blob_id stringlengths 40 40 | bodies listlengths 2 6 | bodies_text stringlengths 196 6.73k | class_docstring stringlengths 0 700 | class_name stringlengths 1 86 | detected_licenses listlengths 0 45 | format_version stringclasses 1
value | full_text stringlengths 438 7.52k | id stringlengths 40 40 | length_bytes int64 506 50k | license_type stringclasses 2
values | methods listlengths 2 6 | n_methods int64 2 6 | original_id stringlengths 38 40 ⌀ | prompt stringlengths 153 4.25k | prompted_full_text stringlengths 645 10.7k | revision_id stringlengths 40 40 | skeleton stringlengths 162 4.34k | snapshot_name stringclasses 1
value | snapshot_source_dir stringclasses 1
value | solution stringlengths 302 7.33k | source stringclasses 1
value | source_path stringlengths 4 177 | source_repo stringlengths 6 110 | split stringclasses 1
value | star_events_count int64 0 209k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
50ba99a16374d14ea8ac3fca26dd55229e62c7cb | [
"world_size = int(os.environ['WORLD_SIZE'])\nnode_rank = int(os.environ['RANK'])\nlocal_rank = int(os.environ['LOCAL_RANK'])\nself.result_file_template = result_file_template\ntorch.distributed.init_process_group(backend='nccl')\ncuda.set_device(local_rank)\nlabel_mapping = {0, 'right', 1, 'left', 2, 'neutral'}\nte... | <|body_start_0|>
world_size = int(os.environ['WORLD_SIZE'])
node_rank = int(os.environ['RANK'])
local_rank = int(os.environ['LOCAL_RANK'])
self.result_file_template = result_file_template
torch.distributed.init_process_group(backend='nccl')
cuda.set_device(local_rank)
... | Pretends to be a training script that is forked into (potentially) multiple processes on multiple machines. This minimal test script is used with test_multiprocess_sampler.py. It merely draws samples from an Sqlite test database via a distributed sampler. Each forked instance of this script runs through two epochs over... | TrainProcessTestHelper | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TrainProcessTestHelper:
"""Pretends to be a training script that is forked into (potentially) multiple processes on multiple machines. This minimal test script is used with test_multiprocess_sampler.py. It merely draws samples from an Sqlite test database via a distributed sampler. Each forked in... | stack_v2_sparse_classes_36k_train_033900 | 6,063 | no_license | [
{
"docstring": "Constructor",
"name": "__init__",
"signature": "def __init__(self, result_file_template)"
},
{
"docstring": "Ask for all the samples in a loop Write the result to a file as a dict @param epoch: @type epoch:",
"name": "run",
"signature": "def run(self, epoch, accumulated_d... | 2 | stack_v2_sparse_classes_30k_train_012632 | Implement the Python class `TrainProcessTestHelper` described below.
Class description:
Pretends to be a training script that is forked into (potentially) multiple processes on multiple machines. This minimal test script is used with test_multiprocess_sampler.py. It merely draws samples from an Sqlite test database vi... | Implement the Python class `TrainProcessTestHelper` described below.
Class description:
Pretends to be a training script that is forked into (potentially) multiple processes on multiple machines. This minimal test script is used with test_multiprocess_sampler.py. It merely draws samples from an Sqlite test database vi... | 854358d573831cd47d926448412daf3062d8c291 | <|skeleton|>
class TrainProcessTestHelper:
"""Pretends to be a training script that is forked into (potentially) multiple processes on multiple machines. This minimal test script is used with test_multiprocess_sampler.py. It merely draws samples from an Sqlite test database via a distributed sampler. Each forked in... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TrainProcessTestHelper:
"""Pretends to be a training script that is forked into (potentially) multiple processes on multiple machines. This minimal test script is used with test_multiprocess_sampler.py. It merely draws samples from an Sqlite test database via a distributed sampler. Each forked instance of thi... | the_stack_v2_python_sparse | src/classifier/training_script_test_helper.py | paepcke/bert_train_parallel | train | 0 |
d205a0585ccfdbb1075d2b33e40a4b0bbbd1cd71 | [
"super().__init__()\nself.decoder = nn.Sequential(nn.Conv2d(512, 512, kernel_size=1), nn.ReLU(inplace=True), nn.Dropout(0.8), nn.Conv2d(512, 512, kernel_size=1), nn.ReLU(inplace=True))\nself.layer = nn.ConvTranspose2d(1280, num_classes, kernel_size=2, stride=2, dilation=1)",
"pool_3, pool_4 = pools\nx = self.deco... | <|body_start_0|>
super().__init__()
self.decoder = nn.Sequential(nn.Conv2d(512, 512, kernel_size=1), nn.ReLU(inplace=True), nn.Dropout(0.8), nn.Conv2d(512, 512, kernel_size=1), nn.ReLU(inplace=True))
self.layer = nn.ConvTranspose2d(1280, num_classes, kernel_size=2, stride=2, dilation=1)
<|end_bo... | Column Decoder. | ColumnDecoder | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ColumnDecoder:
"""Column Decoder."""
def __init__(self, num_classes: int):
"""Initialize Column Decoder. Args: num_classes (int): Number of classes per point."""
<|body_0|>
def forward(self, x, pools):
"""Forward pass. Args: x (tensor): Batch of images to perform... | stack_v2_sparse_classes_36k_train_033901 | 5,468 | no_license | [
{
"docstring": "Initialize Column Decoder. Args: num_classes (int): Number of classes per point.",
"name": "__init__",
"signature": "def __init__(self, num_classes: int)"
},
{
"docstring": "Forward pass. Args: x (tensor): Batch of images to perform forward-pass. pools (Tuple[tensor, tensor]): Th... | 2 | stack_v2_sparse_classes_30k_train_011386 | Implement the Python class `ColumnDecoder` described below.
Class description:
Column Decoder.
Method signatures and docstrings:
- def __init__(self, num_classes: int): Initialize Column Decoder. Args: num_classes (int): Number of classes per point.
- def forward(self, x, pools): Forward pass. Args: x (tensor): Batch... | Implement the Python class `ColumnDecoder` described below.
Class description:
Column Decoder.
Method signatures and docstrings:
- def __init__(self, num_classes: int): Initialize Column Decoder. Args: num_classes (int): Number of classes per point.
- def forward(self, x, pools): Forward pass. Args: x (tensor): Batch... | 7e55a422588c1d1e00f35a3d3a3ff896cce59e18 | <|skeleton|>
class ColumnDecoder:
"""Column Decoder."""
def __init__(self, num_classes: int):
"""Initialize Column Decoder. Args: num_classes (int): Number of classes per point."""
<|body_0|>
def forward(self, x, pools):
"""Forward pass. Args: x (tensor): Batch of images to perform... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ColumnDecoder:
"""Column Decoder."""
def __init__(self, num_classes: int):
"""Initialize Column Decoder. Args: num_classes (int): Number of classes per point."""
super().__init__()
self.decoder = nn.Sequential(nn.Conv2d(512, 512, kernel_size=1), nn.ReLU(inplace=True), nn.Dropout(0... | the_stack_v2_python_sparse | generated/test_tomassosorio_OCR_tablenet.py | jansel/pytorch-jit-paritybench | train | 35 |
5861aa6a68c84768509d543fbd4efcd5c1eb78c1 | [
"lo = 0\nhi = len(nums) - 1\nwhile lo < hi:\n mid = (lo + hi) // 2\n if nums[mid] == target:\n return mid\n elif nums[mid] < target:\n lo = mid + 1\n else:\n hi = mid - 1\nreturn lo if target <= nums[lo] else lo + 1",
"length = len(nums)\nfor i in range(length):\n if nums[i] >=... | <|body_start_0|>
lo = 0
hi = len(nums) - 1
while lo < hi:
mid = (lo + hi) // 2
if nums[mid] == target:
return mid
elif nums[mid] < target:
lo = mid + 1
else:
hi = mid - 1
return lo if target <... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def searchInsert(self, nums, target):
""":type nums: List[int] :type target: int :rtype: int"""
<|body_0|>
def searchInsert_myfirst(self, nums, target):
""":type nums: List[int] :type target: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_s... | stack_v2_sparse_classes_36k_train_033902 | 1,074 | no_license | [
{
"docstring": ":type nums: List[int] :type target: int :rtype: int",
"name": "searchInsert",
"signature": "def searchInsert(self, nums, target)"
},
{
"docstring": ":type nums: List[int] :type target: int :rtype: int",
"name": "searchInsert_myfirst",
"signature": "def searchInsert_myfirs... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def searchInsert(self, nums, target): :type nums: List[int] :type target: int :rtype: int
- def searchInsert_myfirst(self, nums, target): :type nums: List[int] :type target: int ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def searchInsert(self, nums, target): :type nums: List[int] :type target: int :rtype: int
- def searchInsert_myfirst(self, nums, target): :type nums: List[int] :type target: int ... | f0d9070fa292ca36971a465a805faddb12025482 | <|skeleton|>
class Solution:
def searchInsert(self, nums, target):
""":type nums: List[int] :type target: int :rtype: int"""
<|body_0|>
def searchInsert_myfirst(self, nums, target):
""":type nums: List[int] :type target: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def searchInsert(self, nums, target):
""":type nums: List[int] :type target: int :rtype: int"""
lo = 0
hi = len(nums) - 1
while lo < hi:
mid = (lo + hi) // 2
if nums[mid] == target:
return mid
elif nums[mid] < target... | the_stack_v2_python_sparse | 35.SearchInsertPosition.py | JerryRoc/leetcode | train | 0 | |
b2a91db4a2002481d3672358796262551739df3c | [
"self.__logger = State().getLogger('Postprocessing_Component_Logger')\nself.__logger.info('Starting __init__()', 'Postprocessing:__init__')\n'\\n Todo: create some Postprocessing Classes \\n '\nself.__logger.info('Finished __init__()', 'Postprocessing:__init__')",
"self.__logger.info('Starting execu... | <|body_start_0|>
self.__logger = State().getLogger('Postprocessing_Component_Logger')
self.__logger.info('Starting __init__()', 'Postprocessing:__init__')
'\n Todo: create some Postprocessing Classes \n '
self.__logger.info('Finished __init__()', 'Postprocessing:__init__')
... | Postprocessing | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Postprocessing:
def __init__(self, config):
"""Constructor, initialisiert Membervariablen. Parameters ---------- config : Config Die Konfiguration. Example ------- >>> Postprocessing(config)"""
<|body_0|>
def execute(self, classification):
"""Führt Postprocessingschr... | stack_v2_sparse_classes_36k_train_033903 | 1,779 | no_license | [
{
"docstring": "Constructor, initialisiert Membervariablen. Parameters ---------- config : Config Die Konfiguration. Example ------- >>> Postprocessing(config)",
"name": "__init__",
"signature": "def __init__(self, config)"
},
{
"docstring": "Führt Postprocessingschritte auf die Klassifizierung ... | 2 | stack_v2_sparse_classes_30k_train_008889 | Implement the Python class `Postprocessing` described below.
Class description:
Implement the Postprocessing class.
Method signatures and docstrings:
- def __init__(self, config): Constructor, initialisiert Membervariablen. Parameters ---------- config : Config Die Konfiguration. Example ------- >>> Postprocessing(co... | Implement the Python class `Postprocessing` described below.
Class description:
Implement the Postprocessing class.
Method signatures and docstrings:
- def __init__(self, config): Constructor, initialisiert Membervariablen. Parameters ---------- config : Config Die Konfiguration. Example ------- >>> Postprocessing(co... | 3daaa72b193ebfb55894b47b6a752cdc2192bb6b | <|skeleton|>
class Postprocessing:
def __init__(self, config):
"""Constructor, initialisiert Membervariablen. Parameters ---------- config : Config Die Konfiguration. Example ------- >>> Postprocessing(config)"""
<|body_0|>
def execute(self, classification):
"""Führt Postprocessingschr... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Postprocessing:
def __init__(self, config):
"""Constructor, initialisiert Membervariablen. Parameters ---------- config : Config Die Konfiguration. Example ------- >>> Postprocessing(config)"""
self.__logger = State().getLogger('Postprocessing_Component_Logger')
self.__logger.info('Sta... | the_stack_v2_python_sparse | SheetMusicScanner/Postprocessing_Component/Postprocessing/Postprocessing.py | jadeskon/score-scan | train | 0 | |
44e06198f514cdc6420cf78ddcabba26a5d51796 | [
"self.agent_project_id = agent_project_id\nself.conflicting_packages = conflicting_packages\nsuper().__init__(self._build_error_message())",
"conflicting_packages = sorted(self.conflicting_packages, key=str)\nmessage = f\"cannot add project '{self.agent_project_id}': the following AEA dependencies have conflicts ... | <|body_start_0|>
self.agent_project_id = agent_project_id
self.conflicting_packages = conflicting_packages
super().__init__(self._build_error_message())
<|end_body_0|>
<|body_start_1|>
conflicting_packages = sorted(self.conflicting_packages, key=str)
message = f"cannot add proje... | Check consistency of package versions against already added project. | ProjectPackageConsistencyCheckError | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProjectPackageConsistencyCheckError:
"""Check consistency of package versions against already added project."""
def __init__(self, agent_project_id: PublicId, conflicting_packages: List[Tuple[PackageIdPrefix, str, str, Set[PublicId]]]):
"""Initialize the exception. :param agent_proje... | stack_v2_sparse_classes_36k_train_033904 | 43,010 | permissive | [
{
"docstring": "Initialize the exception. :param agent_project_id: the agent project id whose addition has failed. :param conflicting_packages: the conflicting packages.",
"name": "__init__",
"signature": "def __init__(self, agent_project_id: PublicId, conflicting_packages: List[Tuple[PackageIdPrefix, s... | 2 | null | Implement the Python class `ProjectPackageConsistencyCheckError` described below.
Class description:
Check consistency of package versions against already added project.
Method signatures and docstrings:
- def __init__(self, agent_project_id: PublicId, conflicting_packages: List[Tuple[PackageIdPrefix, str, str, Set[P... | Implement the Python class `ProjectPackageConsistencyCheckError` described below.
Class description:
Check consistency of package versions against already added project.
Method signatures and docstrings:
- def __init__(self, agent_project_id: PublicId, conflicting_packages: List[Tuple[PackageIdPrefix, str, str, Set[P... | bec49adaeba661d8d0f03ac9935dc89f39d95a0d | <|skeleton|>
class ProjectPackageConsistencyCheckError:
"""Check consistency of package versions against already added project."""
def __init__(self, agent_project_id: PublicId, conflicting_packages: List[Tuple[PackageIdPrefix, str, str, Set[PublicId]]]):
"""Initialize the exception. :param agent_proje... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ProjectPackageConsistencyCheckError:
"""Check consistency of package versions against already added project."""
def __init__(self, agent_project_id: PublicId, conflicting_packages: List[Tuple[PackageIdPrefix, str, str, Set[PublicId]]]):
"""Initialize the exception. :param agent_project_id: the ag... | the_stack_v2_python_sparse | aea/manager/manager.py | fetchai/agents-aea | train | 192 |
a44ddc9ddf68798ffc106d110f5437c4bb3b80ea | [
"for i in range(self.backupCount - 1, 0, -1):\n sfn = self.rotation_filename('%s.%d' % (self.baseFilename, i))\n dfn = self.rotation_filename('%s.%d' % (self.baseFilename, i + 1))\n if os.path.exists(sfn):\n if os.path.exists(dfn):\n os.remove(dfn)\n os.chmod(sfn, stat.S_IRUSR)\n ... | <|body_start_0|>
for i in range(self.backupCount - 1, 0, -1):
sfn = self.rotation_filename('%s.%d' % (self.baseFilename, i))
dfn = self.rotation_filename('%s.%d' % (self.baseFilename, i + 1))
if os.path.exists(sfn):
if os.path.exists(dfn):
... | Inherit RotatingFileHandler for multiprocess compatibility. | MultiCompatibleRotatingFileHandler | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference",
"MIT",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MultiCompatibleRotatingFileHandler:
"""Inherit RotatingFileHandler for multiprocess compatibility."""
def rolling_rename(self):
"""Rolling rename log files."""
<|body_0|>
def doRollover(self):
"""Do a rollover, as described in __init__()."""
<|body_1|>
... | stack_v2_sparse_classes_36k_train_033905 | 8,220 | permissive | [
{
"docstring": "Rolling rename log files.",
"name": "rolling_rename",
"signature": "def rolling_rename(self)"
},
{
"docstring": "Do a rollover, as described in __init__().",
"name": "doRollover",
"signature": "def doRollover(self)"
},
{
"docstring": "Open the current base file wi... | 3 | null | Implement the Python class `MultiCompatibleRotatingFileHandler` described below.
Class description:
Inherit RotatingFileHandler for multiprocess compatibility.
Method signatures and docstrings:
- def rolling_rename(self): Rolling rename log files.
- def doRollover(self): Do a rollover, as described in __init__().
- d... | Implement the Python class `MultiCompatibleRotatingFileHandler` described below.
Class description:
Inherit RotatingFileHandler for multiprocess compatibility.
Method signatures and docstrings:
- def rolling_rename(self): Rolling rename log files.
- def doRollover(self): Do a rollover, as described in __init__().
- d... | a774d893fb2f21dbc3edb5cd89f9e6eec274ebf1 | <|skeleton|>
class MultiCompatibleRotatingFileHandler:
"""Inherit RotatingFileHandler for multiprocess compatibility."""
def rolling_rename(self):
"""Rolling rename log files."""
<|body_0|>
def doRollover(self):
"""Do a rollover, as described in __init__()."""
<|body_1|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MultiCompatibleRotatingFileHandler:
"""Inherit RotatingFileHandler for multiprocess compatibility."""
def rolling_rename(self):
"""Rolling rename log files."""
for i in range(self.backupCount - 1, 0, -1):
sfn = self.rotation_filename('%s.%d' % (self.baseFilename, i))
... | the_stack_v2_python_sparse | mindinsight/utils/log.py | mindspore-ai/mindinsight | train | 224 |
e5ab5511bfc15c6f36690c752b5cbeb03171476d | [
"context = super(ExhibitionCreateView, self).get_context_data(**kwargs)\ncontext['page_title'] = u'Создание новой выставки'\nreturn context",
"message = super(ExhibitionCreateView, self).form_valid(form)\nmes = u'Выставка {} успешно добавлена.'.format(self.object.name)\nmessages.success(self.request, mes)\nreturn... | <|body_start_0|>
context = super(ExhibitionCreateView, self).get_context_data(**kwargs)
context['page_title'] = u'Создание новой выставки'
return context
<|end_body_0|>
<|body_start_1|>
message = super(ExhibitionCreateView, self).form_valid(form)
mes = u'Выставка {} успешно доба... | Add new exhibition | ExhibitionCreateView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ExhibitionCreateView:
"""Add new exhibition"""
def get_context_data(self, **kwargs):
"""Extends context data :param kwargs: :return: context"""
<|body_0|>
def form_valid(self, form):
"""The successful addition of new exhibition :param form: :return: message"""
... | stack_v2_sparse_classes_36k_train_033906 | 5,515 | no_license | [
{
"docstring": "Extends context data :param kwargs: :return: context",
"name": "get_context_data",
"signature": "def get_context_data(self, **kwargs)"
},
{
"docstring": "The successful addition of new exhibition :param form: :return: message",
"name": "form_valid",
"signature": "def form... | 2 | stack_v2_sparse_classes_30k_train_020389 | Implement the Python class `ExhibitionCreateView` described below.
Class description:
Add new exhibition
Method signatures and docstrings:
- def get_context_data(self, **kwargs): Extends context data :param kwargs: :return: context
- def form_valid(self, form): The successful addition of new exhibition :param form: :... | Implement the Python class `ExhibitionCreateView` described below.
Class description:
Add new exhibition
Method signatures and docstrings:
- def get_context_data(self, **kwargs): Extends context data :param kwargs: :return: context
- def form_valid(self, form): The successful addition of new exhibition :param form: :... | 8eb18b831e034302f90585a179110336bb18af45 | <|skeleton|>
class ExhibitionCreateView:
"""Add new exhibition"""
def get_context_data(self, **kwargs):
"""Extends context data :param kwargs: :return: context"""
<|body_0|>
def form_valid(self, form):
"""The successful addition of new exhibition :param form: :return: message"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ExhibitionCreateView:
"""Add new exhibition"""
def get_context_data(self, **kwargs):
"""Extends context data :param kwargs: :return: context"""
context = super(ExhibitionCreateView, self).get_context_data(**kwargs)
context['page_title'] = u'Создание новой выставки'
return ... | the_stack_v2_python_sparse | exhibition/views.py | YevheniiaSmyrnova/butterflies | train | 0 |
62c9aaf0413b0e8b040f57d2b37a2a3ff5280e51 | [
"super(Timeline, self).__init__(width=width, height=height)\nself._page_title = page_title\nself._time_points = []\nself._option = {'baseOption': {'timeline': {'axisType': 'category', 'autoPlay': is_auto_play, 'loop': is_loop_play, 'rewind': is_rewind_play, 'show': is_timeline_show, 'symbol': timeline_symbol, 'symb... | <|body_start_0|>
super(Timeline, self).__init__(width=width, height=height)
self._page_title = page_title
self._time_points = []
self._option = {'baseOption': {'timeline': {'axisType': 'category', 'autoPlay': is_auto_play, 'loop': is_loop_play, 'rewind': is_rewind_play, 'show': is_timeli... | 时间线轮播多张图 | Timeline | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Timeline:
"""时间线轮播多张图"""
def __init__(self, page_title=PAGE_TITLE, width=800, height=400, is_auto_play=False, is_loop_play=True, is_rewind_play=False, is_timeline_show=True, timeline_play_interval=2000, timeline_symbol='emptyCircle', timeline_symbol_size=10, timeline_left='auto', timeline_ri... | stack_v2_sparse_classes_36k_train_033907 | 4,408 | permissive | [
{
"docstring": ":param is_auto_play: 是否自动播放，默认为 Flase :param is_loop_play: 是否循环播放，默认为 True :param is_rewind_play: 是否方向播放，默认为 Flase :param is_timeline_show: 是否显示 timeline 组件。默认为 True，如果设置为false，不会显示，但是功能还存在。 :param timeline_play_interval: 播放的速度（跳动的间隔），单位毫秒（ms）。 :param timeline_symbol: 标记的图形。有'circle', 'rect', 'r... | 3 | stack_v2_sparse_classes_30k_train_004300 | Implement the Python class `Timeline` described below.
Class description:
时间线轮播多张图
Method signatures and docstrings:
- def __init__(self, page_title=PAGE_TITLE, width=800, height=400, is_auto_play=False, is_loop_play=True, is_rewind_play=False, is_timeline_show=True, timeline_play_interval=2000, timeline_symbol='empt... | Implement the Python class `Timeline` described below.
Class description:
时间线轮播多张图
Method signatures and docstrings:
- def __init__(self, page_title=PAGE_TITLE, width=800, height=400, is_auto_play=False, is_loop_play=True, is_rewind_play=False, is_timeline_show=True, timeline_play_interval=2000, timeline_symbol='empt... | 0bc901fdd31d69a2084355cd63a1e0a54ed5276a | <|skeleton|>
class Timeline:
"""时间线轮播多张图"""
def __init__(self, page_title=PAGE_TITLE, width=800, height=400, is_auto_play=False, is_loop_play=True, is_rewind_play=False, is_timeline_show=True, timeline_play_interval=2000, timeline_symbol='emptyCircle', timeline_symbol_size=10, timeline_left='auto', timeline_ri... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Timeline:
"""时间线轮播多张图"""
def __init__(self, page_title=PAGE_TITLE, width=800, height=400, is_auto_play=False, is_loop_play=True, is_rewind_play=False, is_timeline_show=True, timeline_play_interval=2000, timeline_symbol='emptyCircle', timeline_symbol_size=10, timeline_left='auto', timeline_right='auto', t... | the_stack_v2_python_sparse | pyecharts/custom/timeline.py | yutiansut/pyecharts | train | 2 |
d4b0066044d90a7f8e381a41f2ead03660738d6c | [
"mspec = model.ModelSpec(input={'text_a': types.TextSegment(), 'text_b': types.TextSegment()}, output={})\ndspec = mspec.input\nself.assertTrue(mspec.is_compatible_with_dataset(dspec))",
"mspec = model.ModelSpec(input={'text_a': types.TextSegment(), 'text_b': types.TextSegment()}, output={})\ndspec = {'premise': ... | <|body_start_0|>
mspec = model.ModelSpec(input={'text_a': types.TextSegment(), 'text_b': types.TextSegment()}, output={})
dspec = mspec.input
self.assertTrue(mspec.is_compatible_with_dataset(dspec))
<|end_body_0|>
<|body_start_1|>
mspec = model.ModelSpec(input={'text_a': types.TextSegme... | SpecTest | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SpecTest:
def test_compatibility_fullmatch(self):
"""Test with an exact match."""
<|body_0|>
def test_compatibility_mismatch(self):
"""Test with specs that don't match."""
<|body_1|>
def test_compatibility_extrafield(self):
"""Test with an extra ... | stack_v2_sparse_classes_36k_train_033908 | 4,744 | permissive | [
{
"docstring": "Test with an exact match.",
"name": "test_compatibility_fullmatch",
"signature": "def test_compatibility_fullmatch(self)"
},
{
"docstring": "Test with specs that don't match.",
"name": "test_compatibility_mismatch",
"signature": "def test_compatibility_mismatch(self)"
}... | 5 | null | Implement the Python class `SpecTest` described below.
Class description:
Implement the SpecTest class.
Method signatures and docstrings:
- def test_compatibility_fullmatch(self): Test with an exact match.
- def test_compatibility_mismatch(self): Test with specs that don't match.
- def test_compatibility_extrafield(s... | Implement the Python class `SpecTest` described below.
Class description:
Implement the SpecTest class.
Method signatures and docstrings:
- def test_compatibility_fullmatch(self): Test with an exact match.
- def test_compatibility_mismatch(self): Test with specs that don't match.
- def test_compatibility_extrafield(s... | a41130960d6ccb92acf6ffc603377eaecce8a62b | <|skeleton|>
class SpecTest:
def test_compatibility_fullmatch(self):
"""Test with an exact match."""
<|body_0|>
def test_compatibility_mismatch(self):
"""Test with specs that don't match."""
<|body_1|>
def test_compatibility_extrafield(self):
"""Test with an extra ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SpecTest:
def test_compatibility_fullmatch(self):
"""Test with an exact match."""
mspec = model.ModelSpec(input={'text_a': types.TextSegment(), 'text_b': types.TextSegment()}, output={})
dspec = mspec.input
self.assertTrue(mspec.is_compatible_with_dataset(dspec))
def test_... | the_stack_v2_python_sparse | lit_nlp/api/model_test.py | PAIR-code/lit | train | 3,201 | |
9156ea9d49cc8c34ed1a4f8620566d632ef7ff0d | [
"data_list = models.Server.objects.all()\nserializer = serializers.MySerializer(instance=data_list, many=True)\nreturn JsonResponse(serializer.data, safe=False)",
"data = JSONParser().parse(request)\nserializer = serializers.MySerializer(data=data)\nif serializer.is_valid():\n serializer.save()\nreturn HttpRes... | <|body_start_0|>
data_list = models.Server.objects.all()
serializer = serializers.MySerializer(instance=data_list, many=True)
return JsonResponse(serializer.data, safe=False)
<|end_body_0|>
<|body_start_1|>
data = JSONParser().parse(request)
serializer = serializers.MySerializer... | ServerView | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ServerView:
def get(self, request, *args, **kwargs):
"""获取列表 :param request: :param args: :param kwargs: :return:"""
<|body_0|>
def post(self, request, *args, **kwargs):
"""创建数据 :param request: request经过封装 :param args: :param kwargs: :return:"""
<|body_1|>
<... | stack_v2_sparse_classes_36k_train_033909 | 6,597 | permissive | [
{
"docstring": "获取列表 :param request: :param args: :param kwargs: :return:",
"name": "get",
"signature": "def get(self, request, *args, **kwargs)"
},
{
"docstring": "创建数据 :param request: request经过封装 :param args: :param kwargs: :return:",
"name": "post",
"signature": "def post(self, reques... | 2 | null | Implement the Python class `ServerView` described below.
Class description:
Implement the ServerView class.
Method signatures and docstrings:
- def get(self, request, *args, **kwargs): 获取列表 :param request: :param args: :param kwargs: :return:
- def post(self, request, *args, **kwargs): 创建数据 :param request: request经过封... | Implement the Python class `ServerView` described below.
Class description:
Implement the ServerView class.
Method signatures and docstrings:
- def get(self, request, *args, **kwargs): 获取列表 :param request: :param args: :param kwargs: :return:
- def post(self, request, *args, **kwargs): 创建数据 :param request: request经过封... | 4ff1d02d2b6dd54e96f7179fa000548936b691e7 | <|skeleton|>
class ServerView:
def get(self, request, *args, **kwargs):
"""获取列表 :param request: :param args: :param kwargs: :return:"""
<|body_0|>
def post(self, request, *args, **kwargs):
"""创建数据 :param request: request经过封装 :param args: :param kwargs: :return:"""
<|body_1|>
<... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ServerView:
def get(self, request, *args, **kwargs):
"""获取列表 :param request: :param args: :param kwargs: :return:"""
data_list = models.Server.objects.all()
serializer = serializers.MySerializer(instance=data_list, many=True)
return JsonResponse(serializer.data, safe=False)
... | the_stack_v2_python_sparse | CMDB_SYSTEM/autoserver/server/views.py | MMingLeung/Python_Study | train | 3 | |
af00d63970ed50f846ba6bb2be62bc662bc00015 | [
"queue = deque()\nqueue.append(root)\nwhile queue:\n size = len(queue)\n self.value = queue[0].val\n for _ in range(size):\n node = queue.popleft()\n if node.left:\n queue.append(node.left)\n if node.right:\n queue.append(node.right)\nreturn self.value",
"queue ... | <|body_start_0|>
queue = deque()
queue.append(root)
while queue:
size = len(queue)
self.value = queue[0].val
for _ in range(size):
node = queue.popleft()
if node.left:
queue.append(node.left)
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findBottomLeftValue(self, root: TreeNode) -> int:
"""BFS"""
<|body_0|>
def findBottomLeftValue_1(self, root: TreeNode) -> int:
"""改进版BFS"""
<|body_1|>
def findBottomLeftValue_2(self, root: TreeNode) -> int:
"""DFS"""
<|body_... | stack_v2_sparse_classes_36k_train_033910 | 1,622 | no_license | [
{
"docstring": "BFS",
"name": "findBottomLeftValue",
"signature": "def findBottomLeftValue(self, root: TreeNode) -> int"
},
{
"docstring": "改进版BFS",
"name": "findBottomLeftValue_1",
"signature": "def findBottomLeftValue_1(self, root: TreeNode) -> int"
},
{
"docstring": "DFS",
... | 3 | stack_v2_sparse_classes_30k_train_003683 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findBottomLeftValue(self, root: TreeNode) -> int: BFS
- def findBottomLeftValue_1(self, root: TreeNode) -> int: 改进版BFS
- def findBottomLeftValue_2(self, root: TreeNode) -> in... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findBottomLeftValue(self, root: TreeNode) -> int: BFS
- def findBottomLeftValue_1(self, root: TreeNode) -> int: 改进版BFS
- def findBottomLeftValue_2(self, root: TreeNode) -> in... | 3508e1ce089131b19603c3206aab4cf43023bb19 | <|skeleton|>
class Solution:
def findBottomLeftValue(self, root: TreeNode) -> int:
"""BFS"""
<|body_0|>
def findBottomLeftValue_1(self, root: TreeNode) -> int:
"""改进版BFS"""
<|body_1|>
def findBottomLeftValue_2(self, root: TreeNode) -> int:
"""DFS"""
<|body_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def findBottomLeftValue(self, root: TreeNode) -> int:
"""BFS"""
queue = deque()
queue.append(root)
while queue:
size = len(queue)
self.value = queue[0].val
for _ in range(size):
node = queue.popleft()
... | the_stack_v2_python_sparse | algorithm/leetcode/bfs/13-找树左下角的值.py | lxconfig/UbuntuCode_bak | train | 0 | |
8134be26b083bea97f14a1f9d00d6aa12556a004 | [
"super(PositionalEncoding, self).__init__()\nself.d_model = d_model\nself.reverse = reverse\nself.xscale = math.sqrt(self.d_model)\nself.dropout = torch.nn.Dropout(p=dropout_rate)\nself.pe = None\nself.extend_pe(torch.tensor(0.0).expand(1, max_len))\nself._register_load_state_dict_pre_hook(_pre_hook)",
"if self.p... | <|body_start_0|>
super(PositionalEncoding, self).__init__()
self.d_model = d_model
self.reverse = reverse
self.xscale = math.sqrt(self.d_model)
self.dropout = torch.nn.Dropout(p=dropout_rate)
self.pe = None
self.extend_pe(torch.tensor(0.0).expand(1, max_len))
... | Positional encoding. Args: d_model (int): Embedding dimension. dropout_rate (float): Dropout rate. max_len (int): Maximum input length. reverse (bool): Whether to reverse the input position. | PositionalEncoding | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PositionalEncoding:
"""Positional encoding. Args: d_model (int): Embedding dimension. dropout_rate (float): Dropout rate. max_len (int): Maximum input length. reverse (bool): Whether to reverse the input position."""
def __init__(self, d_model, dropout_rate, max_len=5000, reverse=False):
... | stack_v2_sparse_classes_36k_train_033911 | 37,737 | permissive | [
{
"docstring": "Construct an PositionalEncoding object.",
"name": "__init__",
"signature": "def __init__(self, d_model, dropout_rate, max_len=5000, reverse=False)"
},
{
"docstring": "Reset the positional encodings.",
"name": "extend_pe",
"signature": "def extend_pe(self, x)"
},
{
... | 3 | null | Implement the Python class `PositionalEncoding` described below.
