .prom file format :param metric_name: the name of the Metric we want to build a prom string from :param metric_result: the MetricResult of the executed metric we want to build a prom string from :param help_s... | the_stack_v2_python_sparse | iris/utils/prom_helpers.py | dzhang30/Iris | train | 0 |
f795b2c6e314b2c133ad56870cb312102f7fd1ae | [
"MCMC_Sampler.__init__(self, x, lp_f, thin)\nself.max_width = max_width\nself.width = None",
"logger.debug('Generating %s MCMC samples', n_samples)\nassert n_samples >= 0, 'number of samples cant be negative'\norder = list(range(self.n_dims))\nL_trace = []\nsamples = np.empty([n_samples, self.n_dims])\nif self.wi... | <|body_start_0|>
MCMC_Sampler.__init__(self, x, lp_f, thin)
self.max_width = max_width
self.width = None
<|end_body_0|>
<|body_start_1|>
logger.debug('Generating %s MCMC samples', n_samples)
assert n_samples >= 0, 'number of samples cant be negative'
order = list(range(s... | Slice sampling for multivariate continuous probability distributions. It cycles sampling from each conditional using univariate slice sampling. | SliceSampler | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SliceSampler:
"""Slice sampling for multivariate continuous probability distributions. It cycles sampling from each conditional using univariate slice sampling."""
def __init__(self, x, lp_f, max_width=float('inf'), thin=None):
""":param x: initial state :param lp_f: function that re... | stack_v2_sparse_classes_75kplus_train_066215 | 7,887 | permissive | [
{
"docstring": ":param x: initial state :param lp_f: function that returns the log prob :param max_width: maximum bracket width :param thin: amount of thinning; if None, no thinning",
"name": "__init__",
"signature": "def __init__(self, x, lp_f, max_width=float('inf'), thin=None)"
},
{
"docstrin... | 4 | stack_v2_sparse_classes_30k_train_018517 | Implement the Python class `SliceSampler` described below.
Class description:
Slice sampling for multivariate continuous probability distributions. It cycles sampling from each conditional using univariate slice sampling.
Method signatures and docstrings:
- def __init__(self, x, lp_f, max_width=float('inf'), thin=Non... | Implement the Python class `SliceSampler` described below.
Class description:
Slice sampling for multivariate continuous probability distributions. It cycles sampling from each conditional using univariate slice sampling.
Method signatures and docstrings:
- def __init__(self, x, lp_f, max_width=float('inf'), thin=Non... | b201b3837b7ce92588e89292c86ca9e988e31c10 | <|skeleton|>
class SliceSampler:
"""Slice sampling for multivariate continuous probability distributions. It cycles sampling from each conditional using univariate slice sampling."""
def __init__(self, x, lp_f, max_width=float('inf'), thin=None):
""":param x: initial state :param lp_f: function that re... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SliceSampler:
"""Slice sampling for multivariate continuous probability distributions. It cycles sampling from each conditional using univariate slice sampling."""
def __init__(self, x, lp_f, max_width=float('inf'), thin=None):
""":param x: initial state :param lp_f: function that returns the log... | the_stack_v2_python_sparse | experiments/evaluation/mcmc.py | johannbrehmer/manifold-flow | train | 233 |
446f93db141f6f425732417fb84e211bbd69465d | [
"super().__init__()\nself.mha1 = MultiHeadAttention(dm, h)\nself.mha2 = MultiHeadAttention(dm, h)\nself.ffn = point_wise_feed_forward_network(dm, hidden)\nself.layernorm1 = tf.keras.layers.LayerNormalization(epsilon=1e-06)\nself.layernorm2 = tf.keras.layers.LayerNormalization(epsilon=1e-06)\nself.layernorm3 = tf.ke... | <|body_start_0|>
super().__init__()
self.mha1 = MultiHeadAttention(dm, h)
self.mha2 = MultiHeadAttention(dm, h)
self.ffn = point_wise_feed_forward_network(dm, hidden)
self.layernorm1 = tf.keras.layers.LayerNormalization(epsilon=1e-06)
self.layernorm2 = tf.keras.layers.Lay... | class DecoderBlock | DecoderBlock | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DecoderBlock:
"""class DecoderBlock"""
def __init__(self, dm, h, hidden, drop_rate=0.1):
"""* dm - the dimensionality of the model * h - the number of heads * hidden - the number of hidden units in the fully connected layer * drop_rate - the dropout rate Sets the following public ins... | stack_v2_sparse_classes_75kplus_train_066216 | 18,002 | no_license | [
{
"docstring": "* dm - the dimensionality of the model * h - the number of heads * hidden - the number of hidden units in the fully connected layer * drop_rate - the dropout rate Sets the following public instance attributes: * mha1 - the first MultiHeadAttention layer * mha2 - the second MultiHeadAttention lay... | 2 | stack_v2_sparse_classes_30k_train_047873 | Implement the Python class `DecoderBlock` described below.
Class description:
class DecoderBlock
Method signatures and docstrings:
- def __init__(self, dm, h, hidden, drop_rate=0.1): * dm - the dimensionality of the model * h - the number of heads * hidden - the number of hidden units in the fully connected layer * d... | Implement the Python class `DecoderBlock` described below.
Class description:
class DecoderBlock
Method signatures and docstrings:
- def __init__(self, dm, h, hidden, drop_rate=0.1): * dm - the dimensionality of the model * h - the number of heads * hidden - the number of hidden units in the fully connected layer * d... | 8ad4c2594ff78b345dbd92e9d54d2a143ac4071a | <|skeleton|>
class DecoderBlock:
"""class DecoderBlock"""
def __init__(self, dm, h, hidden, drop_rate=0.1):
"""* dm - the dimensionality of the model * h - the number of heads * hidden - the number of hidden units in the fully connected layer * drop_rate - the dropout rate Sets the following public ins... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DecoderBlock:
"""class DecoderBlock"""
def __init__(self, dm, h, hidden, drop_rate=0.1):
"""* dm - the dimensionality of the model * h - the number of heads * hidden - the number of hidden units in the fully connected layer * drop_rate - the dropout rate Sets the following public instance attribu... | the_stack_v2_python_sparse | supervised_learning/0x12-transformer_apps/5-transformer.py | jorgezafra94/holbertonschool-machine_learning | train | 1 |
2d9fe3a28440caaa4483df7b8fa14d4b2cc5699f | [
"vals = []\n\ndef ser(node):\n if node is None:\n vals.append('#')\n return\n vals.append(str(node.val))\n ser(node.left)\n ser(node.right)\nser(root)\nreturn ' '.join(vals)",
"vals = data.split().__iter__()\n\ndef de(iterv):\n v = next(iterv)\n if v == '#':\n return None\n ... | <|body_start_0|>
vals = []
def ser(node):
if node is None:
vals.append('#')
return
vals.append(str(node.val))
ser(node.left)
ser(node.right)
ser(root)
return ' '.join(vals)
<|end_body_0|>
<|body_start_1|>
... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|>
<|body_... | stack_v2_sparse_classes_75kplus_train_066217 | 1,076 | 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_019252 | 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:... | 80e44f4e9d3a5b592fdebe0bf16d1df54e99991e | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
vals = []
def ser(node):
if node is None:
vals.append('#')
return
vals.append(str(node.val))
ser(node.left)
... | the_stack_v2_python_sparse | Python/297 - Serialize and Deserialize Binary Tree/297_serialize-and-deserialize-binary-tree.py | aptend/leetcode-rua | train | 2 | |
468baf1e64e993c75261dca4da26a130cda50195 | [
"a = nums[0]\nwhile a != nums[a]:\n temp = nums[a]\n nums[a] = a\n a = temp\nreturn a",
"ans = 1\nl, r = (1, len(nums) - 1)\nwhile l <= r:\n m = (l + r) // 2\n n_smaller = sum((1 for n in nums if n < m))\n if n_smaller >= m:\n r = m - 1\n else:\n ans = m\n l = m + 1\nretu... | <|body_start_0|>
a = nums[0]
while a != nums[a]:
temp = nums[a]
nums[a] = a
a = temp
return a
<|end_body_0|>
<|body_start_1|>
ans = 1
l, r = (1, len(nums) - 1)
while l <= r:
m = (l + r) // 2
n_smaller = sum((1 f... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findDuplicate(self, nums: List[int]) -> int:
"""In-place O(N) / O(1)"""
<|body_0|>
def findDuplicate(self, nums: List[int]) -> int:
"""특정 숫자 m보다 작은 원소의 갯수가 m개 이상이면 그보다 작은 숫자에 겹치는 숫자가 있다는 뜻. (m-1개 이하이면 그와 같거나 큰 숫자에 정답이 있다) Binary Search로 해결. 미친 솔루션. 이렇게 ... | stack_v2_sparse_classes_75kplus_train_066218 | 1,969 | no_license | [
{
"docstring": "In-place O(N) / O(1)",
"name": "findDuplicate",
"signature": "def findDuplicate(self, nums: List[int]) -> int"
},
{
"docstring": "특정 숫자 m보다 작은 원소의 갯수가 m개 이상이면 그보다 작은 숫자에 겹치는 숫자가 있다는 뜻. (m-1개 이하이면 그와 같거나 큰 숫자에 정답이 있다) Binary Search로 해결. 미친 솔루션. 이렇게 정답 자체를 가정하고, 범위를 줄여가면서 푸는 테크닉을 알... | 3 | stack_v2_sparse_classes_30k_train_003956 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findDuplicate(self, nums: List[int]) -> int: In-place O(N) / O(1)
- def findDuplicate(self, nums: List[int]) -> int: 특정 숫자 m보다 작은 원소의 갯수가 m개 이상이면 그보다 작은 숫자에 겹치는 숫자가 있다는 뜻. (m... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findDuplicate(self, nums: List[int]) -> int: In-place O(N) / O(1)
- def findDuplicate(self, nums: List[int]) -> int: 특정 숫자 m보다 작은 원소의 갯수가 m개 이상이면 그보다 작은 숫자에 겹치는 숫자가 있다는 뜻. (m... | c26aef2a59e5cc2d9b0658b9c7386a43267ff8a1 | <|skeleton|>
class Solution:
def findDuplicate(self, nums: List[int]) -> int:
"""In-place O(N) / O(1)"""
<|body_0|>
def findDuplicate(self, nums: List[int]) -> int:
"""특정 숫자 m보다 작은 원소의 갯수가 m개 이상이면 그보다 작은 숫자에 겹치는 숫자가 있다는 뜻. (m-1개 이하이면 그와 같거나 큰 숫자에 정답이 있다) Binary Search로 해결. 미친 솔루션. 이렇게 ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def findDuplicate(self, nums: List[int]) -> int:
"""In-place O(N) / O(1)"""
a = nums[0]
while a != nums[a]:
temp = nums[a]
nums[a] = a
a = temp
return a
def findDuplicate(self, nums: List[int]) -> int:
"""특정 숫자 m보다 작은 원... | the_stack_v2_python_sparse | Leetcode/287.py | hanwgyu/algorithm_problem_solving | train | 5 | |
c3f0fe9a653b0155515eb8cee94077a084f3347d | [
"if id is not None:\n self.id = id\nelse:\n Base.__nb_objects = Base.__nb_objects + 1\n self.id = Base.__nb_objects",
"if list_dictionaries is None:\n return '[]'\nelse:\n return json.dumps(list_dictionaries)",
"new_list = []\nfilename = '{}.json'.format(cls.__name__)\nif list_objs is None:\n ... | <|body_start_0|>
if id is not None:
self.id = id
else:
Base.__nb_objects = Base.__nb_objects + 1
self.id = Base.__nb_objects
<|end_body_0|>
<|body_start_1|>
if list_dictionaries is None:
return '[]'
else:
return json.dumps(list... | Class: Base | Base | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Base:
"""Class: Base"""
def __init__(self, id=None):
"""Initialization method"""
<|body_0|>
def to_json_string(list_dictionaries):
"""returns JSON string repr. of object"""
<|body_1|>
def save_to_file(cls, list_objs):
"""writes JSON string re... | stack_v2_sparse_classes_75kplus_train_066219 | 2,236 | no_license | [
{
"docstring": "Initialization method",
"name": "__init__",
"signature": "def __init__(self, id=None)"
},
{
"docstring": "returns JSON string repr. of object",
"name": "to_json_string",
"signature": "def to_json_string(list_dictionaries)"
},
{
"docstring": "writes JSON string rep... | 6 | null | Implement the Python class `Base` described below.
Class description:
Class: Base
Method signatures and docstrings:
- def __init__(self, id=None): Initialization method
- def to_json_string(list_dictionaries): returns JSON string repr. of object
- def save_to_file(cls, list_objs): writes JSON string repr. of object
-... | Implement the Python class `Base` described below.
Class description:
Class: Base
Method signatures and docstrings:
- def __init__(self, id=None): Initialization method
- def to_json_string(list_dictionaries): returns JSON string repr. of object
- def save_to_file(cls, list_objs): writes JSON string repr. of object
-... | db6d8994e5cd8ec6a0a62af72d28b23ef755d5b0 | <|skeleton|>
class Base:
"""Class: Base"""
def __init__(self, id=None):
"""Initialization method"""
<|body_0|>
def to_json_string(list_dictionaries):
"""returns JSON string repr. of object"""
<|body_1|>
def save_to_file(cls, list_objs):
"""writes JSON string re... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Base:
"""Class: Base"""
def __init__(self, id=None):
"""Initialization method"""
if id is not None:
self.id = id
else:
Base.__nb_objects = Base.__nb_objects + 1
self.id = Base.__nb_objects
def to_json_string(list_dictionaries):
"""r... | the_stack_v2_python_sparse | 0x0C-python-almost_a_circle/models/base.py | jerelhenderson/holbertonschool-higher_level_programming | train | 0 |
f82913e2b5b06dd4434667300fc86b4e96daa857 | [
"duplicated_nums = []\nfor i in range(len(nums)):\n num = nums[abs(nums[i]) - 1]\n if num < 0:\n duplicated_nums.append(abs(nums[i]))\n else:\n nums[abs(nums[i]) - 1] = -num\nreturn duplicated_nums",
"num_dict = {}\nfor num in nums:\n num_dict[num] = num_dict.get(num, 0) + 1\nreturn [num... | <|body_start_0|>
duplicated_nums = []
for i in range(len(nums)):
num = nums[abs(nums[i]) - 1]
if num < 0:
duplicated_nums.append(abs(nums[i]))
else:
nums[abs(nums[i]) - 1] = -num
return duplicated_nums
<|end_body_0|>
<|body_sta... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findDuplicates(self, nums):
""":type nums: List[int] :rtype: List[int]"""
<|body_0|>
def hashTable(self, nums):
"""Hash table method, easy. time O(n) but space O(n)"""
<|body_1|>
def SortandSearch(self, nums):
"""This use bubble sor... | stack_v2_sparse_classes_75kplus_train_066220 | 2,318 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: List[int]",
"name": "findDuplicates",
"signature": "def findDuplicates(self, nums)"
},
{
"docstring": "Hash table method, easy. time O(n) but space O(n)",
"name": "hashTable",
"signature": "def hashTable(self, nums)"
},
{
"docstring":... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findDuplicates(self, nums): :type nums: List[int] :rtype: List[int]
- def hashTable(self, nums): Hash table method, easy. time O(n) but space O(n)
- def SortandSearch(self, n... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findDuplicates(self, nums): :type nums: List[int] :rtype: List[int]
- def hashTable(self, nums): Hash table method, easy. time O(n) but space O(n)
- def SortandSearch(self, n... | 54d777e11b91c5debe49c1aef723234c66a5d2cc | <|skeleton|>
class Solution:
def findDuplicates(self, nums):
""":type nums: List[int] :rtype: List[int]"""
<|body_0|>
def hashTable(self, nums):
"""Hash table method, easy. time O(n) but space O(n)"""
<|body_1|>
def SortandSearch(self, nums):
"""This use bubble sor... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def findDuplicates(self, nums):
""":type nums: List[int] :rtype: List[int]"""
duplicated_nums = []
for i in range(len(nums)):
num = nums[abs(nums[i]) - 1]
if num < 0:
duplicated_nums.append(abs(nums[i]))
else:
... | the_stack_v2_python_sparse | leetcode_solution/array/#442.Find_All_Duplicates_in_an_Array.py | HsiangHung/Code-Challenges | train | 0 | |
892cbc07a1524f47caaf9eddeb1e1485bb79c915 | [
"data = form.cleaned_data\nself.success_url = reverse('tokens', kwargs={'level': int(data['level']), 'semester': int(data['semester']), 'course': int(data['course'].id)})\nreturn super().form_valid(form)",
"context = super().get_context_data(**kwargs)\ncontext['title_text'] = 'Choose Course To View The Tokens'\nc... | <|body_start_0|>
data = form.cleaned_data
self.success_url = reverse('tokens', kwargs={'level': int(data['level']), 'semester': int(data['semester']), 'course': int(data['course'].id)})
return super().form_valid(form)
<|end_body_0|>
<|body_start_1|>
context = super().get_context_data(**... | View for choosing course tokens that will be displayed. Check that the user's account is still active. Redirects to tokens view on form valid. | ShowTokensView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ShowTokensView:
"""View for choosing course tokens that will be displayed. Check that the user's account is still active. Redirects to tokens view on form valid."""
def form_valid(self, form):
"""Compute the success URL and call super.form_valid()"""
<|body_0|>
def get_c... | stack_v2_sparse_classes_75kplus_train_066221 | 29,759 | no_license | [
{
"docstring": "Compute the success URL and call super.form_valid()",
"name": "form_valid",
"signature": "def form_valid(self, form)"
},
{
"docstring": "Return the data used in the templates rendering.",
"name": "get_context_data",
"signature": "def get_context_data(self, **kwargs)"
}
... | 2 | stack_v2_sparse_classes_30k_train_009669 | Implement the Python class `ShowTokensView` described below.
Class description:
View for choosing course tokens that will be displayed. Check that the user's account is still active. Redirects to tokens view on form valid.
Method signatures and docstrings:
- def form_valid(self, form): Compute the success URL and cal... | Implement the Python class `ShowTokensView` described below.
Class description:
View for choosing course tokens that will be displayed. Check that the user's account is still active. Redirects to tokens view on form valid.
Method signatures and docstrings:
- def form_valid(self, form): Compute the success URL and cal... | 06bc577d01d3dbf6c425e03dcb903977a38e377c | <|skeleton|>
class ShowTokensView:
"""View for choosing course tokens that will be displayed. Check that the user's account is still active. Redirects to tokens view on form valid."""
def form_valid(self, form):
"""Compute the success URL and call super.form_valid()"""
<|body_0|>
def get_c... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ShowTokensView:
"""View for choosing course tokens that will be displayed. Check that the user's account is still active. Redirects to tokens view on form valid."""
def form_valid(self, form):
"""Compute the success URL and call super.form_valid()"""
data = form.cleaned_data
self.... | the_stack_v2_python_sparse | cbt/views.py | Festusali/CBTest | train | 6 |
a68b9565a97edec62497eafc94f3d89a1e5616cc | [
"Part = self.old_state.apps.get_model('part', 'part')\nCompany = self.old_state.apps.get_model('company', 'company')\nSupplierPart = self.old_state.apps.get_model('company', 'supplierpart')\npart = Part.objects.create(name='CAP CER 0.1UF 10V X5R 0402', description='CAP CER 0.1UF 10V X5R 0402', purchaseable=True, le... | <|body_start_0|>
Part = self.old_state.apps.get_model('part', 'part')
Company = self.old_state.apps.get_model('company', 'company')
SupplierPart = self.old_state.apps.get_model('company', 'supplierpart')
part = Part.objects.create(name='CAP CER 0.1UF 10V X5R 0402', description='CAP CER 0... | Tests for migration 0034-0037 which added and transitioned to the ManufacturerPart model. | TestManufacturerPart | [
"MIT",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestManufacturerPart:
"""Tests for migration 0034-0037 which added and transitioned to the ManufacturerPart model."""
def prepare(self):
"""Prepare the database by adding some test data 'before' the change: - Part object - Company object (supplier) - SupplierPart object"""
<|... | stack_v2_sparse_classes_75kplus_train_066222 | 12,626 | permissive | [
{
"docstring": "Prepare the database by adding some test data 'before' the change: - Part object - Company object (supplier) - SupplierPart object",
"name": "prepare",
"signature": "def prepare(self)"
},
{
"docstring": "Test that the new companies have been created successfully.",
"name": "t... | 2 | stack_v2_sparse_classes_30k_train_013894 | Implement the Python class `TestManufacturerPart` described below.
Class description:
Tests for migration 0034-0037 which added and transitioned to the ManufacturerPart model.
Method signatures and docstrings:
- def prepare(self): Prepare the database by adding some test data 'before' the change: - Part object - Comp... | Implement the Python class `TestManufacturerPart` described below.
Class description:
Tests for migration 0034-0037 which added and transitioned to the ManufacturerPart model.
Method signatures and docstrings:
- def prepare(self): Prepare the database by adding some test data 'before' the change: - Part object - Comp... | e88a8e99a5f0b201c67a95cba097c729f090d5e2 | <|skeleton|>
class TestManufacturerPart:
"""Tests for migration 0034-0037 which added and transitioned to the ManufacturerPart model."""
def prepare(self):
"""Prepare the database by adding some test data 'before' the change: - Part object - Company object (supplier) - SupplierPart object"""
<|... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TestManufacturerPart:
"""Tests for migration 0034-0037 which added and transitioned to the ManufacturerPart model."""
def prepare(self):
"""Prepare the database by adding some test data 'before' the change: - Part object - Company object (supplier) - SupplierPart object"""
Part = self.old... | the_stack_v2_python_sparse | InvenTree/company/test_migrations.py | inventree/InvenTree | train | 3,077 |
e2dde53487c8c9f78fa93b254ddf5aa6204719b5 | [
"AliasingCompensation.__init__(self, input_signal=input_signal, maximum_harmonics=maximum_harmonics)\nif resampling_algorithm is None:\n self._resampling_algorithm = sumpf.modules.ResampleSignal.SPECTRUM\nelse:\n self._resampling_algorithm = resampling_algorithm",
"if input_signal is None:\n input_signal... | <|body_start_0|>
AliasingCompensation.__init__(self, input_signal=input_signal, maximum_harmonics=maximum_harmonics)
if resampling_algorithm is None:
self._resampling_algorithm = sumpf.modules.ResampleSignal.SPECTRUM
else:
self._resampling_algorithm = resampling_algorithm... | A class to compensate the aliasing introduced in a nonlinear model using an upsampler. The upsampling factor of the upsampler is chosen such that aliasing is prevented in the whole spectrum of the nonlinearly processed signals. | FullUpsamplingAliasingCompensation | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FullUpsamplingAliasingCompensation:
"""A class to compensate the aliasing introduced in a nonlinear model using an upsampler. The upsampling factor of the upsampler is chosen such that aliasing is prevented in the whole spectrum of the nonlinearly processed signals."""
def __init__(self, inp... | stack_v2_sparse_classes_75kplus_train_066223 | 15,804 | no_license | [
{
"docstring": ":param input_signal: the input signal :type input_signal: sumpf.Signal() :param maximum_harmonics: the maximum harmonics :type maximum_harmonics: int :param resampling_algorithm: the resampling algorithm :type resampling_algorithm: Eg, sumpf.modules.ResampleSignal.SPECTRUM()",
"name": "__ini... | 5 | stack_v2_sparse_classes_30k_train_007088 | Implement the Python class `FullUpsamplingAliasingCompensation` described below.
Class description:
A class to compensate the aliasing introduced in a nonlinear model using an upsampler. The upsampling factor of the upsampler is chosen such that aliasing is prevented in the whole spectrum of the nonlinearly processed ... | Implement the Python class `FullUpsamplingAliasingCompensation` described below.
Class description:
A class to compensate the aliasing introduced in a nonlinear model using an upsampler. The upsampling factor of the upsampler is chosen such that aliasing is prevented in the whole spectrum of the nonlinearly processed ... | 41ba79cddeb8f76ffed1d3435d629e014f7d04c5 | <|skeleton|>
class FullUpsamplingAliasingCompensation:
"""A class to compensate the aliasing introduced in a nonlinear model using an upsampler. The upsampling factor of the upsampler is chosen such that aliasing is prevented in the whole spectrum of the nonlinearly processed signals."""
def __init__(self, inp... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class FullUpsamplingAliasingCompensation:
"""A class to compensate the aliasing introduced in a nonlinear model using an upsampler. The upsampling factor of the upsampler is chosen such that aliasing is prevented in the whole spectrum of the nonlinearly processed signals."""
def __init__(self, input_signal=Non... | the_stack_v2_python_sparse | aliasing_compensation/aliasing_compensation_techniques.py | zuowanbushiwo/systemidentifier | train | 0 |
1a6cbdeb85df4e8b27d5761cf29aefcb6a64df72 | [
"super(AttentionDecoderRNN, self).__init__()\nself.embed_dim = embed_dim\nself.hidden_dim = self.rnn_dim = rnn_dim\nself.vocab_size = vocab_size\nself.padding_idx = padding_idx\nself.dropout = nn.Dropout(dropout)\nself.num_layers = num_layers\nself.input_feed = input_feed\nself.rnn_type = rnn_type\nself.embedding =... | <|body_start_0|>
super(AttentionDecoderRNN, self).__init__()
self.embed_dim = embed_dim
self.hidden_dim = self.rnn_dim = rnn_dim
self.vocab_size = vocab_size
self.padding_idx = padding_idx
self.dropout = nn.Dropout(dropout)
self.num_layers = num_layers
sel... | AttentionDecoderRNN | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AttentionDecoderRNN:
def __init__(self, embed_dim, rnn_dim, vocab_size, padding_idx, dropout=0.3, num_layers=2, input_feed=True, rnn_type='LSTM'):
"""Parameters ---------- embed_dim: int The dimensionality of the embedding layer. rnn_dim: int The dimensionality of the decoder RNN hidden ... | stack_v2_sparse_classes_75kplus_train_066224 | 5,458 | no_license | [
{
"docstring": "Parameters ---------- embed_dim: int The dimensionality of the embedding layer. rnn_dim: int The dimensionality of the decoder RNN hidden layer / output. Note that this should be the same rnn_dim used in the encoder. vocab_size: int The size of the vocabulary. padding_idx: int The index in the d... | 2 | null | Implement the Python class `AttentionDecoderRNN` described below.
Class description:
Implement the AttentionDecoderRNN class.
Method signatures and docstrings:
- def __init__(self, embed_dim, rnn_dim, vocab_size, padding_idx, dropout=0.3, num_layers=2, input_feed=True, rnn_type='LSTM'): Parameters ---------- embed_di... | Implement the Python class `AttentionDecoderRNN` described below.
Class description:
Implement the AttentionDecoderRNN class.
Method signatures and docstrings:
- def __init__(self, embed_dim, rnn_dim, vocab_size, padding_idx, dropout=0.3, num_layers=2, input_feed=True, rnn_type='LSTM'): Parameters ---------- embed_di... | 710d7ef3b72c16369e99833fe0aa359e1fb7b2f0 | <|skeleton|>
class AttentionDecoderRNN:
def __init__(self, embed_dim, rnn_dim, vocab_size, padding_idx, dropout=0.3, num_layers=2, input_feed=True, rnn_type='LSTM'):
"""Parameters ---------- embed_dim: int The dimensionality of the embedding layer. rnn_dim: int The dimensionality of the decoder RNN hidden ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AttentionDecoderRNN:
def __init__(self, embed_dim, rnn_dim, vocab_size, padding_idx, dropout=0.3, num_layers=2, input_feed=True, rnn_type='LSTM'):
"""Parameters ---------- embed_dim: int The dimensionality of the embedding layer. rnn_dim: int The dimensionality of the decoder RNN hidden layer / output... | the_stack_v2_python_sparse | oov/models/seq2seq/modules/attention_decoder_rnn.py | nelson-liu/oov-translation | train | 1 | |
2392cf9eb64b0a5add52caed6c8027dd1fbd3b18 | [
"n = len(nums)\nif n < 2:\n return False\nif sum(nums) & 1:\n return False\ntarget = sum(nums) // 2\ndp = [0] * (target + 1)\nfor i in range(1, n + 1):\n for j in range(target, nums[i - 1] - 1, -1):\n dp[j] = max(dp[j], dp[j - nums[i - 1]] + nums[i - 1])\n if dp[j] == target:\n ret... | <|body_start_0|>
n = len(nums)
if n < 2:
return False
if sum(nums) & 1:
return False
target = sum(nums) // 2
dp = [0] * (target + 1)
for i in range(1, n + 1):
for j in range(target, nums[i - 1] - 1, -1):
dp[j] = max(dp[j... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def canPartition1(self, nums: List[int]) -> bool:
"""思路：01背包问题"""
<|body_0|>
def canPartition2(self, nums: List[int]) -> bool:
"""思路：01背包问题"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
n = len(nums)
if n < 2:
return ... | stack_v2_sparse_classes_75kplus_train_066225 | 1,998 | no_license | [
{
"docstring": "思路：01背包问题",
"name": "canPartition1",
"signature": "def canPartition1(self, nums: List[int]) -> bool"
},
{
"docstring": "思路：01背包问题",
"name": "canPartition2",
"signature": "def canPartition2(self, nums: List[int]) -> bool"
}
] | 2 | stack_v2_sparse_classes_30k_val_000903 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def canPartition1(self, nums: List[int]) -> bool: 思路：01背包问题
- def canPartition2(self, nums: List[int]) -> bool: 思路：01背包问题 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def canPartition1(self, nums: List[int]) -> bool: 思路：01背包问题
- def canPartition2(self, nums: List[int]) -> bool: 思路：01背包问题
<|skeleton|>
class Solution:
def canPartition1(sel... | e43ee86c5a8cdb808da09b4b6138e10275abadb5 | <|skeleton|>
class Solution:
def canPartition1(self, nums: List[int]) -> bool:
"""思路：01背包问题"""
<|body_0|>
def canPartition2(self, nums: List[int]) -> bool:
"""思路：01背包问题"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def canPartition1(self, nums: List[int]) -> bool:
"""思路：01背包问题"""
n = len(nums)
if n < 2:
return False
if sum(nums) & 1:
return False
target = sum(nums) // 2
dp = [0] * (target + 1)
for i in range(1, n + 1):
... | the_stack_v2_python_sparse | LeetCode/动态规划法(dp)/背包问题/416. 分割等和子集.py | yiming1012/MyLeetCode | train | 2 | |
1cb0a3e2cab7ef95893fdb45f6a3f49c16dff589 | [
"ys = np.linspace(extent[2], extent[3], shape_native[1] + 1)\nxs = np.linspace(extent[0], extent[1], shape_native[0] + 1)\nfor x in xs:\n plt.plot([x, x], [ys[0], ys[-1]], **self.config_dict)\nfor y in ys:\n plt.plot([xs[0], xs[-1]], [y, y], **self.config_dict)",
"try:\n plt.plot(grid[:, 1], grid[:, 0], ... | <|body_start_0|>
ys = np.linspace(extent[2], extent[3], shape_native[1] + 1)
xs = np.linspace(extent[0], extent[1], shape_native[0] + 1)
for x in xs:
plt.plot([x, x], [ys[0], ys[-1]], **self.config_dict)
for y in ys:
plt.plot([xs[0], xs[-1]], [y, y], **self.config... | Plots `Grid2D` data structure that are better visualized as solid lines, for example rectangular lines that are plotted over an image and grids of (y,x) coordinates as lines (as opposed to a scatter of points using the `GridScatter` object). This object wraps the following Matplotlib methods: - plt.plot: https://matplo... | GridPlot | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GridPlot:
"""Plots `Grid2D` data structure that are better visualized as solid lines, for example rectangular lines that are plotted over an image and grids of (y,x) coordinates as lines (as opposed to a scatter of points using the `GridScatter` object). This object wraps the following Matplotlib... | stack_v2_sparse_classes_75kplus_train_066226 | 21,101 | permissive | [
{
"docstring": "Plots a rectangular grid of lines on a plot, using the coordinate system of the figure. The size and shape of the grid is specified by the `extent` and `shape_native` properties of a data structure which will provide the rectangaular grid lines on a suitable coordinate system for the plot. Param... | 3 | stack_v2_sparse_classes_30k_train_003453 | Implement the Python class `GridPlot` described below.
Class description:
Plots `Grid2D` data structure that are better visualized as solid lines, for example rectangular lines that are plotted over an image and grids of (y,x) coordinates as lines (as opposed to a scatter of points using the `GridScatter` object). Thi... | Implement the Python class `GridPlot` described below.
Class description:
Plots `Grid2D` data structure that are better visualized as solid lines, for example rectangular lines that are plotted over an image and grids of (y,x) coordinates as lines (as opposed to a scatter of points using the `GridScatter` object). Thi... | c21e8859bdb20737352147b9904797ac99985b73 | <|skeleton|>
class GridPlot:
"""Plots `Grid2D` data structure that are better visualized as solid lines, for example rectangular lines that are plotted over an image and grids of (y,x) coordinates as lines (as opposed to a scatter of points using the `GridScatter` object). This object wraps the following Matplotlib... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class GridPlot:
"""Plots `Grid2D` data structure that are better visualized as solid lines, for example rectangular lines that are plotted over an image and grids of (y,x) coordinates as lines (as opposed to a scatter of points using the `GridScatter` object). This object wraps the following Matplotlib methods: - p... | the_stack_v2_python_sparse | autoarray/plot/mat_wrap/wrap/wrap_2d.py | jonathanfrawley/PyAutoArray_copy | train | 0 |
499c539212c14e60b0adecc683c940442d641b4f | [
"try:\n return json.dumps(value)\nexcept TypeError:\n if isinstance(value, _literal_bindparam):\n return value.value\n raise",
"if value is None:\n return\nreturn json.loads(value)"
] | <|body_start_0|>
try:
return json.dumps(value)
except TypeError:
if isinstance(value, _literal_bindparam):
return value.value
raise
<|end_body_0|>
<|body_start_1|>
if value is None:
return
return json.loads(value)
<|end_bod... | A json object stored as a string. json encoding/decoding is handled by SQLAlchemy, so this type is database agnostic and is not affected by differences in underlying JSON types implementations. | JSONString | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class JSONString:
"""A json object stored as a string. json encoding/decoding is handled by SQLAlchemy, so this type is database agnostic and is not affected by differences in underlying JSON types implementations."""
def process_bind_param(self, value, dialect):
"""Encode object to a stri... | stack_v2_sparse_classes_75kplus_train_066227 | 11,229 | permissive | [
{
"docstring": "Encode object to a string before inserting into database.",
"name": "process_bind_param",
"signature": "def process_bind_param(self, value, dialect)"
},
{
"docstring": "Decode string to an object after selecting from database.",
"name": "process_result_value",
"signature"... | 2 | stack_v2_sparse_classes_30k_train_049474 | Implement the Python class `JSONString` described below.
Class description:
A json object stored as a string. json encoding/decoding is handled by SQLAlchemy, so this type is database agnostic and is not affected by differences in underlying JSON types implementations.
Method signatures and docstrings:
- def process_... | Implement the Python class `JSONString` described below.
Class description:
A json object stored as a string. json encoding/decoding is handled by SQLAlchemy, so this type is database agnostic and is not affected by differences in underlying JSON types implementations.
Method signatures and docstrings:
- def process_... | c0de6442e1d7653fad824d75e571802a74eee605 | <|skeleton|>
class JSONString:
"""A json object stored as a string. json encoding/decoding is handled by SQLAlchemy, so this type is database agnostic and is not affected by differences in underlying JSON types implementations."""
def process_bind_param(self, value, dialect):
"""Encode object to a stri... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class JSONString:
"""A json object stored as a string. json encoding/decoding is handled by SQLAlchemy, so this type is database agnostic and is not affected by differences in underlying JSON types implementations."""
def process_bind_param(self, value, dialect):
"""Encode object to a string before ins... | the_stack_v2_python_sparse | rest-service/manager_rest/storage/models_base.py | cloudify-cosmo/cloudify-manager | train | 146 |
863ec30c381cea0e13045bab89b662271773de83 | [
"self._text_maze = text_maze\nself._wall_char = wall_char\nself._make_odd_sized_walls = make_odd_sized_walls\nself._covered = np.full(text_maze.shape, False, dtype=np.bool)\nself._maze_size = GridCoordinates(*text_maze.shape)\nself._next_start = GridCoordinates(0, 0)\nself._calculated = False\nself._walls = ()",
... | <|body_start_0|>
self._text_maze = text_maze
self._wall_char = wall_char
self._make_odd_sized_walls = make_odd_sized_walls
self._covered = np.full(text_maze.shape, False, dtype=np.bool)
self._maze_size = GridCoordinates(*text_maze.shape)
self._next_start = GridCoordinates... | Calculates a covering of text mazes with overlapping rectangular walls. This class uses a greedy algorithm to try and minimize the number of geoms generated to create a given maze. The solution is not guaranteed to be optimal, but in most cases should result in a significantly smaller number of geoms than if each cell ... | _MazeWallCoveringContext | [
"Apache-2.0",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class _MazeWallCoveringContext:
"""Calculates a covering of text mazes with overlapping rectangular walls. This class uses a greedy algorithm to try and minimize the number of geoms generated to create a given maze. The solution is not guaranteed to be optimal, but in most cases should result in a sign... | stack_v2_sparse_classes_75kplus_train_066228 | 5,466 | permissive | [
{
"docstring": "Initializes this _MazeWallCoveringContext. Args: text_maze: A `labmaze.TextGrid` instance. wall_char: (optional) The character that signifies a wall. make_odd_sized_walls: (optional) A boolean, if `True` all wall sections generated span odd numbers of grid cells. This option exists primarily to ... | 5 | stack_v2_sparse_classes_30k_train_018753 | Implement the Python class `_MazeWallCoveringContext` described below.
Class description:
Calculates a covering of text mazes with overlapping rectangular walls. This class uses a greedy algorithm to try and minimize the number of geoms generated to create a given maze. The solution is not guaranteed to be optimal, bu... | Implement the Python class `_MazeWallCoveringContext` described below.
Class description:
Calculates a covering of text mazes with overlapping rectangular walls. This class uses a greedy algorithm to try and minimize the number of geoms generated to create a given maze. The solution is not guaranteed to be optimal, bu... | 33d3ea2682409ee82bf9c5129ceaf06ab01cd48e | <|skeleton|>
class _MazeWallCoveringContext:
"""Calculates a covering of text mazes with overlapping rectangular walls. This class uses a greedy algorithm to try and minimize the number of geoms generated to create a given maze. The solution is not guaranteed to be optimal, but in most cases should result in a sign... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class _MazeWallCoveringContext:
"""Calculates a covering of text mazes with overlapping rectangular walls. This class uses a greedy algorithm to try and minimize the number of geoms generated to create a given maze. The solution is not guaranteed to be optimal, but in most cases should result in a significantly sma... | the_stack_v2_python_sparse | src/env/dm_control/dm_control/locomotion/arenas/covering.py | nicklashansen/svea-vit | train | 16 |
a9fa36ae5eab3868b96042f88178ed764c70450a | [
"body_1 = {'reqId': '32位UUID', 'areaCode': 'atYA-A', 'startTime': '20181010' + '06000000', 'endTime': '20181023' + '06000000'}\na = api_v1_analysis_pre_security_passrate(body_1)\ndict_data = json.loads(a)\nself.assertNotEqual(dict_data['results'][0]['num'], 0)",
"body_1 = {'reqId': '32位UUID', 'areaCode': 'atYA-A'... | <|body_start_0|>
body_1 = {'reqId': '32位UUID', 'areaCode': 'atYA-A', 'startTime': '20181010' + '06000000', 'endTime': '20181023' + '06000000'}
a = api_v1_analysis_pre_security_passrate(body_1)
dict_data = json.loads(a)
self.assertNotEqual(dict_data['results'][0]['num'], 0)
<|end_body_0|>... | 预安检通过率接口测试回归 | TestApiAnalysisPreSecurityPassRate | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestApiAnalysisPreSecurityPassRate:
"""预安检通过率接口测试回归"""
def test_01(self):
"""查询通过率"""
<|body_0|>
def test_02(self):
"""不在当前时间不能查出来"""
<|body_1|>
def test_03(self):
"""区域通道不存在时不能查询相关信息"""
<|body_2|>
def test_04(self):
"""验... | stack_v2_sparse_classes_75kplus_train_066229 | 2,178 | no_license | [
{
"docstring": "查询通过率",
"name": "test_01",
"signature": "def test_01(self)"
},
{
"docstring": "不在当前时间不能查出来",
"name": "test_02",
"signature": "def test_02(self)"
},
{
"docstring": "区域通道不存在时不能查询相关信息",
"name": "test_03",
"signature": "def test_03(self)"
},
{
"docstri... | 4 | stack_v2_sparse_classes_30k_train_015366 | Implement the Python class `TestApiAnalysisPreSecurityPassRate` described below.
Class description:
预安检通过率接口测试回归
Method signatures and docstrings:
- def test_01(self): 查询通过率
- def test_02(self): 不在当前时间不能查出来
- def test_03(self): 区域通道不存在时不能查询相关信息
- def test_04(self): 验证服务器响应时间小于1S | Implement the Python class `TestApiAnalysisPreSecurityPassRate` described below.
Class description:
预安检通过率接口测试回归
Method signatures and docstrings:
- def test_01(self): 查询通过率
- def test_02(self): 不在当前时间不能查出来
- def test_03(self): 区域通道不存在时不能查询相关信息
- def test_04(self): 验证服务器响应时间小于1S
<|skeleton|>
class TestApiAnalysisPre... | aa0749f4a237ee76a61579dc5984635a7127a631 | <|skeleton|>
class TestApiAnalysisPreSecurityPassRate:
"""预安检通过率接口测试回归"""
def test_01(self):
"""查询通过率"""
<|body_0|>
def test_02(self):
"""不在当前时间不能查出来"""
<|body_1|>
def test_03(self):
"""区域通道不存在时不能查询相关信息"""
<|body_2|>
def test_04(self):
"""验... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TestApiAnalysisPreSecurityPassRate:
"""预安检通过率接口测试回归"""
def test_01(self):
"""查询通过率"""
body_1 = {'reqId': '32位UUID', 'areaCode': 'atYA-A', 'startTime': '20181010' + '06000000', 'endTime': '20181023' + '06000000'}
a = api_v1_analysis_pre_security_passrate(body_1)
dict_data =... | the_stack_v2_python_sparse | Airport/Auto_return/TestCase/test_data_platform_082.py | jingshiyue/zhongkeyuan_workspace | train | 0 |
f92cd9775dfb2d18325bd58c1947049014b29fc4 | [
"if poisonCnt < 1:\n return 0\nbottleCnt = int(math.ceil(math.log2(poisonCnt)))\nreturn bottleCnt",
"\"\"\"Suppose: node 5 is poison \"\"\"\nantCnt = int(math.ceil(math.log2(poisonCnt)))\np1 = [1]\np2 = []\nfor i in range(1, antCnt):\n p1.append(1 << i | p1[i - 1])\nfor i in range(0, (len(p1) + 1) // 2):\n ... | <|body_start_0|>
if poisonCnt < 1:
return 0
bottleCnt = int(math.ceil(math.log2(poisonCnt)))
return bottleCnt
<|end_body_0|>
<|body_start_1|>
"""Suppose: node 5 is poison """
antCnt = int(math.ceil(math.log2(poisonCnt)))
p1 = [1]
p2 = []
for i... | Author: xuwei x17133 At 2018/08/02 dsc: 1.use binary mask solve 'mice drink poison' problem. 2.show one posibility on detail. 3.use self.lensi to control output length. 4.use shift move(replacement) left/right to replace multiplication/division. 5.use a special func to convering bianry to string for outputing. | BitMask | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BitMask:
"""Author: xuwei x17133 At 2018/08/02 dsc: 1.use binary mask solve 'mice drink poison' problem. 2.show one posibility on detail. 3.use self.lensi to control output length. 4.use shift move(replacement) left/right to replace multiplication/division. 5.use a special func to convering bianr... | stack_v2_sparse_classes_75kplus_train_066230 | 2,313 | no_license | [
{
"docstring": "find minum count for poison test; if u need detailed process, try to use the 'showCalcuProcess' to show all",
"name": "calcuAnimalCnt",
"signature": "def calcuAnimalCnt(self, poisonCnt)"
},
{
"docstring": "Caution: this function is used to show one possibility, no which one is im... | 3 | stack_v2_sparse_classes_30k_train_018061 | Implement the Python class `BitMask` described below.
Class description:
Author: xuwei x17133 At 2018/08/02 dsc: 1.use binary mask solve 'mice drink poison' problem. 2.show one posibility on detail. 3.use self.lensi to control output length. 4.use shift move(replacement) left/right to replace multiplication/division. ... | Implement the Python class `BitMask` described below.
Class description:
Author: xuwei x17133 At 2018/08/02 dsc: 1.use binary mask solve 'mice drink poison' problem. 2.show one posibility on detail. 3.use self.lensi to control output length. 4.use shift move(replacement) left/right to replace multiplication/division. ... | 886b1bd53d610d33ac861dcded0f0f89dea7aafd | <|skeleton|>
class BitMask:
"""Author: xuwei x17133 At 2018/08/02 dsc: 1.use binary mask solve 'mice drink poison' problem. 2.show one posibility on detail. 3.use self.lensi to control output length. 4.use shift move(replacement) left/right to replace multiplication/division. 5.use a special func to convering bianr... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class BitMask:
"""Author: xuwei x17133 At 2018/08/02 dsc: 1.use binary mask solve 'mice drink poison' problem. 2.show one posibility on detail. 3.use self.lensi to control output length. 4.use shift move(replacement) left/right to replace multiplication/division. 5.use a special func to convering bianry to string f... | the_stack_v2_python_sparse | BitMask/BitMask.py | jeanbond/lintcode | train | 1 |
3dc24a201856c950dcf6e30091767db83e2ffeb2 | [
"if not email:\n raise ValueError('Users must have an email')\nuser = self.model(email=email, full_name=full_name, phone=phone)\nuser.set_password(password)\nuser.save(using=self._db)\nreturn user",
"user = self.create_user(email=email, password=password, full_name=None)\nuser.full_name = 'Administrator'\nuser... | <|body_start_0|>
if not email:
raise ValueError('Users must have an email')
user = self.model(email=email, full_name=full_name, phone=phone)
user.set_password(password)
user.save(using=self._db)
return user
<|end_body_0|>
<|body_start_1|>
user = self.create_u... | Main user manager | CustomUserManager | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CustomUserManager:
"""Main user manager"""
def create_user(self, full_name, email, phone=None, password=None):
"""Creates and saves a user with the given phone."""
<|body_0|>
def create_superuser(self, email, password):
"""Creates and saves a superuser with the g... | stack_v2_sparse_classes_75kplus_train_066231 | 2,505 | no_license | [
{
"docstring": "Creates and saves a user with the given phone.",
"name": "create_user",
"signature": "def create_user(self, full_name, email, phone=None, password=None)"
},
{
"docstring": "Creates and saves a superuser with the given email and password",
"name": "create_superuser",
"sign... | 2 | stack_v2_sparse_classes_30k_train_007322 | Implement the Python class `CustomUserManager` described below.
Class description:
Main user manager
Method signatures and docstrings:
- def create_user(self, full_name, email, phone=None, password=None): Creates and saves a user with the given phone.
- def create_superuser(self, email, password): Creates and saves a... | Implement the Python class `CustomUserManager` described below.
Class description:
Main user manager
Method signatures and docstrings:
- def create_user(self, full_name, email, phone=None, password=None): Creates and saves a user with the given phone.
- def create_superuser(self, email, password): Creates and saves a... | c171ac925c1dce01d2c496847fd30e804764254a | <|skeleton|>
class CustomUserManager:
"""Main user manager"""
def create_user(self, full_name, email, phone=None, password=None):
"""Creates and saves a user with the given phone."""
<|body_0|>
def create_superuser(self, email, password):
"""Creates and saves a superuser with the g... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CustomUserManager:
"""Main user manager"""
def create_user(self, full_name, email, phone=None, password=None):
"""Creates and saves a user with the given phone."""
if not email:
raise ValueError('Users must have an email')
user = self.model(email=email, full_name=full_... | the_stack_v2_python_sparse | src/core/users/models.py | zhumakhan/sample-django-project-with-caching | train | 1 |
672cdab38bcbc5817b8d16904c9db78e1612bb42 | [
"diagonal = {}\nfor i, lst in enumerate(nums):\n for j, num in enumerate(lst):\n if i + j not in diagonal:\n diagonal[i + j] = []\n diagonal[i + j].append(num)\nrst = []\nfor i in range(len(diagonal)):\n rst.extend(list(reversed(diagonal[i])))\nreturn rst",
"rst = []\nfor i, lst in ... | <|body_start_0|>
diagonal = {}
for i, lst in enumerate(nums):
for j, num in enumerate(lst):
if i + j not in diagonal:
diagonal[i + j] = []
diagonal[i + j].append(num)
rst = []
for i in range(len(diagonal)):
rst.e... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findDiagonalOrder(self, nums: List[List[int]]) -> List[int]:
"""使用dict存储"""
<|body_0|>
def findDiagonalOrder_2(self, nums: List[List[int]]) -> List[int]:
"""使用list存储"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
diagonal = {}
... | stack_v2_sparse_classes_75kplus_train_066232 | 1,309 | no_license | [
{
"docstring": "使用dict存储",
"name": "findDiagonalOrder",
"signature": "def findDiagonalOrder(self, nums: List[List[int]]) -> List[int]"
},
{
"docstring": "使用list存储",
"name": "findDiagonalOrder_2",
"signature": "def findDiagonalOrder_2(self, nums: List[List[int]]) -> List[int]"
}
] | 2 | stack_v2_sparse_classes_30k_train_029437 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findDiagonalOrder(self, nums: List[List[int]]) -> List[int]: 使用dict存储
- def findDiagonalOrder_2(self, nums: List[List[int]]) -> List[int]: 使用list存储 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findDiagonalOrder(self, nums: List[List[int]]) -> List[int]: 使用dict存储
- def findDiagonalOrder_2(self, nums: List[List[int]]) -> List[int]: 使用list存储
<|skeleton|>
class Soluti... | e420eb456086db32d1d6b9576c8dcd73e041cbef | <|skeleton|>
class Solution:
def findDiagonalOrder(self, nums: List[List[int]]) -> List[int]:
"""使用dict存储"""
<|body_0|>
def findDiagonalOrder_2(self, nums: List[List[int]]) -> List[int]:
"""使用list存储"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def findDiagonalOrder(self, nums: List[List[int]]) -> List[int]:
"""使用dict存储"""
diagonal = {}
for i, lst in enumerate(nums):
for j, num in enumerate(lst):
if i + j not in diagonal:
diagonal[i + j] = []
diagonal[i... | the_stack_v2_python_sparse | TrainFor1024/others/1424.py | yangwei-nlp/LeetCode-Python | train | 0 | |
3d3d8bab58ae8312b8f256cdb1fc23b1b535385f | [
"self.capacity = capacity\nself.cache = {}\nself.count_to_node = collections.defaultdict(collections.OrderedDict)\nself.min_count = 0",
"if key not in self.cache:\n return -1\nnode = self.cache[key]\ndel self.count_to_node[node.count][key]\nnode.count += 1\nself.count_to_node[node.count][key] = node\nif not se... | <|body_start_0|>
self.capacity = capacity
self.cache = {}
self.count_to_node = collections.defaultdict(collections.OrderedDict)
self.min_count = 0
<|end_body_0|>
<|body_start_1|>
if key not in self.cache:
return -1
node = self.cache[key]
del self.coun... | LFUCache | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LFUCache:
def __init__(self, capacity):
""":type capacity: int"""
<|body_0|>
def get(self, key):
""":type key: int :rtype: int"""
<|body_1|>
def put(self, key, value):
""":type key: int :type value: int :rtype: None"""
<|body_2|>
<|end_s... | stack_v2_sparse_classes_75kplus_train_066233 | 3,450 | no_license | [
{
"docstring": ":type capacity: int",
"name": "__init__",
"signature": "def __init__(self, capacity)"
},
{
"docstring": ":type key: int :rtype: int",
"name": "get",
"signature": "def get(self, key)"
},
{
"docstring": ":type key: int :type value: int :rtype: None",
"name": "pu... | 3 | stack_v2_sparse_classes_30k_train_027621 | Implement the Python class `LFUCache` described below.
Class description:
Implement the LFUCache class.
Method signatures and docstrings:
- def __init__(self, capacity): :type capacity: int
- def get(self, key): :type key: int :rtype: int
- def put(self, key, value): :type key: int :type value: int :rtype: None | Implement the Python class `LFUCache` described below.
Class description:
Implement the LFUCache class.
Method signatures and docstrings:
- def __init__(self, capacity): :type capacity: int
- def get(self, key): :type key: int :rtype: int
- def put(self, key, value): :type key: int :type value: int :rtype: None
<|sk... | 54ff328131bf2ef387292f31a0e2a2c2cf612cdd | <|skeleton|>
class LFUCache:
def __init__(self, capacity):
""":type capacity: int"""
<|body_0|>
def get(self, key):
""":type key: int :rtype: int"""
<|body_1|>
def put(self, key, value):
""":type key: int :type value: int :rtype: None"""
<|body_2|>
<|end_s... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class LFUCache:
def __init__(self, capacity):
""":type capacity: int"""
self.capacity = capacity
self.cache = {}
self.count_to_node = collections.defaultdict(collections.OrderedDict)
self.min_count = 0
def get(self, key):
""":type key: int :rtype: int"""
... | the_stack_v2_python_sparse | hashtable/460.lfu-cache.py | hjlarry/leetcode | train | 0 | |
8c30eb20d96c5c93de83d3c88332c0453ccfb25d | [
"keys = ['times', 'timens', 'encoder', 'counter', 'di']\nself.data = pd.read_csv(fpath, delimiter=' ', header=None)\nself.data.columns = keys\nself.data['timestamp'] = self.data['times'] + 1e-09 * self.data['timens']\nself.data['encoder'] = self.data['encoder'].apply(lambda x: int(x) if int(x) <= 0 else -(int(x) ^ ... | <|body_start_0|>
keys = ['times', 'timens', 'encoder', 'counter', 'di']
self.data = pd.read_csv(fpath, delimiter=' ', header=None)
self.data.columns = keys
self.data['timestamp'] = self.data['times'] + 1e-09 * self.data['timens']
self.data['encoder'] = self.data['encoder'].apply(... | PizzaBoxEncHandlerTxt | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PizzaBoxEncHandlerTxt:
def __init__(self, fpath, chunk_size=0):
"""adds the chunks of data to a list This combines the chunks together and ignores the chunk size to speed things up."""
<|body_0|>
def __call__(self, chunk_num):
"""returns specified chunk number/index ... | stack_v2_sparse_classes_75kplus_train_066234 | 6,501 | permissive | [
{
"docstring": "adds the chunks of data to a list This combines the chunks together and ignores the chunk size to speed things up.",
"name": "__init__",
"signature": "def __init__(self, fpath, chunk_size=0)"
},
{
"docstring": "returns specified chunk number/index from list of all chunks created"... | 2 | stack_v2_sparse_classes_30k_train_031784 | Implement the Python class `PizzaBoxEncHandlerTxt` described below.
Class description:
Implement the PizzaBoxEncHandlerTxt class.
Method signatures and docstrings:
- def __init__(self, fpath, chunk_size=0): adds the chunks of data to a list This combines the chunks together and ignores the chunk size to speed things ... | Implement the Python class `PizzaBoxEncHandlerTxt` described below.
Class description:
Implement the PizzaBoxEncHandlerTxt class.
Method signatures and docstrings:
- def __init__(self, fpath, chunk_size=0): adds the chunks of data to a list This combines the chunks together and ignores the chunk size to speed things ... | 14638d04636c9784e4dfa3de28b7251120ee27e7 | <|skeleton|>
class PizzaBoxEncHandlerTxt:
def __init__(self, fpath, chunk_size=0):
"""adds the chunks of data to a list This combines the chunks together and ignores the chunk size to speed things up."""
<|body_0|>
def __call__(self, chunk_num):
"""returns specified chunk number/index ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PizzaBoxEncHandlerTxt:
def __init__(self, fpath, chunk_size=0):
"""adds the chunks of data to a list This combines the chunks together and ignores the chunk size to speed things up."""
keys = ['times', 'timens', 'encoder', 'counter', 'di']
self.data = pd.read_csv(fpath, delimiter=' ', ... | the_stack_v2_python_sparse | startup/11-handlers.py | NSLS-II-QAS/profile_collection | train | 0 | |
c23ce6598da18687bd7ae46d14cb5d4914c503b6 | [
"self._basis_name = 'Kazhdan-Lusztig'\nCombinatorialFreeModule.__init__(self, M.base_ring(), tuple(M._lattice), prefix=prefix, category=MoebiusAlgebraBases(M))\nE = M.E()\nphi = self.module_morphism(self._to_natural_basis, codomain=E, category=self.category(), triangular='lower', unitriangular=True, key=M._lattice.... | <|body_start_0|>
self._basis_name = 'Kazhdan-Lusztig'
CombinatorialFreeModule.__init__(self, M.base_ring(), tuple(M._lattice), prefix=prefix, category=MoebiusAlgebraBases(M))
E = M.E()
phi = self.module_morphism(self._to_natural_basis, codomain=E, category=self.category(), triangular='lo... | The Kazhdan-Lusztig basis of a quantum Möbius algebra. The Kazhdan-Lusztig basis `\\{ B_x \\mid x \\in L \\}` of `M_L` for some lattice `L` is defined by .. MATH:: B_x = \\sum_{y \\geq x} P_{x,y}(q) E_a, where `P_{x,y}(q)` is the Kazhdan-Lusztig polynomial of `L`, following the definition given in [EPW14]_. EXAMPLES: W... | KL | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class KL:
"""The Kazhdan-Lusztig basis of a quantum Möbius algebra. The Kazhdan-Lusztig basis `\\{ B_x \\mid x \\in L \\}` of `M_L` for some lattice `L` is defined by .. MATH:: B_x = \\sum_{y \\geq x} P_{x,y}(q) E_a, where `P_{x,y}(q)` is the Kazhdan-Lusztig polynomial of `L`, following the definition ... | stack_v2_sparse_classes_75kplus_train_066235 | 26,467 | no_license | [
{
"docstring": "Initialize ``self``. TESTS:: sage: L = posets.BooleanLattice(4) sage: M = L.quantum_moebius_algebra() sage: TestSuite(M.KL()).run() # long time",
"name": "__init__",
"signature": "def __init__(self, M, prefix='KL')"
},
{
"docstring": "Convert the element indexed by ``x`` to the n... | 2 | stack_v2_sparse_classes_30k_val_000427 | Implement the Python class `KL` described below.
Class description:
The Kazhdan-Lusztig basis of a quantum Möbius algebra. The Kazhdan-Lusztig basis `\\{ B_x \\mid x \\in L \\}` of `M_L` for some lattice `L` is defined by .. MATH:: B_x = \\sum_{y \\geq x} P_{x,y}(q) E_a, where `P_{x,y}(q)` is the Kazhdan-Lusztig polyn... | Implement the Python class `KL` described below.