Class description:
Positional encoding. Args: d_model (int): Embedding dimension. dropout_rate (float): Dropout rate. max_len (int): Maximum input length. reverse (bool): Whether to reverse the input position.
Method signatures and docstrings:
- def __i... | Implement the Python class `PositionalEncoding` described below.
Class description:
Positional encoding. Args: d_model (int): Embedding dimension. dropout_rate (float): Dropout rate. max_len (int): Maximum input length. reverse (bool): Whether to reverse the input position.
Method signatures and docstrings:
- def __i... | 31d50b1ea1dea92f4182c5b2b6fe9fe4c981ae39 | <|skeleton|>
class PositionalEncoding:
"""Positional encoding. Args: d_model (int): Embedding dimension. dropout_rate (float): Dropout rate. max_len (int): Maximum input length. reverse (bool): Whether to reverse the input position."""
def __init__(self, d_model, dropout_rate, max_len=5000, reverse=False):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PositionalEncoding:
"""Positional encoding. Args: d_model (int): Embedding dimension. dropout_rate (float): Dropout rate. max_len (int): Maximum input length. reverse (bool): Whether to reverse the input position."""
def __init__(self, d_model, dropout_rate, max_len=5000, reverse=False):
"""Const... | the_stack_v2_python_sparse | SVS/model/layers/conformer_related.py | SJTMusicTeam/SVS_system | train | 85 |
c61e854800f4d24ed7d1d7c5f493e2b6729f036a | [
"if self.code == 'qcloud':\n _logger.info('>>>{}-正在使用腾讯云短信发送验证码<<<'.format(phone))\n templates = self.env['sms.template'].search([('partner_id', '=', self.id), ('ttype', '=', 'code')])\n if not templates:\n return {'state': False, 'msg': '发送失败：系统没有找到可用于发送验证码的模板'}\n s_sender = SmsSingleSender(self... | <|body_start_0|>
if self.code == 'qcloud':
_logger.info('>>>{}-正在使用腾讯云短信发送验证码<<<'.format(phone))
templates = self.env['sms.template'].search([('partner_id', '=', self.id), ('ttype', '=', 'code')])
if not templates:
return {'state': False, 'msg': '发送失败：系统没有找到可用... | SmsPartner | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SmsPartner:
def send_message_code(self, user, phone, ttype):
"""发送验证码方法 :param user: 系统用户 :param phone: 手机号码 :param ttype: 消息类型 :return:"""
<|body_0|>
def send_registration_message(self, user, phone):
"""新用户创建成功后发送通知短信： 短信参数为两个参数，分别为账号和密码 短信模板： 《您的账号已创建成功。账号：${userna... | stack_v2_sparse_classes_36k_train_033912 | 3,415 | permissive | [
{
"docstring": "发送验证码方法 :param user: 系统用户 :param phone: 手机号码 :param ttype: 消息类型 :return:",
"name": "send_message_code",
"signature": "def send_message_code(self, user, phone, ttype)"
},
{
"docstring": "新用户创建成功后发送通知短信： 短信参数为两个参数，分别为账号和密码 短信模板： 《您的账号已创建成功。账号：${username}，初始密码：${pwd}，请及时修改初始密码。》 :pa... | 2 | null | Implement the Python class `SmsPartner` described below.
Class description:
Implement the SmsPartner class.
Method signatures and docstrings:
- def send_message_code(self, user, phone, ttype): 发送验证码方法 :param user: 系统用户 :param phone: 手机号码 :param ttype: 消息类型 :return:
- def send_registration_message(self, user, phone): ... | Implement the Python class `SmsPartner` described below.
Class description:
Implement the SmsPartner class.
Method signatures and docstrings:
- def send_message_code(self, user, phone, ttype): 发送验证码方法 :param user: 系统用户 :param phone: 手机号码 :param ttype: 消息类型 :return:
- def send_registration_message(self, user, phone): ... | 8608aaeae7a8c86d53b68ce26b7b308f779c3dd8 | <|skeleton|>
class SmsPartner:
def send_message_code(self, user, phone, ttype):
"""发送验证码方法 :param user: 系统用户 :param phone: 手机号码 :param ttype: 消息类型 :return:"""
<|body_0|>
def send_registration_message(self, user, phone):
"""新用户创建成功后发送通知短信： 短信参数为两个参数，分别为账号和密码 短信模板： 《您的账号已创建成功。账号：${userna... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SmsPartner:
def send_message_code(self, user, phone, ttype):
"""发送验证码方法 :param user: 系统用户 :param phone: 手机号码 :param ttype: 消息类型 :return:"""
if self.code == 'qcloud':
_logger.info('>>>{}-正在使用腾讯云短信发送验证码<<<'.format(phone))
templates = self.env['sms.template'].search([('par... | the_stack_v2_python_sparse | sms_qcloud/models/sms_partner.py | niulinlnc/odooExtModel | train | 4 | |
be46f6b3c9e2aa853af8435c713ef4fe43b694f5 | [
"super(TempDirMixin, self).setUp()\nif self.tempDirPrefix is not None:\n prefix = self.tempDirPrefix\nelse:\n prefix = 'test_'\nself.temp_dir = tempfile.mkdtemp(prefix=prefix)",
"super(TempDirMixin, self).tearDown()\ntry:\n shutil.rmtree(six.text_type(self.temp_dir))\nexcept OSError:\n msg = 'Failed t... | <|body_start_0|>
super(TempDirMixin, self).setUp()
if self.tempDirPrefix is not None:
prefix = self.tempDirPrefix
else:
prefix = 'test_'
self.temp_dir = tempfile.mkdtemp(prefix=prefix)
<|end_body_0|>
<|body_start_1|>
super(TempDirMixin, self).tearDown()
... | TempDirMixin | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TempDirMixin:
def setUp(self):
"""Creates a pristine temp directory."""
<|body_0|>
def tearDown(self):
"""Removes temp directory and all its contents."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
super(TempDirMixin, self).setUp()
if self.... | stack_v2_sparse_classes_36k_train_033913 | 877 | permissive | [
{
"docstring": "Creates a pristine temp directory.",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "Removes temp directory and all its contents.",
"name": "tearDown",
"signature": "def tearDown(self)"
}
] | 2 | null | Implement the Python class `TempDirMixin` described below.
Class description:
Implement the TempDirMixin class.
Method signatures and docstrings:
- def setUp(self): Creates a pristine temp directory.
- def tearDown(self): Removes temp directory and all its contents. | Implement the Python class `TempDirMixin` described below.
Class description:
Implement the TempDirMixin class.
Method signatures and docstrings:
- def setUp(self): Creates a pristine temp directory.
- def tearDown(self): Removes temp directory and all its contents.
<|skeleton|>
class TempDirMixin:
def setUp(se... | 1ef9a42d4eaa70d9b3e6e7fa519396c1e1174fcb | <|skeleton|>
class TempDirMixin:
def setUp(self):
"""Creates a pristine temp directory."""
<|body_0|>
def tearDown(self):
"""Removes temp directory and all its contents."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TempDirMixin:
def setUp(self):
"""Creates a pristine temp directory."""
super(TempDirMixin, self).setUp()
if self.tempDirPrefix is not None:
prefix = self.tempDirPrefix
else:
prefix = 'test_'
self.temp_dir = tempfile.mkdtemp(prefix=prefix)
d... | the_stack_v2_python_sparse | yepes/test_mixins/tempdir.py | samuelmaudo/yepes | train | 0 | |
6e8232eead4a1f47b24718ff0c85c9d620cf1f1b | [
"if super(PointLight, self).Light(lightID, mode):\n glLightf(lightID, GL_CONSTANT_ATTENUATION, self.attenuation[0])\n glLightf(lightID, GL_LINEAR_ATTENUATION, self.attenuation[1])\n glLightf(lightID, GL_QUADRATIC_ATTENUATION, self.attenuation[2])\n return 1\nelse:\n return 0",
"if direction is None... | <|body_start_0|>
if super(PointLight, self).Light(lightID, mode):
glLightf(lightID, GL_CONSTANT_ATTENUATION, self.attenuation[0])
glLightf(lightID, GL_LINEAR_ATTENUATION, self.attenuation[1])
glLightf(lightID, GL_QUADRATIC_ATTENUATION, self.attenuation[2])
return ... | PointLight node attributes: attenuation -- 3 values giving the light-attenuation values for constant, linear and quadratic attenuation (+ Light attributes) http://www.web3d.org/x3d/specifications/vrml/ISO-IEC-14772-IS-VRML97WithAmendment1/part1/nodesRef.html#PointLight | PointLight | [
"GPL-1.0-or-later",
"MIT",
"LicenseRef-scancode-warranty-disclaimer",
"LicenseRef-scancode-other-copyleft",
"LGPL-2.1-or-later",
"GPL-3.0-only",
"LGPL-2.0-or-later",
"GPL-3.0-or-later"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PointLight:
"""PointLight node attributes: attenuation -- 3 values giving the light-attenuation values for constant, linear and quadratic attenuation (+ Light attributes) http://www.web3d.org/x3d/specifications/vrml/ISO-IEC-14772-IS-VRML97WithAmendment1/part1/nodesRef.html#PointLight"""
def ... | stack_v2_sparse_classes_36k_train_033914 | 6,768 | permissive | [
{
"docstring": "Render the light (i.e. cause it to alter the scene",
"name": "Light",
"signature": "def Light(self, lightID, mode=None)"
},
{
"docstring": "Calculate our model-side matrix",
"name": "modelMatrix",
"signature": "def modelMatrix(self, direction=None)"
}
] | 2 | null | Implement the Python class `PointLight` described below.
Class description:
PointLight node attributes: attenuation -- 3 values giving the light-attenuation values for constant, linear and quadratic attenuation (+ Light attributes) http://www.web3d.org/x3d/specifications/vrml/ISO-IEC-14772-IS-VRML97WithAmendment1/part... | Implement the Python class `PointLight` described below.
Class description:
PointLight node attributes: attenuation -- 3 values giving the light-attenuation values for constant, linear and quadratic attenuation (+ Light attributes) http://www.web3d.org/x3d/specifications/vrml/ISO-IEC-14772-IS-VRML97WithAmendment1/part... | 7f600ad153270feff12aa7aa86d7ed0a49ebc71c | <|skeleton|>
class PointLight:
"""PointLight node attributes: attenuation -- 3 values giving the light-attenuation values for constant, linear and quadratic attenuation (+ Light attributes) http://www.web3d.org/x3d/specifications/vrml/ISO-IEC-14772-IS-VRML97WithAmendment1/part1/nodesRef.html#PointLight"""
def ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PointLight:
"""PointLight node attributes: attenuation -- 3 values giving the light-attenuation values for constant, linear and quadratic attenuation (+ Light attributes) http://www.web3d.org/x3d/specifications/vrml/ISO-IEC-14772-IS-VRML97WithAmendment1/part1/nodesRef.html#PointLight"""
def Light(self, l... | the_stack_v2_python_sparse | pythonAnimations/pyOpenGLChess/engineDirectory/oglc-env/lib/python2.7/site-packages/OpenGLContext/scenegraph/light.py | alexus37/AugmentedRealityChess | train | 1 |
13fd766f365af07d6b4f89e1bff3fcce008cea0c | [
"super(Linear, self).__init__()\nself.fc0 = paddle.nn.Linear(in_features=in_features, out_features=out_features)\nself.sigmoid = paddle.nn.Sigmoid()",
"out = self.fc0(x)\nout = self.sigmoid(out)\nreturn out"
] | <|body_start_0|>
super(Linear, self).__init__()
self.fc0 = paddle.nn.Linear(in_features=in_features, out_features=out_features)
self.sigmoid = paddle.nn.Sigmoid()
<|end_body_0|>
<|body_start_1|>
out = self.fc0(x)
out = self.sigmoid(out)
return out
<|end_body_1|>
| Linear | Linear | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Linear:
"""Linear"""
def __init__(self, in_features=3, out_features=10):
"""init"""
<|body_0|>
def forward(self, x):
"""forward"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
super(Linear, self).__init__()
self.fc0 = paddle.nn.Linear(in... | stack_v2_sparse_classes_36k_train_033915 | 543 | no_license | [
{
"docstring": "init",
"name": "__init__",
"signature": "def __init__(self, in_features=3, out_features=10)"
},
{
"docstring": "forward",
"name": "forward",
"signature": "def forward(self, x)"
}
] | 2 | stack_v2_sparse_classes_30k_train_013853 | Implement the Python class `Linear` described below.
Class description:
Linear
Method signatures and docstrings:
- def __init__(self, in_features=3, out_features=10): init
- def forward(self, x): forward | Implement the Python class `Linear` described below.
Class description:
Linear
Method signatures and docstrings:
- def __init__(self, in_features=3, out_features=10): init
- def forward(self, x): forward
<|skeleton|>
class Linear:
"""Linear"""
def __init__(self, in_features=3, out_features=10):
"""i... | bd3790ce72a2a26611b5eda3901651b5a809348f | <|skeleton|>
class Linear:
"""Linear"""
def __init__(self, in_features=3, out_features=10):
"""init"""
<|body_0|>
def forward(self, x):
"""forward"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Linear:
"""Linear"""
def __init__(self, in_features=3, out_features=10):
"""init"""
super(Linear, self).__init__()
self.fc0 = paddle.nn.Linear(in_features=in_features, out_features=out_features)
self.sigmoid = paddle.nn.Sigmoid()
def forward(self, x):
"""forwa... | the_stack_v2_python_sparse | framework/e2e/moduletrans/diy/layer/linear.py | PaddlePaddle/PaddleTest | train | 42 |
828108489105deb1c9e53751fbbdc299c430d8c0 | [
"assert self.EOS not in s, 'Input string cannot contain null character (%s)' % self.EOS\ns += self.EOS\nrotations = []\nfor i in range(len(s)):\n rotations.append(s[i:] + s[:i])\n sortedRotations = sorted(rotations)\nbwtTransformedString = ''\nfor rotation in sortedRotations:\n bwtTransformedString += rota... | <|body_start_0|>
assert self.EOS not in s, 'Input string cannot contain null character (%s)' % self.EOS
s += self.EOS
rotations = []
for i in range(len(s)):
rotations.append(s[i:] + s[:i])
sortedRotations = sorted(rotations)
bwtTransformedString = ''
... | BurrowsWheeler | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BurrowsWheeler:
def transform(self, s):
"""Simplest Burrows-Wheeler transform implementation, O(n^2) respective to the length of the text."""
<|body_0|>
def inverse(self, s):
"""Simplest Inverse Burrow-Wheeler transform implementation."""
<|body_1|>
<|end_sk... | stack_v2_sparse_classes_36k_train_033916 | 5,036 | no_license | [
{
"docstring": "Simplest Burrows-Wheeler transform implementation, O(n^2) respective to the length of the text.",
"name": "transform",
"signature": "def transform(self, s)"
},
{
"docstring": "Simplest Inverse Burrow-Wheeler transform implementation.",
"name": "inverse",
"signature": "def... | 2 | null | Implement the Python class `BurrowsWheeler` described below.
Class description:
Implement the BurrowsWheeler class.
Method signatures and docstrings:
- def transform(self, s): Simplest Burrows-Wheeler transform implementation, O(n^2) respective to the length of the text.
- def inverse(self, s): Simplest Inverse Burro... | Implement the Python class `BurrowsWheeler` described below.
Class description:
Implement the BurrowsWheeler class.
Method signatures and docstrings:
- def transform(self, s): Simplest Burrows-Wheeler transform implementation, O(n^2) respective to the length of the text.
- def inverse(self, s): Simplest Inverse Burro... | ff77118fe81d82c835f71a41e70e3f7f303028bf | <|skeleton|>
class BurrowsWheeler:
def transform(self, s):
"""Simplest Burrows-Wheeler transform implementation, O(n^2) respective to the length of the text."""
<|body_0|>
def inverse(self, s):
"""Simplest Inverse Burrow-Wheeler transform implementation."""
<|body_1|>
<|end_sk... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BurrowsWheeler:
def transform(self, s):
"""Simplest Burrows-Wheeler transform implementation, O(n^2) respective to the length of the text."""
assert self.EOS not in s, 'Input string cannot contain null character (%s)' % self.EOS
s += self.EOS
rotations = []
for i in ran... | the_stack_v2_python_sparse | genomics/bio/alignment/bwt.py | HussainAther/biology | train | 11 | |
2a5c8224f6d8021823e5c34a03fd5f9334161d2d | [
"self._enc_out = ChaCha20Poly1305(out_key)\nself._enc_in = ChaCha20Poly1305(in_key)\nself._out_counter = 0\nself._in_counter = 0\nself._nonce_length = nonce_length",
"if nounce is None:\n nounce = self._out_counter.to_bytes(length=self._nonce_length, byteorder='little')\n self._out_counter += 1\nif len(noun... | <|body_start_0|>
self._enc_out = ChaCha20Poly1305(out_key)
self._enc_in = ChaCha20Poly1305(in_key)
self._out_counter = 0
self._in_counter = 0
self._nonce_length = nonce_length
<|end_body_0|>
<|body_start_1|>
if nounce is None:
nounce = self._out_counter.to_by... | CHACHA20 encryption/decryption layer. | Chacha20Cipher | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Chacha20Cipher:
"""CHACHA20 encryption/decryption layer."""
def __init__(self, out_key, in_key, nonce_length=8):
"""Initialize a new Chacha20Cipher."""
<|body_0|>
def encrypt(self, data, nounce=None, aad=None):
"""Encrypt data with counter or specified nounce."""... | stack_v2_sparse_classes_36k_train_033917 | 1,498 | permissive | [
{
"docstring": "Initialize a new Chacha20Cipher.",
"name": "__init__",
"signature": "def __init__(self, out_key, in_key, nonce_length=8)"
},
{
"docstring": "Encrypt data with counter or specified nounce.",
"name": "encrypt",
"signature": "def encrypt(self, data, nounce=None, aad=None)"
... | 3 | stack_v2_sparse_classes_30k_train_012316 | Implement the Python class `Chacha20Cipher` described below.
Class description:
CHACHA20 encryption/decryption layer.
Method signatures and docstrings:
- def __init__(self, out_key, in_key, nonce_length=8): Initialize a new Chacha20Cipher.
- def encrypt(self, data, nounce=None, aad=None): Encrypt data with counter or... | Implement the Python class `Chacha20Cipher` described below.
Class description:
CHACHA20 encryption/decryption layer.
Method signatures and docstrings:
- def __init__(self, out_key, in_key, nonce_length=8): Initialize a new Chacha20Cipher.
- def encrypt(self, data, nounce=None, aad=None): Encrypt data with counter or... | 6d47d0b807992343d08927f3e511b1451b396421 | <|skeleton|>
class Chacha20Cipher:
"""CHACHA20 encryption/decryption layer."""
def __init__(self, out_key, in_key, nonce_length=8):
"""Initialize a new Chacha20Cipher."""
<|body_0|>
def encrypt(self, data, nounce=None, aad=None):
"""Encrypt data with counter or specified nounce."""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Chacha20Cipher:
"""CHACHA20 encryption/decryption layer."""
def __init__(self, out_key, in_key, nonce_length=8):
"""Initialize a new Chacha20Cipher."""
self._enc_out = ChaCha20Poly1305(out_key)
self._enc_in = ChaCha20Poly1305(in_key)
self._out_counter = 0
self._in_... | the_stack_v2_python_sparse | pyatv/support/chacha20.py | cchampignon/pyatv | train | 0 |
e6fcededbfd5e5af9392bc246fc7de3efdcfaff1 | [
"params = request.query_params\npage = int(params.get('page', 1))\npage_size = int(params.get('page_size', 10))\nkeyword = params.get('keyword')\ntotal_only = params.get('total_only')\nsort_by = request.data.get('sort_by')\nobj = Strategy.objects\nif keyword:\n obj = obj.filter(name__icontains=keyword)\ntotal_co... | <|body_start_0|>
params = request.query_params
page = int(params.get('page', 1))
page_size = int(params.get('page_size', 10))
keyword = params.get('keyword')
total_only = params.get('total_only')
sort_by = request.data.get('sort_by')
obj = Strategy.objects
... | StrategiesAPIView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StrategiesAPIView:
def get(request):
"""策略列表接口"""
<|body_0|>
def post(request):
"""策略创建接口"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
params = request.query_params
page = int(params.get('page', 1))
page_size = int(params.get('pag... | stack_v2_sparse_classes_36k_train_033918 | 9,461 | no_license | [
{
"docstring": "策略列表接口",
"name": "get",
"signature": "def get(request)"
},
{
"docstring": "策略创建接口",
"name": "post",
"signature": "def post(request)"
}
] | 2 | stack_v2_sparse_classes_30k_train_005851 | Implement the Python class `StrategiesAPIView` described below.
Class description:
Implement the StrategiesAPIView class.
Method signatures and docstrings:
- def get(request): 策略列表接口
- def post(request): 策略创建接口 | Implement the Python class `StrategiesAPIView` described below.
Class description:
Implement the StrategiesAPIView class.
Method signatures and docstrings:
- def get(request): 策略列表接口
- def post(request): 策略创建接口
<|skeleton|>
class StrategiesAPIView:
def get(request):
"""策略列表接口"""
<|body_0|>
... | bb85b52598d68956bde8756c8321ade7b8479ba7 | <|skeleton|>
class StrategiesAPIView:
def get(request):
"""策略列表接口"""
<|body_0|>
def post(request):
"""策略创建接口"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class StrategiesAPIView:
def get(request):
"""策略列表接口"""
params = request.query_params
page = int(params.get('page', 1))
page_size = int(params.get('page_size', 10))
keyword = params.get('keyword')
total_only = params.get('total_only')
sort_by = request.data.ge... | the_stack_v2_python_sparse | curd_test/configure/views.py | huiiiuh/huihuiproject | train | 0 | |
00f16caf3bbf4332331b9c95d63fd6fb6374db70 | [
"count = {}\nfor i in nums:\n if i in count:\n count[i] += 1\n else:\n count[i] = 1\nfor i in count:\n if count[i] > len(nums) // 2:\n return i",
"count = 0\nres = None\nfor num in nums:\n if count == 0:\n res = num\n if num == res:\n count += 1\n else:\n ... | <|body_start_0|>
count = {}
for i in nums:
if i in count:
count[i] += 1
else:
count[i] = 1
for i in count:
if count[i] > len(nums) // 2:
return i
<|end_body_0|>
<|body_start_1|>
count = 0
res = N... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def majorityElement(self, nums):
"""时间复杂度 O(n) 空间复杂度 O(n) :type nums: List[int] :rtype: int"""
<|body_0|>
def mmm(self, nums):
"""时间复杂度 O(n) 空间复杂度 O(1) :param nums: :return:"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
count = {}
... | stack_v2_sparse_classes_36k_train_033919 | 1,650 | no_license | [
{
"docstring": "时间复杂度 O(n) 空间复杂度 O(n) :type nums: List[int] :rtype: int",
"name": "majorityElement",
"signature": "def majorityElement(self, nums)"
},
{
"docstring": "时间复杂度 O(n) 空间复杂度 O(1) :param nums: :return:",
"name": "mmm",
"signature": "def mmm(self, nums)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def majorityElement(self, nums): 时间复杂度 O(n) 空间复杂度 O(n) :type nums: List[int] :rtype: int
- def mmm(self, nums): 时间复杂度 O(n) 空间复杂度 O(1) :param nums: :return: | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def majorityElement(self, nums): 时间复杂度 O(n) 空间复杂度 O(n) :type nums: List[int] :rtype: int
- def mmm(self, nums): 时间复杂度 O(n) 空间复杂度 O(1) :param nums: :return:
<|skeleton|>
class So... | 1040b5dbbe509abe42df848bc34dd1626d7a05fb | <|skeleton|>
class Solution:
def majorityElement(self, nums):
"""时间复杂度 O(n) 空间复杂度 O(n) :type nums: List[int] :rtype: int"""
<|body_0|>
def mmm(self, nums):
"""时间复杂度 O(n) 空间复杂度 O(1) :param nums: :return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def majorityElement(self, nums):
"""时间复杂度 O(n) 空间复杂度 O(n) :type nums: List[int] :rtype: int"""
count = {}
for i in nums:
if i in count:
count[i] += 1
else:
count[i] = 1
for i in count:
if count[i] > l... | the_stack_v2_python_sparse | list/majorityElement.py | NJ-zero/LeetCode_Answer | train | 1 | |
b642a17b1d605b3659eb2f7f368b2f4ee2ab8594 | [
"raw = super(self.__class__, self).get_value_for_datastore(model_instance)\nif raw is None:\n raise ValueError(_(\"Password can't be empty\"))\ntry:\n if len(raw) > 12:\n alg, seed, passw = raw.split('$')\n return raw\nexcept Exception:\n pass\nif len(raw) < 5:\n raise ValueError(_('Invali... | <|body_start_0|>
raw = super(self.__class__, self).get_value_for_datastore(model_instance)
if raw is None:
raise ValueError(_("Password can't be empty"))
try:
if len(raw) > 12:
alg, seed, passw = raw.split('$')
return raw
except Exc... | Extends default TextProperty, so we are sure that passwords are always saved encrypted with SHA1 | PasswordProperty | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PasswordProperty:
"""Extends default TextProperty, so we are sure that passwords are always saved encrypted with SHA1"""
def get_value_for_datastore(self, model_instance):
"""Extract the value from a model instance and convert it to a encrypted password that goes in the datastore."""... | stack_v2_sparse_classes_36k_train_033920 | 2,797 | no_license | [
{
"docstring": "Extract the value from a model instance and convert it to a encrypted password that goes in the datastore.",
"name": "get_value_for_datastore",
"signature": "def get_value_for_datastore(self, model_instance)"
},
{
"docstring": "Convert a value as found in the datastore to string.... | 2 | stack_v2_sparse_classes_30k_train_017656 | Implement the Python class `PasswordProperty` described below.
Class description:
Extends default TextProperty, so we are sure that passwords are always saved encrypted with SHA1
Method signatures and docstrings:
- def get_value_for_datastore(self, model_instance): Extract the value from a model instance and convert ... | Implement the Python class `PasswordProperty` described below.
Class description:
Extends default TextProperty, so we are sure that passwords are always saved encrypted with SHA1
Method signatures and docstrings:
- def get_value_for_datastore(self, model_instance): Extract the value from a model instance and convert ... | f8315a2d37db6dca26c8b4af100fd6f1d6fcae20 | <|skeleton|>
class PasswordProperty:
"""Extends default TextProperty, so we are sure that passwords are always saved encrypted with SHA1"""
def get_value_for_datastore(self, model_instance):
"""Extract the value from a model instance and convert it to a encrypted password that goes in the datastore."""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PasswordProperty:
"""Extends default TextProperty, so we are sure that passwords are always saved encrypted with SHA1"""
def get_value_for_datastore(self, model_instance):
"""Extract the value from a model instance and convert it to a encrypted password that goes in the datastore."""
raw ... | the_stack_v2_python_sparse | trunk/src/webapp/geouser/properties.py | hhkaos/GeoRemindMe_Web | train | 0 |
ab87269cb25a751db5b14e4c1fe2914a25778318 | [
"super(MinMaxPreprocessor, self).__init__(mdp_info, clip_obs, alpha)\nobs_low, obs_high = (mdp_info.observation_space.low.copy(), mdp_info.observation_space.high.copy())\nself._obs_mask = np.where(np.logical_and(np.abs(obs_low) < 1e+20, np.abs(obs_high) < 1e+20))\nassert np.squeeze(self._obs_mask).size > 0, 'All ob... | <|body_start_0|>
super(MinMaxPreprocessor, self).__init__(mdp_info, clip_obs, alpha)
obs_low, obs_high = (mdp_info.observation_space.low.copy(), mdp_info.observation_space.high.copy())
self._obs_mask = np.where(np.logical_and(np.abs(obs_low) < 1e+20, np.abs(obs_high) < 1e+20))
assert np.... | Preprocess observations from the environment using the bounds of the observation space of the environment. For observations that are not limited falls back to using running mean standardization. | MinMaxPreprocessor | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MinMaxPreprocessor:
"""Preprocess observations from the environment using the bounds of the observation space of the environment. For observations that are not limited falls back to using running mean standardization."""
def __init__(self, mdp_info, clip_obs=10.0, alpha=1e-32):
"""Co... | stack_v2_sparse_classes_36k_train_033921 | 4,016 | permissive | [
{
"docstring": "Constructor. Args: mdp_info (MDPInfo): information of the MDP; clip_obs (float, 10.): values to clip the normalized observations; alpha (float, 1e-32): moving average catchup parameter for the normalization.",
"name": "__init__",
"signature": "def __init__(self, mdp_info, clip_obs=10.0, ... | 2 | stack_v2_sparse_classes_30k_train_021028 | Implement the Python class `MinMaxPreprocessor` described below.
Class description:
Preprocess observations from the environment using the bounds of the observation space of the environment. For observations that are not limited falls back to using running mean standardization.
Method signatures and docstrings:
- def... | Implement the Python class `MinMaxPreprocessor` described below.
Class description:
Preprocess observations from the environment using the bounds of the observation space of the environment. For observations that are not limited falls back to using running mean standardization.
Method signatures and docstrings:
- def... | 2decae31459a3481130afe1263bc0a5ba7954a99 | <|skeleton|>
class MinMaxPreprocessor:
"""Preprocess observations from the environment using the bounds of the observation space of the environment. For observations that are not limited falls back to using running mean standardization."""
def __init__(self, mdp_info, clip_obs=10.0, alpha=1e-32):
"""Co... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MinMaxPreprocessor:
"""Preprocess observations from the environment using the bounds of the observation space of the environment. For observations that are not limited falls back to using running mean standardization."""
def __init__(self, mdp_info, clip_obs=10.0, alpha=1e-32):
"""Constructor. Ar... | the_stack_v2_python_sparse | mushroom_rl/utils/preprocessors.py | MushroomRL/mushroom-rl | train | 477 |
ca68f8d026cd743949c19a3efad8a44e0f8a1f44 | [
"super().__init__(name=name, **kwargs)\nif background_weight < 0 or background_weight > 1:\n raise ValueError(f'The background weight for Cross Entropy must be within [0, 1], got {background_weight}.')\nself.binary = binary\nself.background_weight = background_weight\nself.smooth = smooth\nself.flatten = tf.kera... | <|body_start_0|>
super().__init__(name=name, **kwargs)
if background_weight < 0 or background_weight > 1:
raise ValueError(f'The background weight for Cross Entropy must be within [0, 1], got {background_weight}.')
self.binary = binary
self.background_weight = background_weig... | Define weighted cross-entropy. The formulation is: loss = − w_fg * y_true log(y_pred) - w_bg * (1−y_true) log(1−y_pred) | CrossEntropy | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CrossEntropy:
"""Define weighted cross-entropy. The formulation is: loss = − w_fg * y_true log(y_pred) - w_bg * (1−y_true) log(1−y_pred)"""
def __init__(self, binary: bool=False, background_weight: float=0.0, smooth: float=EPS, name: str='CrossEntropy', **kwargs):
"""Init. :param bin... | stack_v2_sparse_classes_36k_train_033922 | 12,718 | permissive | [
{
"docstring": "Init. :param binary: if True, project y_true, y_pred to 0 or 1 :param background_weight: weight for background, where y == 0. :param smooth: smooth constant for log. :param name: name of the loss. :param kwargs: additional arguments.",
"name": "__init__",
"signature": "def __init__(self,... | 3 | null | Implement the Python class `CrossEntropy` described below.
Class description:
Define weighted cross-entropy. The formulation is: loss = − w_fg * y_true log(y_pred) - w_bg * (1−y_true) log(1−y_pred)
Method signatures and docstrings:
- def __init__(self, binary: bool=False, background_weight: float=0.0, smooth: float=E... | Implement the Python class `CrossEntropy` described below.