Class description:
The Kazhdan-Lusztig basis of a quantum Möbius algebra. The Kazhdan-Lusztig basis `\\{ B_x \\mid x \\in L \\}` of `M_L` for some lattice `L` is defined by .. MATH:: B_x = \\sum_{y \\geq x} P_{x,y}(q) E_a, where `P_{x,y}(q)` is the Kazhdan-Lusztig polyn... | 0d9eacbf74e2acffefde93e39f8bcbec745cdaba | <|skeleton|>
class KL:
"""The Kazhdan-Lusztig basis of a quantum Möbius algebra. The Kazhdan-Lusztig basis `\\{ B_x \\mid x \\in L \\}` of `M_L` for some lattice `L` is defined by .. MATH:: B_x = \\sum_{y \\geq x} P_{x,y}(q) E_a, where `P_{x,y}(q)` is the Kazhdan-Lusztig polynomial of `L`, following the definition ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class KL:
"""The Kazhdan-Lusztig basis of a quantum Möbius algebra. The Kazhdan-Lusztig basis `\\{ B_x \\mid x \\in L \\}` of `M_L` for some lattice `L` is defined by .. MATH:: B_x = \\sum_{y \\geq x} P_{x,y}(q) E_a, where `P_{x,y}(q)` is the Kazhdan-Lusztig polynomial of `L`, following the definition given in [EPW... | the_stack_v2_python_sparse | sage/src/sage/combinat/posets/moebius_algebra.py | bopopescu/geosci | train | 0 |
a16ca73de77154b147c3e70ca080cfec7e490710 | [
"self._rng = make_np_rng(rng, which_method=['random_integers', 'shuffle'])\nassert num_batches is None or num_batches >= 0\nself._dataset_size = dataset_size\nif batch_size is None:\n if num_batches is not None:\n batch_size = int(numpy.ceil(self._dataset_size / num_batches))\n else:\n raise Val... | <|body_start_0|>
self._rng = make_np_rng(rng, which_method=['random_integers', 'shuffle'])
assert num_batches is None or num_batches >= 0
self._dataset_size = dataset_size
if batch_size is None:
if num_batches is not None:
batch_size = int(numpy.ceil(self._dat... | Returns minibatches randomly, but sequential inside each minibatch | BatchwiseShuffledSequentialIterator | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BatchwiseShuffledSequentialIterator:
"""Returns minibatches randomly, but sequential inside each minibatch"""
def __init__(self, dataset_size, batch_size, num_batches=None, rng=None):
""".. todo:: WRITEME"""
<|body_0|>
def next(self):
""".. todo:: WRITEME"""
... | stack_v2_sparse_classes_75kplus_train_066236 | 17,332 | no_license | [
{
"docstring": ".. todo:: WRITEME",
"name": "__init__",
"signature": "def __init__(self, dataset_size, batch_size, num_batches=None, rng=None)"
},
{
"docstring": ".. todo:: WRITEME",
"name": "next",
"signature": "def next(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_018892 | Implement the Python class `BatchwiseShuffledSequentialIterator` described below.
Class description:
Returns minibatches randomly, but sequential inside each minibatch
Method signatures and docstrings:
- def __init__(self, dataset_size, batch_size, num_batches=None, rng=None): .. todo:: WRITEME
- def next(self): .. t... | Implement the Python class `BatchwiseShuffledSequentialIterator` described below.
Class description:
Returns minibatches randomly, but sequential inside each minibatch
Method signatures and docstrings:
- def __init__(self, dataset_size, batch_size, num_batches=None, rng=None): .. todo:: WRITEME
- def next(self): .. t... | 73b99cdbdb609fecff3cf85e500c1f1bfd589930 | <|skeleton|>
class BatchwiseShuffledSequentialIterator:
"""Returns minibatches randomly, but sequential inside each minibatch"""
def __init__(self, dataset_size, batch_size, num_batches=None, rng=None):
""".. todo:: WRITEME"""
<|body_0|>
def next(self):
""".. todo:: WRITEME"""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class BatchwiseShuffledSequentialIterator:
"""Returns minibatches randomly, but sequential inside each minibatch"""
def __init__(self, dataset_size, batch_size, num_batches=None, rng=None):
""".. todo:: WRITEME"""
self._rng = make_np_rng(rng, which_method=['random_integers', 'shuffle'])
... | the_stack_v2_python_sparse | pylearn2/utils/iteration.py | lpigou/chalearn2014 | train | 2 |
78c4a417387845f68beff6f4c0d64d25900a554a | [
"from keras.preprocessing.image import ImageDataGenerator\nsuper(Cifar10PreprocessedAugmentDataGenerator, self).__init__(next_batch_size=next_batch_size, path_prefix=path_prefix, filenames=['data_batch_%d' % x for x in range(1, 6)])\nself.datagen = ImageDataGenerator(featurewise_center=True, samplewise_center=False... | <|body_start_0|>
from keras.preprocessing.image import ImageDataGenerator
super(Cifar10PreprocessedAugmentDataGenerator, self).__init__(next_batch_size=next_batch_size, path_prefix=path_prefix, filenames=['data_batch_%d' % x for x in range(1, 6)])
self.datagen = ImageDataGenerator(featurewise_ce... | Cifar10PreprocessedAugmentDataGenerator | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Cifar10PreprocessedAugmentDataGenerator:
def __init__(self, next_batch_size, path_prefix='./cifar10_data'):
"""使用 Keras 处理的数据, 用于训练集 :param next_batch_size: 下一批的数据大小 :param path_prefix: 数据前导路径"""
<|body_0|>
def generate_augment_batch(self):
"""产生一批次的数据（可迭代对象, 有限形式） :... | stack_v2_sparse_classes_75kplus_train_066237 | 7,748 | no_license | [
{
"docstring": "使用 Keras 处理的数据, 用于训练集 :param next_batch_size: 下一批的数据大小 :param path_prefix: 数据前导路径",
"name": "__init__",
"signature": "def __init__(self, next_batch_size, path_prefix='./cifar10_data')"
},
{
"docstring": "产生一批次的数据（可迭代对象, 有限形式） :return: 图像 [BATCH SIZE, HEIGHT, WIDTH, CHANNEL], 标签（O... | 2 | stack_v2_sparse_classes_30k_test_002538 | Implement the Python class `Cifar10PreprocessedAugmentDataGenerator` described below.
Class description:
Implement the Cifar10PreprocessedAugmentDataGenerator class.
Method signatures and docstrings:
- def __init__(self, next_batch_size, path_prefix='./cifar10_data'): 使用 Keras 处理的数据, 用于训练集 :param next_batch_size: 下一批... | Implement the Python class `Cifar10PreprocessedAugmentDataGenerator` described below.
Class description:
Implement the Cifar10PreprocessedAugmentDataGenerator class.
Method signatures and docstrings:
- def __init__(self, next_batch_size, path_prefix='./cifar10_data'): 使用 Keras 处理的数据, 用于训练集 :param next_batch_size: 下一批... | 7fca2e00624b2ea22887f9ae45b56435dbf73418 | <|skeleton|>
class Cifar10PreprocessedAugmentDataGenerator:
def __init__(self, next_batch_size, path_prefix='./cifar10_data'):
"""使用 Keras 处理的数据, 用于训练集 :param next_batch_size: 下一批的数据大小 :param path_prefix: 数据前导路径"""
<|body_0|>
def generate_augment_batch(self):
"""产生一批次的数据（可迭代对象, 有限形式） :... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Cifar10PreprocessedAugmentDataGenerator:
def __init__(self, next_batch_size, path_prefix='./cifar10_data'):
"""使用 Keras 处理的数据, 用于训练集 :param next_batch_size: 下一批的数据大小 :param path_prefix: 数据前导路径"""
from keras.preprocessing.image import ImageDataGenerator
super(Cifar10PreprocessedAugmentD... | the_stack_v2_python_sparse | homework/cnn_cifar/cifar10_loadFile.py | ddayzzz/machine_learning | train | 0 | |
362c935bb20e114323fb3f0cc3734d961070b3c2 | [
"self.logo = logo\nself.alternate_logo = alternate_logo\nself.icon = icon\nself.primary_color = primary_color\nself.title = title\nself.additional_properties = additional_properties",
"if dictionary is None:\n return None\nlogo = dictionary.get('logo')\nalternate_logo = dictionary.get('alternateLogo')\nicon = ... | <|body_start_0|>
self.logo = logo
self.alternate_logo = alternate_logo
self.icon = icon
self.primary_color = primary_color
self.title = title
self.additional_properties = additional_properties
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
ret... | Implementation of the 'Branding' model. All assets are SVGs so can be slightly resized without any issues. Attributes: logo (string): File path of the institution's logo. For white backgrounds designed at 375 x 72, has built in spacing around it to normalize brand sizing. alternate_logo (string): File path of the insti... | Branding | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Branding:
"""Implementation of the 'Branding' model. All assets are SVGs so can be slightly resized without any issues. Attributes: logo (string): File path of the institution's logo. For white backgrounds designed at 375 x 72, has built in spacing around it to normalize brand sizing. alternate_l... | stack_v2_sparse_classes_75kplus_train_066238 | 3,029 | permissive | [
{
"docstring": "Constructor for the Branding class",
"name": "__init__",
"signature": "def __init__(self, logo=None, alternate_logo=None, icon=None, primary_color=None, title=None, additional_properties={})"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: dictionary ... | 2 | stack_v2_sparse_classes_30k_train_038626 | Implement the Python class `Branding` described below.
Class description:
Implementation of the 'Branding' model. All assets are SVGs so can be slightly resized without any issues. Attributes: logo (string): File path of the institution's logo. For white backgrounds designed at 375 x 72, has built in spacing around it... | Implement the Python class `Branding` described below.
Class description:
Implementation of the 'Branding' model. All assets are SVGs so can be slightly resized without any issues. Attributes: logo (string): File path of the institution's logo. For white backgrounds designed at 375 x 72, has built in spacing around it... | b2ab1ded435db75c78d42261f5e4acd2a3061487 | <|skeleton|>
class Branding:
"""Implementation of the 'Branding' model. All assets are SVGs so can be slightly resized without any issues. Attributes: logo (string): File path of the institution's logo. For white backgrounds designed at 375 x 72, has built in spacing around it to normalize brand sizing. alternate_l... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Branding:
"""Implementation of the 'Branding' model. All assets are SVGs so can be slightly resized without any issues. Attributes: logo (string): File path of the institution's logo. For white backgrounds designed at 375 x 72, has built in spacing around it to normalize brand sizing. alternate_logo (string):... | the_stack_v2_python_sparse | finicityapi/models/branding.py | monarchmoney/finicity-python | train | 0 |
4459ed2430b5a854ade13b9bd65f81668cf2c59e | [
"serializer = self.get_serializer(data=request.data)\nserializer.is_valid(raise_exception=True)\nserializer.save()\nresponse = Response(serializer.data, status=status.HTTP_201_CREATED)\nuser = self.user\nmerge_cookie_cart_to_redis(request, user, response)\nreturn response",
"code = request.query_params.get('code'... | <|body_start_0|>
serializer = self.get_serializer(data=request.data)
serializer.is_valid(raise_exception=True)
serializer.save()
response = Response(serializer.data, status=status.HTTP_201_CREATED)
user = self.user
merge_cookie_cart_to_redis(request, user, response)
... | QQAuthUserView | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class QQAuthUserView:
def post(self, request):
"""保存qq登录用户绑定数据 1.获取参数并进行校验（参数完整性，手机号格式，短信验证码是否正确，access_token是否有效） 2.保存绑定用户的数据并签发jwt token 3.返回应答，绑定成功"""
<|body_0|>
def get(self, request):
"""获取QQ登录用户的openid并处理 1.获取code并校验 2.获取QQ登录用户的openid 2.1根据code请求QQ服务器获取access_token 2... | stack_v2_sparse_classes_75kplus_train_066239 | 8,213 | permissive | [
{
"docstring": "保存qq登录用户绑定数据 1.获取参数并进行校验（参数完整性，手机号格式，短信验证码是否正确，access_token是否有效） 2.保存绑定用户的数据并签发jwt token 3.返回应答，绑定成功",
"name": "post",
"signature": "def post(self, request)"
},
{
"docstring": "获取QQ登录用户的openid并处理 1.获取code并校验 2.获取QQ登录用户的openid 2.1根据code请求QQ服务器获取access_token 2.2根据access_token请求QQ服务... | 2 | stack_v2_sparse_classes_30k_train_018264 | Implement the Python class `QQAuthUserView` described below.
Class description:
Implement the QQAuthUserView class.
Method signatures and docstrings:
- def post(self, request): 保存qq登录用户绑定数据 1.获取参数并进行校验（参数完整性，手机号格式，短信验证码是否正确，access_token是否有效） 2.保存绑定用户的数据并签发jwt token 3.返回应答，绑定成功
- def get(self, request): 获取QQ登录用户的openi... | Implement the Python class `QQAuthUserView` described below.
Class description:
Implement the QQAuthUserView class.
Method signatures and docstrings:
- def post(self, request): 保存qq登录用户绑定数据 1.获取参数并进行校验（参数完整性，手机号格式，短信验证码是否正确，access_token是否有效） 2.保存绑定用户的数据并签发jwt token 3.返回应答，绑定成功
- def get(self, request): 获取QQ登录用户的openi... | faa4443c11d1534642c8dc9f8262f818f489c554 | <|skeleton|>
class QQAuthUserView:
def post(self, request):
"""保存qq登录用户绑定数据 1.获取参数并进行校验（参数完整性，手机号格式，短信验证码是否正确，access_token是否有效） 2.保存绑定用户的数据并签发jwt token 3.返回应答，绑定成功"""
<|body_0|>
def get(self, request):
"""获取QQ登录用户的openid并处理 1.获取code并校验 2.获取QQ登录用户的openid 2.1根据code请求QQ服务器获取access_token 2... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class QQAuthUserView:
def post(self, request):
"""保存qq登录用户绑定数据 1.获取参数并进行校验（参数完整性，手机号格式，短信验证码是否正确，access_token是否有效） 2.保存绑定用户的数据并签发jwt token 3.返回应答，绑定成功"""
serializer = self.get_serializer(data=request.data)
serializer.is_valid(raise_exception=True)
serializer.save()
response =... | the_stack_v2_python_sparse | Ethanyan_mall/Ethanyan_mall/apps/oauth/views.py | wenmingshuo/E-commerce-sites | train | 0 | |
2ea516eb208dbcaba9b8e26345298187a8e21f67 | [
"self.n = n\nself.m = m\nself.lamb = lamb\nself.R = R\nself.A = A\nself.b = b",
"x = cvx.Variable(self.m)\nprob = cvx.Minimize(0)\nfor i in range(self.n):\n for j in range(len(self.A[i])):\n prob += cvx.Minimize(cvx.logistic(self.A[i][j] * x) - self.b[i][j] * (self.A[i][j] * x))\n prob += cvx.Minimiz... | <|body_start_0|>
self.n = n
self.m = m
self.lamb = lamb
self.R = R
self.A = A
self.b = b
<|end_body_0|>
<|body_start_1|>
x = cvx.Variable(self.m)
prob = cvx.Minimize(0)
for i in range(self.n):
for j in range(len(self.A[i])):
... | Optimal | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Optimal:
def __init__(self, n, m, A, b, lamb, R):
""":param n: int :param m: int :param lamb: float :return: float,float,float"""
<|body_0|>
def optimal(self):
""":return: float, float"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.n = n
... | stack_v2_sparse_classes_75kplus_train_066240 | 1,330 | no_license | [
{
"docstring": ":param n: int :param m: int :param lamb: float :return: float,float,float",
"name": "__init__",
"signature": "def __init__(self, n, m, A, b, lamb, R)"
},
{
"docstring": ":return: float, float",
"name": "optimal",
"signature": "def optimal(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_047298 | Implement the Python class `Optimal` described below.
Class description:
Implement the Optimal class.
Method signatures and docstrings:
- def __init__(self, n, m, A, b, lamb, R): :param n: int :param m: int :param lamb: float :return: float,float,float
- def optimal(self): :return: float, float | Implement the Python class `Optimal` described below.
Class description:
Implement the Optimal class.
Method signatures and docstrings:
- def __init__(self, n, m, A, b, lamb, R): :param n: int :param m: int :param lamb: float :return: float,float,float
- def optimal(self): :return: float, float
<|skeleton|>
class Op... | d64010f2299591f337391c642438a483f670cf61 | <|skeleton|>
class Optimal:
def __init__(self, n, m, A, b, lamb, R):
""":param n: int :param m: int :param lamb: float :return: float,float,float"""
<|body_0|>
def optimal(self):
""":return: float, float"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Optimal:
def __init__(self, n, m, A, b, lamb, R):
""":param n: int :param m: int :param lamb: float :return: float,float,float"""
self.n = n
self.m = m
self.lamb = lamb
self.R = R
self.A = A
self.b = b
def optimal(self):
""":return: float, f... | the_stack_v2_python_sparse | event_trigger_subgrad/optimal.py | kajiyama1126/Doctor_simulation | train | 0 | |
6e7fe974bfdb2964c75073d35c1401f4750fea78 | [
"super(BasicBlock, self).__init__()\nself.conv1 = conv3x3(in_planes, planes, stride)\nself.bn1 = nn.BatchNorm2d(planes)\nself.conv2 = conv3x3(planes, planes)\nself.bn2 = nn.BatchNorm2d(planes)\nself.shortcut = nn.Sequential()\nif stride != 1 or in_planes != self.expansion * planes:\n self.shortcut = nn.Sequentia... | <|body_start_0|>
super(BasicBlock, self).__init__()
self.conv1 = conv3x3(in_planes, planes, stride)
self.bn1 = nn.BatchNorm2d(planes)
self.conv2 = conv3x3(planes, planes)
self.bn2 = nn.BatchNorm2d(planes)
self.shortcut = nn.Sequential()
if stride != 1 or in_planes... | The basic block of ResNet. | BasicBlock | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BasicBlock:
"""The basic block of ResNet."""
def __init__(self, in_planes: int, planes: int, stride: int=1) -> None:
"""Instantiates the basic block of the network. :param in_planes: the number of input channels :param planes: the number of channels (to be possibly expanded)"""
... | stack_v2_sparse_classes_75kplus_train_066241 | 7,594 | permissive | [
{
"docstring": "Instantiates the basic block of the network. :param in_planes: the number of input channels :param planes: the number of channels (to be possibly expanded)",
"name": "__init__",
"signature": "def __init__(self, in_planes: int, planes: int, stride: int=1) -> None"
},
{
"docstring"... | 2 | stack_v2_sparse_classes_30k_train_045789 | Implement the Python class `BasicBlock` described below.
Class description:
The basic block of ResNet.
Method signatures and docstrings:
- def __init__(self, in_planes: int, planes: int, stride: int=1) -> None: Instantiates the basic block of the network. :param in_planes: the number of input channels :param planes: ... | Implement the Python class `BasicBlock` described below.
Class description:
The basic block of ResNet.
Method signatures and docstrings:
- def __init__(self, in_planes: int, planes: int, stride: int=1) -> None: Instantiates the basic block of the network. :param in_planes: the number of input channels :param planes: ... | 0e39b1f4791f0444ed3ee4e8c6fc55bfcc2d001c | <|skeleton|>
class BasicBlock:
"""The basic block of ResNet."""
def __init__(self, in_planes: int, planes: int, stride: int=1) -> None:
"""Instantiates the basic block of the network. :param in_planes: the number of input channels :param planes: the number of channels (to be possibly expanded)"""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class BasicBlock:
"""The basic block of ResNet."""
def __init__(self, in_planes: int, planes: int, stride: int=1) -> None:
"""Instantiates the basic block of the network. :param in_planes: the number of input channels :param planes: the number of channels (to be possibly expanded)"""
super(Basi... | the_stack_v2_python_sparse | backbone/ResNet18.py | wutong8023/Continual-MM | train | 1 |
3b21d808c8e8129510e98e92c54df31b72418480 | [
"super(MultiHeadedAttention, self).__init__()\nassert d_model % h == 0\nself.d_k = d_model // h\nself.h = h\nself.linears = clones(nn.Linear(d_model, d_model), 4)\nself.attn = None\nself.dropout = nn.Dropout(p=dropout)",
"if mask is not None:\n mask = mask.unsqueeze(1)\nnbatches = query.size(0)\nquery, key, va... | <|body_start_0|>
super(MultiHeadedAttention, self).__init__()
assert d_model % h == 0
self.d_k = d_model // h
self.h = h
self.linears = clones(nn.Linear(d_model, d_model), 4)
self.attn = None
self.dropout = nn.Dropout(p=dropout)
<|end_body_0|>
<|body_start_1|>
... | MultiHeadedAttention | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MultiHeadedAttention:
def __init__(self, h, d_model, dropout=0.1):
"""Take in model size and number of heads."""
<|body_0|>
def forward(self, query, key, value, mask=None, num_outputs=1, attn=None, attn_dropout=True, dependent_posterior=0, temperature=None):
"""Imple... | stack_v2_sparse_classes_75kplus_train_066242 | 45,569 | no_license | [
{
"docstring": "Take in model size and number of heads.",
"name": "__init__",
"signature": "def __init__(self, h, d_model, dropout=0.1)"
},
{
"docstring": "Implements Figure 2",
"name": "forward",
"signature": "def forward(self, query, key, value, mask=None, num_outputs=1, attn=None, att... | 2 | stack_v2_sparse_classes_30k_train_007808 | Implement the Python class `MultiHeadedAttention` described below.
Class description:
Implement the MultiHeadedAttention class.
Method signatures and docstrings:
- def __init__(self, h, d_model, dropout=0.1): Take in model size and number of heads.
- def forward(self, query, key, value, mask=None, num_outputs=1, attn... | Implement the Python class `MultiHeadedAttention` described below.
Class description:
Implement the MultiHeadedAttention class.
Method signatures and docstrings:
- def __init__(self, h, d_model, dropout=0.1): Take in model size and number of heads.
- def forward(self, query, key, value, mask=None, num_outputs=1, attn... | 63b69e31239b5676616722b25062b74ad9c399f3 | <|skeleton|>
class MultiHeadedAttention:
def __init__(self, h, d_model, dropout=0.1):
"""Take in model size and number of heads."""
<|body_0|>
def forward(self, query, key, value, mask=None, num_outputs=1, attn=None, attn_dropout=True, dependent_posterior=0, temperature=None):
"""Imple... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MultiHeadedAttention:
def __init__(self, h, d_model, dropout=0.1):
"""Take in model size and number of heads."""
super(MultiHeadedAttention, self).__init__()
assert d_model % h == 0
self.d_k = d_model // h
self.h = h
self.linears = clones(nn.Linear(d_model, d_mo... | the_stack_v2_python_sparse | model.py | da03/energy-network | train | 1 | |
7444b5029f2d1205696058eceaf2a7ba9aafa096 | [
"ret = self.libssock.SCIONListen(self.fd)\nself.port = self.libssock.SCIONGetPort(self.fd)\nreturn ret",
"newfd = self.libssock.SCIONAccept(self.fd)\nlogging.debug('Accepted socket %d' % newfd)\nreturn (ScionBaseSocket(self.proto, self.sciond_addr, newfd), None)"
] | <|body_start_0|>
ret = self.libssock.SCIONListen(self.fd)
self.port = self.libssock.SCIONGetPort(self.fd)
return ret
<|end_body_0|>
<|body_start_1|>
newfd = self.libssock.SCIONAccept(self.fd)
logging.debug('Accepted socket %d' % newfd)
return (ScionBaseSocket(self.proto,... | Server side wrapper of the SCION Multi-Path Socket. | ScionServerSocket | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ScionServerSocket:
"""Server side wrapper of the SCION Multi-Path Socket."""
def listen(self):
"""Setup the socket to receive incoming connection requests. :returns: 0 on success, -1 on failure :rtype: int"""
<|body_0|>
def accept(self):
"""Accepts a connection. ... | stack_v2_sparse_classes_75kplus_train_066243 | 19,489 | permissive | [
{
"docstring": "Setup the socket to receive incoming connection requests. :returns: 0 on success, -1 on failure :rtype: int",
"name": "listen",
"signature": "def listen(self)"
},
{
"docstring": "Accepts a connection. The return value is a pair (conn, address) where conn is a new ScionBaseSocket ... | 2 | stack_v2_sparse_classes_30k_train_014438 | Implement the Python class `ScionServerSocket` described below.
Class description:
Server side wrapper of the SCION Multi-Path Socket.
Method signatures and docstrings:
- def listen(self): Setup the socket to receive incoming connection requests. :returns: 0 on success, -1 on failure :rtype: int
- def accept(self): A... | Implement the Python class `ScionServerSocket` described below.
Class description:
Server side wrapper of the SCION Multi-Path Socket.
Method signatures and docstrings:
- def listen(self): Setup the socket to receive incoming connection requests. :returns: 0 on success, -1 on failure :rtype: int
- def accept(self): A... | 06f3f0b82dc8a535ce8b0a128282af00a8425a06 | <|skeleton|>
class ScionServerSocket:
"""Server side wrapper of the SCION Multi-Path Socket."""
def listen(self):
"""Setup the socket to receive incoming connection requests. :returns: 0 on success, -1 on failure :rtype: int"""
<|body_0|>
def accept(self):
"""Accepts a connection. ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ScionServerSocket:
"""Server side wrapper of the SCION Multi-Path Socket."""
def listen(self):
"""Setup the socket to receive incoming connection requests. :returns: 0 on success, -1 on failure :rtype: int"""
ret = self.libssock.SCIONListen(self.fd)
self.port = self.libssock.SCION... | the_stack_v2_python_sparse | endhost/scion_socket.py | marcoeilers/scion | train | 1 |
6d15a8bef7d7ebcb241c8f923b0370473904210c | [
"self.x_values = x_values\nself.y_values = y_values\nself.poly = np.poly1d(np.polyfit(x_values, y_values, 3))\nself.error = sum(np.square(self.poly(self.x_values) - self.y_values))\nself.min_x = min(x_values)\nself.max_x = max(x_values)",
"if self._deriv is None:\n self._deriv = self.poly.deriv()\nreturn self.... | <|body_start_0|>
self.x_values = x_values
self.y_values = y_values
self.poly = np.poly1d(np.polyfit(x_values, y_values, 3))
self.error = sum(np.square(self.poly(self.x_values) - self.y_values))
self.min_x = min(x_values)
self.max_x = max(x_values)
<|end_body_0|>
<|body_s... | Polynomial of 3rd degree fitted on the given values. | FittedPolynomial | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FittedPolynomial:
"""Polynomial of 3rd degree fitted on the given values."""
def __init__(self, x_values, y_values):
"""Initialize fitted polynomial."""
<|body_0|>
def deriv(self):
"""Return first derivative of the polynomial."""
<|body_1|>
def deriv... | stack_v2_sparse_classes_75kplus_train_066244 | 3,200 | permissive | [
{
"docstring": "Initialize fitted polynomial.",
"name": "__init__",
"signature": "def __init__(self, x_values, y_values)"
},
{
"docstring": "Return first derivative of the polynomial.",
"name": "deriv",
"signature": "def deriv(self)"
},
{
"docstring": "Return real roots of the fi... | 5 | stack_v2_sparse_classes_30k_train_017510 | Implement the Python class `FittedPolynomial` described below.
Class description:
Polynomial of 3rd degree fitted on the given values.
Method signatures and docstrings:
- def __init__(self, x_values, y_values): Initialize fitted polynomial.
- def deriv(self): Return first derivative of the polynomial.
- def deriv_roo... | Implement the Python class `FittedPolynomial` described below.
Class description:
Polynomial of 3rd degree fitted on the given values.
Method signatures and docstrings:
- def __init__(self, x_values, y_values): Initialize fitted polynomial.
- def deriv(self): Return first derivative of the polynomial.
- def deriv_roo... | bae6105812c2f2414d0c10ddd465bf589503f61a | <|skeleton|>
class FittedPolynomial:
"""Polynomial of 3rd degree fitted on the given values."""
def __init__(self, x_values, y_values):
"""Initialize fitted polynomial."""
<|body_0|>
def deriv(self):
"""Return first derivative of the polynomial."""
<|body_1|>
def deriv... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class FittedPolynomial:
"""Polynomial of 3rd degree fitted on the given values."""
def __init__(self, x_values, y_values):
"""Initialize fitted polynomial."""
self.x_values = x_values
self.y_values = y_values
self.poly = np.poly1d(np.polyfit(x_values, y_values, 3))
self.... | the_stack_v2_python_sparse | src/lactolyse/analyses/utils.py | dblenkus/lactolyse | train | 2 |
da817dd980b415840fd0993a05d82e623f44d1e2 | [
"if x < 2:\n return x\nleft, right = (0, x // 2)\nwhile left < right:\n pivot = left + (right - left) // 2\n num = pivot * pivot\n if num < x:\n left = pivot + 1\n elif num > x:\n right = pivot - 1\n else:\n return pivot\nreturn right",
"from math import e, log\nif x < 2:\n ... | <|body_start_0|>
if x < 2:
return x
left, right = (0, x // 2)
while left < right:
pivot = left + (right - left) // 2
num = pivot * pivot
if num < x:
left = pivot + 1
elif num > x:
right = pivot - 1
... | SquareRoot | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SquareRoot:
def answer(self, x: int) -> int:
"""Approach: Binary Search Condition: 0 < 1 < x / 2 Time Complexity: O(log N) Space Complexity: O(1) :param x: :return:"""
<|body_0|>
def answer_(self, x: int) -> int:
"""Approach: Pocket Calculator Time Complexity: O(1) S... | stack_v2_sparse_classes_75kplus_train_066245 | 1,291 | no_license | [
{
"docstring": "Approach: Binary Search Condition: 0 < 1 < x / 2 Time Complexity: O(log N) Space Complexity: O(1) :param x: :return:",
"name": "answer",
"signature": "def answer(self, x: int) -> int"
},
{
"docstring": "Approach: Pocket Calculator Time Complexity: O(1) Space Complexity: O(1) :par... | 2 | null | Implement the Python class `SquareRoot` described below.
Class description:
Implement the SquareRoot class.
Method signatures and docstrings:
- def answer(self, x: int) -> int: Approach: Binary Search Condition: 0 < 1 < x / 2 Time Complexity: O(log N) Space Complexity: O(1) :param x: :return:
- def answer_(self, x: i... | Implement the Python class `SquareRoot` described below.
Class description:
Implement the SquareRoot class.
Method signatures and docstrings:
- def answer(self, x: int) -> int: Approach: Binary Search Condition: 0 < 1 < x / 2 Time Complexity: O(log N) Space Complexity: O(1) :param x: :return:
- def answer_(self, x: i... | 65cc78b5afa0db064f9fe8f06597e3e120f7363d | <|skeleton|>
class SquareRoot:
def answer(self, x: int) -> int:
"""Approach: Binary Search Condition: 0 < 1 < x / 2 Time Complexity: O(log N) Space Complexity: O(1) :param x: :return:"""
<|body_0|>
def answer_(self, x: int) -> int:
"""Approach: Pocket Calculator Time Complexity: O(1) S... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SquareRoot:
def answer(self, x: int) -> int:
"""Approach: Binary Search Condition: 0 < 1 < x / 2 Time Complexity: O(log N) Space Complexity: O(1) :param x: :return:"""
if x < 2:
return x
left, right = (0, x // 2)
while left < right:
pivot = left + (right... | the_stack_v2_python_sparse | revisited_2021/math_and_string/square_root.py | Shiv2157k/leet_code | train | 1 | |
6639a52fe035376e27d36b6c69b3fa15f564f458 | [
"self.sum_hit_at_one = 0.0\nself.sum_perr = 0.0\nself.sum_loss = 0.0\nself.map_calculator = map_calculator.MeanAveragePrecisionCalculator(num_class)\nself.global_ap_calculator = ap_calculator.AveragePrecisionCalculator()\nself.pr_calculator = PRCalculator()\nself.pr_calculator_per_tag = PRCalculatorPerTag(num_class... | <|body_start_0|>
self.sum_hit_at_one = 0.0
self.sum_perr = 0.0
self.sum_loss = 0.0
self.map_calculator = map_calculator.MeanAveragePrecisionCalculator(num_class)
self.global_ap_calculator = ap_calculator.AveragePrecisionCalculator()
self.pr_calculator = PRCalculator()
... | A class to store the evaluation metrics. | EvaluationMetrics | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EvaluationMetrics:
"""A class to store the evaluation metrics."""
def __init__(self, num_class, top_k, accumulate_per_tag=False):
"""Construct an EvaluationMetrics object to store the evaluation metrics. Args: num_class: A positive integer specifying the number of classes. top_k: A p... | stack_v2_sparse_classes_75kplus_train_066246 | 24,184 | no_license | [
{
"docstring": "Construct an EvaluationMetrics object to store the evaluation metrics. Args: num_class: A positive integer specifying the number of classes. top_k: A positive integer specifying how many predictions are considered per video. Raises: ValueError: An error occurred when MeanAveragePrecisionCalculat... | 4 | stack_v2_sparse_classes_30k_train_047500 | Implement the Python class `EvaluationMetrics` described below.
Class description:
A class to store the evaluation metrics.
Method signatures and docstrings:
- def __init__(self, num_class, top_k, accumulate_per_tag=False): Construct an EvaluationMetrics object to store the evaluation metrics. Args: num_class: A posi... | Implement the Python class `EvaluationMetrics` described below.
Class description:
A class to store the evaluation metrics.
Method signatures and docstrings:
- def __init__(self, num_class, top_k, accumulate_per_tag=False): Construct an EvaluationMetrics object to store the evaluation metrics. Args: num_class: A posi... | aa5083f15e68b637403cd96bd43633b93dc59844 | <|skeleton|>
class EvaluationMetrics:
"""A class to store the evaluation metrics."""
def __init__(self, num_class, top_k, accumulate_per_tag=False):
"""Construct an EvaluationMetrics object to store the evaluation metrics. Args: num_class: A positive integer specifying the number of classes. top_k: A p... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class EvaluationMetrics:
"""A class to store the evaluation metrics."""
def __init__(self, num_class, top_k, accumulate_per_tag=False):
"""Construct an EvaluationMetrics object to store the evaluation metrics. Args: num_class: A positive integer specifying the number of classes. top_k: A positive integ... | the_stack_v2_python_sparse | utils/train_util.py | hezhiqian01/MultiModal-Tagging | train | 4 |
d5cacbf48d08affed6a6fb7e4d4c55059bd4b274 | [
"self.num = num\nfor i, x in enumerate(events):\n if 'addC' in x.Event:\n for y in range(i + 1, i + PLAYER_COUNT):\n events[y].Event = dict()\nbidRows = filter(lambda x: 'bid' in x.Event, events)\nplayRows = filter(lambda x: 'playC' in x.Event, events)\nscoreRow = filter(lambda x: 'sco' in x.Ev... | <|body_start_0|>
self.num = num
for i, x in enumerate(events):
if 'addC' in x.Event:
for y in range(i + 1, i + PLAYER_COUNT):
events[y].Event = dict()
bidRows = filter(lambda x: 'bid' in x.Event, events)
playRows = filter(lambda x: 'playC' ... | Helper class for parsing game logs. Attributes: num (int): The hand number within the game. trump (int): The trump for the hand. bids (dict): With the keys: - values (list): Bid amounts in pNum order (list index == pNum). - dealer (int): pNum of dealer. - winner (int): pNum of bid winner. tricks (list): Each element is... | Hand | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Hand:
"""Helper class for parsing game logs. Attributes: num (int): The hand number within the game. trump (int): The trump for the hand. bids (dict): With the keys: - values (list): Bid amounts in pNum order (list index == pNum). - dealer (int): pNum of dealer. - winner (int): pNum of bid winner... | stack_v2_sparse_classes_75kplus_train_066247 | 5,091 | permissive | [
{
"docstring": "Process events and store hand data. Args: num (int): Hand number events (list): List of events for this hand.",
"name": "__init__",
"signature": "def __init__(self, num, events)"
},
{
"docstring": "Set the bids attribute for the Hand. The 'actvP' in the final bid is the bid winne... | 4 | stack_v2_sparse_classes_30k_train_002248 | Implement the Python class `Hand` described below.
Class description:
Helper class for parsing game logs. Attributes: num (int): The hand number within the game. trump (int): The trump for the hand. bids (dict): With the keys: - values (list): Bid amounts in pNum order (list index == pNum). - dealer (int): pNum of dea... | Implement the Python class `Hand` described below.
Class description:
Helper class for parsing game logs. Attributes: num (int): The hand number within the game. trump (int): The trump for the hand. bids (dict): With the keys: - values (list): Bid amounts in pNum order (list index == pNum). - dealer (int): pNum of dea... | f8b9e8c073f555ff827fa7887153e82b263a8aab | <|skeleton|>
class Hand:
"""Helper class for parsing game logs. Attributes: num (int): The hand number within the game. trump (int): The trump for the hand. bids (dict): With the keys: - values (list): Bid amounts in pNum order (list index == pNum). - dealer (int): pNum of dealer. - winner (int): pNum of bid winner... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Hand:
"""Helper class for parsing game logs. Attributes: num (int): The hand number within the game. trump (int): The trump for the hand. bids (dict): With the keys: - values (list): Bid amounts in pNum order (list index == pNum). - dealer (int): pNum of dealer. - winner (int): pNum of bid winner. tricks (lis... | the_stack_v2_python_sparse | db/parseLog.py | JackieChiles/Cinch | train | 2 |
331e2ff3c5f8d31e5f2a7d34eded954dca5e6759 | [
"bert = BertModel.shared(config=config, name='bert')\nsequence_output, pooled_output = bert(input_ids, input_mask, type_ids, deterministic=deterministic)\nif masked_lm_positions is None:\n return (sequence_output, pooled_output)\nmasked_lm_input = GatherIndexes(sequence_output, masked_lm_positions)\nmasked_lm_in... | <|body_start_0|>
bert = BertModel.shared(config=config, name='bert')
sequence_output, pooled_output = bert(input_ids, input_mask, type_ids, deterministic=deterministic)
if masked_lm_positions is None:
return (sequence_output, pooled_output)
masked_lm_input = GatherIndexes(seq... | Bert model for pre-training. | BertForPreTraining | [
"CC-BY-4.0",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BertForPreTraining:
"""Bert model for pre-training."""
def apply(self, input_ids, input_mask, type_ids, masked_lm_positions=None, masked_lm_labels=None, masked_lm_weights=None, next_sentence_labels=None, *, config, deterministic=False):
"""Applies BERT for pre-training."""
<|... | stack_v2_sparse_classes_75kplus_train_066248 | 8,883 | permissive | [
{
"docstring": "Applies BERT for pre-training.",
"name": "apply",
"signature": "def apply(self, input_ids, input_mask, type_ids, masked_lm_positions=None, masked_lm_labels=None, masked_lm_weights=None, next_sentence_labels=None, *, config, deterministic=False)"
},
{
"docstring": "Computes the pr... | 2 | stack_v2_sparse_classes_30k_train_026644 | Implement the Python class `BertForPreTraining` described below.
Class description:
Bert model for pre-training.
Method signatures and docstrings:
- def apply(self, input_ids, input_mask, type_ids, masked_lm_positions=None, masked_lm_labels=None, masked_lm_weights=None, next_sentence_labels=None, *, config, determini... | Implement the Python class `BertForPreTraining` described below.
Class description:
Bert model for pre-training.
Method signatures and docstrings:
- def apply(self, input_ids, input_mask, type_ids, masked_lm_positions=None, masked_lm_labels=None, masked_lm_weights=None, next_sentence_labels=None, *, config, determini... | 0714e9a5a3934d922c0b9dd017943a8e511eb5bc | <|skeleton|>
class BertForPreTraining:
"""Bert model for pre-training."""
def apply(self, input_ids, input_mask, type_ids, masked_lm_positions=None, masked_lm_labels=None, masked_lm_weights=None, next_sentence_labels=None, *, config, deterministic=False):
"""Applies BERT for pre-training."""
<|... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class BertForPreTraining:
"""Bert model for pre-training."""
def apply(self, input_ids, input_mask, type_ids, masked_lm_positions=None, masked_lm_labels=None, masked_lm_weights=None, next_sentence_labels=None, *, config, deterministic=False):
"""Applies BERT for pre-training."""
bert = BertMode... | the_stack_v2_python_sparse | flax_models/bert/models.py | pdybczak/google-research | train | 1 |
122a88d597095b1ec328c2f67925de2182365551 | [
"self.env.revert_snapshot('deploy_ha_influxdb_grafana')\nmanipulated_node = {'slave-03': ['controller']}\nself.helpers.remove_nodes_from_cluster(manipulated_node)\nself.check_plugin_online()\nself.helpers.run_ostf(should_fail=1)\nself.helpers.add_nodes_to_cluster(manipulated_node)\nself.check_plugin_online()\nself.... | <|body_start_0|>
self.env.revert_snapshot('deploy_ha_influxdb_grafana')
manipulated_node = {'slave-03': ['controller']}
self.helpers.remove_nodes_from_cluster(manipulated_node)
self.check_plugin_online()
self.helpers.run_ostf(should_fail=1)
self.helpers.add_nodes_to_clust... | Class for system tests for InfluxDB-Grafana plugin. | TestNodesInfluxdbPlugin | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestNodesInfluxdbPlugin:
"""Class for system tests for InfluxDB-Grafana plugin."""
def add_remove_controller_influxdb_grafana(self):
"""Verify that the number of controllers can scale up and down Scenario: 1. Revert snapshot with 9 deployed nodes in HA configuration 2. Remove one con... | stack_v2_sparse_classes_75kplus_train_066249 | 7,472 | no_license | [
{
"docstring": "Verify that the number of controllers can scale up and down Scenario: 1. Revert snapshot with 9 deployed nodes in HA configuration 2. Remove one controller node and update the cluster 3. Check that plugin is working 4. Run OSTF 5. Add one controller node (return previous state) and update the cl... | 5 | stack_v2_sparse_classes_30k_train_000375 | Implement the Python class `TestNodesInfluxdbPlugin` described below.
Class description:
Class for system tests for InfluxDB-Grafana plugin.
Method signatures and docstrings:
- def add_remove_controller_influxdb_grafana(self): Verify that the number of controllers can scale up and down Scenario: 1. Revert snapshot wi... | Implement the Python class `TestNodesInfluxdbPlugin` described below.
Class description:
Class for system tests for InfluxDB-Grafana plugin.
Method signatures and docstrings:
- def add_remove_controller_influxdb_grafana(self): Verify that the number of controllers can scale up and down Scenario: 1. Revert snapshot wi... | 179249df2d206eeabb3955c9dc8cb78cac3c36c6 | <|skeleton|>
class TestNodesInfluxdbPlugin:
"""Class for system tests for InfluxDB-Grafana plugin."""
def add_remove_controller_influxdb_grafana(self):
"""Verify that the number of controllers can scale up and down Scenario: 1. Revert snapshot with 9 deployed nodes in HA configuration 2. Remove one con... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TestNodesInfluxdbPlugin:
"""Class for system tests for InfluxDB-Grafana plugin."""
def add_remove_controller_influxdb_grafana(self):
"""Verify that the number of controllers can scale up and down Scenario: 1. Revert snapshot with 9 deployed nodes in HA configuration 2. Remove one controller node ... | the_stack_v2_python_sparse | stacklight_tests/influxdb_grafana/test_system.py | rkhozinov/stacklight-integration-tests | train | 1 |
e1f2c067e1b18b0688adaa425b177c218225e8e7 | [
"super(ResNet, self).__init__()\nself.blocks = blocks\nself.in_channels = in_channels\nself.num_classes = num_classes\nself.global_pool = global_pool\nself.output_stride = output_stride\nself.include_root_block = include_root_block\nself.conv2d_same = Conv2dSame(self.in_channels, 64, 7, 2)\nself.max_pool2d = nn.Max... | <|body_start_0|>
super(ResNet, self).__init__()
self.blocks = blocks
self.in_channels = in_channels
self.num_classes = num_classes
self.global_pool = global_pool
self.output_stride = output_stride
self.include_root_block = include_root_block
self.conv2d_sa... | Resnet | ResNet | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference",
"LicenseRef-scancode-proprietary-license"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ResNet:
"""Resnet"""
def __init__(self, blocks, in_channels, num_classes=None, global_pool=True, output_stride=None, include_root_block=True):
"""Args: blocks: blocks config. should be generated by _make_block in_channels: in channels num_classes: the number of classes global_pool: I... | stack_v2_sparse_classes_75kplus_train_066250 | 11,719 | permissive | [
{
"docstring": "Args: blocks: blocks config. should be generated by _make_block in_channels: in channels num_classes: the number of classes global_pool: If True, we perform global average pooling before computing the logits. Set to True for image classification, False for dense prediction. output_stride: If Non... | 2 | stack_v2_sparse_classes_30k_train_047409 | Implement the Python class `ResNet` described below.
Class description:
Resnet
Method signatures and docstrings:
- def __init__(self, blocks, in_channels, num_classes=None, global_pool=True, output_stride=None, include_root_block=True): Args: blocks: blocks config. should be generated by _make_block in_channels: in c... | Implement the Python class `ResNet` described below.
Class description:
Resnet
Method signatures and docstrings:
- def __init__(self, blocks, in_channels, num_classes=None, global_pool=True, output_stride=None, include_root_block=True): Args: blocks: blocks config. should be generated by _make_block in_channels: in c... | eab643f51336dbf7d711f02d27e6516e5affee59 | <|skeleton|>
class ResNet:
"""Resnet"""
def __init__(self, blocks, in_channels, num_classes=None, global_pool=True, output_stride=None, include_root_block=True):
"""Args: blocks: blocks config. should be generated by _make_block in_channels: in channels num_classes: the number of classes global_pool: I... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ResNet:
"""Resnet"""
def __init__(self, blocks, in_channels, num_classes=None, global_pool=True, output_stride=None, include_root_block=True):
"""Args: blocks: blocks config. should be generated by _make_block in_channels: in channels num_classes: the number of classes global_pool: If True, we pe... | the_stack_v2_python_sparse | research/cv/ArtTrack/src/model/resnet/resnet.py | mindspore-ai/models | train | 301 |
4829de30ea0dc00650aac0d42f868ebdf300f416 | [
"self._parameters = parameters\nself._mapper = OCPGCPProviderMap(provider=self.provider, report_type=parameters.report_type)\nif parameters.get_filter('enabled') is None:\n parameters.set_filter(**{'enabled': True})\nsuper().__init__(parameters)",
"filter_map = deepcopy(TagQueryHandler.FILTER_MAP)\nif self._pa... | <|body_start_0|>
self._parameters = parameters
self._mapper = OCPGCPProviderMap(provider=self.provider, report_type=parameters.report_type)
if parameters.get_filter('enabled') is None:
parameters.set_filter(**{'enabled': True})
super().__init__(parameters)
<|end_body_0|>
<|b... | Handles tag queries and responses for OCP-on-GCP. | OCPGCPTagQueryHandler | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OCPGCPTagQueryHandler:
"""Handles tag queries and responses for OCP-on-GCP."""
def __init__(self, parameters):
"""Establish GCP report query handler. Args: parameters (QueryParameters): parameter object for query"""
<|body_0|>
def filter_map(self):
"""Establish w... | stack_v2_sparse_classes_75kplus_train_066251 | 3,966 | permissive | [
{
"docstring": "Establish GCP report query handler. Args: parameters (QueryParameters): parameter object for query",
"name": "__init__",
"signature": "def __init__(self, parameters)"
},
{
"docstring": "Establish which filter map to use based on tag API.",
"name": "filter_map",
"signature... | 2 | stack_v2_sparse_classes_30k_train_030827 | Implement the Python class `OCPGCPTagQueryHandler` described below.
Class description:
Handles tag queries and responses for OCP-on-GCP.
Method signatures and docstrings:
- def __init__(self, parameters): Establish GCP report query handler. Args: parameters (QueryParameters): parameter object for query
- def filter_m... | Implement the Python class `OCPGCPTagQueryHandler` described below.
Class description:
Handles tag queries and responses for OCP-on-GCP.
Method signatures and docstrings:
- def __init__(self, parameters): Establish GCP report query handler. Args: parameters (QueryParameters): parameter object for query
- def filter_m... | 0416e5216eb1ec4b41c8dd4999adde218b1ab2e1 | <|skeleton|>
class OCPGCPTagQueryHandler:
"""Handles tag queries and responses for OCP-on-GCP."""
def __init__(self, parameters):
"""Establish GCP report query handler. Args: parameters (QueryParameters): parameter object for query"""
<|body_0|>
def filter_map(self):
"""Establish w... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class OCPGCPTagQueryHandler:
"""Handles tag queries and responses for OCP-on-GCP."""
def __init__(self, parameters):
"""Establish GCP report query handler. Args: parameters (QueryParameters): parameter object for query"""
self._parameters = parameters
self._mapper = OCPGCPProviderMap(pr... | the_stack_v2_python_sparse | koku/api/tags/gcp/openshift/queries.py | project-koku/koku | train | 225 |
c66654e5ce8afdd80b6d98ce11865674951ace1c | [
"self.Wh = np.random.randn(i + h, h)\nself.Wy = np.random.randn(h, o)\nself.bh = np.zeros((1, h))\nself.by = np.zeros((1, o))",
"Exp = np.exp(h)\nExp = Exp / np.sum(Exp, 1, keepdims=True)\nreturn Exp",
"h_next = np.tanh(np.hstack((h_prev, x_t)) @ self.Wh + self.bh)\ny = self.softmax(h_next @ self.Wy + self.by)\... | <|body_start_0|>
self.Wh = np.random.randn(i + h, h)
self.Wy = np.random.randn(h, o)
self.bh = np.zeros((1, h))
self.by = np.zeros((1, o))
<|end_body_0|>
<|body_start_1|>
Exp = np.exp(h)
Exp = Exp / np.sum(Exp, 1, keepdims=True)
return Exp
<|end_body_1|>
<|body_... | represents a cell of a simple RNN | RNNCell | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RNNCell:
"""represents a cell of a simple RNN"""
def __init__(self, i, h, o):
"""Class constructor"""
<|body_0|>
def softmax(h):
"""softmax activation function"""
<|body_1|>
def forward(self, h_prev, x_t):
"""represent the weights and biases ... | stack_v2_sparse_classes_75kplus_train_066252 | 855 | no_license | [
{
"docstring": "Class constructor",
"name": "__init__",
"signature": "def __init__(self, i, h, o)"
},
{
"docstring": "softmax activation function",
"name": "softmax",
"signature": "def softmax(h)"
},
{
"docstring": "represent the weights and biases of the cell",
"name": "forw... | 3 | stack_v2_sparse_classes_30k_train_011436 | Implement the Python class `RNNCell` described below.
Class description:
represents a cell of a simple RNN
Method signatures and docstrings:
- def __init__(self, i, h, o): Class constructor
- def softmax(h): softmax activation function
- def forward(self, h_prev, x_t): represent the weights and biases of the cell | Implement the Python class `RNNCell` described below.
Class description:
represents a cell of a simple RNN
Method signatures and docstrings:
- def __init__(self, i, h, o): Class constructor
- def softmax(h): softmax activation function
- def forward(self, h_prev, x_t): represent the weights and biases of the cell
<|... | c23deee331a71a089197547fcae4c1eefb8d24ef | <|skeleton|>
class RNNCell:
"""represents a cell of a simple RNN"""
def __init__(self, i, h, o):
"""Class constructor"""
<|body_0|>
def softmax(h):
"""softmax activation function"""
<|body_1|>
def forward(self, h_prev, x_t):
"""represent the weights and biases ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class RNNCell:
"""represents a cell of a simple RNN"""
def __init__(self, i, h, o):
"""Class constructor"""
self.Wh = np.random.randn(i + h, h)
self.Wy = np.random.randn(h, o)
self.bh = np.zeros((1, h))
self.by = np.zeros((1, o))
def softmax(h):
"""softmax a... | the_stack_v2_python_sparse | supervised_learning/0x0D-RNNs/0-rnn_cell.py | YosriGFX/holbertonschool-machine_learning | train | 0 |
ffbcf06dfb4ca6f267808f4235baf87d86dcaf11 | [
"E0 = a0 * m_e * c ** 2 * k0 / e\nself.k0 = k0\nself.waist = waist\nself.inv_tau = 1.0 / tau\nself.t_peak = t_peak\nself.E0 = E0\nself.v_antenna = source_v\nself.boost = boost\nself.temporal_order = temporal_order\nself.theta_zx = theta_zx\nself.x_center = x_center\nself.geom_coeff = get_geometric_coeff(dim)",
"t... | <|body_start_0|>
E0 = a0 * m_e * c ** 2 * k0 / e
self.k0 = k0
self.waist = waist
self.inv_tau = 1.0 / tau
self.t_peak = t_peak
self.E0 = E0
self.v_antenna = source_v
self.boost = boost
self.temporal_order = temporal_order
self.theta_zx = th... | Class that calculates a laser pulse with transverse Jinc profile, longitudinal Gaussian profile and propagating at an arbitrary angle with respect to z. | JincGaussianAngleProfile | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class JincGaussianAngleProfile:
"""Class that calculates a laser pulse with transverse Jinc profile, longitudinal Gaussian profile and propagating at an arbitrary angle with respect to z."""
def __init__(self, k0, waist, tau, t_peak, a0, dim, temporal_order=2, boost=None, source_v=0, theta_zx=0.0,... | stack_v2_sparse_classes_75kplus_train_066253 | 34,589 | permissive | [
{
"docstring": "Define a laser profile with is a Jinc function transversely and a supergaussian function longitudinally. The antenna is orthogonal to z, but this profile supports a non-zero angle in the (z, x) plane, and is compatible with the boosted frame and a moving window. Note 1: The focal plane is the pl... | 2 | stack_v2_sparse_classes_30k_train_028748 | Implement the Python class `JincGaussianAngleProfile` described below.
Class description:
Class that calculates a laser pulse with transverse Jinc profile, longitudinal Gaussian profile and propagating at an arbitrary angle with respect to z.
Method signatures and docstrings:
- def __init__(self, k0, waist, tau, t_pe... | Implement the Python class `JincGaussianAngleProfile` described below.
Class description:
Class that calculates a laser pulse with transverse Jinc profile, longitudinal Gaussian profile and propagating at an arbitrary angle with respect to z.
Method signatures and docstrings:
- def __init__(self, k0, waist, tau, t_pe... | 091c982f82788209017315e13eb7d0e743687d46 | <|skeleton|>
class JincGaussianAngleProfile:
"""Class that calculates a laser pulse with transverse Jinc profile, longitudinal Gaussian profile and propagating at an arbitrary angle with respect to z."""
def __init__(self, k0, waist, tau, t_peak, a0, dim, temporal_order=2, boost=None, source_v=0, theta_zx=0.0,... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class JincGaussianAngleProfile:
"""Class that calculates a laser pulse with transverse Jinc profile, longitudinal Gaussian profile and propagating at an arbitrary angle with respect to z."""
def __init__(self, k0, waist, tau, t_peak, a0, dim, temporal_order=2, boost=None, source_v=0, theta_zx=0.0, x_center=0.0... | the_stack_v2_python_sparse | scripts/field_solvers/laser/laser_profiles.py | giadarol/warp | train | 0 |
eaed4300547a49bf6e86ad1ce1b1c709c9a25b92 | [
"self.access_zone_id = access_zone_id\nself.description = description\nself.share_name = share_name",
"if dictionary is None:\n return None\naccess_zone_id = dictionary.get('accessZoneId')\ndescription = dictionary.get('description')\nshare_name = dictionary.get('shareName')\nreturn cls(access_zone_id, descrip... | <|body_start_0|>
self.access_zone_id = access_zone_id
self.description = description
self.share_name = share_name
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
access_zone_id = dictionary.get('accessZoneId')
description = dictionary.get('... | Implementation of the 'IsilonSmbMountPoint' model. Specifies information specific to SMB shares exposed by Isilon file system. Attributes: access_zone_id (long|int): Specifies the Access Zone Id. description (string): Specifies the description of the NFS mount point. share_name (string): Specifies the name of the SMB/C... | IsilonSmbMountPoint | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IsilonSmbMountPoint:
"""Implementation of the 'IsilonSmbMountPoint' model. Specifies information specific to SMB shares exposed by Isilon file system. Attributes: access_zone_id (long|int): Specifies the Access Zone Id. description (string): Specifies the description of the NFS mount point. share... | stack_v2_sparse_classes_75kplus_train_066254 | 1,925 | permissive | [
{
"docstring": "Constructor for the IsilonSmbMountPoint class",
"name": "__init__",
"signature": "def __init__(self, access_zone_id=None, description=None, share_name=None)"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: dictionary (dictionary): A dictionary represe... | 2 | stack_v2_sparse_classes_30k_val_000527 | Implement the Python class `IsilonSmbMountPoint` described below.
Class description:
Implementation of the 'IsilonSmbMountPoint' model. Specifies information specific to SMB shares exposed by Isilon file system. Attributes: access_zone_id (long|int): Specifies the Access Zone Id. description (string): Specifies the de... | Implement the Python class `IsilonSmbMountPoint` described below.
Class description:
Implementation of the 'IsilonSmbMountPoint' model. Specifies information specific to SMB shares exposed by Isilon file system. Attributes: access_zone_id (long|int): Specifies the Access Zone Id. description (string): Specifies the de... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class IsilonSmbMountPoint:
"""Implementation of the 'IsilonSmbMountPoint' model. Specifies information specific to SMB shares exposed by Isilon file system. Attributes: access_zone_id (long|int): Specifies the Access Zone Id. description (string): Specifies the description of the NFS mount point. share... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class IsilonSmbMountPoint:
"""Implementation of the 'IsilonSmbMountPoint' model. Specifies information specific to SMB shares exposed by Isilon file system. Attributes: access_zone_id (long|int): Specifies the Access Zone Id. description (string): Specifies the description of the NFS mount point. share_name (string... | the_stack_v2_python_sparse | cohesity_management_sdk/models/isilon_smb_mount_point.py | cohesity/management-sdk-python | train | 24 |
79c7025eef0c00e5531062fc253b8ce6ef85cb1f | [
"super().__init__(data, seed=seed, shuffle=shuffle)\nif fields_to_merge is not None:\n if merged_field is not None:\n log.info('Merging fields <<{}>> to new field <<{}>>'.format(fields_to_merge, merged_field))\n self._merge_data(fields_to_merge=fields_to_merge, merged_field=merged_field)\n else:... | <|body_start_0|>
super().__init__(data, seed=seed, shuffle=shuffle)
if fields_to_merge is not None:
if merged_field is not None:
log.info('Merging fields <<{}>> to new field <<{}>>'.format(fields_to_merge, merged_field))
self._merge_data(fields_to_merge=fields... | Class gets data dictionary from DatasetReader instance, merge fields if necessary, split a field if necessary Args: data: dictionary of data with fields "train", "valid" and "test" (or some of them) fields_to_merge: list of fields (out of ``"train", "valid", "test"``) to merge merged_field: name of field (out of ``"tra... | BasicClassificationDatasetIterator | [
"Python-2.0",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BasicClassificationDatasetIterator:
"""Class gets data dictionary from DatasetReader instance, merge fields if necessary, split a field if necessary Args: data: dictionary of data with fields "train", "valid" and "test" (or some of them) fields_to_merge: list of fields (out of ``"train", "valid",... | stack_v2_sparse_classes_75kplus_train_066255 | 5,935 | permissive | [
{
"docstring": "Initialize dataset using data from DatasetReader, merges and splits fields according to the given parameters.",
"name": "__init__",
"signature": "def __init__(self, data: dict, fields_to_merge: List[str]=None, merged_field: str=None, field_to_split: str=None, split_fields: List[str]=None... | 3 | stack_v2_sparse_classes_30k_train_010959 | Implement the Python class `BasicClassificationDatasetIterator` described below.
Class description:
Class gets data dictionary from DatasetReader instance, merge fields if necessary, split a field if necessary Args: data: dictionary of data with fields "train", "valid" and "test" (or some of them) fields_to_merge: lis... | Implement the Python class `BasicClassificationDatasetIterator` described below.