Class description:
Define weighted cross-entropy. The formulation is: loss = − w_fg * y_true log(y_pred) - w_bg * (1−y_true) log(1−y_pred)
Method signatures and docstrings:
- def __init__(self, binary: bool=False, background_weight: float=0.0, smooth: float=E... | 650a2f1a88ad3c6932be305d6a98a36e26feedc6 | <|skeleton|>
class CrossEntropy:
"""Define weighted cross-entropy. The formulation is: loss = − w_fg * y_true log(y_pred) - w_bg * (1−y_true) log(1−y_pred)"""
def __init__(self, binary: bool=False, background_weight: float=0.0, smooth: float=EPS, name: str='CrossEntropy', **kwargs):
"""Init. :param bin... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CrossEntropy:
"""Define weighted cross-entropy. The formulation is: loss = − w_fg * y_true log(y_pred) - w_bg * (1−y_true) log(1−y_pred)"""
def __init__(self, binary: bool=False, background_weight: float=0.0, smooth: float=EPS, name: str='CrossEntropy', **kwargs):
"""Init. :param binary: if True,... | the_stack_v2_python_sparse | deepreg/loss/label.py | DeepRegNet/DeepReg | train | 509 |
cba4696bc488650a83a6f7a0a0c4c33f1770df5e | [
"assert type(data) is list\nif len(data) > 1:\n self.images = torch.cat(tuple([data_set_data['images'] for data_set_data in data]), 0).to(device)\n self.ltr_targets = torch.cat(tuple([data_set_data['ltr_targets'] for data_set_data in data]), 0)[:, :-1].to(device)\n self.rtl_targets = torch.cat(tuple([data_... | <|body_start_0|>
assert type(data) is list
if len(data) > 1:
self.images = torch.cat(tuple([data_set_data['images'] for data_set_data in data]), 0).to(device)
self.ltr_targets = torch.cat(tuple([data_set_data['ltr_targets'] for data_set_data in data]), 0)[:, :-1].to(device)
... | Batch class, Contains all the attributes for one training iteration | Batch | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Batch:
"""Batch class, Contains all the attributes for one training iteration"""
def __init__(self, data, device, pad_id=0, bidirectional=False):
""":param data: list with dictionaries with all the data attributes for one training pass, each dict is from one dataset :param device: re... | stack_v2_sparse_classes_36k_train_033923 | 2,534 | no_license | [
{
"docstring": ":param data: list with dictionaries with all the data attributes for one training pass, each dict is from one dataset :param device: reference to GPU or CPU depending on the configurations :param: bidirectional: if True, decode sequence bidirectional :param pad_id: padding symbol id",
"name"... | 2 | stack_v2_sparse_classes_30k_train_019692 | Implement the Python class `Batch` described below.
Class description:
Batch class, Contains all the attributes for one training iteration
Method signatures and docstrings:
- def __init__(self, data, device, pad_id=0, bidirectional=False): :param data: list with dictionaries with all the data attributes for one train... | Implement the Python class `Batch` described below.
Class description:
Batch class, Contains all the attributes for one training iteration
Method signatures and docstrings:
- def __init__(self, data, device, pad_id=0, bidirectional=False): :param data: list with dictionaries with all the data attributes for one train... | ab83a47ef2e107dd7160ea0ca1832fa0531926b7 | <|skeleton|>
class Batch:
"""Batch class, Contains all the attributes for one training iteration"""
def __init__(self, data, device, pad_id=0, bidirectional=False):
""":param data: list with dictionaries with all the data attributes for one training pass, each dict is from one dataset :param device: re... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Batch:
"""Batch class, Contains all the attributes for one training iteration"""
def __init__(self, data, device, pad_id=0, bidirectional=False):
""":param data: list with dictionaries with all the data attributes for one training pass, each dict is from one dataset :param device: reference to GP... | the_stack_v2_python_sparse | src/Batch.py | MauritsBleeker/Bi-STET | train | 72 |
1099acb6e84b4c95dcd0779733248cdc778f5d8a | [
"self.start = start\nself.end = end\ndx = end[0] - start[0]\nif dx == 0:\n self.m = None\n self.n = None\nelse:\n self.m = float(end[1] - start[1]) / dx\n self.n = float(start[1] * end[0] - end[1] * start[0]) / dx",
"if self.m == None:\n if abs(x - self.start[0]) > 0.6:\n return False\n e... | <|body_start_0|>
self.start = start
self.end = end
dx = end[0] - start[0]
if dx == 0:
self.m = None
self.n = None
else:
self.m = float(end[1] - start[1]) / dx
self.n = float(start[1] * end[0] - end[1] * start[0]) / dx
<|end_body_0|>... | Represents a line between two points. | Segment | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Segment:
"""Represents a line between two points."""
def __init__(self, start, end):
"""Constructor. - start: An (x, y) pair with the coordinates where the line starts. - end: An (x, y) pair with the coordinates where the line ends."""
<|body_0|>
def contains_point(self,... | stack_v2_sparse_classes_36k_train_033924 | 8,303 | no_license | [
{
"docstring": "Constructor. - start: An (x, y) pair with the coordinates where the line starts. - end: An (x, y) pair with the coordinates where the line ends.",
"name": "__init__",
"signature": "def __init__(self, start, end)"
},
{
"docstring": "Determines if the point is part of the segment."... | 3 | stack_v2_sparse_classes_30k_train_008807 | Implement the Python class `Segment` described below.
Class description:
Represents a line between two points.
Method signatures and docstrings:
- def __init__(self, start, end): Constructor. - start: An (x, y) pair with the coordinates where the line starts. - end: An (x, y) pair with the coordinates where the line ... | Implement the Python class `Segment` described below.
Class description:
Represents a line between two points.
Method signatures and docstrings:
- def __init__(self, start, end): Constructor. - start: An (x, y) pair with the coordinates where the line starts. - end: An (x, y) pair with the coordinates where the line ... | 3a7762c06d1c1fd115cf6e563a45b323c78926bd | <|skeleton|>
class Segment:
"""Represents a line between two points."""
def __init__(self, start, end):
"""Constructor. - start: An (x, y) pair with the coordinates where the line starts. - end: An (x, y) pair with the coordinates where the line ends."""
<|body_0|>
def contains_point(self,... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Segment:
"""Represents a line between two points."""
def __init__(self, start, end):
"""Constructor. - start: An (x, y) pair with the coordinates where the line starts. - end: An (x, y) pair with the coordinates where the line ends."""
self.start = start
self.end = end
dx ... | the_stack_v2_python_sparse | game/framework/geometry.py | sugar-activities/4444-activity | train | 0 |
c6c2d01db5c4093f6b325c8dd9fd8c5501ba34dc | [
"fetch_full_feed = False\nlast_fetch_time = 'last_fetch_mock'\ninitial_interval = 'initial_mock'\nassert get_added_after(fetch_full_feed, initial_interval, last_fetch_time) == last_fetch_time",
"fetch_full_feed = True\nlast_fetch_time = 'last_fetch_mock'\ninitial_interval = 'initial_mock'\nassert get_added_after(... | <|body_start_0|>
fetch_full_feed = False
last_fetch_time = 'last_fetch_mock'
initial_interval = 'initial_mock'
assert get_added_after(fetch_full_feed, initial_interval, last_fetch_time) == last_fetch_time
<|end_body_0|>
<|body_start_1|>
fetch_full_feed = True
last_fetch_... | Scenario: Test get_added_after | TestGetAddedAfter | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestGetAddedAfter:
"""Scenario: Test get_added_after"""
def test_get_last_fetch_time(self):
"""Scenario: fetch_full_feed and last fetch is set Given: - fetch_full_feed is false - last fetch time is set When: - calling get_added_after Then: - return last fetch time"""
<|body_0... | stack_v2_sparse_classes_36k_train_033925 | 9,956 | permissive | [
{
"docstring": "Scenario: fetch_full_feed and last fetch is set Given: - fetch_full_feed is false - last fetch time is set When: - calling get_added_after Then: - return last fetch time",
"name": "test_get_last_fetch_time",
"signature": "def test_get_last_fetch_time(self)"
},
{
"docstring": "Sce... | 3 | stack_v2_sparse_classes_30k_train_014939 | Implement the Python class `TestGetAddedAfter` described below.
Class description:
Scenario: Test get_added_after
Method signatures and docstrings:
- def test_get_last_fetch_time(self): Scenario: fetch_full_feed and last fetch is set Given: - fetch_full_feed is false - last fetch time is set When: - calling get_added... | Implement the Python class `TestGetAddedAfter` described below.
Class description:
Scenario: Test get_added_after
Method signatures and docstrings:
- def test_get_last_fetch_time(self): Scenario: fetch_full_feed and last fetch is set Given: - fetch_full_feed is false - last fetch time is set When: - calling get_added... | 01b57f8c658c2faed047313d3034e8052ffa83ce | <|skeleton|>
class TestGetAddedAfter:
"""Scenario: Test get_added_after"""
def test_get_last_fetch_time(self):
"""Scenario: fetch_full_feed and last fetch is set Given: - fetch_full_feed is false - last fetch time is set When: - calling get_added_after Then: - return last fetch time"""
<|body_0... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestGetAddedAfter:
"""Scenario: Test get_added_after"""
def test_get_last_fetch_time(self):
"""Scenario: fetch_full_feed and last fetch is set Given: - fetch_full_feed is false - last fetch time is set When: - calling get_added_after Then: - return last fetch time"""
fetch_full_feed = Fal... | the_stack_v2_python_sparse | Packs/FeedTAXII/Integrations/FeedTAXII2/FeedTAXII2_test.py | adambaumeister/content | train | 2 |
6f446e2ef3f403c60ff5f7f25eb434eea7ca3343 | [
"rt = []\n\ndef inorder(root):\n if not root:\n return\n rt.append(str(root.val))\n inorder(root.left)\n inorder(root.right)\ninorder(root)\nreturn ' '.join(rt)",
"vals = collections.deque((int(i) for i in data.split()))\n\ndef buildTree(min, max):\n if vals and vals[0] > min and (vals[0] < ... | <|body_start_0|>
rt = []
def inorder(root):
if not root:
return
rt.append(str(root.val))
inorder(root.left)
inorder(root.right)
inorder(root)
return ' '.join(rt)
<|end_body_0|>
<|body_start_1|>
vals = collections.d... | Codec2 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec2:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|>
<|body... | stack_v2_sparse_classes_36k_train_033926 | 3,374 | 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_006436 | Implement the Python class `Codec2` described below.
Class description:
Implement the Codec2 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 :rtyp... | Implement the Python class `Codec2` described below.
Class description:
Implement the Codec2 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 :rtyp... | 0e99f9a5226507706b3ee66fd04bae813755ef40 | <|skeleton|>
class Codec2:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Codec2:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
rt = []
def inorder(root):
if not root:
return
rt.append(str(root.val))
inorder(root.left)
inorder(root.right)
... | the_stack_v2_python_sparse | medium/tree/test_449_Serialize_and_Deserialize_BST.py | wuxu1019/leetcode_sophia | train | 1 | |
fe35a416008fe22430b51b9de591ddb2c81fa175 | [
"self._each_result_cont = each_result_cont\nself._num_expected_results = num_expected_results\nself._num_continuations_issued = 0\nself._all_results_cont = all_results_cont\nself._results_received = 0",
"assert self._num_continuations_issued < self._num_expected_results\nself._num_continuations_issued += 1\nthis_... | <|body_start_0|>
self._each_result_cont = each_result_cont
self._num_expected_results = num_expected_results
self._num_continuations_issued = 0
self._all_results_cont = all_results_cont
self._results_received = 0
<|end_body_0|>
<|body_start_1|>
assert self._num_continuat... | A simple utility class for scheduling an continuation to be executed when several calls have all completed (regardless of the order in which they complete). Allows an action to be executed when each individual result arrives, as well as another when all have arrived. Note nothing is done to combine together the results... | WhenAllResultsReceived | [
"MIT",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WhenAllResultsReceived:
"""A simple utility class for scheduling an continuation to be executed when several calls have all completed (regardless of the order in which they complete). Allows an action to be executed when each individual result arrives, as well as another when all have arrived. No... | stack_v2_sparse_classes_36k_train_033927 | 12,637 | permissive | [
{
"docstring": "Creates a ResultsCombiner that will invoke <all_results_cont> (with no arguments) when it has received <num_expected_results> (via the `continuation_for_result` method). <each_result_cont> is a continuation which is invoked with each individual result.",
"name": "__init__",
"signature": ... | 2 | null | Implement the Python class `WhenAllResultsReceived` described below.
Class description:
A simple utility class for scheduling an continuation to be executed when several calls have all completed (regardless of the order in which they complete). Allows an action to be executed when each individual result arrives, as we... | Implement the Python class `WhenAllResultsReceived` described below.
Class description:
A simple utility class for scheduling an continuation to be executed when several calls have all completed (regardless of the order in which they complete). Allows an action to be executed when each individual result arrives, as we... | 8fa75e67c0db8f632b135379740051cd10ff31f2 | <|skeleton|>
class WhenAllResultsReceived:
"""A simple utility class for scheduling an continuation to be executed when several calls have all completed (regardless of the order in which they complete). Allows an action to be executed when each individual result arrives, as well as another when all have arrived. No... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class WhenAllResultsReceived:
"""A simple utility class for scheduling an continuation to be executed when several calls have all completed (regardless of the order in which they complete). Allows an action to be executed when each individual result arrives, as well as another when all have arrived. Note nothing is... | the_stack_v2_python_sparse | rlo/src/rlo/worker.py | tomjaguarpaw/knossos-ksc | train | 0 |
2779e52c6a1efaeadd4bb2177176091dc8fb1da7 | [
"self.time_range = params_pre['time_range']\nself.plot_dir = params_pre['plot_dir']\nself.logger = logging.getLogger('simple')",
"plotter = plot_ecei_timeslice(data_chunk)\ntidx_plot = [data_chunk.tb.time_to_idx(t) for t in self.time_range]\nif tidx_plot[0] is not None:\n self.logger.info(f'Plotting data into ... | <|body_start_0|>
self.time_range = params_pre['time_range']
self.plot_dir = params_pre['plot_dir']
self.logger = logging.getLogger('simple')
<|end_body_0|>
<|body_start_1|>
plotter = plot_ecei_timeslice(data_chunk)
tidx_plot = [data_chunk.tb.time_to_idx(t) for t in self.time_ran... | Plots the pre-processed data and stores it to a file. Plots are made using the instantaneous data in the pipeline. That is, the position of the plot routine in the preprocessing pipeline is important. | pre_plot | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class pre_plot:
"""Plots the pre-processed data and stores it to a file. Plots are made using the instantaneous data in the pipeline. That is, the position of the plot routine in the preprocessing pipeline is important."""
def __init__(self, params_pre):
"""Instantiates the pre_plot class ... | stack_v2_sparse_classes_36k_train_033928 | 1,831 | no_license | [
{
"docstring": "Instantiates the pre_plot class as a callable. Args: params_pre (dictionary): Preprocessing section of Delta configuration Returns: None",
"name": "__init__",
"signature": "def __init__(self, params_pre)"
},
{
"docstring": "Plots the data chunk. Args: data_chunk (2d image): Data ... | 2 | stack_v2_sparse_classes_30k_train_018372 | Implement the Python class `pre_plot` described below.
Class description:
Plots the pre-processed data and stores it to a file. Plots are made using the instantaneous data in the pipeline. That is, the position of the plot routine in the preprocessing pipeline is important.
Method signatures and docstrings:
- def __i... | Implement the Python class `pre_plot` described below.
Class description:
Plots the pre-processed data and stores it to a file. Plots are made using the instantaneous data in the pipeline. That is, the position of the plot routine in the preprocessing pipeline is important.
Method signatures and docstrings:
- def __i... | 7ce63705e18c427f448c8d720c950a54add07966 | <|skeleton|>
class pre_plot:
"""Plots the pre-processed data and stores it to a file. Plots are made using the instantaneous data in the pipeline. That is, the position of the plot routine in the preprocessing pipeline is important."""
def __init__(self, params_pre):
"""Instantiates the pre_plot class ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class pre_plot:
"""Plots the pre-processed data and stores it to a file. Plots are made using the instantaneous data in the pipeline. That is, the position of the plot routine in the preprocessing pipeline is important."""
def __init__(self, params_pre):
"""Instantiates the pre_plot class as a callable... | the_stack_v2_python_sparse | delta/preprocess/pre_plot.py | rkube/delta | train | 7 |
1e15e54e6f32fd3b7a97542a8a025be3e74543fe | [
"if target <= 1:\n raise ValueError(f'Target iteration of ETA must be > 1, got {target}')\nself.targetIteration = target\nself._ti = None\nself._xi = None",
"if self._ti is None:\n if current > 0:\n self._ti = time.time()\n self._xi = current\n return None\nif current <= self._xi:\n retu... | <|body_start_0|>
if target <= 1:
raise ValueError(f'Target iteration of ETA must be > 1, got {target}')
self.targetIteration = target
self._ti = None
self._xi = None
<|end_body_0|>
<|body_start_1|>
if self._ti is None:
if current > 0:
self... | ! Estimate the time of arrival for iterations. The ETA is computed from a linear regression to the starting time and current time (time at execution of the __call__ method). This is not very stable for strongly changing durations of individual iterations but gives a good estimate for mostly stable durations. The start ... | ETA | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ETA:
"""! Estimate the time of arrival for iterations. The ETA is computed from a linear regression to the starting time and current time (time at execution of the __call__ method). This is not very stable for strongly changing durations of individual iterations but gives a good estimate for most... | stack_v2_sparse_classes_36k_train_033929 | 29,663 | permissive | [
{
"docstring": "!Initialize with a given target iteration number.",
"name": "__init__",
"signature": "def __init__(self, target)"
},
{
"docstring": "! Estimate the time of arrival given a current iteration. \\\\param current Iteration number the loop is currently at. \\\\returns - Estimated time... | 3 | stack_v2_sparse_classes_30k_train_020378 | Implement the Python class `ETA` described below.
Class description:
! Estimate the time of arrival for iterations. The ETA is computed from a linear regression to the starting time and current time (time at execution of the __call__ method). This is not very stable for strongly changing durations of individual iterat... | Implement the Python class `ETA` described below.
Class description:
! Estimate the time of arrival for iterations. The ETA is computed from a linear regression to the starting time and current time (time at execution of the __call__ method). This is not very stable for strongly changing durations of individual iterat... | 41557db1965bf3801bfadf9ece39ec1dab9b7660 | <|skeleton|>
class ETA:
"""! Estimate the time of arrival for iterations. The ETA is computed from a linear regression to the starting time and current time (time at execution of the __call__ method). This is not very stable for strongly changing durations of individual iterations but gives a good estimate for most... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ETA:
"""! Estimate the time of arrival for iterations. The ETA is computed from a linear regression to the starting time and current time (time at execution of the __call__ method). This is not very stable for strongly changing durations of individual iterations but gives a good estimate for mostly stable dur... | the_stack_v2_python_sparse | src/isle/cli.py | evanberkowitz/isle | train | 3 |
aca1ca176e186147cd154092535529a837d984a3 | [
"super().__init__()\nself.in_channels = in_channels\nself.out_channels = out_channels\nself.stride = stride",
"for p in self.parameters():\n p.requires_grad = False\nFrozenBatchNorm2d.convert_frozen_batchnorm(self)\nreturn self"
] | <|body_start_0|>
super().__init__()
self.in_channels = in_channels
self.out_channels = out_channels
self.stride = stride
<|end_body_0|>
<|body_start_1|>
for p in self.parameters():
p.requires_grad = False
FrozenBatchNorm2d.convert_frozen_batchnorm(self)
... | A CNN block is assumed to have input channels, output channels and a stride. The input and output of `forward()` method must be NCHW tensors. The method can perform arbitrary computation but must match the given channels and stride specification. Attribute: in_channels (int): out_channels (int): stride (int): | CNNBlockBase | [
"GPL-1.0-or-later",
"Apache-2.0",
"BSD-2-Clause",
"MIT",
"BSD-3-Clause",
"LicenseRef-scancode-generic-cla",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CNNBlockBase:
"""A CNN block is assumed to have input channels, output channels and a stride. The input and output of `forward()` method must be NCHW tensors. The method can perform arbitrary computation but must match the given channels and stride specification. Attribute: in_channels (int): out... | stack_v2_sparse_classes_36k_train_033930 | 4,708 | permissive | [
{
"docstring": "The `__init__` method of any subclass should also contain these arguments. Args: in_channels (int): out_channels (int): stride (int):",
"name": "__init__",
"signature": "def __init__(self, in_channels, out_channels, stride)"
},
{
"docstring": "Make this block not trainable. This ... | 2 | stack_v2_sparse_classes_30k_train_019861 | Implement the Python class `CNNBlockBase` described below.
Class description:
A CNN block is assumed to have input channels, output channels and a stride. The input and output of `forward()` method must be NCHW tensors. The method can perform arbitrary computation but must match the given channels and stride specifica... | Implement the Python class `CNNBlockBase` described below.
Class description:
A CNN block is assumed to have input channels, output channels and a stride. The input and output of `forward()` method must be NCHW tensors. The method can perform arbitrary computation but must match the given channels and stride specifica... | 92acc188d3a0f634de58463b6676e70df83ef808 | <|skeleton|>
class CNNBlockBase:
"""A CNN block is assumed to have input channels, output channels and a stride. The input and output of `forward()` method must be NCHW tensors. The method can perform arbitrary computation but must match the given channels and stride specification. Attribute: in_channels (int): out... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CNNBlockBase:
"""A CNN block is assumed to have input channels, output channels and a stride. The input and output of `forward()` method must be NCHW tensors. The method can perform arbitrary computation but must match the given channels and stride specification. Attribute: in_channels (int): out_channels (in... | the_stack_v2_python_sparse | PyTorch/dev/cv/image_classification/SlowFast_ID0646_for_PyTorch/detectron2/detectron2/layers/blocks.py | Ascend/ModelZoo-PyTorch | train | 23 |
d50deeb81f686e7080bee79b5bcf135dc77cb782 | [
"drawing = Drawing(200, 280)\ngraph = VerticalBarChart()\ngraph.x = self.graph_x\ngraph.y = self.graph_y\ngraph.width = self.width\ngraph.height = self.height\ngraph.valueAxis.forceZero = 1\ngraph.valueAxis.valueMin = self.value_min\ngraph.valueAxis.valueMax = self.value_max\ngraph.valueAxis.valueStep = self.value_... | <|body_start_0|>
drawing = Drawing(200, 280)
graph = VerticalBarChart()
graph.x = self.graph_x
graph.y = self.graph_y
graph.width = self.width
graph.height = self.height
graph.valueAxis.forceZero = 1
graph.valueAxis.valueMin = self.value_min
graph.... | Class for drawing a customized bar chart | BarChart | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BarChart:
"""Class for drawing a customized bar chart"""
def vertical_bar_chart(self):
"""Draws a vertical bar chart :return: vertical bar chart"""
<|body_0|>
def horizontal_bar_graph(self):
"""Draws a horizontal bar chart :return: horizontal bar chart"""
... | stack_v2_sparse_classes_36k_train_033931 | 9,685 | no_license | [
{
"docstring": "Draws a vertical bar chart :return: vertical bar chart",
"name": "vertical_bar_chart",
"signature": "def vertical_bar_chart(self)"
},
{
"docstring": "Draws a horizontal bar chart :return: horizontal bar chart",
"name": "horizontal_bar_graph",
"signature": "def horizontal_... | 2 | stack_v2_sparse_classes_30k_val_000453 | Implement the Python class `BarChart` described below.
Class description:
Class for drawing a customized bar chart
Method signatures and docstrings:
- def vertical_bar_chart(self): Draws a vertical bar chart :return: vertical bar chart
- def horizontal_bar_graph(self): Draws a horizontal bar chart :return: horizontal... | Implement the Python class `BarChart` described below.
Class description:
Class for drawing a customized bar chart
Method signatures and docstrings:
- def vertical_bar_chart(self): Draws a vertical bar chart :return: vertical bar chart
- def horizontal_bar_graph(self): Draws a horizontal bar chart :return: horizontal... | 941e8b2870f8724db3d5103dda5157fd597cfcc7 | <|skeleton|>
class BarChart:
"""Class for drawing a customized bar chart"""
def vertical_bar_chart(self):
"""Draws a vertical bar chart :return: vertical bar chart"""
<|body_0|>
def horizontal_bar_graph(self):
"""Draws a horizontal bar chart :return: horizontal bar chart"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BarChart:
"""Class for drawing a customized bar chart"""
def vertical_bar_chart(self):
"""Draws a vertical bar chart :return: vertical bar chart"""
drawing = Drawing(200, 280)
graph = VerticalBarChart()
graph.x = self.graph_x
graph.y = self.graph_y
graph.wi... | the_stack_v2_python_sparse | backend/martin_helder/services/report_service.py | JoaoAlvaroFerreira/FEUP-LGP | train | 1 |
76fa9560349137f2b5fce217ef75085fc321a3a2 | [
"toSend = ''\nfor s in self.strings:\n toSend += self.receiver.encode(s)\nfor packetSize in range(1, 20):\n a = self.receiver(maxLength=699)\n got = []\n for s in diceString(toSend, packetSize):\n out, code = a.getNewFrames(s)\n self.assertEqual(decoders.OK, code)\n got.extend(out)\... | <|body_start_0|>
toSend = ''
for s in self.strings:
toSend += self.receiver.encode(s)
for packetSize in range(1, 20):
a = self.receiver(maxLength=699)
got = []
for s in diceString(toSend, packetSize):
out, code = a.getNewFrames(s)
... | CommonTests | [
"MIT",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CommonTests:
def test_buffer(self):
"""Test that when strings are received in chunks of different lengths, they are still parsed correctly."""
<|body_0|>
def test_illegalWithPacketSizes(self):
"""Assert that illegal strings return the correct error code even when the... | stack_v2_sparse_classes_36k_train_033932 | 7,794 | permissive | [
{
"docstring": "Test that when strings are received in chunks of different lengths, they are still parsed correctly.",
"name": "test_buffer",
"signature": "def test_buffer(self)"
},
{
"docstring": "Assert that illegal strings return the correct error code even when they arrive in variable packet... | 2 | stack_v2_sparse_classes_30k_train_001325 | Implement the Python class `CommonTests` described below.
Class description:
Implement the CommonTests class.
Method signatures and docstrings:
- def test_buffer(self): Test that when strings are received in chunks of different lengths, they are still parsed correctly.
- def test_illegalWithPacketSizes(self): Assert ... | Implement the Python class `CommonTests` described below.
Class description:
Implement the CommonTests class.
Method signatures and docstrings:
- def test_buffer(self): Test that when strings are received in chunks of different lengths, they are still parsed correctly.
- def test_illegalWithPacketSizes(self): Assert ... | 386e1aeb5197e197e806b3b6a0c11ab9315c8ab5 | <|skeleton|>
class CommonTests:
def test_buffer(self):
"""Test that when strings are received in chunks of different lengths, they are still parsed correctly."""
<|body_0|>
def test_illegalWithPacketSizes(self):
"""Assert that illegal strings return the correct error code even when the... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CommonTests:
def test_buffer(self):
"""Test that when strings are received in chunks of different lengths, they are still parsed correctly."""
toSend = ''
for s in self.strings:
toSend += self.receiver.encode(s)
for packetSize in range(1, 20):
a = self.r... | the_stack_v2_python_sparse | minerva/test_decoders.py | ludiosarchive/Minerva | train | 1 | |
544dcc39c796d7e7ac8c22d8a17dbce670697412 | [
"if self.request.get('sheriff'):\n self._DumpAnomalyDataForSheriff()\nelif self.request.get('test_path'):\n self._DumpTestData()\nelse:\n self.ReportError('No parameters specified.')",
"test_path = self.request.get('test_path')\nnum_points = int(self.request.get('num_points', _DEFAULT_MAX_POINTS))\nend_r... | <|body_start_0|>
if self.request.get('sheriff'):
self._DumpAnomalyDataForSheriff()
elif self.request.get('test_path'):
self._DumpTestData()
else:
self.ReportError('No parameters specified.')
<|end_body_0|>
<|body_start_1|>
test_path = self.request.get... | Handler for extracting entities from datastore. | DumpGraphJsonHandler | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DumpGraphJsonHandler:
"""Handler for extracting entities from datastore."""
def get(self):
"""Handles dumping dashboard data."""
<|body_0|>
def _DumpTestData(self):
"""Dumps data for the requested test. Request parameters: test_path: A single full test path, incl... | stack_v2_sparse_classes_36k_train_033933 | 6,420 | permissive | [
{
"docstring": "Handles dumping dashboard data.",
"name": "get",
"signature": "def get(self)"
},
{
"docstring": "Dumps data for the requested test. Request parameters: test_path: A single full test path, including master/bot. num_points: Max number of Row entities (optional). end_rev: Ending rev... | 5 | null | Implement the Python class `DumpGraphJsonHandler` described below.
Class description:
Handler for extracting entities from datastore.
Method signatures and docstrings:
- def get(self): Handles dumping dashboard data.
- def _DumpTestData(self): Dumps data for the requested test. Request parameters: test_path: A single... | Implement the Python class `DumpGraphJsonHandler` described below.
Class description:
Handler for extracting entities from datastore.
Method signatures and docstrings:
- def get(self): Handles dumping dashboard data.
- def _DumpTestData(self): Dumps data for the requested test. Request parameters: test_path: A single... | 53102de187a48ac2cfc241fef54dcbc29c453a8e | <|skeleton|>
class DumpGraphJsonHandler:
"""Handler for extracting entities from datastore."""
def get(self):
"""Handles dumping dashboard data."""
<|body_0|>
def _DumpTestData(self):
"""Dumps data for the requested test. Request parameters: test_path: A single full test path, incl... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DumpGraphJsonHandler:
"""Handler for extracting entities from datastore."""
def get(self):
"""Handles dumping dashboard data."""
if self.request.get('sheriff'):
self._DumpAnomalyDataForSheriff()
elif self.request.get('test_path'):
self._DumpTestData()
... | the_stack_v2_python_sparse | dashboard/dashboard/dump_graph_json.py | catapult-project/catapult | train | 2,032 |
678d91f20f0ef249524e84ef9db262846b6e4c00 | [
"with ClusterRpcProxy(CONFIG_RPC) as rpc:\n response_data = rpc.query_brands.list(num_page, limit)\n return Response(response=response_data, status=200, mimetype='application/json')",
"data = request.json\nwith ClusterRpcProxy(CONFIG_RPC) as rpc:\n response_data = rpc.command_brands.add(data)\n return... | <|body_start_0|>
with ClusterRpcProxy(CONFIG_RPC) as rpc:
response_data = rpc.query_brands.list(num_page, limit)
return Response(response=response_data, status=200, mimetype='application/json')
<|end_body_0|>
<|body_start_1|>
data = request.json
with ClusterRpcProxy(CONF... | BrandsCollection | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BrandsCollection:
def get(self, num_page=5, limit=5):
"""returns a list of brands"""
<|body_0|>
def post(self):
"""creates a new brand"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
with ClusterRpcProxy(CONFIG_RPC) as rpc:
response_data... | stack_v2_sparse_classes_36k_train_033934 | 2,584 | no_license | [
{
"docstring": "returns a list of brands",
"name": "get",
"signature": "def get(self, num_page=5, limit=5)"
},
{
"docstring": "creates a new brand",
"name": "post",
"signature": "def post(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_017601 | Implement the Python class `BrandsCollection` described below.
Class description:
Implement the BrandsCollection class.
Method signatures and docstrings:
- def get(self, num_page=5, limit=5): returns a list of brands
- def post(self): creates a new brand | Implement the Python class `BrandsCollection` described below.
Class description:
Implement the BrandsCollection class.