Class description:
Class gets data dictionary from DatasetReader instance, merge fields if necessary, split a field if necessary Args: data: dictionary of data with fields "train", "valid" and "test" (or some of them) fields_to_merge: lis... | 65f69dfb898f5444cc2c98ae03ec7b3f44266df2 | <|skeleton|>
class BasicClassificationDatasetIterator:
"""Class gets data dictionary from DatasetReader instance, merge fields if necessary, split a field if necessary Args: data: dictionary of data with fields "train", "valid" and "test" (or some of them) fields_to_merge: list of fields (out of ``"train", "valid",... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class BasicClassificationDatasetIterator:
"""Class gets data dictionary from DatasetReader instance, merge fields if necessary, split a field if necessary Args: data: dictionary of data with fields "train", "valid" and "test" (or some of them) fields_to_merge: list of fields (out of ``"train", "valid", "test"``) to... | the_stack_v2_python_sparse | deeppavlov/dataset_iterators/basic_classification_iterator.py | vintagexav/DeepPavlov | train | 2 |
716a49e260e69a61f581213e629fd5c4cc6b6470 | [
"delay = 0\nrow = []\nfor val in prev:\n row.append(val + delay)\n delay = val\nrow.append(delay)\nreturn row",
"self.tri = []\nif numRows >= 1:\n self.tri.append([1])\nif numRows >= 2:\n self.tri.append([1, 1])\ni = 3\nwhile i <= numRows:\n self.tri.append(self.nextRow(self.tri[-1]))\n i = i + ... | <|body_start_0|>
delay = 0
row = []
for val in prev:
row.append(val + delay)
delay = val
row.append(delay)
return row
<|end_body_0|>
<|body_start_1|>
self.tri = []
if numRows >= 1:
self.tri.append([1])
if numRows >= 2:
... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def nextRow(self, prev):
""":type prev: List[int] :rtype: List[int] difference equation: y(n) = x(n) + x(n-1)"""
<|body_0|>
def generate(self, numRows):
""":type numRows: int :rtype: List[List[int]]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_75kplus_train_066256 | 1,004 | permissive | [
{
"docstring": ":type prev: List[int] :rtype: List[int] difference equation: y(n) = x(n) + x(n-1)",
"name": "nextRow",
"signature": "def nextRow(self, prev)"
},
{
"docstring": ":type numRows: int :rtype: List[List[int]]",
"name": "generate",
"signature": "def generate(self, numRows)"
}... | 2 | stack_v2_sparse_classes_30k_train_050413 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def nextRow(self, prev): :type prev: List[int] :rtype: List[int] difference equation: y(n) = x(n) + x(n-1)
- def generate(self, numRows): :type numRows: int :rtype: List[List[int... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def nextRow(self, prev): :type prev: List[int] :rtype: List[int] difference equation: y(n) = x(n) + x(n-1)
- def generate(self, numRows): :type numRows: int :rtype: List[List[int... | 0521e27097a01a0a2ba2af30f3185d8bb5e3e227 | <|skeleton|>
class Solution:
def nextRow(self, prev):
""":type prev: List[int] :rtype: List[int] difference equation: y(n) = x(n) + x(n-1)"""
<|body_0|>
def generate(self, numRows):
""":type numRows: int :rtype: List[List[int]]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def nextRow(self, prev):
""":type prev: List[int] :rtype: List[int] difference equation: y(n) = x(n) + x(n-1)"""
delay = 0
row = []
for val in prev:
row.append(val + delay)
delay = val
row.append(delay)
return row
def gener... | the_stack_v2_python_sparse | P118-PascalsTriangle/main.py | rlan/LeetCode | train | 0 | |
9ba89c3cee2ffc636c9107167a553c07f1fc1597 | [
"self.assertTrue(reverse('abc') == 'cba')\nself.assertTrue(reverse('abd') == 'cba')\nself.assertTrue(reverse('abc') == 'abc')",
"self.assertTrue(list(rev_enumerate('Python')) == [(5, 'n'), (4, 'o'), (3, 'h'), (2, 't'), (1, 'y'), (0, 'P')])\nself.assertTrue(list(rev_enumerate('hell')) == [(4, 'o'), (3, 'l'), (2, '... | <|body_start_0|>
self.assertTrue(reverse('abc') == 'cba')
self.assertTrue(reverse('abd') == 'cba')
self.assertTrue(reverse('abc') == 'abc')
<|end_body_0|>
<|body_start_1|>
self.assertTrue(list(rev_enumerate('Python')) == [(5, 'n'), (4, 'o'), (3, 'h'), (2, 't'), (1, 'y'), (0, 'P')])
... | TestString | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestString:
def test_reverse(self):
"""to verify that reverse works properly"""
<|body_0|>
def test_rev_enumerate(self):
"""to verify that rev_enumerate works"""
<|body_1|>
def test_find_second(self):
"""to verify that find_second works"""
... | stack_v2_sparse_classes_75kplus_train_066257 | 1,556 | no_license | [
{
"docstring": "to verify that reverse works properly",
"name": "test_reverse",
"signature": "def test_reverse(self)"
},
{
"docstring": "to verify that rev_enumerate works",
"name": "test_rev_enumerate",
"signature": "def test_rev_enumerate(self)"
},
{
"docstring": "to verify tha... | 4 | null | Implement the Python class `TestString` described below.
Class description:
Implement the TestString class.
Method signatures and docstrings:
- def test_reverse(self): to verify that reverse works properly
- def test_rev_enumerate(self): to verify that rev_enumerate works
- def test_find_second(self): to verify that ... | Implement the Python class `TestString` described below.
Class description:
Implement the TestString class.
Method signatures and docstrings:
- def test_reverse(self): to verify that reverse works properly
- def test_rev_enumerate(self): to verify that rev_enumerate works
- def test_find_second(self): to verify that ... | 228897e2a76c45b5c7c7e40711cfd81adf1037cb | <|skeleton|>
class TestString:
def test_reverse(self):
"""to verify that reverse works properly"""
<|body_0|>
def test_rev_enumerate(self):
"""to verify that rev_enumerate works"""
<|body_1|>
def test_find_second(self):
"""to verify that find_second works"""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TestString:
def test_reverse(self):
"""to verify that reverse works properly"""
self.assertTrue(reverse('abc') == 'cba')
self.assertTrue(reverse('abd') == 'cba')
self.assertTrue(reverse('abc') == 'abc')
def test_rev_enumerate(self):
"""to verify that rev_enumerate ... | the_stack_v2_python_sparse | Homework05/HW05_Test_Dinesh_Nadar.py | DineshNadar95/CS-810 | train | 0 | |
742e0f8ce81152eac381de7e4b2e09b117ccee26 | [
"super(Test200SmartSanityForce001, self).prepare()\nself.logger.info('Preconditions:')\nself.logger.info('1. Open Micro/WIN; ')\nself.logger.info('2. Set up connection with PLC;')\nself.MicroWIN.test_prepare('force_qb0.smart', False)",
"super(Test200SmartSanityForce001, self).process()\nself.logger.info('Step ac... | <|body_start_0|>
super(Test200SmartSanityForce001, self).prepare()
self.logger.info('Preconditions:')
self.logger.info('1. Open Micro/WIN; ')
self.logger.info('2. Set up connection with PLC;')
self.MicroWIN.test_prepare('force_qb0.smart', False)
<|end_body_0|>
<|body_start_1|>
... | Force and unforce new value No.: test_200smart_sanity_force_001 Preconditions: 1. Open Micro/WIN; 2. Set up connection with PLC; Step actions: 1. Make the PLC in run Mode, open status chart, Force a new value to QB0; 2. Unforce the forced new value; Expected results: 1. Force successful, the value of QB0 is same with t... | Test200SmartSanityForce001 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Test200SmartSanityForce001:
"""Force and unforce new value No.: test_200smart_sanity_force_001 Preconditions: 1. Open Micro/WIN; 2. Set up connection with PLC; Step actions: 1. Make the PLC in run Mode, open status chart, Force a new value to QB0; 2. Unforce the forced new value; Expected results... | stack_v2_sparse_classes_75kplus_train_066258 | 3,173 | no_license | [
{
"docstring": "the preparation before executing the test steps Args: Example: Return: Author: Cai, Yong IsInterface: False ChangeInfo: Cai, Yong 2019-09-20 create",
"name": "prepare",
"signature": "def prepare(self)"
},
{
"docstring": "execute the test steps Args: Example: Return: Author: Cai, ... | 3 | null | Implement the Python class `Test200SmartSanityForce001` described below.
Class description:
Force and unforce new value No.: test_200smart_sanity_force_001 Preconditions: 1. Open Micro/WIN; 2. Set up connection with PLC; Step actions: 1. Make the PLC in run Mode, open status chart, Force a new value to QB0; 2. Unforce... | Implement the Python class `Test200SmartSanityForce001` described below.
Class description:
Force and unforce new value No.: test_200smart_sanity_force_001 Preconditions: 1. Open Micro/WIN; 2. Set up connection with PLC; Step actions: 1. Make the PLC in run Mode, open status chart, Force a new value to QB0; 2. Unforce... | 2d3490393737b3e5f086cb6623369b988ffce67f | <|skeleton|>
class Test200SmartSanityForce001:
"""Force and unforce new value No.: test_200smart_sanity_force_001 Preconditions: 1. Open Micro/WIN; 2. Set up connection with PLC; Step actions: 1. Make the PLC in run Mode, open status chart, Force a new value to QB0; 2. Unforce the forced new value; Expected results... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Test200SmartSanityForce001:
"""Force and unforce new value No.: test_200smart_sanity_force_001 Preconditions: 1. Open Micro/WIN; 2. Set up connection with PLC; Step actions: 1. Make the PLC in run Mode, open status chart, Force a new value to QB0; 2. Unforce the forced new value; Expected results: 1. Force su... | the_stack_v2_python_sparse | test_case/task/test_200smart_sanity_force_001.py | Lewescaiyong/auto_test_framework | train | 1 |
806b47c1df93405d490948e7ff1e15270c702b6a | [
"yield ('Unit', '()')\nyield ('Pair', '(,)')\nyield ('Cons', ':')\nyield ('Nil', '[]')\nyield ('True_', 'True')\nyield ('False_', 'False')",
"yield '[]'\nyield 'IO'\nfor typename, _ in self.TYPES:\n if inspect.isa_tuple_name(typename):\n yield typename\nyield '(->)'\nyield '_biGenerator'\nfor funcname, ... | <|body_start_0|>
yield ('Unit', '()')
yield ('Pair', '(,)')
yield ('Cons', ':')
yield ('Nil', '[]')
yield ('True_', 'True')
yield ('False_', 'False')
<|end_body_0|>
<|body_start_1|>
yield '[]'
yield 'IO'
for typename, _ in self.TYPES:
... | PreludeSpecification | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PreludeSpecification:
def aliases(self):
"""Returns prelude aliases. Simply for convenience."""
<|body_0|>
def exports(self):
"""Returns the name of each symbol that must be copied to the Prelude. This is allowed to clobber symbols defined in Prelude.curry."""
... | stack_v2_sparse_classes_75kplus_train_066259 | 7,396 | no_license | [
{
"docstring": "Returns prelude aliases. Simply for convenience.",
"name": "aliases",
"signature": "def aliases(self)"
},
{
"docstring": "Returns the name of each symbol that must be copied to the Prelude. This is allowed to clobber symbols defined in Prelude.curry.",
"name": "exports",
... | 2 | null | Implement the Python class `PreludeSpecification` described below.
Class description:
Implement the PreludeSpecification class.
Method signatures and docstrings:
- def aliases(self): Returns prelude aliases. Simply for convenience.
- def exports(self): Returns the name of each symbol that must be copied to the Prelud... | Implement the Python class `PreludeSpecification` described below.
Class description:
Implement the PreludeSpecification class.
Method signatures and docstrings:
- def aliases(self): Returns prelude aliases. Simply for convenience.
- def exports(self): Returns the name of each symbol that must be copied to the Prelud... | c28c09ca100ac102fcaa8559ad2e12eb0d12d7d5 | <|skeleton|>
class PreludeSpecification:
def aliases(self):
"""Returns prelude aliases. Simply for convenience."""
<|body_0|>
def exports(self):
"""Returns the name of each symbol that must be copied to the Prelude. This is allowed to clobber symbols defined in Prelude.curry."""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PreludeSpecification:
def aliases(self):
"""Returns prelude aliases. Simply for convenience."""
yield ('Unit', '()')
yield ('Pair', '(,)')
yield ('Cons', ':')
yield ('Nil', '[]')
yield ('True_', 'True')
yield ('False_', 'False')
def exports(self):
... | the_stack_v2_python_sparse | src/python/backends/generic/currylib/prelude.py | andyjost/Sprite | train | 5 | |
4ab294eed45070e1819e6bbb58fa92f6a0ee9be7 | [
"assert capacity >= 1, 'capacity should be a positive integer in (0, inf)'\nself.capacity = capacity\nself._buffer = {'params': [None] * capacity, 'sim_data': [None] * capacity}\nself._idx = 0\nself.size_in_batches = 0\nself._is_full = False",
"if self._is_full:\n self._overwrite(params, sim_data)\nelse:\n ... | <|body_start_0|>
assert capacity >= 1, 'capacity should be a positive integer in (0, inf)'
self.capacity = capacity
self._buffer = {'params': [None] * capacity, 'sim_data': [None] * capacity}
self._idx = 0
self.size_in_batches = 0
self._is_full = False
<|end_body_0|>
<|b... | Implements a memory replay buffer for simulation-based inference. Attributes ---------- capacity: int Maximum number of batches to store in the buffer size_in_batches: int Number of currently stored batches _buffer : dict Buffer data as a dictionary with keys `'params', 'sim_data'` | MemoryReplayBuffer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MemoryReplayBuffer:
"""Implements a memory replay buffer for simulation-based inference. Attributes ---------- capacity: int Maximum number of batches to store in the buffer size_in_batches: int Number of currently stored batches _buffer : dict Buffer data as a dictionary with keys `'params', 'si... | stack_v2_sparse_classes_75kplus_train_066260 | 3,103 | no_license | [
{
"docstring": "Creates a memory replay buffer for simulation-based inference. Parameters ---------- capacity : int Maximum number of batches to store in buffer",
"name": "__init__",
"signature": "def __init__(self, capacity)"
},
{
"docstring": "Stores params and simulated data. If buffer is not... | 4 | null | Implement the Python class `MemoryReplayBuffer` described below.
Class description:
Implements a memory replay buffer for simulation-based inference. Attributes ---------- capacity: int Maximum number of batches to store in the buffer size_in_batches: int Number of currently stored batches _buffer : dict Buffer data a... | Implement the Python class `MemoryReplayBuffer` described below.
Class description:
Implements a memory replay buffer for simulation-based inference. Attributes ---------- capacity: int Maximum number of batches to store in the buffer size_in_batches: int Number of currently stored batches _buffer : dict Buffer data a... | 37c25b35175382a286657e2bde9d7896e853b881 | <|skeleton|>
class MemoryReplayBuffer:
"""Implements a memory replay buffer for simulation-based inference. Attributes ---------- capacity: int Maximum number of batches to store in the buffer size_in_batches: int Number of currently stored batches _buffer : dict Buffer data as a dictionary with keys `'params', 'si... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MemoryReplayBuffer:
"""Implements a memory replay buffer for simulation-based inference. Attributes ---------- capacity: int Maximum number of batches to store in the buffer size_in_batches: int Number of currently stored batches _buffer : dict Buffer data as a dictionary with keys `'params', 'sim_data'`"""
... | the_stack_v2_python_sparse | Conversion/Conversion (data interpolation, n_obs=3)/bayesflow/buffer.py | zijianwang2000/BA_MissingData | train | 0 |
074d22760e2360dfd0e11f9acf434031bb601245 | [
"if not id:\n raise JsonError('ID不能为空')\nobj = Friendlink.Q.filter(Friendlink.id == id).first()\nreturn obj",
"query = Friendlink.Q\nif 'status' in where.keys():\n query = query.filter(Friendlink.status == where['status'])\nelse:\n query = query.filter(Friendlink.status != -1)\nquery = query.order_by(Fri... | <|body_start_0|>
if not id:
raise JsonError('ID不能为空')
obj = Friendlink.Q.filter(Friendlink.id == id).first()
return obj
<|end_body_0|>
<|body_start_1|>
query = Friendlink.Q
if 'status' in where.keys():
query = query.filter(Friendlink.status == where['stat... | FriendlinkService | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FriendlinkService:
def get(id):
"""获取单条记录 [description] Arguments: id int -- 主键 return: Friendlink Model 实例 | None"""
<|body_0|>
def get_list(where, limit=12):
"""列表记录 Arguments: where dict -- 查询条件 page int -- 当前页 per_page int -- 每页记录数 return: Paginate 对象 | None"""
... | stack_v2_sparse_classes_75kplus_train_066261 | 1,257 | permissive | [
{
"docstring": "获取单条记录 [description] Arguments: id int -- 主键 return: Friendlink Model 实例 | None",
"name": "get",
"signature": "def get(id)"
},
{
"docstring": "列表记录 Arguments: where dict -- 查询条件 page int -- 当前页 per_page int -- 每页记录数 return: Paginate 对象 | None",
"name": "get_list",
"signat... | 2 | stack_v2_sparse_classes_30k_train_050224 | Implement the Python class `FriendlinkService` described below.
Class description:
Implement the FriendlinkService class.
Method signatures and docstrings:
- def get(id): 获取单条记录 [description] Arguments: id int -- 主键 return: Friendlink Model 实例 | None
- def get_list(where, limit=12): 列表记录 Arguments: where dict -- 查询条件... | Implement the Python class `FriendlinkService` described below.
Class description:
Implement the FriendlinkService class.
Method signatures and docstrings:
- def get(id): 获取单条记录 [description] Arguments: id int -- 主键 return: Friendlink Model 实例 | None
- def get_list(where, limit=12): 列表记录 Arguments: where dict -- 查询条件... | 3300561c5686b674197ffc097cf781a931fd4787 | <|skeleton|>
class FriendlinkService:
def get(id):
"""获取单条记录 [description] Arguments: id int -- 主键 return: Friendlink Model 实例 | None"""
<|body_0|>
def get_list(where, limit=12):
"""列表记录 Arguments: where dict -- 查询条件 page int -- 当前页 per_page int -- 每页记录数 return: Paginate 对象 | None"""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class FriendlinkService:
def get(id):
"""获取单条记录 [description] Arguments: id int -- 主键 return: Friendlink Model 实例 | None"""
if not id:
raise JsonError('ID不能为空')
obj = Friendlink.Q.filter(Friendlink.id == id).first()
return obj
def get_list(where, limit=12):
"... | the_stack_v2_python_sparse | applications/huifeng/services/friendlink.py | leeyisoft/py_admin | train | 17 | |
b3ac2504aa8a11a80ff4d33d2fb3bd8f509571d9 | [
"test_args = list(kwargs.get('test_args') or [])\ntest_args.append('--enable-run-ios-unittests-with-xctest')\nkwargs['test_args'] = test_args\nsuper(DeviceXCTestUnitTestsApp, self).__init__(tests_app, **kwargs)",
"plugins_dir = os.path.join(self.test_app_path, 'PlugIns')\nif not os.path.exists(plugins_dir):\n ... | <|body_start_0|>
test_args = list(kwargs.get('test_args') or [])
test_args.append('--enable-run-ios-unittests-with-xctest')
kwargs['test_args'] = test_args
super(DeviceXCTestUnitTestsApp, self).__init__(tests_app, **kwargs)
<|end_body_0|>
<|body_start_1|>
plugins_dir = os.path.j... | XCTest hosted unit tests to run on devices. This is for the XCTest framework hosted unit tests running on devices. Stores data about tests: tests_app: full path to tests app. project_path: root project folder. module_name: egtests module name. included_tests: List of tests to run. excluded_tests: List of tests not to r... | DeviceXCTestUnitTestsApp | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DeviceXCTestUnitTestsApp:
"""XCTest hosted unit tests to run on devices. This is for the XCTest framework hosted unit tests running on devices. Stores data about tests: tests_app: full path to tests app. project_path: root project folder. module_name: egtests module name. included_tests: List of ... | stack_v2_sparse_classes_75kplus_train_066262 | 24,623 | permissive | [
{
"docstring": "Initialize the class. Args: tests_app: (str) full path to tests app. (Following are potential args in **kwargs) included_tests: (list) Specific tests to run E.g. [ 'TestCaseClass1/testMethod1', 'TestCaseClass2/testMethod2'] excluded_tests: (list) Specific tests not to run E.g. [ 'TestCaseClass1'... | 3 | stack_v2_sparse_classes_30k_train_032231 | Implement the Python class `DeviceXCTestUnitTestsApp` described below.
Class description:
XCTest hosted unit tests to run on devices. This is for the XCTest framework hosted unit tests running on devices. Stores data about tests: tests_app: full path to tests app. project_path: root project folder. module_name: egtest... | Implement the Python class `DeviceXCTestUnitTestsApp` described below.
Class description:
XCTest hosted unit tests to run on devices. This is for the XCTest framework hosted unit tests running on devices. Stores data about tests: tests_app: full path to tests app. project_path: root project folder. module_name: egtest... | a401d6cf4f7bf0e2d2e964c512ebb923c3d8832c | <|skeleton|>
class DeviceXCTestUnitTestsApp:
"""XCTest hosted unit tests to run on devices. This is for the XCTest framework hosted unit tests running on devices. Stores data about tests: tests_app: full path to tests app. project_path: root project folder. module_name: egtests module name. included_tests: List of ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DeviceXCTestUnitTestsApp:
"""XCTest hosted unit tests to run on devices. This is for the XCTest framework hosted unit tests running on devices. Stores data about tests: tests_app: full path to tests app. project_path: root project folder. module_name: egtests module name. included_tests: List of tests to run.... | the_stack_v2_python_sparse | ios/build/bots/scripts/test_apps.py | chromium/chromium | train | 17,408 |
3f781aac821dda05baa8d8a105a05895aa9de4b0 | [
"EPF.download(directory)\nclass_group = EPFInfo.get_group(group)\npath = f'{directory}/epf/datasets'\nfile = f'{path}/{group}.csv'\ndf = pd.read_csv(file)\ndf.columns = ['ds', 'y'] + [f'Exogenous{i}' for i in range(1, len(df.columns) - 1)]\ndf['unique_id'] = group\ndf['ds'] = pd.to_datetime(df['ds'])\ndf['week_day'... | <|body_start_0|>
EPF.download(directory)
class_group = EPFInfo.get_group(group)
path = f'{directory}/epf/datasets'
file = f'{path}/{group}.csv'
df = pd.read_csv(file)
df.columns = ['ds', 'y'] + [f'Exogenous{i}' for i in range(1, len(df.columns) - 1)]
df['unique_id... | EPF | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EPF:
def load(directory: str, group: str) -> Tuple[pd.DataFrame, Optional[pd.DataFrame], Optional[pd.DataFrame]]:
"""Downloads and loads EPF data. Parameters ---------- directory: str Directory where data will be downloaded. group: str Group name. Allowed groups: 'NP', 'PJM', 'BE', 'FR',... | stack_v2_sparse_classes_75kplus_train_066263 | 5,353 | permissive | [
{
"docstring": "Downloads and loads EPF data. Parameters ---------- directory: str Directory where data will be downloaded. group: str Group name. Allowed groups: 'NP', 'PJM', 'BE', 'FR', 'DE'.",
"name": "load",
"signature": "def load(directory: str, group: str) -> Tuple[pd.DataFrame, Optional[pd.DataFr... | 3 | stack_v2_sparse_classes_30k_train_018116 | Implement the Python class `EPF` described below.
Class description:
Implement the EPF class.
Method signatures and docstrings:
- def load(directory: str, group: str) -> Tuple[pd.DataFrame, Optional[pd.DataFrame], Optional[pd.DataFrame]]: Downloads and loads EPF data. Parameters ---------- directory: str Directory wh... | Implement the Python class `EPF` described below.
Class description:
Implement the EPF class.
Method signatures and docstrings:
- def load(directory: str, group: str) -> Tuple[pd.DataFrame, Optional[pd.DataFrame], Optional[pd.DataFrame]]: Downloads and loads EPF data. Parameters ---------- directory: str Directory wh... | cc4726198bd1f8ecddeb4faeab939f87d8df57e6 | <|skeleton|>
class EPF:
def load(directory: str, group: str) -> Tuple[pd.DataFrame, Optional[pd.DataFrame], Optional[pd.DataFrame]]:
"""Downloads and loads EPF data. Parameters ---------- directory: str Directory where data will be downloaded. group: str Group name. Allowed groups: 'NP', 'PJM', 'BE', 'FR',... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class EPF:
def load(directory: str, group: str) -> Tuple[pd.DataFrame, Optional[pd.DataFrame], Optional[pd.DataFrame]]:
"""Downloads and loads EPF data. Parameters ---------- directory: str Directory where data will be downloaded. group: str Group name. Allowed groups: 'NP', 'PJM', 'BE', 'FR', 'DE'."""
... | the_stack_v2_python_sparse | nixtlats/data/datasets/epf.py | dhutexas/nixtlats | train | 0 | |
f49d02863cdca5431859a3da1ebb79a26bc14c9c | [
"z = z.copy()\nz[z < 0] = 0\nz[z > 6] = 6\nreturn z",
"z = z.copy()\nz[np.where(np.logical_and(z >= 0, z <= 6))] = 1\nz[z < 0] = 0\nz[z > 6] = 0\nreturn z"
] | <|body_start_0|>
z = z.copy()
z[z < 0] = 0
z[z > 6] = 6
return z
<|end_body_0|>
<|body_start_1|>
z = z.copy()
z[np.where(np.logical_and(z >= 0, z <= 6))] = 1
z[z < 0] = 0
z[z > 6] = 0
return z
<|end_body_1|>
| ReLU6 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ReLU6:
def f(self, z):
"""f: Real -> [0,inf)"""
<|body_0|>
def f_prime(self, z):
"""f: Real -> [0,inf)"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
z = z.copy()
z[z < 0] = 0
z[z > 6] = 6
return z
<|end_body_0|>
<|body_sta... | stack_v2_sparse_classes_75kplus_train_066264 | 2,027 | no_license | [
{
"docstring": "f: Real -> [0,inf)",
"name": "f",
"signature": "def f(self, z)"
},
{
"docstring": "f: Real -> [0,inf)",
"name": "f_prime",
"signature": "def f_prime(self, z)"
}
] | 2 | stack_v2_sparse_classes_30k_train_043707 | Implement the Python class `ReLU6` described below.
Class description:
Implement the ReLU6 class.
Method signatures and docstrings:
- def f(self, z): f: Real -> [0,inf)
- def f_prime(self, z): f: Real -> [0,inf) | Implement the Python class `ReLU6` described below.
Class description:
Implement the ReLU6 class.
Method signatures and docstrings:
- def f(self, z): f: Real -> [0,inf)
- def f_prime(self, z): f: Real -> [0,inf)
<|skeleton|>
class ReLU6:
def f(self, z):
"""f: Real -> [0,inf)"""
<|body_0|>
d... | 84e4ad5d1792fcce214d6be81c2175939a3a9a09 | <|skeleton|>
class ReLU6:
def f(self, z):
"""f: Real -> [0,inf)"""
<|body_0|>
def f_prime(self, z):
"""f: Real -> [0,inf)"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ReLU6:
def f(self, z):
"""f: Real -> [0,inf)"""
z = z.copy()
z[z < 0] = 0
z[z > 6] = 6
return z
def f_prime(self, z):
"""f: Real -> [0,inf)"""
z = z.copy()
z[np.where(np.logical_and(z >= 0, z <= 6))] = 1
z[z < 0] = 0
z[z > 6]... | the_stack_v2_python_sparse | deep-q-learning/lib/activation_function.py | felixjchen/learning | train | 0 | |
1f0541256fd276183bf28bcfd9f444b62353313b | [
"files = self.files.all()\nresult = '<ul class=\"order-files-list\">'\nfor file_obj in files:\n result += '<li><a href=\"%s%s\" target=\"_blank\">%s</a></li>' % (settings.SITE_URL, file_obj.data.url, file_obj.filename)\nresult += '</ul>'\nreturn result",
"try:\n upload = Upload.objects.get(data=attachment, ... | <|body_start_0|>
files = self.files.all()
result = '<ul class="order-files-list">'
for file_obj in files:
result += '<li><a href="%s%s" target="_blank">%s</a></li>' % (settings.SITE_URL, file_obj.data.url, file_obj.filename)
result += '</ul>'
return result
<|end_body_... | Миксин для моделей с возможностью загрузки файлов | UploadMixin | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UploadMixin:
"""Миксин для моделей с возможностью загрузки файлов"""
def files_list(self):
"""Выводит список файлов объекта"""
<|body_0|>
def attach_file(self, attachment):
"""Добавляет файл к текущему объекту attachment - путь к файлу относительно MEDIA_URL"""
... | stack_v2_sparse_classes_75kplus_train_066265 | 3,750 | no_license | [
{
"docstring": "Выводит список файлов объекта",
"name": "files_list",
"signature": "def files_list(self)"
},
{
"docstring": "Добавляет файл к текущему объекту attachment - путь к файлу относительно MEDIA_URL",
"name": "attach_file",
"signature": "def attach_file(self, attachment)"
}
] | 2 | stack_v2_sparse_classes_30k_train_054256 | Implement the Python class `UploadMixin` described below.
Class description:
Миксин для моделей с возможностью загрузки файлов
Method signatures and docstrings:
- def files_list(self): Выводит список файлов объекта
- def attach_file(self, attachment): Добавляет файл к текущему объекту attachment - путь к файлу относи... | Implement the Python class `UploadMixin` described below.