Method signatures and docstrings:
- def get(self, num_page=5, limit=5): returns a list of brands
- def post(self): creates a new brand
<|skeleton|>
class BrandsCollection:
def get(self, num_pa... | 3f4c93c631e5d5b52acd2ce11e220ff3fbec07b6 | <|skeleton|>
class BrandsCollection:
def get(self, num_page=5, limit=5):
"""returns a list of brands"""
<|body_0|>
def post(self):
"""creates a new brand"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BrandsCollection:
def get(self, num_page=5, limit=5):
"""returns a list of brands"""
with ClusterRpcProxy(CONFIG_RPC) as rpc:
response_data = rpc.query_brands.list(num_page, limit)
return Response(response=response_data, status=200, mimetype='application/json')
def... | the_stack_v2_python_sparse | orchestrator/apis/brand_ns.py | bsmi021/eahub_shopco | train | 0 | |
0c537649fc89f3a6db7c05b8ef1c75265fe7524d | [
"reflection_table = SumAndPrfIntensityReducer.reduce_on_intensities(reflection_table)\nreflection_table = ScaleIntensityReducer.reduce_on_intensities(reflection_table)\nreturn reflection_table",
"reflection_table = SumAndPrfIntensityReducer.apply_scaling_factors(reflection_table)\nreflection_table = ScaleIntensit... | <|body_start_0|>
reflection_table = SumAndPrfIntensityReducer.reduce_on_intensities(reflection_table)
reflection_table = ScaleIntensityReducer.reduce_on_intensities(reflection_table)
return reflection_table
<|end_body_0|>
<|body_start_1|>
reflection_table = SumAndPrfIntensityReducer.app... | Reduction methods for data with sum, profile and scale intensities. Only reflections with valid values for all intensity types are retained. | AllSumPrfScaleIntensityReducer | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AllSumPrfScaleIntensityReducer:
"""Reduction methods for data with sum, profile and scale intensities. Only reflections with valid values for all intensity types are retained."""
def reduce_on_intensities(reflection_table):
"""Select those with valid reflections for all values."""
... | stack_v2_sparse_classes_36k_train_033935 | 38,270 | permissive | [
{
"docstring": "Select those with valid reflections for all values.",
"name": "reduce_on_intensities",
"signature": "def reduce_on_intensities(reflection_table)"
},
{
"docstring": "Apply corrections to the intensities and variances.",
"name": "apply_scaling_factors",
"signature": "def ap... | 2 | null | Implement the Python class `AllSumPrfScaleIntensityReducer` described below.
Class description:
Reduction methods for data with sum, profile and scale intensities. Only reflections with valid values for all intensity types are retained.
Method signatures and docstrings:
- def reduce_on_intensities(reflection_table): ... | Implement the Python class `AllSumPrfScaleIntensityReducer` described below.
Class description:
Reduction methods for data with sum, profile and scale intensities. Only reflections with valid values for all intensity types are retained.
Method signatures and docstrings:
- def reduce_on_intensities(reflection_table): ... | 88bf7f7c5ac44defc046ebf0719cde748092cfff | <|skeleton|>
class AllSumPrfScaleIntensityReducer:
"""Reduction methods for data with sum, profile and scale intensities. Only reflections with valid values for all intensity types are retained."""
def reduce_on_intensities(reflection_table):
"""Select those with valid reflections for all values."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AllSumPrfScaleIntensityReducer:
"""Reduction methods for data with sum, profile and scale intensities. Only reflections with valid values for all intensity types are retained."""
def reduce_on_intensities(reflection_table):
"""Select those with valid reflections for all values."""
reflect... | the_stack_v2_python_sparse | src/dials/util/filter_reflections.py | dials/dials | train | 71 |
c496dbd0244bc28e482f95e7d831f9c6b753f613 | [
"self.device_bus = device_bus\nself.device_index = device_index\nself.disk_size_bytes = disk_size_bytes",
"if dictionary is None:\n return None\ndevice_bus = dictionary.get('deviceBus')\ndevice_index = dictionary.get('deviceIndex')\ndisk_size_bytes = dictionary.get('diskSizeBytes')\nreturn cls(device_bus, devi... | <|body_start_0|>
self.device_bus = device_bus
self.device_index = device_index
self.disk_size_bytes = disk_size_bytes
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
device_bus = dictionary.get('deviceBus')
device_index = dictionary.get('de... | Implementation of the 'VirtualDiskConfig' model. Acropolis Virtual Disk Attributes: device_bus (string): The device bus for the virtual disk device. device_index (int): Index of the device on the adapter type. disk_size_bytes (long|int): Disk size in Bytes. | VirtualDiskConfig | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VirtualDiskConfig:
"""Implementation of the 'VirtualDiskConfig' model. Acropolis Virtual Disk Attributes: device_bus (string): The device bus for the virtual disk device. device_index (int): Index of the device on the adapter type. disk_size_bytes (long|int): Disk size in Bytes."""
def __ini... | stack_v2_sparse_classes_36k_train_033936 | 1,862 | permissive | [
{
"docstring": "Constructor for the VirtualDiskConfig class",
"name": "__init__",
"signature": "def __init__(self, device_bus=None, device_index=None, disk_size_bytes=None)"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: dictionary (dictionary): A dictionary represe... | 2 | stack_v2_sparse_classes_30k_train_003230 | Implement the Python class `VirtualDiskConfig` described below.
Class description:
Implementation of the 'VirtualDiskConfig' model. Acropolis Virtual Disk Attributes: device_bus (string): The device bus for the virtual disk device. device_index (int): Index of the device on the adapter type. disk_size_bytes (long|int)... | Implement the Python class `VirtualDiskConfig` described below.
Class description:
Implementation of the 'VirtualDiskConfig' model. Acropolis Virtual Disk Attributes: device_bus (string): The device bus for the virtual disk device. device_index (int): Index of the device on the adapter type. disk_size_bytes (long|int)... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class VirtualDiskConfig:
"""Implementation of the 'VirtualDiskConfig' model. Acropolis Virtual Disk Attributes: device_bus (string): The device bus for the virtual disk device. device_index (int): Index of the device on the adapter type. disk_size_bytes (long|int): Disk size in Bytes."""
def __ini... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class VirtualDiskConfig:
"""Implementation of the 'VirtualDiskConfig' model. Acropolis Virtual Disk Attributes: device_bus (string): The device bus for the virtual disk device. device_index (int): Index of the device on the adapter type. disk_size_bytes (long|int): Disk size in Bytes."""
def __init__(self, dev... | the_stack_v2_python_sparse | cohesity_management_sdk/models/virtual_disk_config.py | cohesity/management-sdk-python | train | 24 |
a82b9c3b0ccd9a8e17c5328e965f7d2e2bc6ce47 | [
"if len(s) < (1 << k) + k - 1:\n return False\ncur = int(s[:k], base=2)\ncodes = set([cur])\nbegin = 0\nend = k\nwhile len(codes) != 2 ** k and end < len(s):\n cur = (cur - 2 ** (k - 1) * int(s[begin]) << 1) + int(s[end])\n codes.add(cur)\n end += 1\n begin += 1\nreturn len(codes) == 2 ** k",
"code... | <|body_start_0|>
if len(s) < (1 << k) + k - 1:
return False
cur = int(s[:k], base=2)
codes = set([cur])
begin = 0
end = k
while len(codes) != 2 ** k and end < len(s):
cur = (cur - 2 ** (k - 1) * int(s[begin]) << 1) + int(s[end])
codes.a... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def hasAllCodes(self, s, k):
""":type s: str :type k: int :rtype: bool"""
<|body_0|>
def hasAllCodes1(self, s, k):
""":type s: str :type k: int :rtype: bool"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if len(s) < (1 << k) + k - 1:
... | stack_v2_sparse_classes_36k_train_033937 | 1,032 | no_license | [
{
"docstring": ":type s: str :type k: int :rtype: bool",
"name": "hasAllCodes",
"signature": "def hasAllCodes(self, s, k)"
},
{
"docstring": ":type s: str :type k: int :rtype: bool",
"name": "hasAllCodes1",
"signature": "def hasAllCodes1(self, s, k)"
}
] | 2 | stack_v2_sparse_classes_30k_train_015569 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def hasAllCodes(self, s, k): :type s: str :type k: int :rtype: bool
- def hasAllCodes1(self, s, k): :type s: str :type k: int :rtype: bool | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def hasAllCodes(self, s, k): :type s: str :type k: int :rtype: bool
- def hasAllCodes1(self, s, k): :type s: str :type k: int :rtype: bool
<|skeleton|>
class Solution:
def ... | 9d394cd2862703cfb7a7b505b35deda7450a692e | <|skeleton|>
class Solution:
def hasAllCodes(self, s, k):
""":type s: str :type k: int :rtype: bool"""
<|body_0|>
def hasAllCodes1(self, s, k):
""":type s: str :type k: int :rtype: bool"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def hasAllCodes(self, s, k):
""":type s: str :type k: int :rtype: bool"""
if len(s) < (1 << k) + k - 1:
return False
cur = int(s[:k], base=2)
codes = set([cur])
begin = 0
end = k
while len(codes) != 2 ** k and end < len(s):
... | the_stack_v2_python_sparse | 1461.检查一个字符串是否包含所有长度为-k-的二进制子串.py | Ezi4Zy/leetcode | train | 0 | |
7f2af0ebde25c221a0a63c207324e765d46e704c | [
"super(SVRenderLayer, self).__init__()\nself.layer = render_layer\nself.camera = camera\nself.keep = keep_output\nself.attr = attr",
"self.layer.renderer.eye = self.camera\nself.layer.renderer.light_direction = -self.camera\nout = self.layer(input)\nif self.keep:\n setattr(input, self.attr, out)\nreturn out"
] | <|body_start_0|>
super(SVRenderLayer, self).__init__()
self.layer = render_layer
self.camera = camera
self.keep = keep_output
self.attr = attr
<|end_body_0|>
<|body_start_1|>
self.layer.renderer.eye = self.camera
self.layer.renderer.light_direction = -self.camera... | A class representing a signle view rendering layer Attributes ---------- layer : RenderLayer a rendering layer camera : Tensor the positions of the camera keep : bool if True keeps the output in an attribute of the input data attr : str the name of the attribute to store the output to Methods ------- forward(input) ret... | SVRenderLayer | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SVRenderLayer:
"""A class representing a signle view rendering layer Attributes ---------- layer : RenderLayer a rendering layer camera : Tensor the positions of the camera keep : bool if True keeps the output in an attribute of the input data attr : str the name of the attribute to store the out... | stack_v2_sparse_classes_36k_train_033938 | 9,441 | permissive | [
{
"docstring": "Parameters ---------- render_layer : RenderLayer a rendering layer camera : Tensor the positions of the camera keep_output : bool (optional) if True keeps the output in an attribute of the input data (default is False) attr : str (optional) the name of the attribute to store the output to (defau... | 2 | stack_v2_sparse_classes_30k_val_000035 | Implement the Python class `SVRenderLayer` described below.
Class description:
A class representing a signle view rendering layer Attributes ---------- layer : RenderLayer a rendering layer camera : Tensor the positions of the camera keep : bool if True keeps the output in an attribute of the input data attr : str the... | Implement the Python class `SVRenderLayer` described below.
Class description:
A class representing a signle view rendering layer Attributes ---------- layer : RenderLayer a rendering layer camera : Tensor the positions of the camera keep : bool if True keeps the output in an attribute of the input data attr : str the... | 2615b66dd4addfd5c03d9d91a24c7da414294308 | <|skeleton|>
class SVRenderLayer:
"""A class representing a signle view rendering layer Attributes ---------- layer : RenderLayer a rendering layer camera : Tensor the positions of the camera keep : bool if True keeps the output in an attribute of the input data attr : str the name of the attribute to store the out... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SVRenderLayer:
"""A class representing a signle view rendering layer Attributes ---------- layer : RenderLayer a rendering layer camera : Tensor the positions of the camera keep : bool if True keeps the output in an attribute of the input data attr : str the name of the attribute to store the output to Method... | the_stack_v2_python_sparse | ACME/layer/RenderLayer.py | mauriziokovacic/ACME | train | 3 |
739b536a345bfca29f875fc78d6b8a083759b866 | [
"coininfo.query.__init__(self, coin_bw_info.eventname)\nself.interfaces = interfaces\nif self.interfaces == None:\n self.interfaces = []\nself.mode = mode",
"ilist = ''\nfor i in self.interfaces:\n ilist += 'interface=\"' + str(i) + '\"'\n ilist += ' or '\nreturn ilist[:-3]",
"s = '*'\nif self.mode == ... | <|body_start_0|>
coininfo.query.__init__(self, coin_bw_info.eventname)
self.interfaces = interfaces
if self.interfaces == None:
self.interfaces = []
self.mode = mode
<|end_body_0|>
<|body_start_1|>
ilist = ''
for i in self.interfaces:
ilist += 'in... | Class to query bandwidth @author ykk @date Aug 2011 | bandwidth_query | [
"LicenseRef-scancode-x11-stanford"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class bandwidth_query:
"""Class to query bandwidth @author ykk @date Aug 2011"""
def __init__(self, mode, interfaces=None):
"""Initialize @param interfaces list of interfaces to return result"""
<|body_0|>
def get_condition(self):
"""Get conditions"""
<|body_1|... | stack_v2_sparse_classes_36k_train_033939 | 8,177 | permissive | [
{
"docstring": "Initialize @param interfaces list of interfaces to return result",
"name": "__init__",
"signature": "def __init__(self, mode, interfaces=None)"
},
{
"docstring": "Get conditions",
"name": "get_condition",
"signature": "def get_condition(self)"
},
{
"docstring": "R... | 3 | null | Implement the Python class `bandwidth_query` described below.
Class description:
Class to query bandwidth @author ykk @date Aug 2011
Method signatures and docstrings:
- def __init__(self, mode, interfaces=None): Initialize @param interfaces list of interfaces to return result
- def get_condition(self): Get conditions... | Implement the Python class `bandwidth_query` described below.
Class description:
Class to query bandwidth @author ykk @date Aug 2011
Method signatures and docstrings:
- def __init__(self, mode, interfaces=None): Initialize @param interfaces list of interfaces to return result
- def get_condition(self): Get conditions... | c3f5a31b74d5587671329eea9582ac8aed0c58a4 | <|skeleton|>
class bandwidth_query:
"""Class to query bandwidth @author ykk @date Aug 2011"""
def __init__(self, mode, interfaces=None):
"""Initialize @param interfaces list of interfaces to return result"""
<|body_0|>
def get_condition(self):
"""Get conditions"""
<|body_1|... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class bandwidth_query:
"""Class to query bandwidth @author ykk @date Aug 2011"""
def __init__(self, mode, interfaces=None):
"""Initialize @param interfaces list of interfaces to return result"""
coininfo.query.__init__(self, coin_bw_info.eventname)
self.interfaces = interfaces
i... | the_stack_v2_python_sparse | yapc/local/networkstate.py | yapkke/yapc | train | 1 |
c3aaf0ee533e346a02fd9548f8f84618e50da679 | [
"self.var_lags = var_lags\nself.model = model\nself.datafreq = datafreq",
"lagged_data = []\nfor i, v in enumerate(var_lags):\n for l in var_lags[v]:\n if l == 'cur':\n lagged_data.append(X[:, [i]])\n elif l.endswith('M'):\n lag_avg = rolling_mean(X[:, [i]], l[:-1], datafreq... | <|body_start_0|>
self.var_lags = var_lags
self.model = model
self.datafreq = datafreq
<|end_body_0|>
<|body_start_1|>
lagged_data = []
for i, v in enumerate(var_lags):
for l in var_lags[v]:
if l == 'cur':
lagged_data.append(X[:, [i... | Modelwrapper that lags takes Tair, SWdown, RelHum, Wind, and Rainf, and lags them to estimate Qle fluxes. | LagAverageWrapper | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LagAverageWrapper:
"""Modelwrapper that lags takes Tair, SWdown, RelHum, Wind, and Rainf, and lags them to estimate Qle fluxes."""
def __init__(self, var_lags, model, datafreq=0.5):
"""Model wrapper :var_lags: OrderedDict like {'Tair': ['cur', '2d'], 'Rainf': ['cur', '2h', '7d', '30d... | stack_v2_sparse_classes_36k_train_033940 | 19,534 | permissive | [
{
"docstring": "Model wrapper :var_lags: OrderedDict like {'Tair': ['cur', '2d'], 'Rainf': ['cur', '2h', '7d', '30d', ... :model: model to use lagged variables with :datafreq: data frequency in hours",
"name": "__init__",
"signature": "def __init__(self, var_lags, model, datafreq=0.5)"
},
{
"doc... | 5 | stack_v2_sparse_classes_30k_train_002541 | Implement the Python class `LagAverageWrapper` described below.
Class description:
Modelwrapper that lags takes Tair, SWdown, RelHum, Wind, and Rainf, and lags them to estimate Qle fluxes.
Method signatures and docstrings:
- def __init__(self, var_lags, model, datafreq=0.5): Model wrapper :var_lags: OrderedDict like ... | Implement the Python class `LagAverageWrapper` described below.
Class description:
Modelwrapper that lags takes Tair, SWdown, RelHum, Wind, and Rainf, and lags them to estimate Qle fluxes.
Method signatures and docstrings:
- def __init__(self, var_lags, model, datafreq=0.5): Model wrapper :var_lags: OrderedDict like ... | b82c3f50f69f2cd5be5e97897009e1afee6b167d | <|skeleton|>
class LagAverageWrapper:
"""Modelwrapper that lags takes Tair, SWdown, RelHum, Wind, and Rainf, and lags them to estimate Qle fluxes."""
def __init__(self, var_lags, model, datafreq=0.5):
"""Model wrapper :var_lags: OrderedDict like {'Tair': ['cur', '2d'], 'Rainf': ['cur', '2h', '7d', '30d... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LagAverageWrapper:
"""Modelwrapper that lags takes Tair, SWdown, RelHum, Wind, and Rainf, and lags them to estimate Qle fluxes."""
def __init__(self, var_lags, model, datafreq=0.5):
"""Model wrapper :var_lags: OrderedDict like {'Tair': ['cur', '2d'], 'Rainf': ['cur', '2h', '7d', '30d', ... :model... | the_stack_v2_python_sparse | empirical_lsm/transforms.py | naught101/empirical_lsm | train | 3 |
c32129c77f04840651d90ebb9a50df32385d6cc9 | [
"dp = [float('inf') for _ in range(amount + 1)]\ndp[0] = 0\nfor n in range(amount + 1):\n for coin in coins:\n if n + coin <= amount:\n dp[n + coin] = min(dp[n + coin], dp[n] + 1)\nreturn dp[-1] if dp[-1] < float('inf') else -1",
"def search(amount, count, index):\n if amount == 0:\n ... | <|body_start_0|>
dp = [float('inf') for _ in range(amount + 1)]
dp[0] = 0
for n in range(amount + 1):
for coin in coins:
if n + coin <= amount:
dp[n + coin] = min(dp[n + coin], dp[n] + 1)
return dp[-1] if dp[-1] < float('inf') else -1
<|end... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def coinChange(self, coins, amount):
""":type coins: List[int] :type amount: int :rtype: int"""
<|body_0|>
def coinChange_search(self, coins, amount):
""":type coins: List[int] :type amount: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_st... | stack_v2_sparse_classes_36k_train_033941 | 2,530 | no_license | [
{
"docstring": ":type coins: List[int] :type amount: int :rtype: int",
"name": "coinChange",
"signature": "def coinChange(self, coins, amount)"
},
{
"docstring": ":type coins: List[int] :type amount: int :rtype: int",
"name": "coinChange_search",
"signature": "def coinChange_search(self,... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def coinChange(self, coins, amount): :type coins: List[int] :type amount: int :rtype: int
- def coinChange_search(self, coins, amount): :type coins: List[int] :type amount: int :... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def coinChange(self, coins, amount): :type coins: List[int] :type amount: int :rtype: int
- def coinChange_search(self, coins, amount): :type coins: List[int] :type amount: int :... | e60ba45fe2f2e5e3b3abfecec3db76f5ce1fde59 | <|skeleton|>
class Solution:
def coinChange(self, coins, amount):
""":type coins: List[int] :type amount: int :rtype: int"""
<|body_0|>
def coinChange_search(self, coins, amount):
""":type coins: List[int] :type amount: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def coinChange(self, coins, amount):
""":type coins: List[int] :type amount: int :rtype: int"""
dp = [float('inf') for _ in range(amount + 1)]
dp[0] = 0
for n in range(amount + 1):
for coin in coins:
if n + coin <= amount:
... | the_stack_v2_python_sparse | src/lt_322.py | oxhead/CodingYourWay | train | 0 | |
7ffc2ef2ec955cff639e2b275b0d2ee44708282f | [
"if not root:\n return None\nelse:\n root.left, root.right = (self.invertTree1(root.right), self.invertTree1(root.left))\nreturn root",
"if not root:\n return root\nstack = [root]\nwhile stack:\n node = stack.pop()\n if node:\n node.left, node.right = (node.right, node.left)\n stack +... | <|body_start_0|>
if not root:
return None
else:
root.left, root.right = (self.invertTree1(root.right), self.invertTree1(root.left))
return root
<|end_body_0|>
<|body_start_1|>
if not root:
return root
stack = [root]
while stack:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def invertTree1(self, root):
""":type root: TreeNode :rtype: TreeNode"""
<|body_0|>
def invertTree2(self, root):
""":type root: TreeNode :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not root:
return None
... | stack_v2_sparse_classes_36k_train_033942 | 916 | no_license | [
{
"docstring": ":type root: TreeNode :rtype: TreeNode",
"name": "invertTree1",
"signature": "def invertTree1(self, root)"
},
{
"docstring": ":type root: TreeNode :rtype: TreeNode",
"name": "invertTree2",
"signature": "def invertTree2(self, root)"
}
] | 2 | stack_v2_sparse_classes_30k_train_009427 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def invertTree1(self, root): :type root: TreeNode :rtype: TreeNode
- def invertTree2(self, root): :type root: TreeNode :rtype: TreeNode | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def invertTree1(self, root): :type root: TreeNode :rtype: TreeNode
- def invertTree2(self, root): :type root: TreeNode :rtype: TreeNode
<|skeleton|>
class Solution:
def inv... | 8fb6c1d947046dabd58ff8482b2c0b41f39aa988 | <|skeleton|>
class Solution:
def invertTree1(self, root):
""":type root: TreeNode :rtype: TreeNode"""
<|body_0|>
def invertTree2(self, root):
""":type root: TreeNode :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def invertTree1(self, root):
""":type root: TreeNode :rtype: TreeNode"""
if not root:
return None
else:
root.left, root.right = (self.invertTree1(root.right), self.invertTree1(root.left))
return root
def invertTree2(self, root):
""... | the_stack_v2_python_sparse | Python/LeetCode/226.py | czx94/Algorithms-Collection | train | 2 | |
45bbf26a7c8806afc1ba58bebe5c39579533d567 | [
"if not self._errors:\n self._errors = ErrorDict()\nself._errors['upload_of_work'] = self.error_class([self.DEF_NO_UPLOAD])",
"cleaned_data = self.cleaned_data\nupload = cleaned_data.get('upload_of_work')\nif not upload:\n raise gsoc_forms.ValidationError(self.DEF_NO_UPLOAD)\nreturn upload"
] | <|body_start_0|>
if not self._errors:
self._errors = ErrorDict()
self._errors['upload_of_work'] = self.error_class([self.DEF_NO_UPLOAD])
<|end_body_0|>
<|body_start_1|>
cleaned_data = self.cleaned_data
upload = cleaned_data.get('upload_of_work')
if not upload:
... | Django form for submitting code samples for a project. | CodeSampleUploadFileForm | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CodeSampleUploadFileForm:
"""Django form for submitting code samples for a project."""
def addFileRequiredError(self):
"""Appends a form error message indicating that this field is required."""
<|body_0|>
def clean_upload_of_work(self):
"""Ensure that file field ... | stack_v2_sparse_classes_36k_train_033943 | 21,398 | permissive | [
{
"docstring": "Appends a form error message indicating that this field is required.",
"name": "addFileRequiredError",
"signature": "def addFileRequiredError(self)"
},
{
"docstring": "Ensure that file field has data.",
"name": "clean_upload_of_work",
"signature": "def clean_upload_of_wor... | 2 | null | Implement the Python class `CodeSampleUploadFileForm` described below.
Class description:
Django form for submitting code samples for a project.
Method signatures and docstrings:
- def addFileRequiredError(self): Appends a form error message indicating that this field is required.
- def clean_upload_of_work(self): En... | Implement the Python class `CodeSampleUploadFileForm` described below.
Class description:
Django form for submitting code samples for a project.
Method signatures and docstrings:
- def addFileRequiredError(self): Appends a form error message indicating that this field is required.
- def clean_upload_of_work(self): En... | f581989f168189fa3a58c028eff327a16c03e438 | <|skeleton|>
class CodeSampleUploadFileForm:
"""Django form for submitting code samples for a project."""
def addFileRequiredError(self):
"""Appends a form error message indicating that this field is required."""
<|body_0|>
def clean_upload_of_work(self):
"""Ensure that file field ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CodeSampleUploadFileForm:
"""Django form for submitting code samples for a project."""
def addFileRequiredError(self):
"""Appends a form error message indicating that this field is required."""
if not self._errors:
self._errors = ErrorDict()
self._errors['upload_of_wor... | the_stack_v2_python_sparse | app/soc/modules/gsoc/views/project_details.py | sambitgaan/nupic.son | train | 0 |
ab50a40c51ec49071ac28573eca681a990def741 | [
"self.role_id = arg.get('role_id')\nself.user_id = arg.get('user_id')\nself.active = arg.get('active')",
"if commit:\n db.session.add(self)\n db.session.commit()",
"search = {'user_id': user_id, 'role_id': role_id}\nuser_role = UserRole.query\nresult = user_role.filter_by(**search).first()\nreturn result"... | <|body_start_0|>
self.role_id = arg.get('role_id')
self.user_id = arg.get('user_id')
self.active = arg.get('active')
<|end_body_0|>
<|body_start_1|>
if commit:
db.session.add(self)
db.session.commit()
<|end_body_1|>
<|body_start_2|>
search = {'user_id': ... | User role model | UserRole | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserRole:
"""User role model"""
def __init__(self, **arg):
"""User role cobstructor"""
<|body_0|>
def save(self, commit=True):
"""User role save"""
<|body_1|>
def get_by_uid_rid(self, user_id, role_id):
"""User role uid rid"""
<|body_... | stack_v2_sparse_classes_36k_train_033944 | 1,979 | no_license | [
{
"docstring": "User role cobstructor",
"name": "__init__",
"signature": "def __init__(self, **arg)"
},
{
"docstring": "User role save",
"name": "save",
"signature": "def save(self, commit=True)"
},
{
"docstring": "User role uid rid",
"name": "get_by_uid_rid",
"signature"... | 3 | stack_v2_sparse_classes_30k_train_018049 | Implement the Python class `UserRole` described below.
Class description:
User role model
Method signatures and docstrings:
- def __init__(self, **arg): User role cobstructor
- def save(self, commit=True): User role save
- def get_by_uid_rid(self, user_id, role_id): User role uid rid | Implement the Python class `UserRole` described below.
Class description:
User role model
Method signatures and docstrings:
- def __init__(self, **arg): User role cobstructor
- def save(self, commit=True): User role save
- def get_by_uid_rid(self, user_id, role_id): User role uid rid
<|skeleton|>
class UserRole:
... | 4dc5f5e816e3c461b8a60c5f61c7eafc08050579 | <|skeleton|>
class UserRole:
"""User role model"""
def __init__(self, **arg):
"""User role cobstructor"""
<|body_0|>
def save(self, commit=True):
"""User role save"""
<|body_1|>
def get_by_uid_rid(self, user_id, role_id):
"""User role uid rid"""
<|body_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UserRole:
"""User role model"""
def __init__(self, **arg):
"""User role cobstructor"""
self.role_id = arg.get('role_id')
self.user_id = arg.get('user_id')
self.active = arg.get('active')
def save(self, commit=True):
"""User role save"""
if commit:
... | the_stack_v2_python_sparse | app/models/user_role.py | ekramulmostafa/ms-auth | train | 0 |
2858c938ca3a0c39bdec654ba994f789328e59bb | [
"self.mins = mins\nself.maxs = maxs\nself.children = []",
"for axis in range(3):\n if coord[axis] < self.mins[axis] or coord[axis] > self.maxs[axis]:\n return False\nreturn True",
"for corner in itertools.product(*zip(self.mins, self.maxs)):\n if manhattan_dist(nanobot.coord, corner) > nanobot.r:\n... | <|body_start_0|>
self.mins = mins
self.maxs = maxs
self.children = []
<|end_body_0|>
<|body_start_1|>
for axis in range(3):
if coord[axis] < self.mins[axis] or coord[axis] > self.maxs[axis]:
return False
return True
<|end_body_1|>
<|body_start_2|>
... | Node in an octree | OctreeNode | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OctreeNode:
"""Node in an octree"""
def __init__(self, mins, maxs):
"""Constructor mins: [x, y, z] lower bound maxs: [x, y, z] (inclusive) upper-bound"""
<|body_0|>
def in_node(self, coord):
"""Return True if coord is in this node"""
<|body_1|>
def n... | stack_v2_sparse_classes_36k_train_033945 | 8,665 | permissive | [
{
"docstring": "Constructor mins: [x, y, z] lower bound maxs: [x, y, z] (inclusive) upper-bound",
"name": "__init__",
"signature": "def __init__(self, mins, maxs)"
},
{
"docstring": "Return True if coord is in this node",
"name": "in_node",
"signature": "def in_node(self, coord)"
},
... | 4 | stack_v2_sparse_classes_30k_train_011285 | Implement the Python class `OctreeNode` described below.
Class description:
Node in an octree
Method signatures and docstrings:
- def __init__(self, mins, maxs): Constructor mins: [x, y, z] lower bound maxs: [x, y, z] (inclusive) upper-bound
- def in_node(self, coord): Return True if coord is in this node
- def nanob... | Implement the Python class `OctreeNode` described below.
Class description:
Node in an octree
Method signatures and docstrings:
- def __init__(self, mins, maxs): Constructor mins: [x, y, z] lower bound maxs: [x, y, z] (inclusive) upper-bound
- def in_node(self, coord): Return True if coord is in this node
- def nanob... | 6671ef8c16a837f697bb3fb91004d1bd892814ba | <|skeleton|>
class OctreeNode:
"""Node in an octree"""
def __init__(self, mins, maxs):
"""Constructor mins: [x, y, z] lower bound maxs: [x, y, z] (inclusive) upper-bound"""
<|body_0|>
def in_node(self, coord):
"""Return True if coord is in this node"""
<|body_1|>
def n... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class OctreeNode:
"""Node in an octree"""
def __init__(self, mins, maxs):
"""Constructor mins: [x, y, z] lower bound maxs: [x, y, z] (inclusive) upper-bound"""
self.mins = mins
self.maxs = maxs
self.children = []
def in_node(self, coord):
"""Return True if coord is ... | the_stack_v2_python_sparse | 2018/day23/challenge.py | ericgreveson/adventofcode | train | 0 |
8c1333ec140f6f4614400c1978dff5049c1b46d5 | [
"result = list()\nfor num in range(1, n + 1):\n devide_by_3 = num % 3 == 0\n devide_by_5 = num % 5 == 0\n if devide_by_5 and devide_by_3:\n result.append('FizzBuzz')\n elif devide_by_3:\n result.append('Fizz')\n elif devide_by_5:\n result.append('Buzz')\n else:\n result... | <|body_start_0|>
result = list()
for num in range(1, n + 1):
devide_by_3 = num % 3 == 0
devide_by_5 = num % 5 == 0
if devide_by_5 and devide_by_3:
result.append('FizzBuzz')
elif devide_by_3:
result.append('Fizz')
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def fizzBuzz(self, n: int) -> List[str]:
""":param n: :return: 模拟法 就像你每次玩 FizzBuzz 那样，你只需要判断这个数是能被 3 整除？ 还是能被 5 整除？ 或者是都能被整除。 初始化一个空的答案列表。 遍历 1 ... N1...N。 对于每个数，判断它能不能同时被 3 和 5 整除，如果可以就把 FizzBuzz 加入答案列表。 如果不行，判断它能不能被 3 整除，如果可以，把 Fizz 加入答案列表。 如果还是不行，判断它能不能被 5 整除，如果可以，把 Buzz 加入答... | stack_v2_sparse_classes_36k_train_033946 | 4,650 | no_license | [
{
"docstring": ":param n: :return: 模拟法 就像你每次玩 FizzBuzz 那样，你只需要判断这个数是能被 3 整除？ 还是能被 5 整除？ 或者是都能被整除。 初始化一个空的答案列表。 遍历 1 ... N1...N。 对于每个数，判断它能不能同时被 3 和 5 整除，如果可以就把 FizzBuzz 加入答案列表。 如果不行，判断它能不能被 3 整除，如果可以，把 Fizz 加入答案列表。 如果还是不行，判断它能不能被 5 整除，如果可以，把 Buzz 加入答案列表。 如果以上都不行，把这个数加入答案列表。 时间击败62.51%，内存击败8.54%",
"name": "f... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def fizzBuzz(self, n: int) -> List[str]: :param n: :return: 模拟法 就像你每次玩 FizzBuzz 那样，你只需要判断这个数是能被 3 整除？ 还是能被 5 整除？ 或者是都能被整除。 初始化一个空的答案列表。 遍历 1 ... N1...N。 对于每个数，判断它能不能同时被 3 和 5 整除，... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def fizzBuzz(self, n: int) -> List[str]: :param n: :return: 模拟法 就像你每次玩 FizzBuzz 那样，你只需要判断这个数是能被 3 整除？ 还是能被 5 整除？ 或者是都能被整除。 初始化一个空的答案列表。 遍历 1 ... N1...N。 对于每个数，判断它能不能同时被 3 和 5 整除，... | 2dc982e690b153c33bc7e27a63604f754a0df90c | <|skeleton|>
class Solution:
def fizzBuzz(self, n: int) -> List[str]:
""":param n: :return: 模拟法 就像你每次玩 FizzBuzz 那样，你只需要判断这个数是能被 3 整除？ 还是能被 5 整除？ 或者是都能被整除。 初始化一个空的答案列表。 遍历 1 ... N1...N。 对于每个数，判断它能不能同时被 3 和 5 整除，如果可以就把 FizzBuzz 加入答案列表。 如果不行，判断它能不能被 3 整除，如果可以，把 Fizz 加入答案列表。 如果还是不行，判断它能不能被 5 整除，如果可以，把 Buzz 加入答... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def fizzBuzz(self, n: int) -> List[str]:
""":param n: :return: 模拟法 就像你每次玩 FizzBuzz 那样，你只需要判断这个数是能被 3 整除？ 还是能被 5 整除？ 或者是都能被整除。 初始化一个空的答案列表。 遍历 1 ... N1...N。 对于每个数，判断它能不能同时被 3 和 5 整除，如果可以就把 FizzBuzz 加入答案列表。 如果不行，判断它能不能被 3 整除，如果可以，把 Fizz 加入答案列表。 如果还是不行，判断它能不能被 5 整除，如果可以，把 Buzz 加入答案列表。 如果以上都不行，把... | the_stack_v2_python_sparse | 412_fizz-buzz.py | 95275059/Algorithm | train | 0 | |
474533da8eead71a122d484bdba9674e9a70323f | [
"if self.action == 'list':\n return super().get_queryset().filter(Q(created_by=self.request.user) | Q(recipient=self.request.user))\nreturn super().get_queryset()",
"referral = self.get_object()\ncontext = {**self.get_serializer_context(), 'check_association_permissions': False, 'referral': referral, 'user': r... | <|body_start_0|>
if self.action == 'list':
return super().get_queryset().filter(Q(created_by=self.request.user) | Q(recipient=self.request.user))
return super().get_queryset()
<|end_body_0|>
<|body_start_1|>
referral = self.get_object()
context = {**self.get_serializer_conte... | Company referral view set. | CompanyReferralViewSet | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CompanyReferralViewSet:
"""Company referral view set."""
def get_queryset(self):
"""Get a queryset for list action that is filtered to the authenticated user's sent and received referrals, otherwise return original queryset."""
<|body_0|>
def complete(self, request, **kw... | stack_v2_sparse_classes_36k_train_033947 | 2,490 | permissive | [
{
"docstring": "Get a queryset for list action that is filtered to the authenticated user's sent and received referrals, otherwise return original queryset.",
"name": "get_queryset",
"signature": "def get_queryset(self)"
},
{
"docstring": "View for completing a referral. Completing a referral in... | 2 | null | Implement the Python class `CompanyReferralViewSet` described below.
Class description:
Company referral view set.
Method signatures and docstrings:
- def get_queryset(self): Get a queryset for list action that is filtered to the authenticated user's sent and received referrals, otherwise return original queryset.
- ... | Implement the Python class `CompanyReferralViewSet` described below.
Class description:
Company referral view set.
Method signatures and docstrings:
- def get_queryset(self): Get a queryset for list action that is filtered to the authenticated user's sent and received referrals, otherwise return original queryset.
- ... | a92faabf73fb93b5bfd94fd465eafc3e29aa6d8e | <|skeleton|>
class CompanyReferralViewSet:
"""Company referral view set."""
def get_queryset(self):
"""Get a queryset for list action that is filtered to the authenticated user's sent and received referrals, otherwise return original queryset."""
<|body_0|>
def complete(self, request, **kw... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CompanyReferralViewSet:
"""Company referral view set."""
def get_queryset(self):
"""Get a queryset for list action that is filtered to the authenticated user's sent and received referrals, otherwise return original queryset."""
if self.action == 'list':
return super().get_quer... | the_stack_v2_python_sparse | datahub/company_referral/views.py | cgsunkel/data-hub-api | train | 0 |
dce1b2c1ab11b2b9157d0cc875eca336de575a86 | [
"QObject.__init__(self, parent)\nself._lias = []\nself.__logger.info('dtype:%s', dtype)\nassert len(fRefs) == len(phases)\nassert len(fRefs) == len(bws)\nself.nRefs = len(fRefs)\nself.nSamples = 0\nself.subtractOffset = subtractOffset\ndecimations = np.asarray(np.power(2, np.round(np.log2(sampleRate / (bws * 40))))... | <|body_start_0|>
QObject.__init__(self, parent)
self._lias = []
self.__logger.info('dtype:%s', dtype)
assert len(fRefs) == len(phases)
assert len(fRefs) == len(bws)
self.nRefs = len(fRefs)
self.nSamples = 0
self.subtractOffset = subtractOffset
deci... | Combines multiple single lock-in instances under one hood. | LockIns | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LockIns:
"""Combines multiple single lock-in instances under one hood."""
def __init__(self, sampleRate, fRefs, phases, bws, lpfOrders, desiredChunkSize, dcBw, dcFilterOrder, subtractOffset=False, parent=None):
"""Initialize a set of lock-ins given the following input parameters: *sa... | stack_v2_sparse_classes_36k_train_033948 | 44,064 | no_license | [
{
"docstring": "Initialize a set of lock-ins given the following input parameters: *sampleRate*: Sample-rate of input data-stream in Hz *fRefs*: Array of lock-in frequencies *phases*: Array of phase offsets *bws*: Array of bandwidths for the lock-in low-pass filters *lpfOrders*: Array of orders of the LPF filte... | 2 | null | Implement the Python class `LockIns` described below.
Class description:
Combines multiple single lock-in instances under one hood.
Method signatures and docstrings:
- def __init__(self, sampleRate, fRefs, phases, bws, lpfOrders, desiredChunkSize, dcBw, dcFilterOrder, subtractOffset=False, parent=None): Initialize a ... | Implement the Python class `LockIns` described below.
Class description:
Combines multiple single lock-in instances under one hood.
Method signatures and docstrings:
- def __init__(self, sampleRate, fRefs, phases, bws, lpfOrders, desiredChunkSize, dcBw, dcFilterOrder, subtractOffset=False, parent=None): Initialize a ... | ffba586a4aec423c3dd126be535ea07d84b10eff | <|skeleton|>
class LockIns:
"""Combines multiple single lock-in instances under one hood."""
def __init__(self, sampleRate, fRefs, phases, bws, lpfOrders, desiredChunkSize, dcBw, dcFilterOrder, subtractOffset=False, parent=None):
"""Initialize a set of lock-ins given the following input parameters: *sa... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LockIns:
"""Combines multiple single lock-in instances under one hood."""
def __init__(self, sampleRate, fRefs, phases, bws, lpfOrders, desiredChunkSize, dcBw, dcFilterOrder, subtractOffset=False, parent=None):
"""Initialize a set of lock-ins given the following input parameters: *sampleRate*: Sa... | the_stack_v2_python_sparse | TES/MultitoneLockin.py | AvirupRoy/research | train | 0 |
b8190db61cd9e2fbe6e99a5bf851bdf8fcd79d2a | [
"cnt = collections.defaultdict(list)\nfor s in strs:\n cnt[tuple(sorted(Counter(s).items()))].append(s)\nreturn [x for x in cnt.values()]",
"d = collections.defaultdict(list)\nfor s in strs:\n key = frozenset(collections.Counter(s).items())\n d[key].append(s)\nreturn list(d.values())"
] | <|body_start_0|>
cnt = collections.defaultdict(list)
for s in strs:
cnt[tuple(sorted(Counter(s).items()))].append(s)
return [x for x in cnt.values()]
<|end_body_0|>
<|body_start_1|>
d = collections.defaultdict(list)
for s in strs:
key = frozenset(collecti... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def groupAnagrams(self, strs: List[str]) -> List[List[str]]:
"""Runtime: 311 ms, faster than 10.81% Memory Usage: 21.6 MB, less than 9.93% 1 <= strs.length <= 10^4 0 <= strs[i].length <= 100 strs[i] consists of lowercase English letters."""
<|body_0|>
def groupAnag... | stack_v2_sparse_classes_36k_train_033949 | 1,599 | permissive | [
{
"docstring": "Runtime: 311 ms, faster than 10.81% Memory Usage: 21.6 MB, less than 9.93% 1 <= strs.length <= 10^4 0 <= strs[i].length <= 100 strs[i] consists of lowercase English letters.",
"name": "groupAnagrams",
"signature": "def groupAnagrams(self, strs: List[str]) -> List[List[str]]"
},
{
... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def groupAnagrams(self, strs: List[str]) -> List[List[str]]: Runtime: 311 ms, faster than 10.81% Memory Usage: 21.6 MB, less than 9.93% 1 <= strs.length <= 10^4 0 <= strs[i].leng... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def groupAnagrams(self, strs: List[str]) -> List[List[str]]: Runtime: 311 ms, faster than 10.81% Memory Usage: 21.6 MB, less than 9.93% 1 <= strs.length <= 10^4 0 <= strs[i].leng... | 4dd1e54d8d08f7e6590bc76abd08ecaacaf775e5 | <|skeleton|>
class Solution:
def groupAnagrams(self, strs: List[str]) -> List[List[str]]:
"""Runtime: 311 ms, faster than 10.81% Memory Usage: 21.6 MB, less than 9.93% 1 <= strs.length <= 10^4 0 <= strs[i].length <= 100 strs[i] consists of lowercase English letters."""
<|body_0|>
def groupAnag... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def groupAnagrams(self, strs: List[str]) -> List[List[str]]:
"""Runtime: 311 ms, faster than 10.81% Memory Usage: 21.6 MB, less than 9.93% 1 <= strs.length <= 10^4 0 <= strs[i].length <= 100 strs[i] consists of lowercase English letters."""
cnt = collections.defaultdict(list)
... | the_stack_v2_python_sparse | src/49-GroupAnagrams.py | Jiezhi/myleetcode | train | 1 | |
032cef86e10c43d8b85dd26658516506164c5ffb | [
"super(CreateIngest, self).__init__('create_ingest_jobs')\nself.create_ingest_type = None\nself.ingest_id = None\nself.scan_id = None\nself.strike_id = None",
"json_dict = {'create_ingest_type': self.create_ingest_type, 'ingest_id': self.ingest_id}\nif self.create_ingest_type == STRIKE_JOB_TYPE:\n json_dict['s... | <|body_start_0|>
super(CreateIngest, self).__init__('create_ingest_jobs')
self.create_ingest_type = None
self.ingest_id = None
self.scan_id = None
self.strike_id = None
<|end_body_0|>
<|body_start_1|>
json_dict = {'create_ingest_type': self.create_ingest_type, 'ingest_id... | Command message that creates the ingest job | CreateIngest | [
"LicenseRef-scancode-free-unknown",
"Apache-2.0",
"LicenseRef-scancode-public-domain"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CreateIngest:
"""Command message that creates the ingest job"""
def __init__(self):
"""Constructor"""
<|body_0|>
def to_json(self):
"""See :meth:`messaging.messages.message.CommandMessage.to_json`"""
<|body_1|>
def from_json(json_dict):
"""Se... | stack_v2_sparse_classes_36k_train_033950 | 5,186 | permissive | [
{
"docstring": "Constructor",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "See :meth:`messaging.messages.message.CommandMessage.to_json`",
"name": "to_json",
"signature": "def to_json(self)"
},
{
"docstring": "See :meth:`messaging.messages.message.Comm... | 4 | stack_v2_sparse_classes_30k_train_017310 | Implement the Python class `CreateIngest` described below.
Class description:
Command message that creates the ingest job
Method signatures and docstrings:
- def __init__(self): Constructor
- def to_json(self): See :meth:`messaging.messages.message.CommandMessage.to_json`
- def from_json(json_dict): See :meth:`messag... | Implement the Python class `CreateIngest` described below.
Class description:
Command message that creates the ingest job
Method signatures and docstrings:
- def __init__(self): Constructor
- def to_json(self): See :meth:`messaging.messages.message.CommandMessage.to_json`
- def from_json(json_dict): See :meth:`messag... | 28618aee07ceed9e4a6eb7b8d0e6f05b31d8fd6b | <|skeleton|>
class CreateIngest:
"""Command message that creates the ingest job"""
def __init__(self):
"""Constructor"""
<|body_0|>
def to_json(self):
"""See :meth:`messaging.messages.message.CommandMessage.to_json`"""
<|body_1|>
def from_json(json_dict):
"""Se... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CreateIngest:
"""Command message that creates the ingest job"""
def __init__(self):
"""Constructor"""
super(CreateIngest, self).__init__('create_ingest_jobs')
self.create_ingest_type = None
self.ingest_id = None
self.scan_id = None
self.strike_id = None
... | the_stack_v2_python_sparse | scale/ingest/messages/create_ingest_jobs.py | kfconsultant/scale | train | 0 |
d67be9963d1ff3e8431591af26382a2c4182ecf2 | [
"res = {}\n\ndef dfs(node, order):\n if not node:\n return\n res[order] = node.val\n dfs(node.left, order * 2 + 1)\n dfs(node.right, order * 2 + 2)\ndfs(root, 0)\nreturn str(res)",
"l = eval(data)\nfor key in l:\n l[key] = TreeNode(l[key])\nfor k in l:\n if k * 2 + 1 in l:\n l[k].l... | <|body_start_0|>
res = {}
def dfs(node, order):
if not node:
return
res[order] = node.val
dfs(node.left, order * 2 + 1)
dfs(node.right, order * 2 + 2)
dfs(root, 0)
return str(res)
<|end_body_0|>
<|body_start_1|>
l ... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|>
<|body_... | stack_v2_sparse_classes_36k_train_033951 | 1,234 | 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:... | 9ae68ada9f63483323cdeaa0f7da3410a0669371 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
res = {}
def dfs(node, order):
if not node:
return
res[order] = node.val
dfs(node.left, order * 2 + 1)
dfs(node.r... | the_stack_v2_python_sparse | problems/0297.serialize-and-deserialize-binary-tree/serialize-and-deserialize-binary-tree.py | tirsott/lc-go | train | 0 | |
4686f6e5d567a321d2c44bd161d17808b55ca3c5 | [
"self.log = logging.getLogger('OpenPixelLED')\nself.opc_client = opc_client\nself.debug = debug\nself.channel = int(channel)\nself.led = int(led)\nself.opc_client.add_pixel(self.channel, self.led)",
"if self.debug:\n self.log.debug('Setting color: %s', color)\nself.opc_client.set_pixel_color(self.channel, self... | <|body_start_0|>
self.log = logging.getLogger('OpenPixelLED')
self.opc_client = opc_client
self.debug = debug
self.channel = int(channel)
self.led = int(led)
self.opc_client.add_pixel(self.channel, self.led)
<|end_body_0|>
<|body_start_1|>
if self.debug:
... | One LED on the openpixel platform. | OpenPixelLED | [
"MIT",
"CC-BY-4.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OpenPixelLED:
"""One LED on the openpixel platform."""
def __init__(self, opc_client, channel, led, debug):
"""Initialise Openpixel LED obeject."""
<|body_0|>
def color(self, color):
"""Set color of the led. Args: color: color tuple"""
<|body_1|>
<|end_s... | stack_v2_sparse_classes_36k_train_033952 | 7,154 | permissive | [
{
"docstring": "Initialise Openpixel LED obeject.",
"name": "__init__",
"signature": "def __init__(self, opc_client, channel, led, debug)"
},
{
"docstring": "Set color of the led. Args: color: color tuple",
"name": "color",
"signature": "def color(self, color)"
}
] | 2 | stack_v2_sparse_classes_30k_val_000846 | Implement the Python class `OpenPixelLED` described below.
Class description:
One LED on the openpixel platform.
Method signatures and docstrings:
- def __init__(self, opc_client, channel, led, debug): Initialise Openpixel LED obeject.
- def color(self, color): Set color of the led. Args: color: color tuple | Implement the Python class `OpenPixelLED` described below.
Class description:
One LED on the openpixel platform.
Method signatures and docstrings:
- def __init__(self, opc_client, channel, led, debug): Initialise Openpixel LED obeject.
- def color(self, color): Set color of the led. Args: color: color tuple
<|skelet... | 00937ab2ff51b1dc668bf465282ffa8ff1eebbd8 | <|skeleton|>
class OpenPixelLED:
"""One LED on the openpixel platform."""
def __init__(self, opc_client, channel, led, debug):
"""Initialise Openpixel LED obeject."""
<|body_0|>
def color(self, color):
"""Set color of the led. Args: color: color tuple"""
<|body_1|>
<|end_s... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class OpenPixelLED:
"""One LED on the openpixel platform."""
def __init__(self, opc_client, channel, led, debug):
"""Initialise Openpixel LED obeject."""
self.log = logging.getLogger('OpenPixelLED')
self.opc_client = opc_client
self.debug = debug
self.channel = int(chann... | the_stack_v2_python_sparse | mpf/platforms/openpixel.py | vgrillot/mpf | train | 0 |
1f07a9714ea50c7b34cb01050863600b811acce4 | [
"super(RationaleNet, self).__init__()\nif arch == 's2vt':\n self.caption_net = S2VTModel(glove_loader, dropout_p, hidden_size, vid_feat_size, max_len)\nelif arch == 's2vt-att':\n self.caption_net = S2VTAttModel(glove_loader, dropout_p, hidden_size, vid_feat_size, max_len)\nelse:\n raise NotImplementedError... | <|body_start_0|>
super(RationaleNet, self).__init__()
if arch == 's2vt':
self.caption_net = S2VTModel(glove_loader, dropout_p, hidden_size, vid_feat_size, max_len)
elif arch == 's2vt-att':
self.caption_net = S2VTAttModel(glove_loader, dropout_p, hidden_size, vid_feat_size... | RationaleNet | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RationaleNet:
def __init__(self, glove_loader, dropout_p, hidden_size, vid_feat_size, max_len, tau, arch, pretrained_base=None):
"""Args: glove_loader: GLoVe embedding loader dropout_p: Dropout probability for intermediate dropout layers hidden_size: Size of the intermediate linear layer... | stack_v2_sparse_classes_36k_train_033953 | 3,887 | no_license | [
{
"docstring": "Args: glove_loader: GLoVe embedding loader dropout_p: Dropout probability for intermediate dropout layers hidden_size: Size of the intermediate linear layers vid_feat_size: Size of the video features max_len: Max length to rollout tau: non-negative scalar temperature arch: video captioning netwo... | 2 | stack_v2_sparse_classes_30k_train_018749 | Implement the Python class `RationaleNet` described below.
Class description:
Implement the RationaleNet class.
Method signatures and docstrings:
- def __init__(self, glove_loader, dropout_p, hidden_size, vid_feat_size, max_len, tau, arch, pretrained_base=None): Args: glove_loader: GLoVe embedding loader dropout_p: D... | Implement the Python class `RationaleNet` described below.
Class description:
Implement the RationaleNet class.
Method signatures and docstrings:
- def __init__(self, glove_loader, dropout_p, hidden_size, vid_feat_size, max_len, tau, arch, pretrained_base=None): Args: glove_loader: GLoVe embedding loader dropout_p: D... | 5f347de39f5583cd043c6f572178da08f7c0de94 | <|skeleton|>
class RationaleNet:
def __init__(self, glove_loader, dropout_p, hidden_size, vid_feat_size, max_len, tau, arch, pretrained_base=None):
"""Args: glove_loader: GLoVe embedding loader dropout_p: Dropout probability for intermediate dropout layers hidden_size: Size of the intermediate linear layer... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RationaleNet:
def __init__(self, glove_loader, dropout_p, hidden_size, vid_feat_size, max_len, tau, arch, pretrained_base=None):
"""Args: glove_loader: GLoVe embedding loader dropout_p: Dropout probability for intermediate dropout layers hidden_size: Size of the intermediate linear layers vid_feat_siz... | the_stack_v2_python_sparse | model/RationaleNet.py | AmmieQi/pytorch-video-caption-rationale | train | 0 | |
c35d85072252f369e3f6de541b829036b21cf77a | [
"attrs = []\nfor attrName in self.orderedAttributes:\n try:\n attrValue = getattr(self.klass, attrName)\n hookClass = self.klass\n except AttributeError:\n attrValue = getattr(self.modelClass, attrName)\n hookClass = self.modelClass\n if isinstance(attrValue, Type):\n if ... | <|body_start_0|>
attrs = []
for attrName in self.orderedAttributes:
try:
attrValue = getattr(self.klass, attrName)
hookClass = self.klass
except AttributeError:
attrValue = getattr(self.modelClass, attrName)
hookClas... | This class gives information about an Appy class. | ClassDescriptor | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ClassDescriptor:
"""This class gives information about an Appy class."""
def getOrderedAppyAttributes(self, condition=None):
"""Returns the appy types for all attributes of this class and parent class(es). If a p_condition is specified, ony Appy types matching the condition will be r... | stack_v2_sparse_classes_36k_train_033954 | 10,177 | no_license | [
{
"docstring": "Returns the appy types for all attributes of this class and parent class(es). If a p_condition is specified, ony Appy types matching the condition will be returned. p_condition must be a string containing an expression that will be evaluated with, in its context, \"self\" being this ClassDescrip... | 4 | stack_v2_sparse_classes_30k_train_006618 | Implement the Python class `ClassDescriptor` described below.
Class description:
This class gives information about an Appy class.
Method signatures and docstrings:
- def getOrderedAppyAttributes(self, condition=None): Returns the appy types for all attributes of this class and parent class(es). If a p_condition is s... | Implement the Python class `ClassDescriptor` described below.
Class description:
This class gives information about an Appy class.
Method signatures and docstrings:
- def getOrderedAppyAttributes(self, condition=None): Returns the appy types for all attributes of this class and parent class(es). If a p_condition is s... | 866b33c1af866524eb2a3a7bde896c6836fc69f9 | <|skeleton|>
class ClassDescriptor:
"""This class gives information about an Appy class."""
def getOrderedAppyAttributes(self, condition=None):
"""Returns the appy types for all attributes of this class and parent class(es). If a p_condition is specified, ony Appy types matching the condition will be r... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ClassDescriptor:
"""This class gives information about an Appy class."""
def getOrderedAppyAttributes(self, condition=None):
"""Returns the appy types for all attributes of this class and parent class(es). If a p_condition is specified, ony Appy types matching the condition will be returned. p_co... | the_stack_v2_python_sparse | appy/gen/descriptors.py | thefrolov/open-drug-store | train | 0 |
876d1d26635d85f2f94a706ea78757ce80e3824d | [
"if 'even' == 'odd':\n arrayextension = 5\nelse:\n arrayextension = 0\narraylength = 96 + arrayextension\nMaxVal = 255\nMinVal = 0\nself.gentest = bytes([MaxVal // 2] * arraylength)",
"with self.assertRaises(TypeError):\n result = bytesfunc.bmin(1, nosimd=True)\nwith self.assertRaises(TypeError):\n re... | <|body_start_0|>
if 'even' == 'odd':
arrayextension = 5
else:
arrayextension = 0
arraylength = 96 + arrayextension
MaxVal = 255
MinVal = 0
self.gentest = bytes([MaxVal // 2] * arraylength)
<|end_body_0|>
<|body_start_1|>
with self.assertRa... | Test bmin for basic parameter tests. op_template_params | bmin_parameter_even_arraysize_without_simd_bytes | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class bmin_parameter_even_arraysize_without_simd_bytes:
"""Test bmin for basic parameter tests. op_template_params"""
def setUp(self):
"""Initialise."""
<|body_0|>
def test_bmin_param_function_01(self):
"""Test bmin - Sequence type bytes. Test invalid parameter type ev... | stack_v2_sparse_classes_36k_train_033955 | 49,998 | permissive | [
{
"docstring": "Initialise.",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "Test bmin - Sequence type bytes. Test invalid parameter type even length array without SIMD.",
"name": "test_bmin_param_function_01",
"signature": "def test_bmin_param_function_01(self)"
},... | 5 | stack_v2_sparse_classes_30k_train_006922 | Implement the Python class `bmin_parameter_even_arraysize_without_simd_bytes` described below.
Class description:
Test bmin for basic parameter tests. op_template_params
Method signatures and docstrings:
- def setUp(self): Initialise.
- def test_bmin_param_function_01(self): Test bmin - Sequence type bytes. Test inva... | Implement the Python class `bmin_parameter_even_arraysize_without_simd_bytes` described below.
Class description:
Test bmin for basic parameter tests. op_template_params
Method signatures and docstrings:
- def setUp(self): Initialise.
- def test_bmin_param_function_01(self): Test bmin - Sequence type bytes. Test inva... | 28fe0705fc59b0646a4d44e539c919173e8e8b99 | <|skeleton|>
class bmin_parameter_even_arraysize_without_simd_bytes:
"""Test bmin for basic parameter tests. op_template_params"""
def setUp(self):
"""Initialise."""
<|body_0|>
def test_bmin_param_function_01(self):
"""Test bmin - Sequence type bytes. Test invalid parameter type ev... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class bmin_parameter_even_arraysize_without_simd_bytes:
"""Test bmin for basic parameter tests. op_template_params"""
def setUp(self):
"""Initialise."""
if 'even' == 'odd':
arrayextension = 5
else:
arrayextension = 0
arraylength = 96 + arrayextension
... | the_stack_v2_python_sparse | unittest/test_bmin.py | m1griffin/bytesfunc | train | 2 |
88411dd749eb56e49cb92649bcc4932959a13d9f | [
"period_obj = self.pool.get('account.period')\nperiod_ids = period_obj.next(cr, uid, start_period, periods_nbr, context=context)\nif not period_ids:\n return None\nreturn period_obj.browse(cr, uid, period_ids, context=context)",
"period_obj = self.pool.get('account.period')\nids = period_obj.search(cr, uid, [(... | <|body_start_0|>
period_obj = self.pool.get('account.period')
period_ids = period_obj.next(cr, uid, start_period, periods_nbr, context=context)
if not period_ids:
return None
return period_obj.browse(cr, uid, period_ids, context=context)
<|end_body_0|>
<|body_start_1|>
... | add new methods to the account_period object | account_period | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class account_period:
"""add new methods to the account_period object"""
def _get_next_periods(self, cr, uid, start_period, periods_nbr, context=None):
"""return a list of browse record periods that follow the "start_period" for the given version. periods_nbr is the limit of periods to ret... | stack_v2_sparse_classes_36k_train_033956 | 2,473 | no_license | [
{
"docstring": "return a list of browse record periods that follow the \"start_period\" for the given version. periods_nbr is the limit of periods to return",
"name": "_get_next_periods",
"signature": "def _get_next_periods(self, cr, uid, start_period, periods_nbr, context=None)"
},
{
"docstring... | 2 | null | Implement the Python class `account_period` described below.
Class description:
add new methods to the account_period object
Method signatures and docstrings:
- def _get_next_periods(self, cr, uid, start_period, periods_nbr, context=None): return a list of browse record periods that follow the "start_period" for the ... | Implement the Python class `account_period` described below.
Class description:
add new methods to the account_period object
Method signatures and docstrings:
- def _get_next_periods(self, cr, uid, start_period, periods_nbr, context=None): return a list of browse record periods that follow the "start_period" for the ... | 01c8294e969cce818a33fd06682560e0344c217c | <|skeleton|>
class account_period:
"""add new methods to the account_period object"""
def _get_next_periods(self, cr, uid, start_period, periods_nbr, context=None):
"""return a list of browse record periods that follow the "start_period" for the given version. periods_nbr is the limit of periods to ret... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class account_period:
"""add new methods to the account_period object"""
def _get_next_periods(self, cr, uid, start_period, periods_nbr, context=None):
"""return a list of browse record periods that follow the "start_period" for the given version. periods_nbr is the limit of periods to return"""
... | the_stack_v2_python_sparse | Varios/alimentacion/__unported__/budget/account.py | ELNOGAL/GALIPAT_LUGO | train | 0 |
735163253e9db66f44247a3ce6ca1a30873b3af4 | [
"order_id = request.GET.get('order_id')\ntry:\n OrderInfo.objects.get(order_id=order_id, user=request.user)\nexcept OrderInfo.DoesNotExist:\n return http.HttpResponseNotFound('订单不存在')\ntry:\n uncomment_goods = OrderGoods.objects.filter(order_id=order_id, is_commented=False)\nexcept Exception:\n return h... | <|body_start_0|>
order_id = request.GET.get('order_id')
try:
OrderInfo.objects.get(order_id=order_id, user=request.user)
except OrderInfo.DoesNotExist:
return http.HttpResponseNotFound('订单不存在')
try:
uncomment_goods = OrderGoods.objects.filter(order_id=... | 订单商品评价 | OrderCommentView | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OrderCommentView:
"""订单商品评价"""
def get(self, request):
"""展示商品评价页面"""
<|body_0|>
def post(self, request):
"""评价订单商品"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
order_id = request.GET.get('order_id')
try:
OrderInfo.objects... | stack_v2_sparse_classes_36k_train_033957 | 13,412 | permissive | [
{
"docstring": "展示商品评价页面",
"name": "get",
"signature": "def get(self, request)"
},
{
"docstring": "评价订单商品",
"name": "post",
"signature": "def post(self, request)"
}
] | 2 | stack_v2_sparse_classes_30k_train_009712 | Implement the Python class `OrderCommentView` described below.
Class description:
订单商品评价
Method signatures and docstrings:
- def get(self, request): 展示商品评价页面
- def post(self, request): 评价订单商品 | Implement the Python class `OrderCommentView` described below.
Class description:
订单商品评价
Method signatures and docstrings:
- def get(self, request): 展示商品评价页面
- def post(self, request): 评价订单商品
<|skeleton|>
class OrderCommentView:
"""订单商品评价"""
def get(self, request):
"""展示商品评价页面"""
<|body_0|>
... | 2434231795b3319dfda60b19af18442ee5f6fa73 | <|skeleton|>
class OrderCommentView:
"""订单商品评价"""
def get(self, request):
"""展示商品评价页面"""
<|body_0|>
def post(self, request):
"""评价订单商品"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class OrderCommentView:
"""订单商品评价"""
def get(self, request):
"""展示商品评价页面"""
order_id = request.GET.get('order_id')
try:
OrderInfo.objects.get(order_id=order_id, user=request.user)
except OrderInfo.DoesNotExist:
return http.HttpResponseNotFound('订单不存在')
... | the_stack_v2_python_sparse | meiduo_project/meiduo_mall/meiduo_mall/apps/orders/views.py | xlztongxue/meiduoshangcheng | train | 0 |
118e116620c4c28e2f77cc9f0c520ee3c8e82320 | [
"try:\n user_id = EasyUUID(user_id)\nexcept ValueError:\n logger.warn(f'Invalid ACTOR UUID f{user_id}')\n data = user_schema.copy()\n data['id'] = str(user_id)\n data['fullname'] = ''\n return data\nif user_id == SystemUser.id:\n user = SystemUser\nelse:\n user = UserProfile.get(user_id)\nre... | <|body_start_0|>
try:
user_id = EasyUUID(user_id)
except ValueError:
logger.warn(f'Invalid ACTOR UUID f{user_id}')
data = user_schema.copy()
data['id'] = str(user_id)
data['fullname'] = ''
return data
if user_id == SystemUse... | Leica implementation of the IUserProfileQuery interface. | LeicaUserProfileQuery | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LeicaUserProfileQuery:
"""Leica implementation of the IUserProfileQuery interface."""
def get_data(self, user_id: AnyUUID) -> dict:
"""Get a map with user data."""
<|body_0|>
def get_all_data(self, principal_ids: list) -> list:
"""Get all user data from a list of... | stack_v2_sparse_classes_36k_train_033958 | 2,844 | no_license | [
{
"docstring": "Get a map with user data.",
"name": "get_data",
"signature": "def get_data(self, user_id: AnyUUID) -> dict"
},
{
"docstring": "Get all user data from a list of principals.",
"name": "get_all_data",
"signature": "def get_all_data(self, principal_ids: list) -> list"
},
... | 4 | stack_v2_sparse_classes_30k_train_009806 | Implement the Python class `LeicaUserProfileQuery` described below.
Class description:
Leica implementation of the IUserProfileQuery interface.
Method signatures and docstrings:
- def get_data(self, user_id: AnyUUID) -> dict: Get a map with user data.
- def get_all_data(self, principal_ids: list) -> list: Get all use... | Implement the Python class `LeicaUserProfileQuery` described below.
Class description:
Leica implementation of the IUserProfileQuery interface.
Method signatures and docstrings:
- def get_data(self, user_id: AnyUUID) -> dict: Get a map with user data.