Class description:
Миксин для моделей с возможностью загрузки файлов
Method signatures and docstrings:
- def files_list(self): Выводит список файлов объекта
- def attach_file(self, attachment): Добавляет файл к текущему объекту attachment - путь к файлу относи... | 20cee1aee02da192c9c79a51bd0898c1dba0c98f | <|skeleton|>
class UploadMixin:
"""Миксин для моделей с возможностью загрузки файлов"""
def files_list(self):
"""Выводит список файлов объекта"""
<|body_0|>
def attach_file(self, attachment):
"""Добавляет файл к текущему объекту attachment - путь к файлу относительно MEDIA_URL"""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class UploadMixin:
"""Миксин для моделей с возможностью загрузки файлов"""
def files_list(self):
"""Выводит список файлов объекта"""
files = self.files.all()
result = '<ul class="order-files-list">'
for file_obj in files:
result += '<li><a href="%s%s" target="_blank"... | the_stack_v2_python_sparse | apps/uploadifive/models.py | Emilnurg/anas.ru | train | 0 |
c5b69d72cf595b9a998ed6cc341f8fe436254f26 | [
"self.oldstdout = sys.stdout\nself.oldstderr = sys.stderr\nos.chdir(self.config['rundir'])",
"service.IService(self.application).privilegedStartService()\napp.startApplication(self.application, not self.config['no_save'])\napp.startApplication(internet.TimerService(0.1, lambda: None), 0)\nself.startReactor(None, ... | <|body_start_0|>
self.oldstdout = sys.stdout
self.oldstderr = sys.stderr
os.chdir(self.config['rundir'])
<|end_body_0|>
<|body_start_1|>
service.IService(self.application).privilegedStartService()
app.startApplication(self.application, not self.config['no_save'])
app.sta... | An ApplicationRunner which avoids unix-specific things. No forking, no PID files, no privileges. | WindowsApplicationRunner | [
"LicenseRef-scancode-unknown-license-reference",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WindowsApplicationRunner:
"""An ApplicationRunner which avoids unix-specific things. No forking, no PID files, no privileges."""
def preApplication(self):
"""Do pre-application-creation setup."""
<|body_0|>
def postApplication(self):
"""Start the application and ... | stack_v2_sparse_classes_75kplus_train_066266 | 1,540 | permissive | [
{
"docstring": "Do pre-application-creation setup.",
"name": "preApplication",
"signature": "def preApplication(self)"
},
{
"docstring": "Start the application and run the reactor.",
"name": "postApplication",
"signature": "def postApplication(self)"
}
] | 2 | null | Implement the Python class `WindowsApplicationRunner` described below.
Class description:
An ApplicationRunner which avoids unix-specific things. No forking, no PID files, no privileges.
Method signatures and docstrings:
- def preApplication(self): Do pre-application-creation setup.
- def postApplication(self): Start... | Implement the Python class `WindowsApplicationRunner` described below.
Class description:
An ApplicationRunner which avoids unix-specific things. No forking, no PID files, no privileges.
Method signatures and docstrings:
- def preApplication(self): Do pre-application-creation setup.
- def postApplication(self): Start... | 5cee0a8c4180a3108538b4e4ce945a18726595a6 | <|skeleton|>
class WindowsApplicationRunner:
"""An ApplicationRunner which avoids unix-specific things. No forking, no PID files, no privileges."""
def preApplication(self):
"""Do pre-application-creation setup."""
<|body_0|>
def postApplication(self):
"""Start the application and ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class WindowsApplicationRunner:
"""An ApplicationRunner which avoids unix-specific things. No forking, no PID files, no privileges."""
def preApplication(self):
"""Do pre-application-creation setup."""
self.oldstdout = sys.stdout
self.oldstderr = sys.stderr
os.chdir(self.config[... | the_stack_v2_python_sparse | venv/Lib/site-packages/twisted/scripts/_twistw.py | zoelesv/Smathchat | train | 9 |
cf565a0347de89bb47111b777c9e870d0d3f41c0 | [
"self.A = copy.deepcopy(A)\nself.b = b\nself.n = A.colRank\nif x0 == 0:\n self.x0 = FullMatrix(self.n, 1)\nelse:\n self.x0 = x0\nself.tol = tol\nself.max_iter = max_iter\nself.D_inv = SparseMatrix(self.n, self.n)\nself.R = copy.deepcopy(A)\nfor i in range(self.n):\n aii = A.retrieveElement(i, i)\n self.... | <|body_start_0|>
self.A = copy.deepcopy(A)
self.b = b
self.n = A.colRank
if x0 == 0:
self.x0 = FullMatrix(self.n, 1)
else:
self.x0 = x0
self.tol = tol
self.max_iter = max_iter
self.D_inv = SparseMatrix(self.n, self.n)
self.R... | An instance is a representation of the linear system to be solved using the Jacobi iterative method. | Jacobi_Solver | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Jacobi_Solver:
"""An instance is a representation of the linear system to be solved using the Jacobi iterative method."""
def __init__(self, A, b, x0=0, tol=10 ** (-9), max_iter=10 ** 100):
"""Initializes the matrix A, column matrix b, initial guess x0, tolerance, and maximum number ... | stack_v2_sparse_classes_75kplus_train_066267 | 2,750 | no_license | [
{
"docstring": "Initializes the matrix A, column matrix b, initial guess x0, tolerance, and maximum number of iterations max_iter. D_inv is the inverse of the diagonal matrix D obtained from the diagonal elements of A. R is the matrix obtained from (A - D) which is equivalent to (L+U) Db is the product obtained... | 5 | null | Implement the Python class `Jacobi_Solver` described below.
Class description:
An instance is a representation of the linear system to be solved using the Jacobi iterative method.
Method signatures and docstrings:
- def __init__(self, A, b, x0=0, tol=10 ** (-9), max_iter=10 ** 100): Initializes the matrix A, column m... | Implement the Python class `Jacobi_Solver` described below.
Class description:
An instance is a representation of the linear system to be solved using the Jacobi iterative method.
Method signatures and docstrings:
- def __init__(self, A, b, x0=0, tol=10 ** (-9), max_iter=10 ** 100): Initializes the matrix A, column m... | 7439f25c7809f4198e452f70ae4269447873f7db | <|skeleton|>
class Jacobi_Solver:
"""An instance is a representation of the linear system to be solved using the Jacobi iterative method."""
def __init__(self, A, b, x0=0, tol=10 ** (-9), max_iter=10 ** 100):
"""Initializes the matrix A, column matrix b, initial guess x0, tolerance, and maximum number ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Jacobi_Solver:
"""An instance is a representation of the linear system to be solved using the Jacobi iterative method."""
def __init__(self, A, b, x0=0, tol=10 ** (-9), max_iter=10 ** 100):
"""Initializes the matrix A, column matrix b, initial guess x0, tolerance, and maximum number of iterations... | the_stack_v2_python_sparse | PA2/jacobi.py | ta275/Scientific-Computing-in-Python | train | 0 |
c983380edef5d95b87b808fb08bcc876c32012c0 | [
"if not root:\n return ''\nstack = [root]\nres = ''\nwhile stack:\n for i in range(len(stack)):\n node = stack.pop(0)\n if not node:\n res += 'None,'\n else:\n res += str(node.val) + ','\n stack.append(node.left)\n stack.append(node.right)\nretu... | <|body_start_0|>
if not root:
return ''
stack = [root]
res = ''
while stack:
for i in range(len(stack)):
node = stack.pop(0)
if not node:
res += 'None,'
else:
res += str(node.v... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|>
<|body_... | stack_v2_sparse_classes_75kplus_train_066268 | 2,750 | 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:... | 78285a8e1829999cde3fd72bd8564fe8ff383cff | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
if not root:
return ''
stack = [root]
res = ''
while stack:
for i in range(len(stack)):
node = stack.pop(0)
... | the_stack_v2_python_sparse | First Session(By Tag)/Tree/297.Serialize and Deserialize Binary Tree.py | SixuLi/Leetcode-Practice | train | 0 | |
8d664168fe10c45fdb84b7d3f9b78412096ef56c | [
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')",
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')",
"conte... | <|body_start_0|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!')
<|end_body_0|>
<|body_start_1|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not im... | Msg defines the staking Msg service. | MsgServicer | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MsgServicer:
"""Msg defines the staking Msg service."""
def CreateValidator(self, request, context):
"""CreateValidator defines a method for creating a new validator."""
<|body_0|>
def EditValidator(self, request, context):
"""EditValidator defines a method for e... | stack_v2_sparse_classes_75kplus_train_066269 | 10,044 | permissive | [
{
"docstring": "CreateValidator defines a method for creating a new validator.",
"name": "CreateValidator",
"signature": "def CreateValidator(self, request, context)"
},
{
"docstring": "EditValidator defines a method for editing an existing validator.",
"name": "EditValidator",
"signatur... | 5 | null | Implement the Python class `MsgServicer` described below.
Class description:
Msg defines the staking Msg service.
Method signatures and docstrings:
- def CreateValidator(self, request, context): CreateValidator defines a method for creating a new validator.
- def EditValidator(self, request, context): EditValidator d... | Implement the Python class `MsgServicer` described below.
Class description:
Msg defines the staking Msg service.
Method signatures and docstrings:
- def CreateValidator(self, request, context): CreateValidator defines a method for creating a new validator.
- def EditValidator(self, request, context): EditValidator d... | c38a07458a36305457680196e8c47372008db5ab | <|skeleton|>
class MsgServicer:
"""Msg defines the staking Msg service."""
def CreateValidator(self, request, context):
"""CreateValidator defines a method for creating a new validator."""
<|body_0|>
def EditValidator(self, request, context):
"""EditValidator defines a method for e... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MsgServicer:
"""Msg defines the staking Msg service."""
def CreateValidator(self, request, context):
"""CreateValidator defines a method for creating a new validator."""
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise No... | the_stack_v2_python_sparse | bluzelle/codec/cosmos/staking/v1beta1/tx_pb2_grpc.py | hhio618/bluzelle-py | train | 3 |
f17ee66118f23f08c23b01eb4527b6dd94baf973 | [
"result = []\nappend = result.append\nget = PROPERTIES.get\nfor residue in sequence:\n append('O' if get(residue, 0) & HYDROPHOBIC else 'I')\nreturn ''.join(result)",
"hhProperties = self.convertAAToHydrophobicHydrophilic(read.sequence)\nfor match in ALPHA_HELIX_PI.finditer(hhProperties):\n start = match.st... | <|body_start_0|>
result = []
append = result.append
get = PROPERTIES.get
for residue in sequence:
append('O' if get(residue, 0) & HYDROPHOBIC else 'I')
return ''.join(result)
<|end_body_0|>
<|body_start_1|>
hhProperties = self.convertAAToHydrophobicHydrophili... | A class for computing statistics based on Pi alpha helices. Based around the assumption that a pi alpha helix is composed of at least two repeats of one hydrophobic and then 4 hydrophilic amino acids. | AlphaHelix_pi | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AlphaHelix_pi:
"""A class for computing statistics based on Pi alpha helices. Based around the assumption that a pi alpha helix is composed of at least two repeats of one hydrophobic and then 4 hydrophilic amino acids."""
def convertAAToHydrophobicHydrophilic(self, sequence):
"""Take... | stack_v2_sparse_classes_75kplus_train_066270 | 1,555 | no_license | [
{
"docstring": "Takes an amino acid sequence, converts it to a sequence of hydrophobic / hydrophilic. @param sequence: an amino acid sequence.",
"name": "convertAAToHydrophobicHydrophilic",
"signature": "def convertAAToHydrophobicHydrophilic(self, sequence)"
},
{
"docstring": "A function that ch... | 2 | stack_v2_sparse_classes_30k_train_046217 | Implement the Python class `AlphaHelix_pi` described below.
Class description:
A class for computing statistics based on Pi alpha helices. Based around the assumption that a pi alpha helix is composed of at least two repeats of one hydrophobic and then 4 hydrophilic amino acids.
Method signatures and docstrings:
- de... | Implement the Python class `AlphaHelix_pi` described below.
Class description:
A class for computing statistics based on Pi alpha helices. Based around the assumption that a pi alpha helix is composed of at least two repeats of one hydrophobic and then 4 hydrophilic amino acids.
Method signatures and docstrings:
- de... | 3e848dfa66f5fd07f1fb709abc935baff9f43d87 | <|skeleton|>
class AlphaHelix_pi:
"""A class for computing statistics based on Pi alpha helices. Based around the assumption that a pi alpha helix is composed of at least two repeats of one hydrophobic and then 4 hydrophilic amino acids."""
def convertAAToHydrophobicHydrophilic(self, sequence):
"""Take... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AlphaHelix_pi:
"""A class for computing statistics based on Pi alpha helices. Based around the assumption that a pi alpha helix is composed of at least two repeats of one hydrophobic and then 4 hydrophilic amino acids."""
def convertAAToHydrophobicHydrophilic(self, sequence):
"""Takes an amino ac... | the_stack_v2_python_sparse | light/landmarks/alpha_helix_pi.py | acorg/light-matter | train | 0 |
0d95949e900a2914e7da4d36065d6def2de59020 | [
"cache_len = 100000\nself.random_prob_cache = np.random.random(size=(cache_len,))\nself.random_prob_ptr = cache_len - 1",
"value = self.random_prob_cache[self.random_prob_ptr]\nself.random_prob_ptr -= 1\nif self.random_prob_ptr == -1:\n self.reset_random_prob()\nreturn value",
"token = self.token_list[self.t... | <|body_start_0|>
cache_len = 100000
self.random_prob_cache = np.random.random(size=(cache_len,))
self.random_prob_ptr = cache_len - 1
<|end_body_0|>
<|body_start_1|>
value = self.random_prob_cache[self.random_prob_ptr]
self.random_prob_ptr -= 1
if self.random_prob_ptr ==... | A base class that generate multiple random numbers at the same time. | EfficientRandomGen | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EfficientRandomGen:
"""A base class that generate multiple random numbers at the same time."""
def reset_random_prob(self):
"""Generate many random numbers at the same time and cache them."""
<|body_0|>
def get_random_prob(self):
"""Get a random number."""
... | stack_v2_sparse_classes_75kplus_train_066271 | 14,026 | no_license | [
{
"docstring": "Generate many random numbers at the same time and cache them.",
"name": "reset_random_prob",
"signature": "def reset_random_prob(self)"
},
{
"docstring": "Get a random number.",
"name": "get_random_prob",
"signature": "def get_random_prob(self)"
},
{
"docstring": ... | 3 | stack_v2_sparse_classes_30k_train_050465 | Implement the Python class `EfficientRandomGen` described below.
Class description:
A base class that generate multiple random numbers at the same time.
Method signatures and docstrings:
- def reset_random_prob(self): Generate many random numbers at the same time and cache them.
- def get_random_prob(self): Get a ran... | Implement the Python class `EfficientRandomGen` described below.
Class description:
A base class that generate multiple random numbers at the same time.
Method signatures and docstrings:
- def reset_random_prob(self): Generate many random numbers at the same time and cache them.
- def get_random_prob(self): Get a ran... | 778156466bc06ab1e4ecd1661d8ad8b98023afca | <|skeleton|>
class EfficientRandomGen:
"""A base class that generate multiple random numbers at the same time."""
def reset_random_prob(self):
"""Generate many random numbers at the same time and cache them."""
<|body_0|>
def get_random_prob(self):
"""Get a random number."""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class EfficientRandomGen:
"""A base class that generate multiple random numbers at the same time."""
def reset_random_prob(self):
"""Generate many random numbers at the same time and cache them."""
cache_len = 100000
self.random_prob_cache = np.random.random(size=(cache_len,))
s... | the_stack_v2_python_sparse | data/gen_uda_dataset.py | mainliufeng/models | train | 0 |
85003e042f2ee32a40d167c11ced6d3f6cc94ac6 | [
"if not triangle:\n return 0\nn = len(triangle)\ndp = [[0] * n for _ in range(n)]\ndp[0][0] = triangle[0][0]\nfor i in range(1, n):\n dp[i][0] = dp[i - 1][0] + triangle[i][0]\n for j in range(1, i):\n dp[i][j] = min(dp[i - 1][j - 1], dp[i - 1][j]) + triangle[i][j]\n dp[i][i] = dp[i - 1][i - 1] + ... | <|body_start_0|>
if not triangle:
return 0
n = len(triangle)
dp = [[0] * n for _ in range(n)]
dp[0][0] = triangle[0][0]
for i in range(1, n):
dp[i][0] = dp[i - 1][0] + triangle[i][0]
for j in range(1, i):
dp[i][j] = min(dp[i - 1... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def minimumTotal(self, triangle: list) -> int:
"""自顶向下的动态规划"""
<|body_0|>
def minimumTotal_1(self, triangle: list) -> int:
"""自底向上的动态规划"""
<|body_1|>
def minimumTotal_2(self, triangle: list) -> int:
"""自底向上的动态规划 空间优化 发现dp[i][j]只和下一层dp[i... | stack_v2_sparse_classes_75kplus_train_066272 | 1,739 | no_license | [
{
"docstring": "自顶向下的动态规划",
"name": "minimumTotal",
"signature": "def minimumTotal(self, triangle: list) -> int"
},
{
"docstring": "自底向上的动态规划",
"name": "minimumTotal_1",
"signature": "def minimumTotal_1(self, triangle: list) -> int"
},
{
"docstring": "自底向上的动态规划 空间优化 发现dp[i][j]只和下... | 3 | stack_v2_sparse_classes_30k_train_023838 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def minimumTotal(self, triangle: list) -> int: 自顶向下的动态规划
- def minimumTotal_1(self, triangle: list) -> int: 自底向上的动态规划
- def minimumTotal_2(self, triangle: list) -> int: 自底向上的动态规划... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def minimumTotal(self, triangle: list) -> int: 自顶向下的动态规划
- def minimumTotal_1(self, triangle: list) -> int: 自底向上的动态规划
- def minimumTotal_2(self, triangle: list) -> int: 自底向上的动态规划... | 3508e1ce089131b19603c3206aab4cf43023bb19 | <|skeleton|>
class Solution:
def minimumTotal(self, triangle: list) -> int:
"""自顶向下的动态规划"""
<|body_0|>
def minimumTotal_1(self, triangle: list) -> int:
"""自底向上的动态规划"""
<|body_1|>
def minimumTotal_2(self, triangle: list) -> int:
"""自底向上的动态规划 空间优化 发现dp[i][j]只和下一层dp[i... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def minimumTotal(self, triangle: list) -> int:
"""自顶向下的动态规划"""
if not triangle:
return 0
n = len(triangle)
dp = [[0] * n for _ in range(n)]
dp[0][0] = triangle[0][0]
for i in range(1, n):
dp[i][0] = dp[i - 1][0] + triangle[i][0]... | the_stack_v2_python_sparse | algorithm/leetcode/dp/14-三角形最小路径和.py | lxconfig/UbuntuCode_bak | train | 0 | |
c6534f2b02083cc2c84f178595179d566236d323 | [
"logger.info('Processing BioBamBam Filtering')\nif configuration is None:\n configuration = {}\nself.configuration.update(configuration)",
"output_files_generated = {}\noutput_metadata = {}\nb3f = biobambam(self.configuration)\nlogger.progress('BioBamBam Filter', status='RUNNING')\nb3f_files, b3f_meta = b3f.ru... | <|body_start_0|>
logger.info('Processing BioBamBam Filtering')
if configuration is None:
configuration = {}
self.configuration.update(configuration)
<|end_body_0|>
<|body_start_1|>
output_files_generated = {}
output_metadata = {}
b3f = biobambam(self.configur... | Functions for filtering FastQ alignments with BioBamBam. | process_biobambam | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class process_biobambam:
"""Functions for filtering FastQ alignments with BioBamBam."""
def __init__(self, configuration=None):
"""Initialise the class Parameters ---------- configuration : dict a dictionary containing parameters that define how the operation should be carried out, which a... | stack_v2_sparse_classes_75kplus_train_066273 | 5,528 | permissive | [
{
"docstring": "Initialise the class Parameters ---------- configuration : dict a dictionary containing parameters that define how the operation should be carried out, which are specific to each Tool.",
"name": "__init__",
"signature": "def __init__(self, configuration=None)"
},
{
"docstring": "... | 2 | null | Implement the Python class `process_biobambam` described below.
Class description:
Functions for filtering FastQ alignments with BioBamBam.
Method signatures and docstrings:
- def __init__(self, configuration=None): Initialise the class Parameters ---------- configuration : dict a dictionary containing parameters tha... | Implement the Python class `process_biobambam` described below.
Class description:
Functions for filtering FastQ alignments with BioBamBam.
Method signatures and docstrings:
- def __init__(self, configuration=None): Initialise the class Parameters ---------- configuration : dict a dictionary containing parameters tha... | 50c7115c0c1a6af48dc34f275e469d1b9eb02999 | <|skeleton|>
class process_biobambam:
"""Functions for filtering FastQ alignments with BioBamBam."""
def __init__(self, configuration=None):
"""Initialise the class Parameters ---------- configuration : dict a dictionary containing parameters that define how the operation should be carried out, which a... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class process_biobambam:
"""Functions for filtering FastQ alignments with BioBamBam."""
def __init__(self, configuration=None):
"""Initialise the class Parameters ---------- configuration : dict a dictionary containing parameters that define how the operation should be carried out, which are specific t... | the_stack_v2_python_sparse | process_biobambam.py | Multiscale-Genomics/mg-process-fastq | train | 2 |
8e20764c59d17b909ac79ac9d57729e827c591db | [
"z = [0 for _ in range(len(s))]\nL, R = (0, 1)\nfor i in range(1, len(s)):\n if R <= i or z[i - L] >= R - i:\n z[i] = (z[i - L] if i + z[i - L] < R else R - i) if R > i else 0\n while i + z[i] < len(s) and s[i + z[i]] == s[z[i]]:\n z[i] += 1\n if i + z[i] > R:\n L, R = ... | <|body_start_0|>
z = [0 for _ in range(len(s))]
L, R = (0, 1)
for i in range(1, len(s)):
if R <= i or z[i - L] >= R - i:
z[i] = (z[i - L] if i + z[i - L] < R else R - i) if R > i else 0
while i + z[i] < len(s) and s[i + z[i]] == s[z[i]]:
... | ZAlgorithm | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ZAlgorithm:
def longestSubstring(self, s):
""":type s: str :rtype: str"""
<|body_0|>
def longestPalindrome(self, s):
""":type s: str :rtype: str"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
z = [0 for _ in range(len(s))]
L, R = (0, 1)
... | stack_v2_sparse_classes_75kplus_train_066274 | 1,578 | no_license | [
{
"docstring": ":type s: str :rtype: str",
"name": "longestSubstring",
"signature": "def longestSubstring(self, s)"
},
{
"docstring": ":type s: str :rtype: str",
"name": "longestPalindrome",
"signature": "def longestPalindrome(self, s)"
}
] | 2 | stack_v2_sparse_classes_30k_train_042343 | Implement the Python class `ZAlgorithm` described below.
Class description:
Implement the ZAlgorithm class.
Method signatures and docstrings:
- def longestSubstring(self, s): :type s: str :rtype: str
- def longestPalindrome(self, s): :type s: str :rtype: str | Implement the Python class `ZAlgorithm` described below.
Class description:
Implement the ZAlgorithm class.
Method signatures and docstrings:
- def longestSubstring(self, s): :type s: str :rtype: str
- def longestPalindrome(self, s): :type s: str :rtype: str
<|skeleton|>
class ZAlgorithm:
def longestSubstring(s... | 0e93358ecd06e6c44637bc6f67f52c964bc2c1e2 | <|skeleton|>
class ZAlgorithm:
def longestSubstring(self, s):
""":type s: str :rtype: str"""
<|body_0|>
def longestPalindrome(self, s):
""":type s: str :rtype: str"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ZAlgorithm:
def longestSubstring(self, s):
""":type s: str :rtype: str"""
z = [0 for _ in range(len(s))]
L, R = (0, 1)
for i in range(1, len(s)):
if R <= i or z[i - L] >= R - i:
z[i] = (z[i - L] if i + z[i - L] < R else R - i) if R > i else 0
... | the_stack_v2_python_sparse | z.py | easydaniel/leetcode | train | 0 | |
2697b628a60034f76dfd09e9f3cddeecb1e5d11e | [
"super(PreModParser, self).__init__(node)\nif not issubclass(node.process_class, CalculationFactory('premod')):\n raise exceptions.ParsingError('Can only parse PreModCalculation')",
"try:\n output_folder = self.retrieved\nexcept exceptions.NotExistent:\n return self.exit_codes.ERROR_NO_RETRIEVED_FOLDE\nf... | <|body_start_0|>
super(PreModParser, self).__init__(node)
if not issubclass(node.process_class, CalculationFactory('premod')):
raise exceptions.ParsingError('Can only parse PreModCalculation')
<|end_body_0|>
<|body_start_1|>
try:
output_folder = self.retrieved
ex... | Parser class for parsing output of calculation. | PreModParser | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PreModParser:
"""Parser class for parsing output of calculation."""
def __init__(self, node):
"""Initialize Parser instance Checks that the ProcessNode being passed was produced by a PreModCalculation. :param node: ProcessNode of calculation :param type node: :class:`aiida.orm.Proces... | stack_v2_sparse_classes_75kplus_train_066275 | 2,374 | permissive | [
{
"docstring": "Initialize Parser instance Checks that the ProcessNode being passed was produced by a PreModCalculation. :param node: ProcessNode of calculation :param type node: :class:`aiida.orm.ProcessNode`",
"name": "__init__",
"signature": "def __init__(self, node)"
},
{
"docstring": "Parse... | 2 | stack_v2_sparse_classes_30k_train_011855 | Implement the Python class `PreModParser` described below.
Class description:
Parser class for parsing output of calculation.
Method signatures and docstrings:
- def __init__(self, node): Initialize Parser instance Checks that the ProcessNode being passed was produced by a PreModCalculation. :param node: ProcessNode ... | Implement the Python class `PreModParser` described below.
Class description:
Parser class for parsing output of calculation.
Method signatures and docstrings:
- def __init__(self, node): Initialize Parser instance Checks that the ProcessNode being passed was produced by a PreModCalculation. :param node: ProcessNode ... | 6c202841786edc8897a3b8a872792dadb78b13fd | <|skeleton|>
class PreModParser:
"""Parser class for parsing output of calculation."""
def __init__(self, node):
"""Initialize Parser instance Checks that the ProcessNode being passed was produced by a PreModCalculation. :param node: ProcessNode of calculation :param type node: :class:`aiida.orm.Proces... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PreModParser:
"""Parser class for parsing output of calculation."""
def __init__(self, node):
"""Initialize Parser instance Checks that the ProcessNode being passed was produced by a PreModCalculation. :param node: ProcessNode of calculation :param type node: :class:`aiida.orm.ProcessNode`"""
... | the_stack_v2_python_sparse | aiida_premod/parsers/premod.py | SINTEF/aiida-premod | train | 0 |
fcc183c46f90d3cf6067728dd8ce56a5a08d735c | [
"self.directory: str = directory\nself.files_summary: Dict[str, Dict[str, int]] = dict()\nself.analyze_files()",
"py_files: List = [f for f in os.listdir(self.directory) if f.endswith('.py')]\nfor pyf in py_files:\n try:\n file: IO = open(os.path.join(self.directory, pyf), 'r')\n classes: int = 0... | <|body_start_0|>
self.directory: str = directory
self.files_summary: Dict[str, Dict[str, int]] = dict()
self.analyze_files()
<|end_body_0|>
<|body_start_1|>
py_files: List = [f for f in os.listdir(self.directory) if f.endswith('.py')]
for pyf in py_files:
try:
... | Class which checks for python files and analyzes the content. | FileAnalyzer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FileAnalyzer:
"""Class which checks for python files and analyzes the content."""
def __init__(self, directory: str) -> None:
"""Constructor to initialize data structure and call class methods analyze_files and pretty_print."""
<|body_0|>
def analyze_files(self) -> None:... | stack_v2_sparse_classes_75kplus_train_066276 | 3,592 | no_license | [
{
"docstring": "Constructor to initialize data structure and call class methods analyze_files and pretty_print.",
"name": "__init__",
"signature": "def __init__(self, directory: str) -> None"
},
{
"docstring": "Your docstring should go here for the description of the method.",
"name": "analy... | 3 | stack_v2_sparse_classes_30k_train_018961 | Implement the Python class `FileAnalyzer` described below.
Class description:
Class which checks for python files and analyzes the content.
Method signatures and docstrings:
- def __init__(self, directory: str) -> None: Constructor to initialize data structure and call class methods analyze_files and pretty_print.
- ... | Implement the Python class `FileAnalyzer` described below.
Class description:
Class which checks for python files and analyzes the content.
Method signatures and docstrings:
- def __init__(self, directory: str) -> None: Constructor to initialize data structure and call class methods analyze_files and pretty_print.
- ... | f36e34adab9f2723890aa87e1e02fb20ffb440c5 | <|skeleton|>
class FileAnalyzer:
"""Class which checks for python files and analyzes the content."""
def __init__(self, directory: str) -> None:
"""Constructor to initialize data structure and call class methods analyze_files and pretty_print."""
<|body_0|>
def analyze_files(self) -> None:... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class FileAnalyzer:
"""Class which checks for python files and analyzes the content."""
def __init__(self, directory: str) -> None:
"""Constructor to initialize data structure and call class methods analyze_files and pretty_print."""
self.directory: str = directory
self.files_summary: D... | the_stack_v2_python_sparse | Assignments/HW08_Aditya_Kulkarni.py | BeardedAmbivert/SSW-810-Python | train | 0 |
af13a6efae40d4a59114f91cec56a62d07a72054 | [
"node_set = sorted(reduce(lambda x, y: x + y, communities))\nassert (np.arange(len(node_set)) == np.array(node_set)).all(), 'communities is not a partition of {0, 1, ..., n-1}'\nself.no_vertices = len(node_set)\nself.communities = [np.array(c) for c in communities]\nself.no_communities = len(self.communities)\nmemb... | <|body_start_0|>
node_set = sorted(reduce(lambda x, y: x + y, communities))
assert (np.arange(len(node_set)) == np.array(node_set)).all(), 'communities is not a partition of {0, 1, ..., n-1}'
self.no_vertices = len(node_set)
self.communities = [np.array(c) for c in communities]
s... | Wilson, James D., Nathaniel T. Stevens, and William H. Woodall. ``Modeling and estimating change in temporal networks via a dynamic degree corrected stochastic block model.'' arXiv preprint arXiv:1605.04049 (2016). | DegreeCorrectedStochasticBlockModel | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DegreeCorrectedStochasticBlockModel:
"""Wilson, James D., Nathaniel T. Stevens, and William H. Woodall. ``Modeling and estimating change in temporal networks via a dynamic degree corrected stochastic block model.'' arXiv preprint arXiv:1605.04049 (2016)."""
def __init__(self, communities, pr... | stack_v2_sparse_classes_75kplus_train_066277 | 6,435 | permissive | [
{
"docstring": ":param communities: (list of lists) partition of set {0, ..., n-1} :param prob_matrix: (np.ndarray(no_communities, no_communities)) inter- and intra-community link propensity :param theta: (np.ndarray(no_nodes,)) degree correction :param delta: (np.ndarray(no_communities,)) parameters to generat... | 3 | null | Implement the Python class `DegreeCorrectedStochasticBlockModel` described below.