- def get_all_data(self, principal_ids: list) -> list: Get all use... | e85c0ba0992bccb80878e89ec791ee64754646b0 | <|skeleton|>
class LeicaUserProfileQuery:
"""Leica implementation of the IUserProfileQuery interface."""
def get_data(self, user_id: AnyUUID) -> dict:
"""Get a map with user data."""
<|body_0|>
def get_all_data(self, principal_ids: list) -> list:
"""Get all user data from a list of... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LeicaUserProfileQuery:
"""Leica implementation of the IUserProfileQuery interface."""
def get_data(self, user_id: AnyUUID) -> dict:
"""Get a map with user data."""
try:
user_id = EasyUUID(user_id)
except ValueError:
logger.warn(f'Invalid ACTOR UUID f{user_i... | the_stack_v2_python_sparse | src/briefy/leica/utilities/userprofile.py | BriefyHQ/briefy.leica | train | 0 |
a2f874b9f44153708444e521229fb1d1d0639a71 | [
"self.oldStep = None\nself.oldGradient = None\nself.coeff_function = coeff_function",
"newGradient = function.gradient(point)\nif 'direction' in state:\n oldGradient = state['gradient']\n oldStep = state['direction']\n if all(newGradient == oldGradient):\n coeff = 0\n step = -newGradient\n ... | <|body_start_0|>
self.oldStep = None
self.oldGradient = None
self.coeff_function = coeff_function
<|end_body_0|>
<|body_start_1|>
newGradient = function.gradient(point)
if 'direction' in state:
oldGradient = state['gradient']
oldStep = state['direction']
... | The basic conjugate gradient step | ConjugateGradientStep | [
"BSD-3-Clause",
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ConjugateGradientStep:
"""The basic conjugate gradient step"""
def __init__(self, coeff_function):
"""Initialization of the gradient step - coeff_function is the function that will compute the appropriate coefficient"""
<|body_0|>
def __call__(self, function, point, stat... | stack_v2_sparse_classes_36k_train_033959 | 3,963 | permissive | [
{
"docstring": "Initialization of the gradient step - coeff_function is the function that will compute the appropriate coefficient",
"name": "__init__",
"signature": "def __init__(self, coeff_function)"
},
{
"docstring": "Computes a gradient step based on a function and a point",
"name": "__... | 2 | null | Implement the Python class `ConjugateGradientStep` described below.
Class description:
The basic conjugate gradient step
Method signatures and docstrings:
- def __init__(self, coeff_function): Initialization of the gradient step - coeff_function is the function that will compute the appropriate coefficient
- def __ca... | Implement the Python class `ConjugateGradientStep` described below.
Class description:
The basic conjugate gradient step
Method signatures and docstrings:
- def __init__(self, coeff_function): Initialization of the gradient step - coeff_function is the function that will compute the appropriate coefficient
- def __ca... | 3d298e908ff55340cd3612078508be0c791f63a8 | <|skeleton|>
class ConjugateGradientStep:
"""The basic conjugate gradient step"""
def __init__(self, coeff_function):
"""Initialization of the gradient step - coeff_function is the function that will compute the appropriate coefficient"""
<|body_0|>
def __call__(self, function, point, stat... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ConjugateGradientStep:
"""The basic conjugate gradient step"""
def __init__(self, coeff_function):
"""Initialization of the gradient step - coeff_function is the function that will compute the appropriate coefficient"""
self.oldStep = None
self.oldGradient = None
self.coef... | the_stack_v2_python_sparse | PyDSTool/Toolbox/optimizers/step/conjugate_gradient_step.py | mdlama/pydstool | train | 2 |
f1b1fb46dae71dca67c8c0bedd81a6b0fd1922ab | [
"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... | The DLP API is a service that allows clients to detect the presence of Personally Identifiable Information (PII) and other privacy-sensitive data in user-supplied, unstructured data streams, like text blocks or images. The service also includes methods for sensitive data redaction and scheduling of data scans on Google... | DlpServiceServicer | [
"BSD-3-Clause",
"LicenseRef-scancode-unknown-license-reference",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DlpServiceServicer:
"""The DLP API is a service that allows clients to detect the presence of Personally Identifiable Information (PII) and other privacy-sensitive data in user-supplied, unstructured data streams, like text blocks or images. The service also includes methods for sensitive data re... | stack_v2_sparse_classes_36k_train_033960 | 9,424 | permissive | [
{
"docstring": "Find potentially sensitive info in a list of strings. This method has limits on input size, processing time, and output size.",
"name": "InspectContent",
"signature": "def InspectContent(self, request, context)"
},
{
"docstring": "Redact potentially sensitive info from a list of ... | 6 | stack_v2_sparse_classes_30k_train_007374 | Implement the Python class `DlpServiceServicer` described below.
Class description:
The DLP API is a service that allows clients to detect the presence of Personally Identifiable Information (PII) and other privacy-sensitive data in user-supplied, unstructured data streams, like text blocks or images. The service also... | Implement the Python class `DlpServiceServicer` described below.
Class description:
The DLP API is a service that allows clients to detect the presence of Personally Identifiable Information (PII) and other privacy-sensitive data in user-supplied, unstructured data streams, like text blocks or images. The service also... | 86977c0e2e97011359b619c88db47168181908ea | <|skeleton|>
class DlpServiceServicer:
"""The DLP API is a service that allows clients to detect the presence of Personally Identifiable Information (PII) and other privacy-sensitive data in user-supplied, unstructured data streams, like text blocks or images. The service also includes methods for sensitive data re... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DlpServiceServicer:
"""The DLP API is a service that allows clients to detect the presence of Personally Identifiable Information (PII) and other privacy-sensitive data in user-supplied, unstructured data streams, like text blocks or images. The service also includes methods for sensitive data redaction and s... | the_stack_v2_python_sparse | generated/python/proto-google-cloud-dlp-v2beta1/google/cloud/proto/privacy/dlp/v2beta1/dlp_pb2_grpc.py | QPC-github/api-client-staging | train | 1 |
c271a343c58153dda279e8a017bab3a959ced606 | [
"self.public_ip = public_ip\nself.uplink = uplink\nself.port_rules = port_rules",
"if dictionary is None:\n return None\npublic_ip = dictionary.get('publicIp')\nuplink = dictionary.get('uplink')\nport_rules = None\nif dictionary.get('portRules') != None:\n port_rules = list()\n for structure in dictionar... | <|body_start_0|>
self.public_ip = public_ip
self.uplink = uplink
self.port_rules = port_rules
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
public_ip = dictionary.get('publicIp')
uplink = dictionary.get('uplink')
port_rules = None... | Implementation of the 'Rule7' model. TODO: type model description here. Attributes: public_ip (string): The IP address that will be used to access the internal resource from the WAN uplink (Uplink1Enum): The physical WAN interface on which the traffic will arrive ('internet1' or, if available, 'internet2') port_rules (... | Rule7Model | [
"MIT",
"Python-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Rule7Model:
"""Implementation of the 'Rule7' model. TODO: type model description here. Attributes: public_ip (string): The IP address that will be used to access the internal resource from the WAN uplink (Uplink1Enum): The physical WAN interface on which the traffic will arrive ('internet1' or, i... | stack_v2_sparse_classes_36k_train_033961 | 2,338 | permissive | [
{
"docstring": "Constructor for the Rule7Model class",
"name": "__init__",
"signature": "def __init__(self, public_ip=None, uplink=None, port_rules=None)"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: dictionary (dictionary): A dictionary representation of the obje... | 2 | null | Implement the Python class `Rule7Model` described below.
Class description:
Implementation of the 'Rule7' model. TODO: type model description here. Attributes: public_ip (string): The IP address that will be used to access the internal resource from the WAN uplink (Uplink1Enum): The physical WAN interface on which the... | Implement the Python class `Rule7Model` described below.
Class description:
Implementation of the 'Rule7' model. TODO: type model description here. Attributes: public_ip (string): The IP address that will be used to access the internal resource from the WAN uplink (Uplink1Enum): The physical WAN interface on which the... | 9894089eb013318243ae48869cc5130eb37f80c0 | <|skeleton|>
class Rule7Model:
"""Implementation of the 'Rule7' model. TODO: type model description here. Attributes: public_ip (string): The IP address that will be used to access the internal resource from the WAN uplink (Uplink1Enum): The physical WAN interface on which the traffic will arrive ('internet1' or, i... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Rule7Model:
"""Implementation of the 'Rule7' model. TODO: type model description here. Attributes: public_ip (string): The IP address that will be used to access the internal resource from the WAN uplink (Uplink1Enum): The physical WAN interface on which the traffic will arrive ('internet1' or, if available, ... | the_stack_v2_python_sparse | meraki_sdk/models/rule_7_model.py | RaulCatalano/meraki-python-sdk | train | 1 |
d1128666882ce426356e2a13d4c0c5305c48c5f7 | [
"self.od = OrderedDict()\nself.total = 0\nself.last = 300",
"if timestamp < self.last - 299:\n return\nif timestamp > self.last:\n self.last = timestamp\n for t in self.od:\n if t < self.last - 299:\n self.total -= self.od[t]\n del self.od[t]\n else:\n break... | <|body_start_0|>
self.od = OrderedDict()
self.total = 0
self.last = 300
<|end_body_0|>
<|body_start_1|>
if timestamp < self.last - 299:
return
if timestamp > self.last:
self.last = timestamp
for t in self.od:
if t < self.last -... | HitCounter | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HitCounter:
def __init__(self):
"""Initialize your data structure here."""
<|body_0|>
def hit(self, timestamp):
"""Record a hit. @param timestamp - The current timestamp (in seconds granularity). :type timestamp: int :rtype: void"""
<|body_1|>
def getHit... | stack_v2_sparse_classes_36k_train_033962 | 1,677 | no_license | [
{
"docstring": "Initialize your data structure here.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Record a hit. @param timestamp - The current timestamp (in seconds granularity). :type timestamp: int :rtype: void",
"name": "hit",
"signature": "def hit(self, ... | 3 | stack_v2_sparse_classes_30k_train_000810 | Implement the Python class `HitCounter` described below.
Class description:
Implement the HitCounter class.
Method signatures and docstrings:
- def __init__(self): Initialize your data structure here.
- def hit(self, timestamp): Record a hit. @param timestamp - The current timestamp (in seconds granularity). :type ti... | Implement the Python class `HitCounter` described below.
Class description:
Implement the HitCounter class.
Method signatures and docstrings:
- def __init__(self): Initialize your data structure here.
- def hit(self, timestamp): Record a hit. @param timestamp - The current timestamp (in seconds granularity). :type ti... | 70f16a872cb203f77eeddb812e734ad1d46df79d | <|skeleton|>
class HitCounter:
def __init__(self):
"""Initialize your data structure here."""
<|body_0|>
def hit(self, timestamp):
"""Record a hit. @param timestamp - The current timestamp (in seconds granularity). :type timestamp: int :rtype: void"""
<|body_1|>
def getHit... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class HitCounter:
def __init__(self):
"""Initialize your data structure here."""
self.od = OrderedDict()
self.total = 0
self.last = 300
def hit(self, timestamp):
"""Record a hit. @param timestamp - The current timestamp (in seconds granularity). :type timestamp: int :rty... | the_stack_v2_python_sparse | design-hit-counter.py | cannium/leetcode | train | 0 | |
a4e34f5d5a020f5b26d062a7207d2e4712082278 | [
"if HAS_ISBD and ISelectableBrowserDefault.providedBy(target):\n return target.getLayout()\nelse:\n view = target.getTypeInfo().getActionById('view') or 'base_view'\n if view == 'view':\n view = target.portal_type.lower() + '_view'\n return view",
"data = [HelpCenterReferenceManualPage.Searchab... | <|body_start_0|>
if HAS_ISBD and ISelectableBrowserDefault.providedBy(target):
return target.getLayout()
else:
view = target.getTypeInfo().getActionById('view') or 'base_view'
if view == 'view':
view = target.portal_type.lower() + '_view'
r... | Represents a page that can contain Tabbed Pages. | CompositePage | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CompositePage:
"""Represents a page that can contain Tabbed Pages."""
def getTargetObjectLayout(self, target):
"""Returns target object 'view' action page template"""
<|body_0|>
def SearchableText(self):
"""Append references' searchable fields."""
<|body_... | stack_v2_sparse_classes_36k_train_033963 | 6,158 | no_license | [
{
"docstring": "Returns target object 'view' action page template",
"name": "getTargetObjectLayout",
"signature": "def getTargetObjectLayout(self, target)"
},
{
"docstring": "Append references' searchable fields.",
"name": "SearchableText",
"signature": "def SearchableText(self)"
},
... | 3 | null | Implement the Python class `CompositePage` described below.
Class description:
Represents a page that can contain Tabbed Pages.
Method signatures and docstrings:
- def getTargetObjectLayout(self, target): Returns target object 'view' action page template
- def SearchableText(self): Append references' searchable field... | Implement the Python class `CompositePage` described below.
Class description:
Represents a page that can contain Tabbed Pages.
Method signatures and docstrings:
- def getTargetObjectLayout(self, target): Returns target object 'view' action page template
- def SearchableText(self): Append references' searchable field... | 5cf0ba31dfbff8d2c1b4aa8ab6f69c7a0ae9870d | <|skeleton|>
class CompositePage:
"""Represents a page that can contain Tabbed Pages."""
def getTargetObjectLayout(self, target):
"""Returns target object 'view' action page template"""
<|body_0|>
def SearchableText(self):
"""Append references' searchable fields."""
<|body_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CompositePage:
"""Represents a page that can contain Tabbed Pages."""
def getTargetObjectLayout(self, target):
"""Returns target object 'view' action page template"""
if HAS_ISBD and ISelectableBrowserDefault.providedBy(target):
return target.getLayout()
else:
... | the_stack_v2_python_sparse | plone.products/BungeniHelpCenter/branches/plone4/content/CompositePage.py | malangalanga/bungeni-portal | train | 0 |
aae29f00df7c467d5a99deb3678440a9c69c090c | [
"super(SurnameClassifier, self).__init__()\nself.emb = nn.Embedding(num_embeddings=num_embeddings, embedding_dim=embedding_size, padding_idx=padding_idx)\nself.rnn = ElmanRNN(input_size=embedding_size, hidden_size=rnn_hidden_size, batch_first=batch_first)\nself.fc1 = nn.Linear(in_features=rnn_hidden_size, out_featu... | <|body_start_0|>
super(SurnameClassifier, self).__init__()
self.emb = nn.Embedding(num_embeddings=num_embeddings, embedding_dim=embedding_size, padding_idx=padding_idx)
self.rnn = ElmanRNN(input_size=embedding_size, hidden_size=rnn_hidden_size, batch_first=batch_first)
self.fc1 = nn.Line... | A Classifier with an RNN to extract features and an MLP to classify | SurnameClassifier | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SurnameClassifier:
"""A Classifier with an RNN to extract features and an MLP to classify"""
def __init__(self, embedding_size, num_embeddings, num_classes, rnn_hidden_size, batch_first=True, padding_idx=0):
"""Args: embedding_size (int): The size of the character embeddings num_embe... | stack_v2_sparse_classes_36k_train_033964 | 28,260 | no_license | [
{
"docstring": "Args: embedding_size (int): The size of the character embeddings num_embeddings (int): The number of characters to embed num_classes (int): The size of the prediction vector Note: the number of nationalities rnn_hidden_size (int): The size of the RNN's hidden state batch_first (bool): Informs wh... | 2 | stack_v2_sparse_classes_30k_train_018101 | Implement the Python class `SurnameClassifier` described below.
Class description:
A Classifier with an RNN to extract features and an MLP to classify
Method signatures and docstrings:
- def __init__(self, embedding_size, num_embeddings, num_classes, rnn_hidden_size, batch_first=True, padding_idx=0): Args: embedding_... | Implement the Python class `SurnameClassifier` described below.
Class description:
A Classifier with an RNN to extract features and an MLP to classify
Method signatures and docstrings:
- def __init__(self, embedding_size, num_embeddings, num_classes, rnn_hidden_size, batch_first=True, padding_idx=0): Args: embedding_... | ba8feae92c875c1e65ad5a25a2363393ab0daf79 | <|skeleton|>
class SurnameClassifier:
"""A Classifier with an RNN to extract features and an MLP to classify"""
def __init__(self, embedding_size, num_embeddings, num_classes, rnn_hidden_size, batch_first=True, padding_idx=0):
"""Args: embedding_size (int): The size of the character embeddings num_embe... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SurnameClassifier:
"""A Classifier with an RNN to extract features and an MLP to classify"""
def __init__(self, embedding_size, num_embeddings, num_classes, rnn_hidden_size, batch_first=True, padding_idx=0):
"""Args: embedding_size (int): The size of the character embeddings num_embeddings (int):... | the_stack_v2_python_sparse | chapter_6/elman_rnn.py | kerenskybr/nlp_pytorch_book | train | 0 |
0cf0b80f9605081cd12d77fd86260304c714246d | [
"sp = ' ' if opt_sp and self.name in COMPOUND else ''\nif self.elem_type is None:\n return CPP_TYPE[self.name] + sp\nreturn CPP_TYPE[self.name] % self.elem_type.cppType(opt_sp=True) + sp",
"type = self.cppType()\nif self.name in BY_CREF:\n type += ' const&'\nreturn type",
"cpp_type = self.cppType()\nif se... | <|body_start_0|>
sp = ' ' if opt_sp and self.name in COMPOUND else ''
if self.elem_type is None:
return CPP_TYPE[self.name] + sp
return CPP_TYPE[self.name] % self.elem_type.cppType(opt_sp=True) + sp
<|end_body_0|>
<|body_start_1|>
type = self.cppType()
if self.name i... | IDLType | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IDLType:
def cppType(self, opt_sp=False):
"""Gets the C++ type declaration of this IDL type. The opt_sp puts a trailing space after a closing angle bracket if the type itself ends with a closing angle bracket."""
<|body_0|>
def cppArgType(self):
"""Gets the C++ type ... | stack_v2_sparse_classes_36k_train_033965 | 15,282 | no_license | [
{
"docstring": "Gets the C++ type declaration of this IDL type. The opt_sp puts a trailing space after a closing angle bracket if the type itself ends with a closing angle bracket.",
"name": "cppType",
"signature": "def cppType(self, opt_sp=False)"
},
{
"docstring": "Gets the C++ type declaratio... | 4 | stack_v2_sparse_classes_30k_train_021373 | Implement the Python class `IDLType` described below.
Class description:
Implement the IDLType class.
Method signatures and docstrings:
- def cppType(self, opt_sp=False): Gets the C++ type declaration of this IDL type. The opt_sp puts a trailing space after a closing angle bracket if the type itself ends with a closi... | Implement the Python class `IDLType` described below.
Class description:
Implement the IDLType class.
Method signatures and docstrings:
- def cppType(self, opt_sp=False): Gets the C++ type declaration of this IDL type. The opt_sp puts a trailing space after a closing angle bracket if the type itself ends with a closi... | ad831300367843058ee7c01a82e745f026e1fcbf | <|skeleton|>
class IDLType:
def cppType(self, opt_sp=False):
"""Gets the C++ type declaration of this IDL type. The opt_sp puts a trailing space after a closing angle bracket if the type itself ends with a closing angle bracket."""
<|body_0|>
def cppArgType(self):
"""Gets the C++ type ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class IDLType:
def cppType(self, opt_sp=False):
"""Gets the C++ type declaration of this IDL type. The opt_sp puts a trailing space after a closing angle bracket if the type itself ends with a closing angle bracket."""
sp = ' ' if opt_sp and self.name in COMPOUND else ''
if self.elem_type is... | the_stack_v2_python_sparse | python/idl_cpp_types.py | ogoodman/serf | train | 1 | |
ba0588867ab05212f57c28474e4533677104f219 | [
"targ = self.caller.search(self.lhs)\nif not targ:\n return\nself.msg('Modifiers on %s: %s' % (targ, ', '.join((str(ob) for ob in targ.modifiers.all()))))",
"from server.utils.arx_utils import dict_from_choices_field\nchoices = dict_from_choices_field(RollModifier, 'CHECK_CHOICES')\ntry:\n value = int(self.... | <|body_start_0|>
targ = self.caller.search(self.lhs)
if not targ:
return
self.msg('Modifiers on %s: %s' % (targ, ', '.join((str(ob) for ob in targ.modifiers.all()))))
<|end_body_0|>
<|body_start_1|>
from server.utils.arx_utils import dict_from_choices_field
choices =... | Adds modifiers to objects Usage: @modifiers <object> @modifiers/search <tag name> @modifiers/targetmod <object>=<value>,<tag name>,check @modifiers/usermod <object>=<value>,<tag name>,check Sets modifiers for the most common usages - an object providing a bonus against those with a particular tag (targetmod) for a give... | CmdModifiers | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CmdModifiers:
"""Adds modifiers to objects Usage: @modifiers <object> @modifiers/search <tag name> @modifiers/targetmod <object>=<value>,<tag name>,check @modifiers/usermod <object>=<value>,<tag name>,check Sets modifiers for the most common usages - an object providing a bonus against those with... | stack_v2_sparse_classes_36k_train_033966 | 7,392 | permissive | [
{
"docstring": "Displays modifiers on target",
"name": "display_mods",
"signature": "def display_mods(self)"
},
{
"docstring": "Adds a modifier to target",
"name": "add_mod",
"signature": "def add_mod(self)"
},
{
"docstring": "Searches for modifiers for/against a given tag",
... | 4 | null | Implement the Python class `CmdModifiers` described below.
Class description:
Adds modifiers to objects Usage: @modifiers <object> @modifiers/search <tag name> @modifiers/targetmod <object>=<value>,<tag name>,check @modifiers/usermod <object>=<value>,<tag name>,check Sets modifiers for the most common usages - an obje... | Implement the Python class `CmdModifiers` described below.
Class description:
Adds modifiers to objects Usage: @modifiers <object> @modifiers/search <tag name> @modifiers/targetmod <object>=<value>,<tag name>,check @modifiers/usermod <object>=<value>,<tag name>,check Sets modifiers for the most common usages - an obje... | 363a1f14fd1a640580a4bf4486a1afe776757557 | <|skeleton|>
class CmdModifiers:
"""Adds modifiers to objects Usage: @modifiers <object> @modifiers/search <tag name> @modifiers/targetmod <object>=<value>,<tag name>,check @modifiers/usermod <object>=<value>,<tag name>,check Sets modifiers for the most common usages - an object providing a bonus against those with... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CmdModifiers:
"""Adds modifiers to objects Usage: @modifiers <object> @modifiers/search <tag name> @modifiers/targetmod <object>=<value>,<tag name>,check @modifiers/usermod <object>=<value>,<tag name>,check Sets modifiers for the most common usages - an object providing a bonus against those with a particular... | the_stack_v2_python_sparse | world/conditions/condition_commands.py | Arx-Game/arxcode | train | 52 |
ba8f4b5e2c67d01c55534a2a6b80d56f284e47c6 | [
"self.capacity = capacity\nself.valueDict = {}\nself.countDict = {}\nself.frequencyDict = {}\nself.frequencyDict[1] = OrderedDict()\nself.min = -1",
"if key not in self.valueDict:\n return -1\ncount = self.countDict[key]\nself.countDict[key] = count + 1\ndel self.frequencyDict[count][key]\nif count == self.min... | <|body_start_0|>
self.capacity = capacity
self.valueDict = {}
self.countDict = {}
self.frequencyDict = {}
self.frequencyDict[1] = OrderedDict()
self.min = -1
<|end_body_0|>
<|body_start_1|>
if key not in self.valueDict:
return -1
count = self.... | 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: void"""
<|body_2|>
<|end_s... | stack_v2_sparse_classes_36k_train_033967 | 3,706 | 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: void",
"name": "pu... | 3 | null | 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: void | 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: void
<|sk... | 7a459e9742958e63be8886874904e5ab2489411a | <|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: void"""
<|body_2|>
<|end_s... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LFUCache:
def __init__(self, capacity):
""":type capacity: int"""
self.capacity = capacity
self.valueDict = {}
self.countDict = {}
self.frequencyDict = {}
self.frequencyDict[1] = OrderedDict()
self.min = -1
def get(self, key):
""":type key: ... | the_stack_v2_python_sparse | Hard/460.py | Hellofafar/Leetcode | train | 6 | |
0c7b1cfbf2e1d5472abbfe9ae038b643e0d875b3 | [
"cnt, stack = (0, [])\nfor c in s:\n if 0 == len(stack) or stack[-1] == c:\n stack.append(c)\n else:\n stack.pop()\n if 0 == len(stack):\n cnt += 1\nreturn cnt",
"lc, rc, cnt = (0, 0, 0)\nfor c in s:\n if c == 'L':\n lc += 1\n elif c == 'R':\n rc += 1\n if lc =... | <|body_start_0|>
cnt, stack = (0, [])
for c in s:
if 0 == len(stack) or stack[-1] == c:
stack.append(c)
else:
stack.pop()
if 0 == len(stack):
cnt += 1
return cnt
<|end_body_0|>
<|body_start_1|>
lc, rc, c... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def balancedStringSplit0(self, s):
""":type s: str :rtype: int"""
<|body_0|>
def balancedStringSplit(self, s):
""":type s: str :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
cnt, stack = (0, [])
for c in s:
... | stack_v2_sparse_classes_36k_train_033968 | 1,184 | no_license | [
{
"docstring": ":type s: str :rtype: int",
"name": "balancedStringSplit0",
"signature": "def balancedStringSplit0(self, s)"
},
{
"docstring": ":type s: str :rtype: int",
"name": "balancedStringSplit",
"signature": "def balancedStringSplit(self, s)"
}
] | 2 | stack_v2_sparse_classes_30k_train_005703 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def balancedStringSplit0(self, s): :type s: str :rtype: int
- def balancedStringSplit(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 balancedStringSplit0(self, s): :type s: str :rtype: int
- def balancedStringSplit(self, s): :type s: str :rtype: int
<|skeleton|>
class Solution:
def balancedStringSpli... | 5376dd48b1cefb4faba9d2ef6a8a497b6b1d6c67 | <|skeleton|>
class Solution:
def balancedStringSplit0(self, s):
""":type s: str :rtype: int"""
<|body_0|>
def balancedStringSplit(self, s):
""":type s: str :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def balancedStringSplit0(self, s):
""":type s: str :rtype: int"""
cnt, stack = (0, [])
for c in s:
if 0 == len(stack) or stack[-1] == c:
stack.append(c)
else:
stack.pop()
if 0 == len(stack):
c... | the_stack_v2_python_sparse | python/problem-stack-and-queue/split_a_string_in_balanced_strings.py | hyunjun/practice | train | 3 | |
5f149ca45fd6be17ab8a68c8f981ecd76e593a9c | [
"try:\n error = response.json()['error']\n self._message = error['message']\n self.code = error['code']\n self.type = error['type']\nexcept:\n self._message = response.reason\n self.code = response.status_code\n self.type = PINN_ERROR_CODE_MAP[response.status_code]\nsuper(PinnError, self).__ini... | <|body_start_0|>
try:
error = response.json()['error']
self._message = error['message']
self.code = error['code']
self.type = error['type']
except:
self._message = response.reason
self.code = response.status_code
self.ty... | Base exception class for a Pinn API Error. | PinnError | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PinnError:
"""Base exception class for a Pinn API Error."""
def __init__(self, response):
"""Create a PinnError object with a response dictionary object."""
<|body_0|>
def from_response(response):
"""Create an error of the right PinnError subclass from an API res... | stack_v2_sparse_classes_36k_train_033969 | 4,553 | permissive | [
{
"docstring": "Create a PinnError object with a response dictionary object.",
"name": "__init__",
"signature": "def __init__(self, response)"
},
{
"docstring": "Create an error of the right PinnError subclass from an API response.",
"name": "from_response",
"signature": "def from_respon... | 2 | stack_v2_sparse_classes_30k_train_004391 | Implement the Python class `PinnError` described below.
Class description:
Base exception class for a Pinn API Error.
Method signatures and docstrings:
- def __init__(self, response): Create a PinnError object with a response dictionary object.
- def from_response(response): Create an error of the right PinnError sub... | Implement the Python class `PinnError` described below.
Class description:
Base exception class for a Pinn API Error.
Method signatures and docstrings:
- def __init__(self, response): Create a PinnError object with a response dictionary object.
- def from_response(response): Create an error of the right PinnError sub... | d7d3f2d2a4cdc3eb01ae85a117c0e3d8bc1732bd | <|skeleton|>
class PinnError:
"""Base exception class for a Pinn API Error."""
def __init__(self, response):
"""Create a PinnError object with a response dictionary object."""
<|body_0|>
def from_response(response):
"""Create an error of the right PinnError subclass from an API res... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PinnError:
"""Base exception class for a Pinn API Error."""
def __init__(self, response):
"""Create a PinnError object with a response dictionary object."""
try:
error = response.json()['error']
self._message = error['message']
self.code = error['code']... | the_stack_v2_python_sparse | pinn/errors.py | pinntech/pinn-python | train | 2 |
64b7c7f0da2ad9311d1e4b7d4250557d71de380b | [
"can_edit_player(player_id)\ntickets = g.db.query(Ticket).filter(Ticket.player_id == player_id, Ticket.used_date == None)\nret = [add_ticket_links(t) for t in tickets]\nreturn ret",
"args = request.json\nissuer_id = args.get('issuer_id')\nticket_type = args.get('ticket_type')\ndetails = args.get('details')\nexter... | <|body_start_0|>
can_edit_player(player_id)
tickets = g.db.query(Ticket).filter(Ticket.player_id == player_id, Ticket.used_date == None)
ret = [add_ticket_links(t) for t in tickets]
return ret
<|end_body_0|>
<|body_start_1|>
args = request.json
issuer_id = args.get('issu... | TicketsEndpoint | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TicketsEndpoint:
def get(self, player_id):
"""Get a list of outstanding tickets for the player"""
<|body_0|>
def post(self, player_id):
"""Create a ticket for a player. Only available to services"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
can_e... | stack_v2_sparse_classes_36k_train_033970 | 4,333 | permissive | [
{
"docstring": "Get a list of outstanding tickets for the player",
"name": "get",
"signature": "def get(self, player_id)"
},
{
"docstring": "Create a ticket for a player. Only available to services",
"name": "post",
"signature": "def post(self, player_id)"
}
] | 2 | stack_v2_sparse_classes_30k_train_020955 | Implement the Python class `TicketsEndpoint` described below.
Class description:
Implement the TicketsEndpoint class.
Method signatures and docstrings:
- def get(self, player_id): Get a list of outstanding tickets for the player
- def post(self, player_id): Create a ticket for a player. Only available to services | Implement the Python class `TicketsEndpoint` described below.
Class description:
Implement the TicketsEndpoint class.
Method signatures and docstrings:
- def get(self, player_id): Get a list of outstanding tickets for the player
- def post(self, player_id): Create a ticket for a player. Only available to services
<|... | 58439d9398006616bbf438da6c5dbe7c32e7a379 | <|skeleton|>
class TicketsEndpoint:
def get(self, player_id):
"""Get a list of outstanding tickets for the player"""
<|body_0|>
def post(self, player_id):
"""Create a ticket for a player. Only available to services"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TicketsEndpoint:
def get(self, player_id):
"""Get a list of outstanding tickets for the player"""
can_edit_player(player_id)
tickets = g.db.query(Ticket).filter(Ticket.player_id == player_id, Ticket.used_date == None)
ret = [add_ticket_links(t) for t in tickets]
return ... | the_stack_v2_python_sparse | driftbase/players/tickets/endpoints.py | 1939Games/drift-base | train | 0 | |
af45545786eaefc38599295785f64e4a9214a561 | [
"self.total = total\nself.calls = 1\nself.progress = 0.0\nsys.stdout.write('Progress | ' + ' ' * 50 + ' |' + '0.0% ')\nself.init_time = time.time()",
"self.progress = self.calls / float(self.total) * 100\neta, vel = self.compute_eta()\nself.show_progress(eta, vel)\nself.calls += 1",
"end_time = time.time()\nite... | <|body_start_0|>
self.total = total
self.calls = 1
self.progress = 0.0
sys.stdout.write('Progress | ' + ' ' * 50 + ' |' + '0.0% ')
self.init_time = time.time()
<|end_body_0|>
<|body_start_1|>
self.progress = self.calls / float(self.total) * 100
eta, vel = self.co... | Print progress bar in console. | ProgressBar | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProgressBar:
"""Print progress bar in console."""
def __init__(self, total):
"""Create a bar. :param int total: number of iterations"""
<|body_0|>
def __call__(self):
"""Update bar."""
<|body_1|>
def compute_eta(self):
"""Compute ETA. Compare... | stack_v2_sparse_classes_36k_train_033971 | 8,762 | permissive | [
{
"docstring": "Create a bar. :param int total: number of iterations",
"name": "__init__",
"signature": "def __init__(self, total)"
},
{
"docstring": "Update bar.",
"name": "__call__",
"signature": "def __call__(self)"
},
{
"docstring": "Compute ETA. Compare current time with ini... | 4 | stack_v2_sparse_classes_30k_train_016900 | Implement the Python class `ProgressBar` described below.
Class description:
Print progress bar in console.
Method signatures and docstrings:
- def __init__(self, total): Create a bar. :param int total: number of iterations
- def __call__(self): Update bar.
- def compute_eta(self): Compute ETA. Compare current time w... | Implement the Python class `ProgressBar` described below.
Class description:
Print progress bar in console.
Method signatures and docstrings:
- def __init__(self, total): Create a bar. :param int total: number of iterations
- def __call__(self): Update bar.
- def compute_eta(self): Compute ETA. Compare current time w... | 559e1c4574865694e47f52bb202c560fc6252d2d | <|skeleton|>
class ProgressBar:
"""Print progress bar in console."""
def __init__(self, total):
"""Create a bar. :param int total: number of iterations"""
<|body_0|>
def __call__(self):
"""Update bar."""
<|body_1|>
def compute_eta(self):
"""Compute ETA. Compare... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ProgressBar:
"""Print progress bar in console."""
def __init__(self, total):
"""Create a bar. :param int total: number of iterations"""
self.total = total
self.calls = 1
self.progress = 0.0
sys.stdout.write('Progress | ' + ' ' * 50 + ' |' + '0.0% ')
self.in... | the_stack_v2_python_sparse | batman/misc/misc.py | tupui/batman | train | 2 |
4c672518cb3a862842e2fa52f46c34befbc17dd8 | [
"buildflags = OrderedDict()\nif NBURN is not None:\n buildflags['NBURN'] = str(NBURN)\nif JMZ is not None:\n buildflags['JMZ'] = str(JMZ)\nif FULDAT is not None:\n buildflags['FULDAT'] = FULDAT\nif NAME is not None:\n buildflags['NAME'] = NAME\nself.buildflags = buildflags\nself.makeflags = [f'{k}={v}' ... | <|body_start_0|>
buildflags = OrderedDict()
if NBURN is not None:
buildflags['NBURN'] = str(NBURN)
if JMZ is not None:
buildflags['JMZ'] = str(JMZ)
if FULDAT is not None:
buildflags['FULDAT'] = FULDAT
if NAME is not None:
buildflags... | _BuildKepler | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class _BuildKepler:
def __init__(self, NBURN=None, JMZ=None, FULDAT=None, NAME=None, machine='CPU', hashing=False, update=True):
"""Note - all initilisation needed is done in class definition for now. Maybe that should go here instead ..."""
<|body_0|>
def build_library_check(self... | stack_v2_sparse_classes_36k_train_033972 | 4,916 | permissive | [
{
"docstring": "Note - all initilisation needed is done in class definition for now. Maybe that should go here instead ...",
"name": "__init__",
"signature": "def __init__(self, NBURN=None, JMZ=None, FULDAT=None, NAME=None, machine='CPU', hashing=False, update=True)"
},
{
"docstring": "check whe... | 2 | stack_v2_sparse_classes_30k_train_009691 | Implement the Python class `_BuildKepler` described below.
Class description:
Implement the _BuildKepler class.
Method signatures and docstrings:
- def __init__(self, NBURN=None, JMZ=None, FULDAT=None, NAME=None, machine='CPU', hashing=False, update=True): Note - all initilisation needed is done in class definition f... | Implement the Python class `_BuildKepler` described below.
Class description:
Implement the _BuildKepler class.
Method signatures and docstrings:
- def __init__(self, NBURN=None, JMZ=None, FULDAT=None, NAME=None, machine='CPU', hashing=False, update=True): Note - all initilisation needed is done in class definition f... | 98fc181bab054619d12ffa4173ad5c469803c2ec | <|skeleton|>
class _BuildKepler:
def __init__(self, NBURN=None, JMZ=None, FULDAT=None, NAME=None, machine='CPU', hashing=False, update=True):
"""Note - all initilisation needed is done in class definition for now. Maybe that should go here instead ..."""
<|body_0|>
def build_library_check(self... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class _BuildKepler:
def __init__(self, NBURN=None, JMZ=None, FULDAT=None, NAME=None, machine='CPU', hashing=False, update=True):
"""Note - all initilisation needed is done in class definition for now. Maybe that should go here instead ..."""
buildflags = OrderedDict()
if NBURN is not None:
... | the_stack_v2_python_sparse | kepler_python_packages/python_scripts/kepler/code/_build.py | adam-m-jcbs/xrb-sens-datashare | train | 1 | |
56d363c33e789c88e75e1dff26f8d4144e547fbe | [
"self.check_parameters(params)\ncos = np.cos(params[0] / 2)\nsin = -1j * np.sin(params[0] / 2)\nreturn UnitaryMatrix([[cos, 0, 0, sin], [0, cos, sin, 0], [0, sin, cos, 0], [sin, 0, 0, cos]])",
"self.check_parameters(params)\ndcos = -np.sin(params[0] / 2) / 2\ndsin = -1j * np.cos(params[0] / 2) / 2\nreturn np.arra... | <|body_start_0|>
self.check_parameters(params)
cos = np.cos(params[0] / 2)
sin = -1j * np.sin(params[0] / 2)
return UnitaryMatrix([[cos, 0, 0, sin], [0, cos, sin, 0], [0, sin, cos, 0], [sin, 0, 0, cos]])
<|end_body_0|>
<|body_start_1|>
self.check_parameters(params)
dcos ... | A gate representing an arbitrary rotation around the XX axis. | RXXGate | [
"LicenseRef-scancode-unknown-license-reference",
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RXXGate:
"""A gate representing an arbitrary rotation around the XX axis."""
def get_unitary(self, params: Sequence[float]=[]) -> UnitaryMatrix:
"""Returns the unitary for this gate, see Unitary for more info."""
<|body_0|>
def get_grad(self, params: Sequence[float]=[]) ... | stack_v2_sparse_classes_36k_train_033973 | 2,165 | permissive | [
{
"docstring": "Returns the unitary for this gate, see Unitary for more info.",
"name": "get_unitary",
"signature": "def get_unitary(self, params: Sequence[float]=[]) -> UnitaryMatrix"
},
{
"docstring": "Returns the gradient for this gate, see Gate for more info.",
"name": "get_grad",
"s... | 3 | stack_v2_sparse_classes_30k_train_013232 | Implement the Python class `RXXGate` described below.
Class description:
A gate representing an arbitrary rotation around the XX axis.
Method signatures and docstrings:
- def get_unitary(self, params: Sequence[float]=[]) -> UnitaryMatrix: Returns the unitary for this gate, see Unitary for more info.
- def get_grad(se... | Implement the Python class `RXXGate` described below.
Class description:
A gate representing an arbitrary rotation around the XX axis.
Method signatures and docstrings:
- def get_unitary(self, params: Sequence[float]=[]) -> UnitaryMatrix: Returns the unitary for this gate, see Unitary for more info.
- def get_grad(se... | 3083218c2f4e3c3ce4ba027d12caa30c384d7665 | <|skeleton|>
class RXXGate:
"""A gate representing an arbitrary rotation around the XX axis."""
def get_unitary(self, params: Sequence[float]=[]) -> UnitaryMatrix:
"""Returns the unitary for this gate, see Unitary for more info."""
<|body_0|>
def get_grad(self, params: Sequence[float]=[]) ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RXXGate:
"""A gate representing an arbitrary rotation around the XX axis."""
def get_unitary(self, params: Sequence[float]=[]) -> UnitaryMatrix:
"""Returns the unitary for this gate, see Unitary for more info."""
self.check_parameters(params)
cos = np.cos(params[0] / 2)
si... | the_stack_v2_python_sparse | bqskit/ir/gates/parameterized/rxx.py | mtreinish/bqskit | train | 0 |
ad51420c82fd88cfa1a906cea7ecd3984e2feec8 | [
"attr = handler_input.attributes_manager.session_attributes\nplayers_dict = attr.get('players_dict', {})\nif player_name in players_dict.keys():\n logger.warning('create_new_player: Player already found.')\n return\nnew_player = Player(player_name)\nnew_player_dict = PlayerEncoder.encode_player_to_dict(new_pl... | <|body_start_0|>
attr = handler_input.attributes_manager.session_attributes
players_dict = attr.get('players_dict', {})
if player_name in players_dict.keys():
logger.warning('create_new_player: Player already found.')
return
new_player = Player(player_name)
... | Methods for accessing player class through session attributes. | PlayerDict | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PlayerDict:
"""Methods for accessing player class through session attributes."""
def create_new_player(handler_input, player_name: str) -> None:
"""Creates new player and adds it to the players_dict"""
<|body_0|>
def load_player_obj(handler_input) -> object:
"""L... | stack_v2_sparse_classes_36k_train_033974 | 2,835 | permissive | [
{
"docstring": "Creates new player and adds it to the players_dict",
"name": "create_new_player",
"signature": "def create_new_player(handler_input, player_name: str) -> None"
},
{
"docstring": "Loads player object from players_dict",
"name": "load_player_obj",
"signature": "def load_pla... | 3 | null | Implement the Python class `PlayerDict` described below.
Class description:
Methods for accessing player class through session attributes.
Method signatures and docstrings:
- def create_new_player(handler_input, player_name: str) -> None: Creates new player and adds it to the players_dict
- def load_player_obj(handle... | Implement the Python class `PlayerDict` described below.
Class description:
Methods for accessing player class through session attributes.
Method signatures and docstrings:
- def create_new_player(handler_input, player_name: str) -> None: Creates new player and adds it to the players_dict
- def load_player_obj(handle... | 1072dea1a5be0b339211ff39db6a89a90aca64c1 | <|skeleton|>
class PlayerDict:
"""Methods for accessing player class through session attributes."""
def create_new_player(handler_input, player_name: str) -> None:
"""Creates new player and adds it to the players_dict"""
<|body_0|>
def load_player_obj(handler_input) -> object:
"""L... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PlayerDict:
"""Methods for accessing player class through session attributes."""
def create_new_player(handler_input, player_name: str) -> None:
"""Creates new player and adds it to the players_dict"""
attr = handler_input.attributes_manager.session_attributes
players_dict = attr.... | the_stack_v2_python_sparse | 1_code/players/players_dict.py | jaimiles23/Multiplication-Medley | train | 0 |
694980c435f450e71bb63c29850a61355cef16a7 | [
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')",
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')"
] | <|body_start_0|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!')
<|end_body_0|>
<|body_start_1|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not im... | Missing associated documentation comment in .proto file. | EvalDispatcherServicer | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EvalDispatcherServicer:
"""Missing associated documentation comment in .proto file."""
def TakeEvalJob(self, request, context):
"""Missing associated documentation comment in .proto file."""
<|body_0|>
def SubmitEvalJobResult(self, request, context):
"""Missing a... | stack_v2_sparse_classes_36k_train_033975 | 4,546 | permissive | [
{
"docstring": "Missing associated documentation comment in .proto file.",
"name": "TakeEvalJob",
"signature": "def TakeEvalJob(self, request, context)"
},
{
"docstring": "Missing associated documentation comment in .proto file.",
"name": "SubmitEvalJobResult",
"signature": "def SubmitEv... | 2 | stack_v2_sparse_classes_30k_train_005135 | Implement the Python class `EvalDispatcherServicer` described below.
Class description:
Missing associated documentation comment in .proto file.
Method signatures and docstrings:
- def TakeEvalJob(self, request, context): Missing associated documentation comment in .proto file.
- def SubmitEvalJobResult(self, request... | Implement the Python class `EvalDispatcherServicer` described below.
Class description:
Missing associated documentation comment in .proto file.
Method signatures and docstrings:
- def TakeEvalJob(self, request, context): Missing associated documentation comment in .proto file.
- def SubmitEvalJobResult(self, request... | 1ddd92aa56ba10fa468396de8f8824c83ba9d0ba | <|skeleton|>
class EvalDispatcherServicer:
"""Missing associated documentation comment in .proto file."""
def TakeEvalJob(self, request, context):
"""Missing associated documentation comment in .proto file."""
<|body_0|>
def SubmitEvalJobResult(self, request, context):
"""Missing a... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EvalDispatcherServicer:
"""Missing associated documentation comment in .proto file."""
def TakeEvalJob(self, request, context):
"""Missing associated documentation comment in .proto file."""
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemente... | the_stack_v2_python_sparse | grl/algos/p2sro/eval_dispatcher/protobuf/eval_dispatcher_pb2_grpc.py | RL-code-lib/nxdo | train | 0 |
e753452d7460b808bf887b7d8cf0a4474f68da9b | [
"super(PowerOn, self).__init__()\nself.switches = switches\nreturn",
"self.turn_all_off()\nparams = parameters.id_switch.parameters\nself.logger.info(\"Turning on {0} (switch '{1}')\".format(params.identifier, params.switch))\nself.switches[params.identifier](params.switch)\nreturn '{0}'.format(params.identifier)... | <|body_start_0|>
super(PowerOn, self).__init__()
self.switches = switches
return
<|end_body_0|>
<|body_start_1|>
self.turn_all_off()
params = parameters.id_switch.parameters
self.logger.info("Turning on {0} (switch '{1}')".format(params.identifier, params.switch))
... | A class to power-on a networked-switch | PowerOn | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PowerOn:
"""A class to power-on a networked-switch"""
def __init__(self, switches):
""":param: - `switches`: A dictionary of identifiers:switches"""
<|body_0|>
def __call__(self, parameters):
""":param: - `parameters`: namedtuple with parameters.id_switch.paramet... | stack_v2_sparse_classes_36k_train_033976 | 1,138 | permissive | [
{
"docstring": ":param: - `switches`: A dictionary of identifiers:switches",
"name": "__init__",
"signature": "def __init__(self, switches)"
},
{
"docstring": ":param: - `parameters`: namedtuple with parameters.id_switch.parameters",
"name": "__call__",
"signature": "def __call__(self, p... | 3 | null | Implement the Python class `PowerOn` described below.
Class description:
A class to power-on a networked-switch
Method signatures and docstrings:
- def __init__(self, switches): :param: - `switches`: A dictionary of identifiers:switches
- def __call__(self, parameters): :param: - `parameters`: namedtuple with paramet... | Implement the Python class `PowerOn` described below.
Class description:
A class to power-on a networked-switch
Method signatures and docstrings:
- def __init__(self, switches): :param: - `switches`: A dictionary of identifiers:switches
- def __call__(self, parameters): :param: - `parameters`: namedtuple with paramet... | b4d1c77e1d611fe2b30768b42bdc7493afb0ea95 | <|skeleton|>
class PowerOn:
"""A class to power-on a networked-switch"""
def __init__(self, switches):
""":param: - `switches`: A dictionary of identifiers:switches"""
<|body_0|>
def __call__(self, parameters):
""":param: - `parameters`: namedtuple with parameters.id_switch.paramet... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PowerOn:
"""A class to power-on a networked-switch"""
def __init__(self, switches):
""":param: - `switches`: A dictionary of identifiers:switches"""
super(PowerOn, self).__init__()
self.switches = switches
return
def __call__(self, parameters):
""":param: - `p... | the_stack_v2_python_sparse | apetools/commands/poweron.py | russell-n/oldape | train | 0 |
2037e7c5693e1c0d3a05ed9229553eb3c3cd4a81 | [
"re_string = re.compile('[a-zA-Z0-9]')\nline = ''.join(re_string.findall(s)).lower()\nlenth = len(line)\nfor i in range(lenth // 2):\n if line[i] != line[lenth - i - 1]:\n print(line[i], i)\n return False\nreturn True",
"s = s.lower()\ncharacter = 'abcdefghijklmnopqrstuvwxyz0123456789'\nl = []\nf... | <|body_start_0|>
re_string = re.compile('[a-zA-Z0-9]')
line = ''.join(re_string.findall(s)).lower()
lenth = len(line)
for i in range(lenth // 2):
if line[i] != line[lenth - i - 1]:
print(line[i], i)
return False
return True
<|end_body_0... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def isPalindrome(self, s):
""":type s: str :rtype: bool"""
<|body_0|>
def other_isPalindrome(self, s):
""":type s: str :rtype: bool"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
re_string = re.compile('[a-zA-Z0-9]')
line = ''.joi... | stack_v2_sparse_classes_36k_train_033977 | 1,062 | no_license | [
{
"docstring": ":type s: str :rtype: bool",
"name": "isPalindrome",
"signature": "def isPalindrome(self, s)"
},
{
"docstring": ":type s: str :rtype: bool",
"name": "other_isPalindrome",
"signature": "def other_isPalindrome(self, s)"
}
] | 2 | stack_v2_sparse_classes_30k_train_002796 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isPalindrome(self, s): :type s: str :rtype: bool
- def other_isPalindrome(self, s): :type s: str :rtype: bool | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isPalindrome(self, s): :type s: str :rtype: bool
- def other_isPalindrome(self, s): :type s: str :rtype: bool
<|skeleton|>
class Solution:
def isPalindrome(self, s):
... | d156c6a13c89727f80ed6244cae40574395ecf34 | <|skeleton|>
class Solution:
def isPalindrome(self, s):
""":type s: str :rtype: bool"""
<|body_0|>
def other_isPalindrome(self, s):
""":type s: str :rtype: bool"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def isPalindrome(self, s):
""":type s: str :rtype: bool"""
re_string = re.compile('[a-zA-Z0-9]')
line = ''.join(re_string.findall(s)).lower()
lenth = len(line)
for i in range(lenth // 2):
if line[i] != line[lenth - i - 1]:
print(lin... | the_stack_v2_python_sparse | easy/125.py | longhao54/leetcode | train | 0 | |
83eb9591ec43bd8df783ead499a14763e9402da8 | [
"def build(i1, i2, j1, j2):\n if i1 == i2 and j1 == j2:\n return Node(grid[i1][j1], True, None, None, None, None)\n im = i1 + (i2 - i1) // 2\n jm = j1 + (j2 - j1) // 2\n lt = build(i1, im, j1, jm)\n lb = build(im + 1, i2, j1, jm)\n rt = build(i1, im, jm + 1, j2)\n rb = build(im + 1, i2, ... | <|body_start_0|>
def build(i1, i2, j1, j2):
if i1 == i2 and j1 == j2:
return Node(grid[i1][j1], True, None, None, None, None)
im = i1 + (i2 - i1) // 2
jm = j1 + (j2 - j1) // 2
lt = build(i1, im, j1, jm)
lb = build(im + 1, i2, j1, jm)
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def construct(self, grid: List[List[int]]) -> 'Node':
"""Apr 28, 2020 22:55"""
<|body_0|>
def construct(self, grid: List[List[int]]) -> 'Node':
"""Apr 02, 2023 15:21"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
def build(i1, i2, j1, j2)... | stack_v2_sparse_classes_36k_train_033978 | 5,878 | no_license | [
{
"docstring": "Apr 28, 2020 22:55",
"name": "construct",
"signature": "def construct(self, grid: List[List[int]]) -> 'Node'"
},
{
"docstring": "Apr 02, 2023 15:21",
"name": "construct",
"signature": "def construct(self, grid: List[List[int]]) -> 'Node'"
}
] | 2 | stack_v2_sparse_classes_30k_train_008269 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def construct(self, grid: List[List[int]]) -> 'Node': Apr 28, 2020 22:55
- def construct(self, grid: List[List[int]]) -> 'Node': Apr 02, 2023 15:21 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def construct(self, grid: List[List[int]]) -> 'Node': Apr 28, 2020 22:55
- def construct(self, grid: List[List[int]]) -> 'Node': Apr 02, 2023 15:21
<|skeleton|>
class Solution:
... | 1389a009a02e90e8700a7a00e0b7f797c129cdf4 | <|skeleton|>
class Solution:
def construct(self, grid: List[List[int]]) -> 'Node':
"""Apr 28, 2020 22:55"""
<|body_0|>
def construct(self, grid: List[List[int]]) -> 'Node':
"""Apr 02, 2023 15:21"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def construct(self, grid: List[List[int]]) -> 'Node':
"""Apr 28, 2020 22:55"""
def build(i1, i2, j1, j2):
if i1 == i2 and j1 == j2:
return Node(grid[i1][j1], True, None, None, None, None)
im = i1 + (i2 - i1) // 2
jm = j1 + (j2 - j1)... | the_stack_v2_python_sparse | leetcode/solved/772_Construct_Quad_Tree/solution.py | sungminoh/algorithms | train | 0 | |
5730b3d0651858fa7d349af2c34395ade286145a | [
"self.s = []\n\ndef dfs_visit(root):\n if not root:\n self.s.append('null')\n return\n self.s.append(root.val)\n dfs_visit(root.left)\n dfs_visit(root.right)\ndfs_visit(root)\nprint(self.s)\nstrs = ''\nfor i in self.s:\n strs += str(i) + ','\nreturn strs[:-1]",
"s = data.split(',')\ns... | <|body_start_0|>
self.s = []
def dfs_visit(root):
if not root:
self.s.append('null')
return
self.s.append(root.val)
dfs_visit(root.left)
dfs_visit(root.right)
dfs_visit(root)
print(self.s)
strs = ''
... | 199ms | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
"""199ms"""
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_ske... | stack_v2_sparse_classes_36k_train_033979 | 3,990 | 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_012630 | Implement the Python class `Codec` described below.
Class description:
199ms
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: TreeNode | Implement the Python class `Codec` described below.
Class description:
199ms
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: TreeNode
<|skeleton... | 679a2b246b8b6bb7fc55ed1c8096d3047d6d4461 | <|skeleton|>
class Codec:
"""199ms"""
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_ske... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Codec:
"""199ms"""
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
self.s = []
def dfs_visit(root):
if not root:
self.s.append('null')
return
self.s.append(root.val)
... | the_stack_v2_python_sparse | SerializeAndDeserializeBinaryTree_HARD_297.py | 953250587/leetcode-python | train | 2 |
635c6cf359ae76df657825622c906038cf48c194 | [
"if self.field:\n return f'Top results for \"{self.field:s}\"'\nreturn 'Top results for an unknown field'",
"self.field = field\nformatted_field_name = self.format_field_by_type(field)\nencoding = {'x': {'field': field, 'type': 'nominal', 'sort': {'op': 'sum', 'field': order_field, 'order': 'descending'}}, 'y'... | <|body_start_0|>
if self.field:
return f'Top results for "{self.field:s}"'
return 'Top results for an unknown field'
<|end_body_0|>
<|body_start_1|>
self.field = field
formatted_field_name = self.format_field_by_type(field)
encoding = {'x': {'field': field, 'type': '... | Terms Bucket Aggregation. | TermsAggregation | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TermsAggregation:
"""Terms Bucket Aggregation."""
def chart_title(self):
"""Returns a title for the chart."""
<|body_0|>
def run(self, field, limit=10, supported_charts='table', start_time='', end_time='', order_field='count'):
"""Run the aggregation. Args: field... | stack_v2_sparse_classes_36k_train_033980 | 5,187 | permissive | [
{
"docstring": "Returns a title for the chart.",
"name": "chart_title",
"signature": "def chart_title(self)"
},
{
"docstring": "Run the aggregation. Args: field: What field to aggregate on. limit: How many buckets to return. supported_charts: Chart type to render. Defaults to table. start_time: ... | 2 | stack_v2_sparse_classes_30k_train_013886 | Implement the Python class `TermsAggregation` described below.
Class description:
Terms Bucket Aggregation.
Method signatures and docstrings:
- def chart_title(self): Returns a title for the chart.
- def run(self, field, limit=10, supported_charts='table', start_time='', end_time='', order_field='count'): Run the agg... | Implement the Python class `TermsAggregation` described below.
Class description:
Terms Bucket Aggregation.
Method signatures and docstrings:
- def chart_title(self): Returns a title for the chart.
- def run(self, field, limit=10, supported_charts='table', start_time='', end_time='', order_field='count'): Run the agg... | 24f471b58ca4a87cb053961b5f05c07a544ca7b8 | <|skeleton|>
class TermsAggregation:
"""Terms Bucket Aggregation."""
def chart_title(self):
"""Returns a title for the chart."""
<|body_0|>
def run(self, field, limit=10, supported_charts='table', start_time='', end_time='', order_field='count'):
"""Run the aggregation. Args: field... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TermsAggregation:
"""Terms Bucket Aggregation."""
def chart_title(self):
"""Returns a title for the chart."""
if self.field:
return f'Top results for "{self.field:s}"'
return 'Top results for an unknown field'
def run(self, field, limit=10, supported_charts='table... | the_stack_v2_python_sparse | timesketch/lib/aggregators/bucket.py | google/timesketch | train | 2,263 |
d58f1f7d19152545a554fea724914d35321128bd | [
"self.screen_width = 1000\nself.screen_height = 680\nself.bg_color = (230, 230, 230)\nself.ship_speed_factor = 1.5\nself.ship_limit = 3\nself.bullet_speed_factor = 3\nself.bullet_width = 3\nself.bullet_height = 15\nself.bullet_color = (60, 60, 60)\nself.bullet_allowed = 3\nself.alien_speed_factor = 1\nself.fleet_dr... | <|body_start_0|>
self.screen_width = 1000
self.screen_height = 680
self.bg_color = (230, 230, 230)
self.ship_speed_factor = 1.5
self.ship_limit = 3
self.bullet_speed_factor = 3
self.bullet_width = 3
self.bullet_height = 15
self.bullet_color = (60, ... | A Class to store all settings for Alien Invasion | Settings | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Settings:
"""A Class to store all settings for Alien Invasion"""
def __init__(self):
"""Initialize the game setting's"""
<|body_0|>
def initialize_dynamic_setting(self):
"""Initialize setting that change throughout the game"""
<|body_1|>
def increase... | stack_v2_sparse_classes_36k_train_033981 | 1,505 | no_license | [
{
"docstring": "Initialize the game setting's",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Initialize setting that change throughout the game",
"name": "initialize_dynamic_setting",
"signature": "def initialize_dynamic_setting(self)"
},
{
"docstring"... | 3 | stack_v2_sparse_classes_30k_train_010955 | Implement the Python class `Settings` described below.
Class description:
A Class to store all settings for Alien Invasion
Method signatures and docstrings:
- def __init__(self): Initialize the game setting's
- def initialize_dynamic_setting(self): Initialize setting that change throughout the game
- def increase_spe... | Implement the Python class `Settings` described below.
Class description:
A Class to store all settings for Alien Invasion
Method signatures and docstrings:
- def __init__(self): Initialize the game setting's
- def initialize_dynamic_setting(self): Initialize setting that change throughout the game
- def increase_spe... | e85198ab8b95abbe43e9c9bde44661525bca8977 | <|skeleton|>
class Settings:
"""A Class to store all settings for Alien Invasion"""
def __init__(self):
"""Initialize the game setting's"""
<|body_0|>
def initialize_dynamic_setting(self):
"""Initialize setting that change throughout the game"""
<|body_1|>
def increase... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Settings:
"""A Class to store all settings for Alien Invasion"""
def __init__(self):
"""Initialize the game setting's"""
self.screen_width = 1000
self.screen_height = 680
self.bg_color = (230, 230, 230)
self.ship_speed_factor = 1.5
self.ship_limit = 3
... | the_stack_v2_python_sparse | pygame/settings.py | pratikv06/Python-Crash-Course | train | 2 |
92e65c8717bff0abe3e07d54aab2fa8ea88cf683 | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn SolutionsRoot()",
"from .booking_business import BookingBusiness\nfrom .booking_currency import BookingCurrency\nfrom .booking_business import BookingBusiness\nfrom .booking_currency import BookingCurrency\nfields: Dict[str, Callable[[... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return SolutionsRoot()
<|end_body_0|>
<|body_start_1|>
from .booking_business import BookingBusiness
from .booking_currency import BookingCurrency
from .booking_business import BookingB... | SolutionsRoot | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SolutionsRoot:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> SolutionsRoot:
"""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... | stack_v2_sparse_classes_36k_train_033982 | 3,222 | 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: SolutionsRoot",
"name": "create_from_discriminator_value",
"signature": "def create_from_discriminator_value... | 3 | stack_v2_sparse_classes_30k_train_011329 | Implement the Python class `SolutionsRoot` described below.
Class description:
Implement the SolutionsRoot class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> SolutionsRoot: Creates a new instance of the appropriate class based on discriminator value... | Implement the Python class `SolutionsRoot` described below.
Class description:
Implement the SolutionsRoot class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> SolutionsRoot: Creates a new instance of the appropriate class based on discriminator value... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class SolutionsRoot:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> SolutionsRoot:
"""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... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SolutionsRoot:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> SolutionsRoot:
"""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: SolutionsRoo... | the_stack_v2_python_sparse | msgraph/generated/models/solutions_root.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
a2b905b763f9dd3a2e43cef49d236e2cecebff0d | [
"def strfy(node):\n if node is None:\n return ''\n left_string = strfy(node.left)\n right_string = strfy(node.right)\n return str(node.val) + '$' + left_string + right_string\nres = strfy(root)\nreturn res",
"def tree(lst):\n if not lst:\n return None\n node = TreeNode(lst[0])\n ... | <|body_start_0|>
def strfy(node):
if node is None:
return ''
left_string = strfy(node.left)
right_string = strfy(node.right)
return str(node.val) + '$' + left_string + right_string
res = strfy(root)
return res
<|end_body_0|>
<|body... | 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 e.g.: 7$2$5$9$8$10$"""
<|body_1|>
<|end... | stack_v2_sparse_classes_36k_train_033983 | 2,353 | no_license | [
{
"docstring": "Encodes a tree to a single string. :type root: TreeNode :rtype: str",
"name": "serialize",
"signature": "def serialize(self, root)"
},
{
"docstring": "Decodes your encoded data to tree. :type data: str :rtype: TreeNode e.g.: 7$2$5$9$8$10$",
"name": "deserialize",
"signatu... | 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:... | f96a2273c6831a8035e1adacfa452f73c599ae16 | <|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 e.g.: 7$2$5$9$8$10$"""
<|body_1|>
<|end... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
def strfy(node):
if node is None:
return ''
left_string = strfy(node.left)
right_string = strfy(node.right)
return str(nod... | the_stack_v2_python_sparse | Python/449_SerializeandDeserializeBST.py | here0009/LeetCode | train | 1 | |
cabc1ded6accc5b6360ff2b10def6e2d30ac7e4d | [
"super(PixelSelector, self).__init__()\nassert momentManager.kernelWidth == calMomentManager.kernelWidth\nself.keys = copy.copy(MomentManager.keys)\nself.momentManager = momentManager\nself.calMomentManager = calMomentManager",
"if limit.name not in self.keys:\n raise ValueError('Limit name must be in:' + str(... | <|body_start_0|>
super(PixelSelector, self).__init__()
assert momentManager.kernelWidth == calMomentManager.kernelWidth
self.keys = copy.copy(MomentManager.keys)
self.momentManager = momentManager
self.calMomentManager = calMomentManager
<|end_body_0|>
<|body_start_1|>
i... | A simple pixel selector. Inherit from a list, and we'll contain a list of our MomentLimit objects. We'll go through our list, and any pixels which are numerically within the limits for all MomentLimit objects "pass" and are kept. In the end, we return a boolean image with True set for accepted pixels. | PixelSelector | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PixelSelector:
"""A simple pixel selector. Inherit from a list, and we'll contain a list of our MomentLimit objects. We'll go through our list, and any pixels which are numerically within the limits for all MomentLimit objects "pass" and are kept. In the end, we return a boolean image with True s... | stack_v2_sparse_classes_36k_train_033984 | 11,918 | no_license | [
{
"docstring": "Construct @param momentManager MomentManager for the image we're selecting from @param calMomentManager The MomentManager for the calibration image.",
"name": "__init__",
"signature": "def __init__(self, momentManager, calMomentManager)"
},
{
"docstring": "Overload our parent lis... | 4 | stack_v2_sparse_classes_30k_train_007882 | Implement the Python class `PixelSelector` described below.
Class description:
A simple pixel selector. Inherit from a list, and we'll contain a list of our MomentLimit objects. We'll go through our list, and any pixels which are numerically within the limits for all MomentLimit objects "pass" and are kept. In the end... | Implement the Python class `PixelSelector` described below.