Class description:
Wilson, James D., Nathaniel T. Stevens, and William H. Woodall. ``Modeling and estimating change in temporal networks via a dynamic degree corrected stochastic block model.'' arXiv preprint arXiv:1605.04049 (2016).
Me... | Implement the Python class `DegreeCorrectedStochasticBlockModel` described below.
Class description:
Wilson, James D., Nathaniel T. Stevens, and William H. Woodall. ``Modeling and estimating change in temporal networks via a dynamic degree corrected stochastic block model.'' arXiv preprint arXiv:1605.04049 (2016).
Me... | b76f8e4bae01fba3c48e13b1e1c5d9568a20b77c | <|skeleton|>
class DegreeCorrectedStochasticBlockModel:
"""Wilson, James D., Nathaniel T. Stevens, and William H. Woodall. ``Modeling and estimating change in temporal networks via a dynamic degree corrected stochastic block model.'' arXiv preprint arXiv:1605.04049 (2016)."""
def __init__(self, communities, pr... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DegreeCorrectedStochasticBlockModel:
"""Wilson, James D., Nathaniel T. Stevens, and William H. Woodall. ``Modeling and estimating change in temporal networks via a dynamic degree corrected stochastic block model.'' arXiv preprint arXiv:1605.04049 (2016)."""
def __init__(self, communities, prob_matrix, th... | the_stack_v2_python_sparse | cdg/graph/sbm.py | gluon31/cdg | train | 0 |
78db134fffac10f1e3c757a6506cbf1135214a5f | [
"rawline = self.file.readline()\nwhile rawline:\n rematch = self.line_re.match(rawline)\n if not rematch:\n rawline = self.file.readline()\n continue\n while rematch:\n rep = Replica()\n self.reps.append(rep)\n rep.index = [0 for i in range(self.numexchg)]\n rep.po... | <|body_start_0|>
rawline = self.file.readline()
while rawline:
rematch = self.line_re.match(rawline)
if not rematch:
rawline = self.file.readline()
continue
while rematch:
rep = Replica()
self.reps.append... | Replica exchange log file | TempRemLog | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TempRemLog:
"""Replica exchange log file"""
def _get_replicas(self):
"""Gets all of the replica information from the first block of repinfo"""
<|body_0|>
def _parse(self):
"""Parses the rem.log file and loads the data arrays"""
<|body_1|>
<|end_skeleton|... | stack_v2_sparse_classes_75kplus_train_066278 | 12,296 | no_license | [
{
"docstring": "Gets all of the replica information from the first block of repinfo",
"name": "_get_replicas",
"signature": "def _get_replicas(self)"
},
{
"docstring": "Parses the rem.log file and loads the data arrays",
"name": "_parse",
"signature": "def _parse(self)"
}
] | 2 | stack_v2_sparse_classes_30k_val_001263 | Implement the Python class `TempRemLog` described below.
Class description:
Replica exchange log file
Method signatures and docstrings:
- def _get_replicas(self): Gets all of the replica information from the first block of repinfo
- def _parse(self): Parses the rem.log file and loads the data arrays | Implement the Python class `TempRemLog` described below.
Class description:
Replica exchange log file
Method signatures and docstrings:
- def _get_replicas(self): Gets all of the replica information from the first block of repinfo
- def _parse(self): Parses the rem.log file and loads the data arrays
<|skeleton|>
cla... | 5cec8112637be7a19c4aac893f612aa8c354b733 | <|skeleton|>
class TempRemLog:
"""Replica exchange log file"""
def _get_replicas(self):
"""Gets all of the replica information from the first block of repinfo"""
<|body_0|>
def _parse(self):
"""Parses the rem.log file and loads the data arrays"""
<|body_1|>
<|end_skeleton|... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TempRemLog:
"""Replica exchange log file"""
def _get_replicas(self):
"""Gets all of the replica information from the first block of repinfo"""
rawline = self.file.readline()
while rawline:
rematch = self.line_re.match(rawline)
if not rematch:
... | the_stack_v2_python_sparse | remd.py | jeff-wang/JmsScripts | train | 0 |
cef4c317f83761400ab85fbddfa3f418936b94e8 | [
"session = Session()\ntry:\n user = session.query(SystemUser).get(user_id)\n if user is None:\n raise falcon.HTTPNotFound()\n errors = validate_put(req.media, user_id, role_id, session)\n if errors:\n raise HTTPUnprocessableEntity(errors)\n user_role = find_user_role(user_id, role_id, s... | <|body_start_0|>
session = Session()
try:
user = session.query(SystemUser).get(user_id)
if user is None:
raise falcon.HTTPNotFound()
errors = validate_put(req.media, user_id, role_id, session)
if errors:
raise HTTPUnprocessa... | PUT and DELETE a system role to/from a user. | Item | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Item:
"""PUT and DELETE a system role to/from a user."""
def on_put(self, req, resp, user_id, role_id):
"""Adds a role to a system user. :param req: See Falcon Request documentation. :param resp: See Falcon Response documentation. :param user_id: The id of user. :param role_id: The i... | stack_v2_sparse_classes_75kplus_train_066279 | 2,870 | no_license | [
{
"docstring": "Adds a role to a system user. :param req: See Falcon Request documentation. :param resp: See Falcon Response documentation. :param user_id: The id of user. :param role_id: The id of role to be added.",
"name": "on_put",
"signature": "def on_put(self, req, resp, user_id, role_id)"
},
... | 2 | null | Implement the Python class `Item` described below.
Class description:
PUT and DELETE a system role to/from a user.
Method signatures and docstrings:
- def on_put(self, req, resp, user_id, role_id): Adds a role to a system user. :param req: See Falcon Request documentation. :param resp: See Falcon Response documentati... | Implement the Python class `Item` described below.
Class description:
PUT and DELETE a system role to/from a user.
Method signatures and docstrings:
- def on_put(self, req, resp, user_id, role_id): Adds a role to a system user. :param req: See Falcon Request documentation. :param resp: See Falcon Response documentati... | 62723133595829230e5b589431a32cda3b092460 | <|skeleton|>
class Item:
"""PUT and DELETE a system role to/from a user."""
def on_put(self, req, resp, user_id, role_id):
"""Adds a role to a system user. :param req: See Falcon Request documentation. :param resp: See Falcon Response documentation. :param user_id: The id of user. :param role_id: The i... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Item:
"""PUT and DELETE a system role to/from a user."""
def on_put(self, req, resp, user_id, role_id):
"""Adds a role to a system user. :param req: See Falcon Request documentation. :param resp: See Falcon Response documentation. :param user_id: The id of user. :param role_id: The id of role to ... | the_stack_v2_python_sparse | knoweak/api/resources/system_user_role.py | psvaiter/knoweak-api | train | 0 |
fdc2fbb7b22f2d2bb237b4c8d4129692f207ec7e | [
"self.stream = stream\nself.queue = Queue()\nself.thread = Thread(target=self.wait_output)\nself.thread.daemon = True\nself.thread.start()\nself.decoder = OutputDecoder()",
"for line in iter(self.stream.readline, b''):\n self.queue.put(line)\nself.stream.close()",
"result = []\ntry:\n for i in range(0, 10... | <|body_start_0|>
self.stream = stream
self.queue = Queue()
self.thread = Thread(target=self.wait_output)
self.thread.daemon = True
self.thread.start()
self.decoder = OutputDecoder()
<|end_body_0|>
<|body_start_1|>
for line in iter(self.stream.readline, b''):
... | Non-blocking stream reader. Uses in WebConsole. | OutputReader | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OutputReader:
"""Non-blocking stream reader. Uses in WebConsole."""
def __init__(self, stream):
"""Creates thread which wait data from stream and put they in inter-thread queue :param stream: stream to read"""
<|body_0|>
def wait_output(self):
"""Reading thread e... | stack_v2_sparse_classes_75kplus_train_066280 | 1,670 | permissive | [
{
"docstring": "Creates thread which wait data from stream and put they in inter-thread queue :param stream: stream to read",
"name": "__init__",
"signature": "def __init__(self, stream)"
},
{
"docstring": "Reading thread entry point",
"name": "wait_output",
"signature": "def wait_output... | 3 | stack_v2_sparse_classes_30k_train_008822 | Implement the Python class `OutputReader` described below.
Class description:
Non-blocking stream reader. Uses in WebConsole.
Method signatures and docstrings:
- def __init__(self, stream): Creates thread which wait data from stream and put they in inter-thread queue :param stream: stream to read
- def wait_output(se... | Implement the Python class `OutputReader` described below.
Class description:
Non-blocking stream reader. Uses in WebConsole.
Method signatures and docstrings:
- def __init__(self, stream): Creates thread which wait data from stream and put they in inter-thread queue :param stream: stream to read
- def wait_output(se... | a33ba547f553bcce415f7a54bd89c444f82e48ee | <|skeleton|>
class OutputReader:
"""Non-blocking stream reader. Uses in WebConsole."""
def __init__(self, stream):
"""Creates thread which wait data from stream and put they in inter-thread queue :param stream: stream to read"""
<|body_0|>
def wait_output(self):
"""Reading thread e... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class OutputReader:
"""Non-blocking stream reader. Uses in WebConsole."""
def __init__(self, stream):
"""Creates thread which wait data from stream and put they in inter-thread queue :param stream: stream to read"""
self.stream = stream
self.queue = Queue()
self.thread = Thread(... | the_stack_v2_python_sparse | Zoocmd/core/api/util/streams.py | worriy/zoo | train | 0 |
7e2ec42e8a0146bff17f738a6c94158b7e8367d0 | [
"if not matrix:\n return False\nfor x in xrange(len(matrix)):\n if target in matrix[x]:\n return True\nreturn False",
"if not matrix:\n return False\nrow = len(matrix)\ncol = len(matrix[0])\nleft = 0\nright = row * col\nwhile left < right:\n mid = left + (right - left) / 2\n if matrix[mid / ... | <|body_start_0|>
if not matrix:
return False
for x in xrange(len(matrix)):
if target in matrix[x]:
return True
return False
<|end_body_0|>
<|body_start_1|>
if not matrix:
return False
row = len(matrix)
col = len(matrix[... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def searchMatrix(self, matrix, target):
""":type matrix: List[List[int]] :type target: int :rtype: bool"""
<|body_0|>
def BinsearchMatrix(self, matrix, target):
""":type matrix: List[List[int]] :type target: int :rtype: bool"""
<|body_1|>
def B... | stack_v2_sparse_classes_75kplus_train_066281 | 2,285 | no_license | [
{
"docstring": ":type matrix: List[List[int]] :type target: int :rtype: bool",
"name": "searchMatrix",
"signature": "def searchMatrix(self, matrix, target)"
},
{
"docstring": ":type matrix: List[List[int]] :type target: int :rtype: bool",
"name": "BinsearchMatrix",
"signature": "def Bins... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def searchMatrix(self, matrix, target): :type matrix: List[List[int]] :type target: int :rtype: bool
- def BinsearchMatrix(self, matrix, target): :type matrix: List[List[int]] :t... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def searchMatrix(self, matrix, target): :type matrix: List[List[int]] :type target: int :rtype: bool
- def BinsearchMatrix(self, matrix, target): :type matrix: List[List[int]] :t... | 2d5fa4cd696d5035ea8859befeadc5cc436959c9 | <|skeleton|>
class Solution:
def searchMatrix(self, matrix, target):
""":type matrix: List[List[int]] :type target: int :rtype: bool"""
<|body_0|>
def BinsearchMatrix(self, matrix, target):
""":type matrix: List[List[int]] :type target: int :rtype: bool"""
<|body_1|>
def B... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def searchMatrix(self, matrix, target):
""":type matrix: List[List[int]] :type target: int :rtype: bool"""
if not matrix:
return False
for x in xrange(len(matrix)):
if target in matrix[x]:
return True
return False
def Binse... | the_stack_v2_python_sparse | SourceCode/Python/Problem/00074.Search a 2D Matrix.py | roger6blog/LeetCode | train | 0 | |
88dba35202f1a18de87bb1f842951da36c7c6c24 | [
"user = self.request.user\nusername = user.username\ntry:\n article = Article.objects.get(id=article_id)\nexcept:\n return Response({'error': 'No article with that id found.'}, status=status.HTTP_404_NOT_FOUND)\nbookmark = Bookmark.objects.filter(article_id=article_id)\nif bookmark.exists() and (not bookmark[... | <|body_start_0|>
user = self.request.user
username = user.username
try:
article = Article.objects.get(id=article_id)
except:
return Response({'error': 'No article with that id found.'}, status=status.HTTP_404_NOT_FOUND)
bookmark = Bookmark.objects.filter(a... | Contains views that allow a user to create a single bookmark and fetch an article. | CreateBookmark | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CreateBookmark:
"""Contains views that allow a user to create a single bookmark and fetch an article."""
def post(self, request, article_id):
"""Accepts an article id argument as an int from the URL. Creates a bookmark object for an existing article. It then creates a relationship be... | stack_v2_sparse_classes_75kplus_train_066282 | 3,342 | permissive | [
{
"docstring": "Accepts an article id argument as an int from the URL. Creates a bookmark object for an existing article. It then creates a relationship between the current user object and the article bookmark.",
"name": "post",
"signature": "def post(self, request, article_id)"
},
{
"docstring"... | 2 | stack_v2_sparse_classes_30k_test_000743 | Implement the Python class `CreateBookmark` described below.
Class description:
Contains views that allow a user to create a single bookmark and fetch an article.
Method signatures and docstrings:
- def post(self, request, article_id): Accepts an article id argument as an int from the URL. Creates a bookmark object f... | Implement the Python class `CreateBookmark` described below.
Class description:
Contains views that allow a user to create a single bookmark and fetch an article.
Method signatures and docstrings:
- def post(self, request, article_id): Accepts an article id argument as an int from the URL. Creates a bookmark object f... | 4b14cce62be06c0bd652fcc9be3264d8c62f8718 | <|skeleton|>
class CreateBookmark:
"""Contains views that allow a user to create a single bookmark and fetch an article."""
def post(self, request, article_id):
"""Accepts an article id argument as an int from the URL. Creates a bookmark object for an existing article. It then creates a relationship be... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CreateBookmark:
"""Contains views that allow a user to create a single bookmark and fetch an article."""
def post(self, request, article_id):
"""Accepts an article id argument as an int from the URL. Creates a bookmark object for an existing article. It then creates a relationship between the cur... | the_stack_v2_python_sparse | authors/apps/bookmark/views.py | andela/ah-the-answer-backend | train | 0 |
f26b3bed25a3f985b8e2299e4a2efbe94b7f9775 | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn OnenotePage()",
"from .notebook import Notebook\nfrom .onenote_entity_schema_object_model import OnenoteEntitySchemaObjectModel\nfrom .onenote_section import OnenoteSection\nfrom .page_links import PageLinks\nfrom .notebook import Note... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return OnenotePage()
<|end_body_0|>
<|body_start_1|>
from .notebook import Notebook
from .onenote_entity_schema_object_model import OnenoteEntitySchemaObjectModel
from .onenote_section ... | OnenotePage | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OnenotePage:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> OnenotePage:
"""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: On... | stack_v2_sparse_classes_75kplus_train_066283 | 5,456 | 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: OnenotePage",
"name": "create_from_discriminator_value",
"signature": "def create_from_discriminator_value(p... | 3 | stack_v2_sparse_classes_30k_train_051196 | Implement the Python class `OnenotePage` described below.
Class description:
Implement the OnenotePage class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> OnenotePage: Creates a new instance of the appropriate class based on discriminator value Args:... | Implement the Python class `OnenotePage` described below.
Class description:
Implement the OnenotePage class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> OnenotePage: Creates a new instance of the appropriate class based on discriminator value Args:... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class OnenotePage:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> OnenotePage:
"""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: On... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class OnenotePage:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> OnenotePage:
"""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: OnenotePage"""
... | the_stack_v2_python_sparse | msgraph/generated/models/onenote_page.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
d284feb9047341fa3ce83d4216398ebe61aa9dd0 | [
"if not (userName or tabelNumber):\n raise ValueError('Users must have an username and tabel number')\nuser = self.model(userName=userName, tabelNumber=tabelNumber)\nuser.set_password(password)\nuser.save(using=self._db)\nreturn user",
"user = self.create_user(userName, tabelNumber, password=password)\nuser.is... | <|body_start_0|>
if not (userName or tabelNumber):
raise ValueError('Users must have an username and tabel number')
user = self.model(userName=userName, tabelNumber=tabelNumber)
user.set_password(password)
user.save(using=self._db)
return user
<|end_body_0|>
<|body_s... | UserKBManager | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserKBManager:
def create_user(self, userName, tabelNumber, password=None):
"""Creates and saves a User with the given username, date of birth and password."""
<|body_0|>
def create_superuser(self, userName, tabelNumber, password):
"""Creates and saves a superuser wi... | stack_v2_sparse_classes_75kplus_train_066284 | 4,079 | no_license | [
{
"docstring": "Creates and saves a User with the given username, date of birth and password.",
"name": "create_user",
"signature": "def create_user(self, userName, tabelNumber, password=None)"
},
{
"docstring": "Creates and saves a superuser with the given username, date of birth and password."... | 2 | null | Implement the Python class `UserKBManager` described below.
Class description:
Implement the UserKBManager class.
Method signatures and docstrings:
- def create_user(self, userName, tabelNumber, password=None): Creates and saves a User with the given username, date of birth and password.
- def create_superuser(self, ... | Implement the Python class `UserKBManager` described below.
Class description:
Implement the UserKBManager class.
Method signatures and docstrings:
- def create_user(self, userName, tabelNumber, password=None): Creates and saves a User with the given username, date of birth and password.
- def create_superuser(self, ... | a70f2b9c930a07b9db85b08e3bc725cef11d56f6 | <|skeleton|>
class UserKBManager:
def create_user(self, userName, tabelNumber, password=None):
"""Creates and saves a User with the given username, date of birth and password."""
<|body_0|>
def create_superuser(self, userName, tabelNumber, password):
"""Creates and saves a superuser wi... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class UserKBManager:
def create_user(self, userName, tabelNumber, password=None):
"""Creates and saves a User with the given username, date of birth and password."""
if not (userName or tabelNumber):
raise ValueError('Users must have an username and tabel number')
user = self.mod... | the_stack_v2_python_sparse | KB_Users/models.py | party13/ticketProject | train | 0 | |
901129522cc3a85bd4e23a8cd08ff7e9184bc8f0 | [
"self._dist = dist\nself._p = dist.pmf\nself._domain = np.stack(domain)\nself._domain_inv = np.linalg.pinv(self._domain)",
"q = np.dot(x, self._domain)\nq /= q.sum()\nreturn q",
"q = self._q(x)\ndkl = relative_entropy(self._p, q)\nreturn dkl",
"x0 = np.dot(self._p, self._domain_inv)\nbounds = [(0, 1)] * x0.si... | <|body_start_0|>
self._dist = dist
self._p = dist.pmf
self._domain = np.stack(domain)
self._domain_inv = np.linalg.pinv(self._domain)
<|end_body_0|>
<|body_start_1|>
q = np.dot(x, self._domain)
q /= q.sum()
return q
<|end_body_1|>
<|body_start_2|>
q = se... | An optimizer to find the minimum D_KL(p||q) given p and a restriction on the domain of q. | MinDKLOptimizer | [
"LicenseRef-scancode-unknown-license-reference",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MinDKLOptimizer:
"""An optimizer to find the minimum D_KL(p||q) given p and a restriction on the domain of q."""
def __init__(self, dist, domain):
"""Initialize the optimizer. Parameters ---------- dist : Distribution The distribution `p`. domain : list of lists The pmfs defining the... | stack_v2_sparse_classes_75kplus_train_066285 | 5,557 | permissive | [
{
"docstring": "Initialize the optimizer. Parameters ---------- dist : Distribution The distribution `p`. domain : list of lists The pmfs defining the domain over which `q` is optimized.",
"name": "__init__",
"signature": "def __init__(self, dist, domain)"
},
{
"docstring": "Transform `x` into a... | 5 | stack_v2_sparse_classes_30k_train_041976 | Implement the Python class `MinDKLOptimizer` described below.
Class description:
An optimizer to find the minimum D_KL(p||q) given p and a restriction on the domain of q.
Method signatures and docstrings:
- def __init__(self, dist, domain): Initialize the optimizer. Parameters ---------- dist : Distribution The distr... | Implement the Python class `MinDKLOptimizer` described below.
Class description:
An optimizer to find the minimum D_KL(p||q) given p and a restriction on the domain of q.
Method signatures and docstrings:
- def __init__(self, dist, domain): Initialize the optimizer. Parameters ---------- dist : Distribution The distr... | b13c5020a2b8524527a4a0db5a81d8549142228c | <|skeleton|>
class MinDKLOptimizer:
"""An optimizer to find the minimum D_KL(p||q) given p and a restriction on the domain of q."""
def __init__(self, dist, domain):
"""Initialize the optimizer. Parameters ---------- dist : Distribution The distribution `p`. domain : list of lists The pmfs defining the... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MinDKLOptimizer:
"""An optimizer to find the minimum D_KL(p||q) given p and a restriction on the domain of q."""
def __init__(self, dist, domain):
"""Initialize the optimizer. Parameters ---------- dist : Distribution The distribution `p`. domain : list of lists The pmfs defining the domain over ... | the_stack_v2_python_sparse | dit/pid/measures/iproj.py | dit/dit | train | 468 |
9ff5c1cc53d609e2729b3e61fd0dd7faddc563c9 | [
"char_count = {}\nfor c in s:\n char_count[c] = char_count.get(c, 0) + 1\nmax_odd = 1\nmax_pal_len = 0\nhas_max_odd = False\nfor word in char_count:\n if char_count[word] % 2 == 0:\n max_pal_len += char_count[word]\n elif char_count[word] >= max_odd:\n has_max_odd = True\n max_pal_len ... | <|body_start_0|>
char_count = {}
for c in s:
char_count[c] = char_count.get(c, 0) + 1
max_odd = 1
max_pal_len = 0
has_max_odd = False
for word in char_count:
if char_count[word] % 2 == 0:
max_pal_len += char_count[word]
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def longestPalindrome1(self, s):
""":type s: str :rtype: int"""
<|body_0|>
def longestPalindrome(self, s):
""":type s: str :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
char_count = {}
for c in s:
char_cou... | stack_v2_sparse_classes_75kplus_train_066286 | 1,678 | no_license | [
{
"docstring": ":type s: str :rtype: int",
"name": "longestPalindrome1",
"signature": "def longestPalindrome1(self, s)"
},
{
"docstring": ":type s: str :rtype: int",
"name": "longestPalindrome",
"signature": "def longestPalindrome(self, s)"
}
] | 2 | stack_v2_sparse_classes_30k_train_019213 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longestPalindrome1(self, s): :type s: str :rtype: int
- def longestPalindrome(self, s): :type s: str :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longestPalindrome1(self, s): :type s: str :rtype: int
- def longestPalindrome(self, s): :type s: str :rtype: int
<|skeleton|>
class Solution:
def longestPalindrome1(sel... | 852fad258f5070c7b93c35252f7404e85e709ea6 | <|skeleton|>
class Solution:
def longestPalindrome1(self, s):
""":type s: str :rtype: int"""
<|body_0|>
def longestPalindrome(self, s):
""":type s: str :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def longestPalindrome1(self, s):
""":type s: str :rtype: int"""
char_count = {}
for c in s:
char_count[c] = char_count.get(c, 0) + 1
max_odd = 1
max_pal_len = 0
has_max_odd = False
for word in char_count:
if char_count[w... | the_stack_v2_python_sparse | 401-500/409. Longest Palindrome.py | SunnyMarkLiu/LeetCode | train | 1 | |
59b0a26114af22dbfaee93ff23ee86ca39e2fdf5 | [
"probabilities = []\nlist_theoretical_amplitude = []\nbest_algorithms = []\nconfigurations = []\nlist_number_calls_made = []\nimprovements = []\nfor eta_group in self._eta_groups:\n self._global_eta_group = eta_group\n result = self._compute_theoretical_best_configuration()\n best_algorithms.append(result[... | <|body_start_0|>
probabilities = []
list_theoretical_amplitude = []
best_algorithms = []
configurations = []
list_number_calls_made = []
improvements = []
for eta_group in self._eta_groups:
self._global_eta_group = eta_group
result = self._... | Representation of the theoretical One Shot Optimization | TheoreticalOneShotEntangledOptimization | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TheoreticalOneShotEntangledOptimization:
"""Representation of the theoretical One Shot Optimization"""
def compute_theoretical_optimal_results(self) -> TheoreticalOneShotEntangledOptimalConfigurations:
"""Finds out the theoretical optimal entangled configuration for each pair of atte... | stack_v2_sparse_classes_75kplus_train_066287 | 3,912 | permissive | [
{
"docstring": "Finds out the theoretical optimal entangled configuration for each pair of attenuation levels",
"name": "compute_theoretical_optimal_results",
"signature": "def compute_theoretical_optimal_results(self) -> TheoreticalOneShotEntangledOptimalConfigurations"
},
{
"docstring": "Find ... | 2 | stack_v2_sparse_classes_30k_train_019482 | Implement the Python class `TheoreticalOneShotEntangledOptimization` described below.
Class description:
Representation of the theoretical One Shot Optimization
Method signatures and docstrings:
- def compute_theoretical_optimal_results(self) -> TheoreticalOneShotEntangledOptimalConfigurations: Finds out the theoreti... | Implement the Python class `TheoreticalOneShotEntangledOptimization` described below.
Class description:
Representation of the theoretical One Shot Optimization
Method signatures and docstrings:
- def compute_theoretical_optimal_results(self) -> TheoreticalOneShotEntangledOptimalConfigurations: Finds out the theoreti... | ea37fca21fc4c8cf7ac6a39b3a6666e8a4fe5a19 | <|skeleton|>
class TheoreticalOneShotEntangledOptimization:
"""Representation of the theoretical One Shot Optimization"""
def compute_theoretical_optimal_results(self) -> TheoreticalOneShotEntangledOptimalConfigurations:
"""Finds out the theoretical optimal entangled configuration for each pair of atte... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TheoreticalOneShotEntangledOptimization:
"""Representation of the theoretical One Shot Optimization"""
def compute_theoretical_optimal_results(self) -> TheoreticalOneShotEntangledOptimalConfigurations:
"""Finds out the theoretical optimal entangled configuration for each pair of attenuation level... | the_stack_v2_python_sparse | qcd/optimizations/theoreticaloneshotentangledoptimization.py | iamtxena/quantum-channel-discrimination | train | 0 |
b6dc7579deb3358c6d85852a8fba19a696e533e2 | [
"assert self.f.findString('3rd') == self.lines[2]\nassert self.f.currentLine() == self.lines[2]\nself.f.toEOF()\nassert self.f.findString('1st', backward=True) == self.lines[0]\nassert self.f.currentLine() == self.lines[0]",
"assert self.f.findString('line', 2) == self.lines[1]\nassert self.f.currentLine() == sel... | <|body_start_0|>
assert self.f.findString('3rd') == self.lines[2]
assert self.f.currentLine() == self.lines[2]
self.f.toEOF()
assert self.f.findString('1st', backward=True) == self.lines[0]
assert self.f.currentLine() == self.lines[0]
<|end_body_0|>
<|body_start_1|>
asse... | Test findString | FileReaderFindStringTest | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FileReaderFindStringTest:
"""Test findString"""
def testFindStringBasic(self):
"""Findstring functionality/basic search"""
<|body_0|>
def testFindStringCounted(self):
"""Findstring functionality/counted search"""
<|body_1|>
def testFindStringNotFound... | stack_v2_sparse_classes_75kplus_train_066288 | 10,074 | no_license | [
{
"docstring": "Findstring functionality/basic search",
"name": "testFindStringBasic",
"signature": "def testFindStringBasic(self)"
},
{
"docstring": "Findstring functionality/counted search",
"name": "testFindStringCounted",
"signature": "def testFindStringCounted(self)"
},
{
"d... | 4 | stack_v2_sparse_classes_30k_train_000285 | Implement the Python class `FileReaderFindStringTest` described below.
Class description:
Test findString
Method signatures and docstrings:
- def testFindStringBasic(self): Findstring functionality/basic search
- def testFindStringCounted(self): Findstring functionality/counted search
- def testFindStringNotFound(sel... | Implement the Python class `FileReaderFindStringTest` described below.
Class description:
Test findString
Method signatures and docstrings:
- def testFindStringBasic(self): Findstring functionality/basic search
- def testFindStringCounted(self): Findstring functionality/counted search
- def testFindStringNotFound(sel... | 5f92b013018e65bea5354be95e2538b5434d1fe7 | <|skeleton|>
class FileReaderFindStringTest:
"""Test findString"""
def testFindStringBasic(self):
"""Findstring functionality/basic search"""
<|body_0|>
def testFindStringCounted(self):
"""Findstring functionality/counted search"""
<|body_1|>
def testFindStringNotFound... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class FileReaderFindStringTest:
"""Test findString"""
def testFindStringBasic(self):
"""Findstring functionality/basic search"""
assert self.f.findString('3rd') == self.lines[2]
assert self.f.currentLine() == self.lines[2]
self.f.toEOF()
assert self.f.findString('1st', b... | the_stack_v2_python_sparse | code/libraries/testFileReader20.py | stefanoborini/quantum-chemistry | train | 0 |
4b0587f4d4fa067a590dc79ee2796214fa1a7d37 | [
"if isinstance(test, TestModule):\n log.debug('isolating sys.modules changes in %s', test)\n self._mods = sys.modules.copy()",
"if isinstance(test, TestModule):\n to_del = [m for m in sys.modules.keys() if m not in self._mods]\n if to_del:\n log.debug('removing sys modules entries: %s', to_del)... | <|body_start_0|>
if isinstance(test, TestModule):
log.debug('isolating sys.modules changes in %s', test)
self._mods = sys.modules.copy()
<|end_body_0|>
<|body_start_1|>
if isinstance(test, TestModule):
to_del = [m for m in sys.modules.keys() if m not in self._mods]
... | Activate the isolation plugin to isolate changes to external modules to a single test module or package. The isolation plugin resets the contents of sys.modules after each test module or package runs to its state before the test. PLEASE NOTE that this plugin may not be used with the coverage plugin. | IsolationPlugin | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IsolationPlugin:
"""Activate the isolation plugin to isolate changes to external modules to a single test module or package. The isolation plugin resets the contents of sys.modules after each test module or package runs to its state before the test. PLEASE NOTE that this plugin may not be used wi... | stack_v2_sparse_classes_75kplus_train_066289 | 2,101 | no_license | [
{
"docstring": "Save the state of sys.modules if we're starting a test module",
"name": "startTest",
"signature": "def startTest(self, test)"
},
{
"docstring": "Restore the saved state of sys.modules if we're ending a test module",
"name": "stopTest",
"signature": "def stopTest(self, tes... | 2 | stack_v2_sparse_classes_30k_train_010009 | Implement the Python class `IsolationPlugin` described below.
Class description:
Activate the isolation plugin to isolate changes to external modules to a single test module or package. The isolation plugin resets the contents of sys.modules after each test module or package runs to its state before the test. PLEASE N... | Implement the Python class `IsolationPlugin` described below.
Class description:
Activate the isolation plugin to isolate changes to external modules to a single test module or package. The isolation plugin resets the contents of sys.modules after each test module or package runs to its state before the test. PLEASE N... | ca228848364edb204b15a7411fd6192379781c78 | <|skeleton|>
class IsolationPlugin:
"""Activate the isolation plugin to isolate changes to external modules to a single test module or package. The isolation plugin resets the contents of sys.modules after each test module or package runs to its state before the test. PLEASE NOTE that this plugin may not be used wi... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class IsolationPlugin:
"""Activate the isolation plugin to isolate changes to external modules to a single test module or package. The isolation plugin resets the contents of sys.modules after each test module or package runs to its state before the test. PLEASE NOTE that this plugin may not be used with the covera... | the_stack_v2_python_sparse | working-env/lib/python2.5/nose-0.9.3-py2.5.egg/nose/plugins/isolate.py | thraxil/gtreed | train | 1 |
2f63d7bbb540347bc8af6a2cb9cabf9c4c17954d | [
"orderList = Shop_User(id=current_user.id).orderList\nif orderList:\n orderList = marshal(orderList, output_order)\n return Response(data=orderList)\nelse:\n return Response(code=HttpStatus.HTTP_404_NOT_FOUND, message='无符合条件的订单')",
"args = reqparse.RequestParser().add_argument('order_id', type=str, locat... | <|body_start_0|>
orderList = Shop_User(id=current_user.id).orderList
if orderList:
orderList = marshal(orderList, output_order)
return Response(data=orderList)
else:
return Response(code=HttpStatus.HTTP_404_NOT_FOUND, message='无符合条件的订单')
<|end_body_0|>
<|body... | Order | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Order:
def get(self):
"""获取个人订单 :return:"""
<|body_0|>
def post(self):
"""评价个人订单 :return:"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
orderList = Shop_User(id=current_user.id).orderList
if orderList:
orderList = marshal(order... | stack_v2_sparse_classes_75kplus_train_066290 | 2,760 | no_license | [
{
"docstring": "获取个人订单 :return:",
"name": "get",
"signature": "def get(self)"
},
{
"docstring": "评价个人订单 :return:",
"name": "post",
"signature": "def post(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_034786 | Implement the Python class `Order` described below.
Class description:
Implement the Order class.
Method signatures and docstrings:
- def get(self): 获取个人订单 :return:
- def post(self): 评价个人订单 :return: | Implement the Python class `Order` described below.
Class description:
Implement the Order class.
Method signatures and docstrings:
- def get(self): 获取个人订单 :return:
- def post(self): 评价个人订单 :return:
<|skeleton|>
class Order:
def get(self):
"""获取个人订单 :return:"""
<|body_0|>
def post(self):
... | 34a2bf4a51cc40a22dd43cb5eb88af7c2f2c5120 | <|skeleton|>
class Order:
def get(self):
"""获取个人订单 :return:"""
<|body_0|>
def post(self):
"""评价个人订单 :return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Order:
def get(self):
"""获取个人订单 :return:"""
orderList = Shop_User(id=current_user.id).orderList
if orderList:
orderList = marshal(orderList, output_order)
return Response(data=orderList)
else:
return Response(code=HttpStatus.HTTP_404_NOT_FOUN... | the_stack_v2_python_sparse | App/Shop/Controller/UserResource.py | Vulcanhy/api.grooo-master | train | 0 | |
afea820f7a66db0ac8e118890b779efacb2f0b5c | [
"if not preorder or not inorder:\n return None\nval = preorder[0]\nindex = inorder.index(val)\nleft_inorder = inorder[:index]\nright_inorder = inorder[index + 1:]\nleft_preorder = preorder[1:len(left_inorder) + 1]\nright_preorder = preorder[1 + len(left_inorder):]\nnode = TreeNode(val)\nnode.left = self.buildTre... | <|body_start_0|>
if not preorder or not inorder:
return None
val = preorder[0]
index = inorder.index(val)
left_inorder = inorder[:index]
right_inorder = inorder[index + 1:]
left_preorder = preorder[1:len(left_inorder) + 1]
right_preorder = preorder[1 +... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def buildTree(self, preorder, inorder):
"""根据先序遍历和中序遍历，构造二叉树 :type preorder: List[int] :type inorder: List[int] :rtype: TreeNode"""
<|body_0|>
def buildTree2(self, preorder, inorder):
"""根据先序遍历和中序遍历，构造二叉树 :type preorder: List[int] :type inorder: List[int] :... | stack_v2_sparse_classes_75kplus_train_066291 | 2,512 | no_license | [
{
"docstring": "根据先序遍历和中序遍历，构造二叉树 :type preorder: List[int] :type inorder: List[int] :rtype: TreeNode",
"name": "buildTree",
"signature": "def buildTree(self, preorder, inorder)"
},
{
"docstring": "根据先序遍历和中序遍历，构造二叉树 :type preorder: List[int] :type inorder: List[int] :rtype: TreeNode",
"name"... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def buildTree(self, preorder, inorder): 根据先序遍历和中序遍历，构造二叉树 :type preorder: List[int] :type inorder: List[int] :rtype: TreeNode
- def buildTree2(self, preorder, inorder): 根据先序遍历和中序... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def buildTree(self, preorder, inorder): 根据先序遍历和中序遍历，构造二叉树 :type preorder: List[int] :type inorder: List[int] :rtype: TreeNode
- def buildTree2(self, preorder, inorder): 根据先序遍历和中序... | 04d87d76b762f6ea7cfb3a453382b2d7d4e154dc | <|skeleton|>
class Solution:
def buildTree(self, preorder, inorder):
"""根据先序遍历和中序遍历，构造二叉树 :type preorder: List[int] :type inorder: List[int] :rtype: TreeNode"""
<|body_0|>
def buildTree2(self, preorder, inorder):
"""根据先序遍历和中序遍历，构造二叉树 :type preorder: List[int] :type inorder: List[int] :... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def buildTree(self, preorder, inorder):
"""根据先序遍历和中序遍历，构造二叉树 :type preorder: List[int] :type inorder: List[int] :rtype: TreeNode"""
if not preorder or not inorder:
return None
val = preorder[0]
index = inorder.index(val)
left_inorder = inorder[:ind... | the_stack_v2_python_sparse | leetcode/105 Construct Binary Tree from Preorder and Inorder Traversal.py | mofei952/algorithm_exercise | train | 1 | |
e31dfa3dce0318fdec3fef4e324bebae028a5e30 | [
"stack = []\nfinalArr = []\nfor i in range(k):\n stack.append(nums.pop())\nfor i in range(len(stack)):\n finalArr.append(stack.pop())\nfor cur in nums:\n finalArr.append(cur)\nreturn finalArr",
"k %= len(nums)\nj = 0\nfor i in range(len(nums) // 2):\n temp = nums[i]\n nums[i] = nums[len(nums) - 1 -... | <|body_start_0|>
stack = []
finalArr = []
for i in range(k):
stack.append(nums.pop())
for i in range(len(stack)):
finalArr.append(stack.pop())
for cur in nums:
finalArr.append(cur)
return finalArr
<|end_body_0|>
<|body_start_1|>
... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def rotate(self, nums, k):
""":type nums: List[int] :type k: int :rtype: void Do not return anything, modify nums in-place instead."""
<|body_0|>
def rotate_inplace(self, nums, k):
""":type nums: List[int] :type k: int :rtype: void Do not return anything, m... | stack_v2_sparse_classes_75kplus_train_066292 | 2,053 | permissive | [
{
"docstring": ":type nums: List[int] :type k: int :rtype: void Do not return anything, modify nums in-place instead.",
"name": "rotate",
"signature": "def rotate(self, nums, k)"
},
{
"docstring": ":type nums: List[int] :type k: int :rtype: void Do not return anything, modify nums in-place inste... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def rotate(self, nums, k): :type nums: List[int] :type k: int :rtype: void Do not return anything, modify nums in-place instead.
- def rotate_inplace(self, nums, k): :type nums: ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def rotate(self, nums, k): :type nums: List[int] :type k: int :rtype: void Do not return anything, modify nums in-place instead.
- def rotate_inplace(self, nums, k): :type nums: ... | 889bde40bfcd4a4f25f889355f9c5a83b9ead7d7 | <|skeleton|>
class Solution:
def rotate(self, nums, k):
""":type nums: List[int] :type k: int :rtype: void Do not return anything, modify nums in-place instead."""
<|body_0|>
def rotate_inplace(self, nums, k):
""":type nums: List[int] :type k: int :rtype: void Do not return anything, m... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def rotate(self, nums, k):
""":type nums: List[int] :type k: int :rtype: void Do not return anything, modify nums in-place instead."""
stack = []
finalArr = []
for i in range(k):
stack.append(nums.pop())
for i in range(len(stack)):
fina... | the_stack_v2_python_sparse | leetcode/easy/Arrays and Strings/RotateArray.py | rohan8594/DS-Algos | train | 3 | |
1cf037201d6afa486ec53a69b53cf18537942668 | [
"if Resource.base_path == None:\n Resource.base_path = os.path.normpath(path)\nfull_path = os.path.join(os.path.dirname(rpicard.__file__), 'static', second, path)\nif full_path != os.path.abspath(full_path):\n raise RpiCarDExp(errorcode.PARAM_ERROR, \"path '%s' is invalid\" % path)\nreturn '.'.join((full_path... | <|body_start_0|>
if Resource.base_path == None:
Resource.base_path = os.path.normpath(path)
full_path = os.path.join(os.path.dirname(rpicard.__file__), 'static', second, path)
if full_path != os.path.abspath(full_path):
raise RpiCarDExp(errorcode.PARAM_ERROR, "path '%s' i... | Resource | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Resource:
def _get_full_path(self, second, path):
"""Get full path of resource. :second: second part of the path :path: relative file path without suffix :returns: full path"""
<|body_0|>
def _get_html(self, path):
"""Get the html resource. :path: relative file path ... | stack_v2_sparse_classes_75kplus_train_066293 | 3,121 | permissive | [
{
"docstring": "Get full path of resource. :second: second part of the path :path: relative file path without suffix :returns: full path",
"name": "_get_full_path",
"signature": "def _get_full_path(self, second, path)"
},
{
"docstring": "Get the html resource. :path: relative file path without s... | 6 | null | Implement the Python class `Resource` described below.
Class description:
Implement the Resource class.
Method signatures and docstrings:
- def _get_full_path(self, second, path): Get full path of resource. :second: second part of the path :path: relative file path without suffix :returns: full path
- def _get_html(s... | Implement the Python class `Resource` described below.
Class description:
Implement the Resource class.
Method signatures and docstrings:
- def _get_full_path(self, second, path): Get full path of resource. :second: second part of the path :path: relative file path without suffix :returns: full path
- def _get_html(s... | 40a704247594ef2a9bde02e543b169d99804a011 | <|skeleton|>
class Resource:
def _get_full_path(self, second, path):
"""Get full path of resource. :second: second part of the path :path: relative file path without suffix :returns: full path"""
<|body_0|>
def _get_html(self, path):
"""Get the html resource. :path: relative file path ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Resource:
def _get_full_path(self, second, path):
"""Get full path of resource. :second: second part of the path :path: relative file path without suffix :returns: full path"""
if Resource.base_path == None:
Resource.base_path = os.path.normpath(path)
full_path = os.path.jo... | the_stack_v2_python_sparse | rpicard/webserver/resource.py | fortime/rpicard | train | 1 | |
2ee640c9b20521d327afb3fcb75af63c9205460d | [
"user = get_object_or_404(User, id=pk)\nqueryset = Friendship.objects.filter(me=user)\nreturn Response({'friends': [{'id': f.counterpart.get_user_id(), 'username': f.counterpart.get_username(), 'profile_img': Profile.objects.get(user=f.counterpart).get_profile_img(), 'status_msg': Profile.objects.get(user=f.counter... | <|body_start_0|>
user = get_object_or_404(User, id=pk)
queryset = Friendship.objects.filter(me=user)
return Response({'friends': [{'id': f.counterpart.get_user_id(), 'username': f.counterpart.get_username(), 'profile_img': Profile.objects.get(user=f.counterpart).get_profile_img(), 'status_msg': ... | FriendViewSet | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FriendViewSet:
def retrieve(self, request, pk=None):
"""## 친구 목록 조회하기 ### API url에 pk를 받아서 조회"""
<|body_0|>
def create(self, request):
"""## 친구 추가 ### API url에 pk를 받지만 실제론 토큰을 통해서 사용자를 구분한다."""
<|body_1|>
def destroy(self, request, pk=None):
"""#... | stack_v2_sparse_classes_75kplus_train_066294 | 10,169 | no_license | [
{
"docstring": "## 친구 목록 조회하기 ### API url에 pk를 받아서 조회",
"name": "retrieve",
"signature": "def retrieve(self, request, pk=None)"
},
{
"docstring": "## 친구 추가 ### API url에 pk를 받지만 실제론 토큰을 통해서 사용자를 구분한다.",
"name": "create",
"signature": "def create(self, request)"
},
{
"docstring": "... | 3 | null | Implement the Python class `FriendViewSet` described below.
Class description:
Implement the FriendViewSet class.
Method signatures and docstrings:
- def retrieve(self, request, pk=None): ## 친구 목록 조회하기 ### API url에 pk를 받아서 조회
- def create(self, request): ## 친구 추가 ### API url에 pk를 받지만 실제론 토큰을 통해서 사용자를 구분한다.
- def dest... | Implement the Python class `FriendViewSet` described below.
Class description:
Implement the FriendViewSet class.
Method signatures and docstrings:
- def retrieve(self, request, pk=None): ## 친구 목록 조회하기 ### API url에 pk를 받아서 조회
- def create(self, request): ## 친구 추가 ### API url에 pk를 받지만 실제론 토큰을 통해서 사용자를 구분한다.
- def dest... | 41a1bb3a23fed99b8816519ebf529fa029362180 | <|skeleton|>
class FriendViewSet:
def retrieve(self, request, pk=None):
"""## 친구 목록 조회하기 ### API url에 pk를 받아서 조회"""
<|body_0|>
def create(self, request):
"""## 친구 추가 ### API url에 pk를 받지만 실제론 토큰을 통해서 사용자를 구분한다."""
<|body_1|>
def destroy(self, request, pk=None):
"""#... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class FriendViewSet:
def retrieve(self, request, pk=None):
"""## 친구 목록 조회하기 ### API url에 pk를 받아서 조회"""
user = get_object_or_404(User, id=pk)
queryset = Friendship.objects.filter(me=user)
return Response({'friends': [{'id': f.counterpart.get_user_id(), 'username': f.counterpart.get_us... | the_stack_v2_python_sparse | backend/accounts/views.py | applevalley/YOGOMOGO | train | 0 | |
4eb5ed949f32b4c3950f62125948fc484466660c | [
"username = self.cleaned_data.get('username')\nif not checkutils.username_correct(username):\n raise forms.ValidationError(_(u'Username may only contain alphanumeric characters or dashes and cannot begin with a dash'))\ntry:\n User.objects.get(username=username)\nexcept ObjectDoesNotExist:\n return usernam... | <|body_start_0|>
username = self.cleaned_data.get('username')
if not checkutils.username_correct(username):
raise forms.ValidationError(_(u'Username may only contain alphanumeric characters or dashes and cannot begin with a dash'))
try:
User.objects.get(username=username)... | SignupForm | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SignupForm:
def clean_username(self):
"""Checks if the user exists and that the username is only -a-zA-Z"""
<|body_0|>
def clean_password2(self):
"""Checks if the length is correct and both passwords are the same"""
<|body_1|>
def clean_email(self):
... | stack_v2_sparse_classes_75kplus_train_066295 | 3,700 | no_license | [
{
"docstring": "Checks if the user exists and that the username is only -a-zA-Z",
"name": "clean_username",
"signature": "def clean_username(self)"
},
{
"docstring": "Checks if the length is correct and both passwords are the same",
"name": "clean_password2",
"signature": "def clean_pass... | 3 | stack_v2_sparse_classes_30k_train_045663 | Implement the Python class `SignupForm` described below.
Class description:
Implement the SignupForm class.
Method signatures and docstrings:
- def clean_username(self): Checks if the user exists and that the username is only -a-zA-Z
- def clean_password2(self): Checks if the length is correct and both passwords are ... | Implement the Python class `SignupForm` described below.
Class description:
Implement the SignupForm class.
Method signatures and docstrings:
- def clean_username(self): Checks if the user exists and that the username is only -a-zA-Z
- def clean_password2(self): Checks if the length is correct and both passwords are ... | bee916136a67f2203a7ca6078220553ae1ce9c3c | <|skeleton|>
class SignupForm:
def clean_username(self):
"""Checks if the user exists and that the username is only -a-zA-Z"""
<|body_0|>
def clean_password2(self):
"""Checks if the length is correct and both passwords are the same"""
<|body_1|>
def clean_email(self):
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SignupForm:
def clean_username(self):
"""Checks if the user exists and that the username is only -a-zA-Z"""
username = self.cleaned_data.get('username')
if not checkutils.username_correct(username):
raise forms.ValidationError(_(u'Username may only contain alphanumeric char... | the_stack_v2_python_sparse | dwarf/userprofile/forms.py | slok/dwarf | train | 1 | |
f2f1082816e85cd13bca5b0a6a2da3d5295a881b | [
"from statsmodels.tsa.api import VAR\nself.dim = timeseries.shape[1]\nself.order = r\nmodel = VAR(timeseries)\nresults = model.fit(r)\nself.summary = results.summary()\nself.covariance = results.sigma_u_mle\nself.mu = results.params[0, :]\nself.mu_std = results.stderr[0, :]\nself.phi = results.coefs\nself.phi_std =... | <|body_start_0|>
from statsmodels.tsa.api import VAR
self.dim = timeseries.shape[1]
self.order = r
model = VAR(timeseries)
results = model.fit(r)
self.summary = results.summary()
self.covariance = results.sigma_u_mle
self.mu = results.params[0, :]
... | VectorAutoRegression | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VectorAutoRegression:
def __init__(self, timeseries, r):
"""Fit a vector autogressive (VAR) process to data using statsmodels.tsa.vector_ar. The output object is just reduction and renaming of attributes produced after running the fit() method of the VAR class For more detailed docs, see... | stack_v2_sparse_classes_75kplus_train_066296 | 26,530 | permissive | [
{
"docstring": "Fit a vector autogressive (VAR) process to data using statsmodels.tsa.vector_ar. The output object is just reduction and renaming of attributes produced after running the fit() method of the VAR class For more detailed docs, see: https://www.statsmodels.org/dev/vector_ar.html#module-statsmodels.... | 2 | stack_v2_sparse_classes_30k_train_037618 | Implement the Python class `VectorAutoRegression` described below.
Class description:
Implement the VectorAutoRegression class.
Method signatures and docstrings:
- def __init__(self, timeseries, r): Fit a vector autogressive (VAR) process to data using statsmodels.tsa.vector_ar. The output object is just reduction an... | Implement the Python class `VectorAutoRegression` described below.
Class description:
Implement the VectorAutoRegression class.
Method signatures and docstrings:
- def __init__(self, timeseries, r): Fit a vector autogressive (VAR) process to data using statsmodels.tsa.vector_ar. The output object is just reduction an... | e94694f298909352d7e9d912625314a1e46aa5b6 | <|skeleton|>
class VectorAutoRegression:
def __init__(self, timeseries, r):
"""Fit a vector autogressive (VAR) process to data using statsmodels.tsa.vector_ar. The output object is just reduction and renaming of attributes produced after running the fit() method of the VAR class For more detailed docs, see... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class VectorAutoRegression:
def __init__(self, timeseries, r):
"""Fit a vector autogressive (VAR) process to data using statsmodels.tsa.vector_ar. The output object is just reduction and renaming of attributes produced after running the fit() method of the VAR class For more detailed docs, see: https://www.... | the_stack_v2_python_sparse | LLC_Membranes/llclib/timeseries.py | NKM-ML/LLC_Membranes | train | 0 | |
8718b8c740aebbfcd8dab32c1ed96e6262ae3970 | [
"if not request.path.endswith('/manage/'):\n return None\ntry:\n telnet = pexpect.spawn('telnet', [settings.TELNET_HOST, str(settings.TELNET_PORT)], timeout=settings.TELNET_TIMEOUT)\n telnet.expect(':')\n telnet.sendline(settings.TELNET_USERNAME)\n telnet.expect(':')\n telnet.sendline(settings.TEL... | <|body_start_0|>
if not request.path.endswith('/manage/'):
return None
try:
telnet = pexpect.spawn('telnet', [settings.TELNET_HOST, str(settings.TELNET_PORT)], timeout=settings.TELNET_TIMEOUT)
telnet.expect(':')
telnet.sendline(settings.TELNET_USERNAME)
... | TelnetConnectionMiddleware | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TelnetConnectionMiddleware:
def process_request(self, request):
"""Add a telnet connection to all request paths that start with /api/ assuming we only need to connect for these means we avoid unecessary overhead on any other functionality we add, and keeps URL path clear for it."""
... | stack_v2_sparse_classes_75kplus_train_066297 | 4,315 | no_license | [
{
"docstring": "Add a telnet connection to all request paths that start with /api/ assuming we only need to connect for these means we avoid unecessary overhead on any other functionality we add, and keeps URL path clear for it.",
"name": "process_request",
"signature": "def process_request(self, reques... | 2 | null | Implement the Python class `TelnetConnectionMiddleware` described below.
Class description:
Implement the TelnetConnectionMiddleware class.
Method signatures and docstrings:
- def process_request(self, request): Add a telnet connection to all request paths that start with /api/ assuming we only need to connect for th... | Implement the Python class `TelnetConnectionMiddleware` described below.
Class description:
Implement the TelnetConnectionMiddleware class.
Method signatures and docstrings:
- def process_request(self, request): Add a telnet connection to all request paths that start with /api/ assuming we only need to connect for th... | d7dfe74a63663571178843d5e664b2121d4d5943 | <|skeleton|>
class TelnetConnectionMiddleware:
def process_request(self, request):
"""Add a telnet connection to all request paths that start with /api/ assuming we only need to connect for these means we avoid unecessary overhead on any other functionality we add, and keeps URL path clear for it."""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TelnetConnectionMiddleware:
def process_request(self, request):
"""Add a telnet connection to all request paths that start with /api/ assuming we only need to connect for these means we avoid unecessary overhead on any other functionality we add, and keeps URL path clear for it."""
if not requ... | the_stack_v2_python_sparse | main/core/middleware.py | 101t/jasmin-web-panel | train | 66 | |
5279be123f7f6bc9cea2641601a62070ae56e064 | [
"self.net = net\nself.data = data\nself.optimizer = optimizer\nself.loss = loss\nself.step = step\nself.seed = 33",
"paddle.enable_static()\npaddle.disable_static()\npaddle.seed(self.seed)\nnp.random.seed(self.seed)",
"reset(self.seed)\nnet = self.net.get_layer()\nnet.train()\nopt = self.optimizer.get_opt(net=n... | <|body_start_0|>
self.net = net
self.data = data
self.optimizer = optimizer
self.loss = loss
self.step = step
self.seed = 33
<|end_body_0|>
<|body_start_1|>
paddle.enable_static()
paddle.disable_static()
paddle.seed(self.seed)
np.random.se... | 构建Layer训练的通用类 | LayerTrain | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LayerTrain:
"""构建Layer训练的通用类"""
def __init__(self, net, data, optimizer, loss, step):
"""初始化"""
<|body_0|>
def reset(self):
"""重置模型图 :return:"""
<|body_1|>
def dy_train(self):
"""dygraph train"""
<|body_2|>
def dy_train_dl(self):... | stack_v2_sparse_classes_75kplus_train_066298 | 4,955 | no_license | [
{
"docstring": "初始化",
"name": "__init__",
"signature": "def __init__(self, net, data, optimizer, loss, step)"
},
{
"docstring": "重置模型图 :return:",
"name": "reset",
"signature": "def reset(self)"
},
{
"docstring": "dygraph train",
"name": "dy_train",
"signature": "def dy_tr... | 6 | stack_v2_sparse_classes_30k_train_019689 | Implement the Python class `LayerTrain` described below.
Class description:
构建Layer训练的通用类
Method signatures and docstrings:
- def __init__(self, net, data, optimizer, loss, step): 初始化
- def reset(self): 重置模型图 :return:
- def dy_train(self): dygraph train
- def dy_train_dl(self): dygraph train with dataloader
- def dy2... | Implement the Python class `LayerTrain` described below.
Class description:
构建Layer训练的通用类
Method signatures and docstrings:
- def __init__(self, net, data, optimizer, loss, step): 初始化
- def reset(self): 重置模型图 :return:
- def dy_train(self): dygraph train
- def dy_train_dl(self): dygraph train with dataloader
- def dy2... | bd3790ce72a2a26611b5eda3901651b5a809348f | <|skeleton|>
class LayerTrain:
"""构建Layer训练的通用类"""
def __init__(self, net, data, optimizer, loss, step):
"""初始化"""
<|body_0|>
def reset(self):
"""重置模型图 :return:"""
<|body_1|>
def dy_train(self):
"""dygraph train"""
<|body_2|>
def dy_train_dl(self):... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class LayerTrain:
"""构建Layer训练的通用类"""
def __init__(self, net, data, optimizer, loss, step):
"""初始化"""
self.net = net
self.data = data
self.optimizer = optimizer
self.loss = loss
self.step = step
self.seed = 33
def reset(self):
"""重置模型图 :retur... | the_stack_v2_python_sparse | framework/e2e/paddleLT/donotuse/train_origin.py | PaddlePaddle/PaddleTest | train | 42 |
df95e6c92f8ee4009bc7db56a5188cd1c392f7f1 | [
"self.name = name\nself.id = id\nself.date_time = date_time\nself.type = type\nself.payload = payload",
"repr_string = '{}('.format(self.__class__.__name__)\nrepr_string += 'date_time={}, '.format(self.date_time)\nrepr_string += 'name={}, '.format(self.name)\nrepr_string += 'id={}, '.format(self.id)\nrepr_string ... | <|body_start_0|>
self.name = name
self.id = id
self.date_time = date_time
self.type = type
self.payload = payload
<|end_body_0|>
<|body_start_1|>
repr_string = '{}('.format(self.__class__.__name__)
repr_string += 'date_time={}, '.format(self.date_time)
re... | The Message class is used as the vessel for objects sent between process and threads over sockets, pipes and queues. | Message | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Message:
"""The Message class is used as the vessel for objects sent between process and threads over sockets, pipes and queues."""
def __init__(self, name, date_time, type, payload=None, id=0):
"""Initializes a Message with: Args: name: A string name of the sender. id: An integer in... | stack_v2_sparse_classes_75kplus_train_066299 | 1,521 | no_license | [
{
"docstring": "Initializes a Message with: Args: name: A string name of the sender. id: An integer index for objects that have multiple instances. date_time: None or a datetime object indicating the time sent. type: A string indicating the type of message sent. NOTE: An enum would be less error prone, but woul... | 2 | stack_v2_sparse_classes_30k_val_000973 | Implement the Python class `Message` described below.
Class description:
The Message class is used as the vessel for objects sent between process and threads over sockets, pipes and queues.
Method signatures and docstrings:
- def __init__(self, name, date_time, type, payload=None, id=0): Initializes a Message with: A... | Implement the Python class `Message` described below.
Class description:
The Message class is used as the vessel for objects sent between process and threads over sockets, pipes and queues.
Method signatures and docstrings:
- def __init__(self, name, date_time, type, payload=None, id=0): Initializes a Message with: A... | e2b7136c7feda4deb667bd1e6cba3c1ef7eeff9d | <|skeleton|>
class Message:
"""The Message class is used as the vessel for objects sent between process and threads over sockets, pipes and queues."""
def __init__(self, name, date_time, type, payload=None, id=0):
"""Initializes a Message with: Args: name: A string name of the sender. id: An integer in... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Message:
"""The Message class is used as the vessel for objects sent between process and threads over sockets, pipes and queues."""
def __init__(self, name, date_time, type, payload=None, id=0):
"""Initializes a Message with: Args: name: A string name of the sender. id: An integer index for objec... | the_stack_v2_python_sparse | shared/message.py | NickBayard/sf | train | 0 |
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