Class description:
A simple pixel selector. Inherit from a list, and we'll contain a list of our MomentLimit objects. We'll go through our list, and any pixels which are numerically within the limits for all MomentLimit objects "pass" and are kept. In the end... | f826f98369125b9aa0aa6f7228913a503cea80a4 | <|skeleton|>
class PixelSelector:
"""A simple pixel selector. Inherit from a list, and we'll contain a list of our MomentLimit objects. We'll go through our list, and any pixels which are numerically within the limits for all MomentLimit objects "pass" and are kept. In the end, we return a boolean image with True s... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PixelSelector:
"""A simple pixel selector. Inherit from a list, and we'll contain a list of our MomentLimit objects. We'll go through our list, and any pixels which are numerically within the limits for all MomentLimit objects "pass" and are kept. In the end, we return a boolean image with True set for accept... | the_stack_v2_python_sparse | python/lsst/meas/artifact/momentCalculator.py | lsst-dm/meas_artifact | train | 3 |
51159822727d1eef0074618b80366d8c8ae8d915 | [
"group = Group.objects.filter(name='teachers')\nusers = User.objects.filter(groups__in=group)\nif obj in users:\n return 'teachers'\nelse:\n return 'students'",
"exams = []\nqueryset = ExamSheet.objects.filter(owner=obj)\nfor q in queryset:\n exams.append(q.title)\nreturn exams"
] | <|body_start_0|>
group = Group.objects.filter(name='teachers')
users = User.objects.filter(groups__in=group)
if obj in users:
return 'teachers'
else:
return 'students'
<|end_body_0|>
<|body_start_1|>
exams = []
queryset = ExamSheet.objects.filter(... | UserSerializer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserSerializer:
def get_group(self, obj):
"""Simply returns a groups name to which user belongs"""
<|body_0|>
def get_owned_exams(self, obj):
"""Get exams owned by teacher"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
group = Group.objects.filter(... | stack_v2_sparse_classes_36k_train_033985 | 3,922 | no_license | [
{
"docstring": "Simply returns a groups name to which user belongs",
"name": "get_group",
"signature": "def get_group(self, obj)"
},
{
"docstring": "Get exams owned by teacher",
"name": "get_owned_exams",
"signature": "def get_owned_exams(self, obj)"
}
] | 2 | stack_v2_sparse_classes_30k_train_009663 | Implement the Python class `UserSerializer` described below.
Class description:
Implement the UserSerializer class.
Method signatures and docstrings:
- def get_group(self, obj): Simply returns a groups name to which user belongs
- def get_owned_exams(self, obj): Get exams owned by teacher | Implement the Python class `UserSerializer` described below.
Class description:
Implement the UserSerializer class.
Method signatures and docstrings:
- def get_group(self, obj): Simply returns a groups name to which user belongs
- def get_owned_exams(self, obj): Get exams owned by teacher
<|skeleton|>
class UserSeri... | 2651ac12078c7d5435d1fb23585bb275c974ce30 | <|skeleton|>
class UserSerializer:
def get_group(self, obj):
"""Simply returns a groups name to which user belongs"""
<|body_0|>
def get_owned_exams(self, obj):
"""Get exams owned by teacher"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UserSerializer:
def get_group(self, obj):
"""Simply returns a groups name to which user belongs"""
group = Group.objects.filter(name='teachers')
users = User.objects.filter(groups__in=group)
if obj in users:
return 'teachers'
else:
return 'studen... | the_stack_v2_python_sparse | ExamAPI/Sheets/serializers.py | mtyton/ExamSheetEvaluator-API | train | 0 | |
1ccc6b3c837d06beaade1866b8bc0760385d92dd | [
"if n > 0:\n sum = x\n for i in range(n - 1):\n sum *= x\nelif n < 0:\n sum = 1 / x\n for i in range(n + 1, 0):\n sum *= 1 / x\nelse:\n sum = 1\nreturn sum",
"if not x:\n return 1\nif n < 0:\n return 1 / self.myPow3(x, -n)\nif n % 2:\n return x * self.myPow3(x, n - 1)\nreturn... | <|body_start_0|>
if n > 0:
sum = x
for i in range(n - 1):
sum *= x
elif n < 0:
sum = 1 / x
for i in range(n + 1, 0):
sum *= 1 / x
else:
sum = 1
return sum
<|end_body_0|>
<|body_start_1|>
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def myPow2(self, x: float, n: int) -> float:
"""暴力. 使用循环。 leetcode说超过时间限制 Args: x: n: Returns:"""
<|body_0|>
def myPow3(self, x: float, n: int) -> float:
"""分而治之的方法。 x * x * x = y 1. 如果n的个数是偶数 y = x^(n/2) sum = y * y = (x * x)^(n/2) 2. 如果n的个数是奇数 y = x^(x//2... | stack_v2_sparse_classes_36k_train_033986 | 1,987 | no_license | [
{
"docstring": "暴力. 使用循环。 leetcode说超过时间限制 Args: x: n: Returns:",
"name": "myPow2",
"signature": "def myPow2(self, x: float, n: int) -> float"
},
{
"docstring": "分而治之的方法。 x * x * x = y 1. 如果n的个数是偶数 y = x^(n/2) sum = y * y = (x * x)^(n/2) 2. 如果n的个数是奇数 y = x^(x//2) sum = y * y * x = x * (x * x)^((n... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def myPow2(self, x: float, n: int) -> float: 暴力. 使用循环。 leetcode说超过时间限制 Args: x: n: Returns:
- def myPow3(self, x: float, n: int) -> float: 分而治之的方法。 x * x * x = y 1. 如果n的个数是偶数 y =... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def myPow2(self, x: float, n: int) -> float: 暴力. 使用循环。 leetcode说超过时间限制 Args: x: n: Returns:
- def myPow3(self, x: float, n: int) -> float: 分而治之的方法。 x * x * x = y 1. 如果n的个数是偶数 y =... | c0dd577481b46129d950354d567d332a4d091137 | <|skeleton|>
class Solution:
def myPow2(self, x: float, n: int) -> float:
"""暴力. 使用循环。 leetcode说超过时间限制 Args: x: n: Returns:"""
<|body_0|>
def myPow3(self, x: float, n: int) -> float:
"""分而治之的方法。 x * x * x = y 1. 如果n的个数是偶数 y = x^(n/2) sum = y * y = (x * x)^(n/2) 2. 如果n的个数是奇数 y = x^(x//2... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def myPow2(self, x: float, n: int) -> float:
"""暴力. 使用循环。 leetcode说超过时间限制 Args: x: n: Returns:"""
if n > 0:
sum = x
for i in range(n - 1):
sum *= x
elif n < 0:
sum = 1 / x
for i in range(n + 1, 0):
... | the_stack_v2_python_sparse | leetcode/50_POW(x, n).py | tenqaz/crazy_arithmetic | train | 0 | |
b7e586d22a41071ddb8e0d4f850c2456c0d7bd9e | [
"if root is None:\n return 'X#'\nleftSerialized = self.serialize(root.left)\nrightSerialized = self.serialize(root.right)\nreturn str(root.val) + '#' + leftSerialized + rightSerialized",
"def dfs():\n val = next(data)\n if val == 'X':\n return None\n node = TreeNode(int(val))\n node.left = d... | <|body_start_0|>
if root is None:
return 'X#'
leftSerialized = self.serialize(root.left)
rightSerialized = self.serialize(root.right)
return str(root.val) + '#' + leftSerialized + rightSerialized
<|end_body_0|>
<|body_start_1|>
def dfs():
val = next(data)... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root: TreeNode) -> str:
"""Encodes a tree to a single string."""
<|body_0|>
def deserialize(self, data: str) -> TreeNode:
"""Decodes your encoded data to tree."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if root is Non... | stack_v2_sparse_classes_36k_train_033987 | 2,092 | no_license | [
{
"docstring": "Encodes a tree to a single string.",
"name": "serialize",
"signature": "def serialize(self, root: TreeNode) -> str"
},
{
"docstring": "Decodes your encoded data to tree.",
"name": "deserialize",
"signature": "def deserialize(self, data: str) -> TreeNode"
}
] | 2 | null | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root: TreeNode) -> str: Encodes a tree to a single string.
- def deserialize(self, data: str) -> TreeNode: Decodes your encoded data to tree. | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root: TreeNode) -> str: Encodes a tree to a single string.
- def deserialize(self, data: str) -> TreeNode: Decodes your encoded data to tree.
<|skeleton|>
class Co... | 480de9be082fdcbcafe68e2cd5fd819dc7815e64 | <|skeleton|>
class Codec:
def serialize(self, root: TreeNode) -> str:
"""Encodes a tree to a single string."""
<|body_0|>
def deserialize(self, data: str) -> TreeNode:
"""Decodes your encoded data to tree."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Codec:
def serialize(self, root: TreeNode) -> str:
"""Encodes a tree to a single string."""
if root is None:
return 'X#'
leftSerialized = self.serialize(root.left)
rightSerialized = self.serialize(root.right)
return str(root.val) + '#' + leftSerialized + rig... | the_stack_v2_python_sparse | 2021_06_28_serialize-and-deserialize-bst.py | trinhgliedt/Algo_Practice | train | 1 | |
a45844a171ea713c6917c90a037bc0154aa619e9 | [
"if 'email' not in data or data['email'] is '':\n raise MyCustomError(ExceptionType.EmptyField, 'email field should not be empty')\nif 'password' not in data or data['password'] is '':\n raise MyCustomError(ExceptionType.EmptyField, 'password field should not be empty')\nreturn True",
"if len(data['email'])... | <|body_start_0|>
if 'email' not in data or data['email'] is '':
raise MyCustomError(ExceptionType.EmptyField, 'email field should not be empty')
if 'password' not in data or data['password'] is '':
raise MyCustomError(ExceptionType.EmptyField, 'password field should not be empty'... | Validation | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Validation:
def validate_data(data: dict) -> object:
"""it takes data as input and returns boolean value :rtype: boolean"""
<|body_0|>
def validate_register(data: dict) -> object:
"""this method takes dictionary data as input and it validates the length of characters... | stack_v2_sparse_classes_36k_train_033988 | 1,450 | no_license | [
{
"docstring": "it takes data as input and returns boolean value :rtype: boolean",
"name": "validate_data",
"signature": "def validate_data(data: dict) -> object"
},
{
"docstring": "this method takes dictionary data as input and it validates the length of characters :return: True if the data is ... | 2 | stack_v2_sparse_classes_30k_train_002275 | Implement the Python class `Validation` described below.
Class description:
Implement the Validation class.
Method signatures and docstrings:
- def validate_data(data: dict) -> object: it takes data as input and returns boolean value :rtype: boolean
- def validate_register(data: dict) -> object: this method takes dic... | Implement the Python class `Validation` described below.
Class description:
Implement the Validation class.
Method signatures and docstrings:
- def validate_data(data: dict) -> object: it takes data as input and returns boolean value :rtype: boolean
- def validate_register(data: dict) -> object: this method takes dic... | ed986626949590841f5fd0f8f2fa12737bfe48a7 | <|skeleton|>
class Validation:
def validate_data(data: dict) -> object:
"""it takes data as input and returns boolean value :rtype: boolean"""
<|body_0|>
def validate_register(data: dict) -> object:
"""this method takes dictionary data as input and it validates the length of characters... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Validation:
def validate_data(data: dict) -> object:
"""it takes data as input and returns boolean value :rtype: boolean"""
if 'email' not in data or data['email'] is '':
raise MyCustomError(ExceptionType.EmptyField, 'email field should not be empty')
if 'password' not in d... | the_stack_v2_python_sparse | fundoo/fundooapp/utils.py | TarunVyda6/FundooNotes | train | 0 | |
b53e4603b387644eeccbed8a999ac75b4d1f426b | [
"f = self.dtype_f(self.init)\nself.A.mult(u, f.impl)\nfa1 = self.init.getVecArray(f.impl)\nfa1[0] = 0\nfa1[-1] = 0\nfa2 = self.init.getVecArray(f.expl)\nxa = self.init.getVecArray(u)\nfor i in range(self.xs, self.xe):\n fa2[i] = self.lambda0 ** 2 * xa[i] * (1 - xa[i] ** self.nu)\nfa2[0] = 0\nfa2[-1] = 0\nreturn ... | <|body_start_0|>
f = self.dtype_f(self.init)
self.A.mult(u, f.impl)
fa1 = self.init.getVecArray(f.impl)
fa1[0] = 0
fa1[-1] = 0
fa2 = self.init.getVecArray(f.expl)
xa = self.init.getVecArray(u)
for i in range(self.xs, self.xe):
fa2[i] = self.lam... | Problem class implementing the semi-implicit 2D Gray-Scott reaction-diffusion equation with periodic BC and PETSc | petsc_fisher_semiimplicit | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class petsc_fisher_semiimplicit:
"""Problem class implementing the semi-implicit 2D Gray-Scott reaction-diffusion equation with periodic BC and PETSc"""
def eval_f(self, u, t):
"""Routine to evaluate the RHS Args: u (dtype_u): current values t (float): current time Returns: dtype_f: the RH... | stack_v2_sparse_classes_36k_train_033989 | 16,584 | permissive | [
{
"docstring": "Routine to evaluate the RHS Args: u (dtype_u): current values t (float): current time Returns: dtype_f: the RHS",
"name": "eval_f",
"signature": "def eval_f(self, u, t)"
},
{
"docstring": "Simple linear solver for (I-factor*A)u = rhs Args: rhs (dtype_f): right-hand side for the l... | 2 | null | Implement the Python class `petsc_fisher_semiimplicit` described below.
Class description:
Problem class implementing the semi-implicit 2D Gray-Scott reaction-diffusion equation with periodic BC and PETSc
Method signatures and docstrings:
- def eval_f(self, u, t): Routine to evaluate the RHS Args: u (dtype_u): curren... | Implement the Python class `petsc_fisher_semiimplicit` described below.
Class description:
Problem class implementing the semi-implicit 2D Gray-Scott reaction-diffusion equation with periodic BC and PETSc
Method signatures and docstrings:
- def eval_f(self, u, t): Routine to evaluate the RHS Args: u (dtype_u): curren... | 1a51834bedffd4472e344bed28f4d766614b1537 | <|skeleton|>
class petsc_fisher_semiimplicit:
"""Problem class implementing the semi-implicit 2D Gray-Scott reaction-diffusion equation with periodic BC and PETSc"""
def eval_f(self, u, t):
"""Routine to evaluate the RHS Args: u (dtype_u): current values t (float): current time Returns: dtype_f: the RH... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class petsc_fisher_semiimplicit:
"""Problem class implementing the semi-implicit 2D Gray-Scott reaction-diffusion equation with periodic BC and PETSc"""
def eval_f(self, u, t):
"""Routine to evaluate the RHS Args: u (dtype_u): current values t (float): current time Returns: dtype_f: the RHS"""
... | the_stack_v2_python_sparse | pySDC/implementations/problem_classes/GeneralizedFisher_1D_PETSc.py | Parallel-in-Time/pySDC | train | 30 |
9f5e41779b1f788b16a422a70f003d4f6931b65f | [
"conditions = cars_search_query.to_conditions()\nfound_cars = db.query(Car).filter(and_(*conditions)).all()\navailability_dates = cars_search_query.availability_dates\nfound_cars = self._filter_by_availability_dates(db, found_cars, availability_dates)\nreturn found_cars",
"if availability_dates:\n cars = [_car... | <|body_start_0|>
conditions = cars_search_query.to_conditions()
found_cars = db.query(Car).filter(and_(*conditions)).all()
availability_dates = cars_search_query.availability_dates
found_cars = self._filter_by_availability_dates(db, found_cars, availability_dates)
return found_ca... | CarService | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CarService:
def get_by_criteria(self, db: Session, cars_search_query: CarsSearchQuery) -> List[Car]:
"""Returns cars matching criteria given in CarsSearchQuery"""
<|body_0|>
def _filter_by_availability_dates(self, db: Session, cars: List[Car], availability_dates: Optional[Av... | stack_v2_sparse_classes_36k_train_033990 | 1,597 | permissive | [
{
"docstring": "Returns cars matching criteria given in CarsSearchQuery",
"name": "get_by_criteria",
"signature": "def get_by_criteria(self, db: Session, cars_search_query: CarsSearchQuery) -> List[Car]"
},
{
"docstring": "Given list of cars, returns filtered list of cars that excludes cars that... | 2 | stack_v2_sparse_classes_30k_train_005174 | Implement the Python class `CarService` described below.
Class description:
Implement the CarService class.
Method signatures and docstrings:
- def get_by_criteria(self, db: Session, cars_search_query: CarsSearchQuery) -> List[Car]: Returns cars matching criteria given in CarsSearchQuery
- def _filter_by_availability... | Implement the Python class `CarService` described below.
Class description:
Implement the CarService class.
Method signatures and docstrings:
- def get_by_criteria(self, db: Session, cars_search_query: CarsSearchQuery) -> List[Car]: Returns cars matching criteria given in CarsSearchQuery
- def _filter_by_availability... | ba70199d329895a5295ceddd0ecc4c61928890dd | <|skeleton|>
class CarService:
def get_by_criteria(self, db: Session, cars_search_query: CarsSearchQuery) -> List[Car]:
"""Returns cars matching criteria given in CarsSearchQuery"""
<|body_0|>
def _filter_by_availability_dates(self, db: Session, cars: List[Car], availability_dates: Optional[Av... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CarService:
def get_by_criteria(self, db: Session, cars_search_query: CarsSearchQuery) -> List[Car]:
"""Returns cars matching criteria given in CarsSearchQuery"""
conditions = cars_search_query.to_conditions()
found_cars = db.query(Car).filter(and_(*conditions)).all()
availabil... | the_stack_v2_python_sparse | backend/app/services/cars_service.py | BartlomiejRasztabiga/Rentally | train | 2 | |
2bf9372a29a8401b64bf725faf0bcf6e2811db27 | [
"with open(pkl_path, 'r') as f:\n dd = pickle.load(f)\nself.v_template = tf.Variable(undo_chumpy(dd['v_template']), name='v_template', dtype=dtype, trainable=False)\nself.size = [self.v_template.shape[0].value, 3]\nself.num_betas = dd['shapedirs'].shape[-1]\nshapedir = np.reshape(undo_chumpy(dd['shapedirs']), [-... | <|body_start_0|>
with open(pkl_path, 'r') as f:
dd = pickle.load(f)
self.v_template = tf.Variable(undo_chumpy(dd['v_template']), name='v_template', dtype=dtype, trainable=False)
self.size = [self.v_template.shape[0].value, 3]
self.num_betas = dd['shapedirs'].shape[-1]
... | SMPL | [
"BSD-3-Clause",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SMPL:
def __init__(self, pkl_path, joint_type='cocoplus', dtype=tf.float32):
"""pkl_path is the path to a SMPL model"""
<|body_0|>
def __call__(self, beta, theta, get_skin=False, name=None):
"""Obtain SMPL with shape (beta) & pose (theta) inputs. Theta includes the g... | stack_v2_sparse_classes_36k_train_033991 | 5,935 | permissive | [
{
"docstring": "pkl_path is the path to a SMPL model",
"name": "__init__",
"signature": "def __init__(self, pkl_path, joint_type='cocoplus', dtype=tf.float32)"
},
{
"docstring": "Obtain SMPL with shape (beta) & pose (theta) inputs. Theta includes the global rotation. Args: beta: N x 10 theta: N ... | 2 | stack_v2_sparse_classes_30k_train_019585 | Implement the Python class `SMPL` described below.
Class description:
Implement the SMPL class.
Method signatures and docstrings:
- def __init__(self, pkl_path, joint_type='cocoplus', dtype=tf.float32): pkl_path is the path to a SMPL model
- def __call__(self, beta, theta, get_skin=False, name=None): Obtain SMPL with... | Implement the Python class `SMPL` described below.
Class description:
Implement the SMPL class.
Method signatures and docstrings:
- def __init__(self, pkl_path, joint_type='cocoplus', dtype=tf.float32): pkl_path is the path to a SMPL model
- def __call__(self, beta, theta, get_skin=False, name=None): Obtain SMPL with... | 6ff7fc867e9e185d547ada11713a60fbf3caa902 | <|skeleton|>
class SMPL:
def __init__(self, pkl_path, joint_type='cocoplus', dtype=tf.float32):
"""pkl_path is the path to a SMPL model"""
<|body_0|>
def __call__(self, beta, theta, get_skin=False, name=None):
"""Obtain SMPL with shape (beta) & pose (theta) inputs. Theta includes the g... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SMPL:
def __init__(self, pkl_path, joint_type='cocoplus', dtype=tf.float32):
"""pkl_path is the path to a SMPL model"""
with open(pkl_path, 'r') as f:
dd = pickle.load(f)
self.v_template = tf.Variable(undo_chumpy(dd['v_template']), name='v_template', dtype=dtype, trainable=... | the_stack_v2_python_sparse | src/tf_smpl/batch_smpl.py | akanazawa/motion_reconstruction | train | 297 | |
9c397ea40a8b4ad8a5d50d7daadd5034c9214943 | [
"plugin = Plugin(distribution='norm')\nself.assertEqual(plugin.distribution, stats.norm)\nself.assertEqual(plugin.shape_parameters, [])",
"plugin = Plugin(distribution='truncnorm', shape_parameters=[0, np.inf])\nself.assertEqual(plugin.distribution, scipy_cont_distns.truncnorm)\nself.assertEqual(plugin.shape_para... | <|body_start_0|>
plugin = Plugin(distribution='norm')
self.assertEqual(plugin.distribution, stats.norm)
self.assertEqual(plugin.shape_parameters, [])
<|end_body_0|>
<|body_start_1|>
plugin = Plugin(distribution='truncnorm', shape_parameters=[0, np.inf])
self.assertEqual(plugin.d... | Test the __init__ method. | Test__init__ | [
"BSD-3-Clause",
"LicenseRef-scancode-proprietary-license"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Test__init__:
"""Test the __init__ method."""
def test_valid_distribution(self):
"""Test for a valid distribution."""
<|body_0|>
def test_valid_distribution_with_shape_parameters(self):
"""Test for a valid distribution with shape parameters."""
<|body_1|>... | stack_v2_sparse_classes_36k_train_033992 | 5,343 | permissive | [
{
"docstring": "Test for a valid distribution.",
"name": "test_valid_distribution",
"signature": "def test_valid_distribution(self)"
},
{
"docstring": "Test for a valid distribution with shape parameters.",
"name": "test_valid_distribution_with_shape_parameters",
"signature": "def test_v... | 4 | null | Implement the Python class `Test__init__` described below.
Class description:
Test the __init__ method.
Method signatures and docstrings:
- def test_valid_distribution(self): Test for a valid distribution.
- def test_valid_distribution_with_shape_parameters(self): Test for a valid distribution with shape parameters.
... | Implement the Python class `Test__init__` described below.
Class description:
Test the __init__ method.
Method signatures and docstrings:
- def test_valid_distribution(self): Test for a valid distribution.
- def test_valid_distribution_with_shape_parameters(self): Test for a valid distribution with shape parameters.
... | cd2c9019944345df1e703bf8f625db537ad9f559 | <|skeleton|>
class Test__init__:
"""Test the __init__ method."""
def test_valid_distribution(self):
"""Test for a valid distribution."""
<|body_0|>
def test_valid_distribution_with_shape_parameters(self):
"""Test for a valid distribution with shape parameters."""
<|body_1|>... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Test__init__:
"""Test the __init__ method."""
def test_valid_distribution(self):
"""Test for a valid distribution."""
plugin = Plugin(distribution='norm')
self.assertEqual(plugin.distribution, stats.norm)
self.assertEqual(plugin.shape_parameters, [])
def test_valid_di... | the_stack_v2_python_sparse | improver_tests/ensemble_copula_coupling/test_ConvertLocationAndScaleParameters.py | metoppv/improver | train | 101 |
e51e966d8f81dec7292f72803b5a98978663d81c | [
"year = self.get_year()\nmonth = self.get_month()\ndate = _date_from_string(year, self.get_year_format(), month, self.get_month_format())\nif queryset is None:\n queryset = self.get_queryset()\nif not self.allow_future and date > date.today():\n raise Http404('Future {} not available because{}. allow_future i... | <|body_start_0|>
year = self.get_year()
month = self.get_month()
date = _date_from_string(year, self.get_year_format(), month, self.get_month_format())
if queryset is None:
queryset = self.get_queryset()
if not self.allow_future and date > date.today():
ra... | DateObjectMixin | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DateObjectMixin:
def get_object(self, queryset=None):
"""In this method django builds the keyword arguments for the query(to find the object in the database) The method creates the date kwargs for queryset and then pass that query set to the super queryset that contains the slug. :param ... | stack_v2_sparse_classes_36k_train_033993 | 6,230 | permissive | [
{
"docstring": "In this method django builds the keyword arguments for the query(to find the object in the database) The method creates the date kwargs for queryset and then pass that query set to the super queryset that contains the slug. :param queryset: :return:",
"name": "get_object",
"signature": "... | 2 | stack_v2_sparse_classes_30k_train_015443 | Implement the Python class `DateObjectMixin` described below.
Class description:
Implement the DateObjectMixin class.
Method signatures and docstrings:
- def get_object(self, queryset=None): In this method django builds the keyword arguments for the query(to find the object in the database) The method creates the dat... | Implement the Python class `DateObjectMixin` described below.
Class description:
Implement the DateObjectMixin class.
Method signatures and docstrings:
- def get_object(self, queryset=None): In this method django builds the keyword arguments for the query(to find the object in the database) The method creates the dat... | 26f11c944c34cd11b5961ec1b5eeb5cb3a7acdf8 | <|skeleton|>
class DateObjectMixin:
def get_object(self, queryset=None):
"""In this method django builds the keyword arguments for the query(to find the object in the database) The method creates the date kwargs for queryset and then pass that query set to the super queryset that contains the slug. :param ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DateObjectMixin:
def get_object(self, queryset=None):
"""In this method django builds the keyword arguments for the query(to find the object in the database) The method creates the date kwargs for queryset and then pass that query set to the super queryset that contains the slug. :param queryset: :ret... | the_stack_v2_python_sparse | suorganizer/blogs/mixins.py | mohammadasim/suorganiser | train | 0 | |
d8fd92235c7250909a84326b40d03d184af10f6f | [
"rst = {'data': {'list': []}}\ntry:\n rst['errcode'] = 0\n page_num = int(request.params['pageNum']) - 1\n page_size = int(request.params['pageSize'])\n query = request.params['query']\n model = http.request.env['project_manage.project_manage']\n domain = []\n if query and query != '':\n ... | <|body_start_0|>
rst = {'data': {'list': []}}
try:
rst['errcode'] = 0
page_num = int(request.params['pageNum']) - 1
page_size = int(request.params['pageSize'])
query = request.params['query']
model = http.request.env['project_manage.project_man... | 接口 | ProjectManage | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProjectManage:
"""接口"""
def get_project(self, **kw):
"""取得所有的项目 :param kw: :return:"""
<|body_0|>
def get_project_info(self, **kw):
"""取得项目信息 :param kw: :return:"""
<|body_1|>
def get_project_info(self, **kw):
"""获取登陆用户的信息 :param kw: :return:... | stack_v2_sparse_classes_36k_train_033994 | 3,532 | no_license | [
{
"docstring": "取得所有的项目 :param kw: :return:",
"name": "get_project",
"signature": "def get_project(self, **kw)"
},
{
"docstring": "取得项目信息 :param kw: :return:",
"name": "get_project_info",
"signature": "def get_project_info(self, **kw)"
},
{
"docstring": "获取登陆用户的信息 :param kw: :ret... | 3 | null | Implement the Python class `ProjectManage` described below.
Class description:
接口
Method signatures and docstrings:
- def get_project(self, **kw): 取得所有的项目 :param kw: :return:
- def get_project_info(self, **kw): 取得项目信息 :param kw: :return:
- def get_project_info(self, **kw): 获取登陆用户的信息 :param kw: :return: | Implement the Python class `ProjectManage` described below.
Class description:
接口
Method signatures and docstrings:
- def get_project(self, **kw): 取得所有的项目 :param kw: :return:
- def get_project_info(self, **kw): 取得项目信息 :param kw: :return:
- def get_project_info(self, **kw): 获取登陆用户的信息 :param kw: :return:
<|skeleton|>
... | 13b428a5c4ade6278e3e5e996ef10d9fb0fea4b9 | <|skeleton|>
class ProjectManage:
"""接口"""
def get_project(self, **kw):
"""取得所有的项目 :param kw: :return:"""
<|body_0|>
def get_project_info(self, **kw):
"""取得项目信息 :param kw: :return:"""
<|body_1|>
def get_project_info(self, **kw):
"""获取登陆用户的信息 :param kw: :return:... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ProjectManage:
"""接口"""
def get_project(self, **kw):
"""取得所有的项目 :param kw: :return:"""
rst = {'data': {'list': []}}
try:
rst['errcode'] = 0
page_num = int(request.params['pageNum']) - 1
page_size = int(request.params['pageSize'])
que... | the_stack_v2_python_sparse | mdias_addons/project_manage/controllers/controllers.py | rezaghanimi/main_mdias | train | 0 |
20d30ecdbe34ec6c50e6c8d605bcd6f89be0e765 | [
"max_end = min((itv[E] for itvs in schedule for itv in itvs))\nq = []\nfor i, itvs in enumerate(schedule):\n j = 0\n itv = itvs[j]\n heapq.heappush(q, (itv[S], i, j))\nret = []\nwhile q:\n _, i, j = heapq.heappop(q)\n itv = schedule[i][j]\n if max_end < itv[S]:\n ret.append([max_end, itv[S]... | <|body_start_0|>
max_end = min((itv[E] for itvs in schedule for itv in itvs))
q = []
for i, itvs in enumerate(schedule):
j = 0
itv = itvs[j]
heapq.heappush(q, (itv[S], i, j))
ret = []
while q:
_, i, j = heapq.heappop(q)
... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def employeeFreeTime(self, schedule: List[List[List[int]]]) -> List[List[int]]:
"""Method 1 Looking at the head of each list through iterator Merge interval of heads, need to sort, then use heap After merge, find the open interval No need to merge, find the max end time, and co... | stack_v2_sparse_classes_36k_train_033995 | 4,451 | permissive | [
{
"docstring": "Method 1 Looking at the head of each list through iterator Merge interval of heads, need to sort, then use heap After merge, find the open interval No need to merge, find the max end time, and compare to the min start time Method 2 Better algorithm to find the open interval [s, e], we can think ... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def employeeFreeTime(self, schedule: List[List[List[int]]]) -> List[List[int]]: Method 1 Looking at the head of each list through iterator Merge interval of heads, need to sort, ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def employeeFreeTime(self, schedule: List[List[List[int]]]) -> List[List[int]]: Method 1 Looking at the head of each list through iterator Merge interval of heads, need to sort, ... | c82a0a5f8d5e027c614612de7f396d28e8511155 | <|skeleton|>
class Solution:
def employeeFreeTime(self, schedule: List[List[List[int]]]) -> List[List[int]]:
"""Method 1 Looking at the head of each list through iterator Merge interval of heads, need to sort, then use heap After merge, find the open interval No need to merge, find the max end time, and co... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def employeeFreeTime(self, schedule: List[List[List[int]]]) -> List[List[int]]:
"""Method 1 Looking at the head of each list through iterator Merge interval of heads, need to sort, then use heap After merge, find the open interval No need to merge, find the max end time, and compare to the m... | the_stack_v2_python_sparse | LeetCode/759 Employee Free Time.py | firefeifei/CodePool | train | 1 | |
e63d64cb04c0c49b58f5ef17893f5d4da6233fab | [
"self.validate_only_one_lead(data)\nself.validate_force_delete(data)\nreturn data",
"order = self.context['order']\nforce_delete = self.context['force_delete']\nif order.status != OrderStatus.DRAFT and force_delete:\n raise ValidationError('You cannot delete any assignees at this stage.')\nreturn data",
"ord... | <|body_start_0|>
self.validate_only_one_lead(data)
self.validate_force_delete(data)
return data
<|end_body_0|>
<|body_start_1|>
order = self.context['order']
force_delete = self.context['force_delete']
if order.status != OrderStatus.DRAFT and force_delete:
ra... | DRF List serializer for OrderAssignee(s). | OrderAssigneeListSerializer | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OrderAssigneeListSerializer:
"""DRF List serializer for OrderAssignee(s)."""
def validate(self, data):
"""Validate the list of assignees."""
<|body_0|>
def validate_force_delete(self, data):
"""Validate that assignees cannot be deleted if the order.status == paid... | stack_v2_sparse_classes_36k_train_033996 | 21,268 | permissive | [
{
"docstring": "Validate the list of assignees.",
"name": "validate",
"signature": "def validate(self, data)"
},
{
"docstring": "Validate that assignees cannot be deleted if the order.status == paid.",
"name": "validate_force_delete",
"signature": "def validate_force_delete(self, data)"
... | 4 | null | Implement the Python class `OrderAssigneeListSerializer` described below.
Class description:
DRF List serializer for OrderAssignee(s).
Method signatures and docstrings:
- def validate(self, data): Validate the list of assignees.
- def validate_force_delete(self, data): Validate that assignees cannot be deleted if the... | Implement the Python class `OrderAssigneeListSerializer` described below.
Class description:
DRF List serializer for OrderAssignee(s).
Method signatures and docstrings:
- def validate(self, data): Validate the list of assignees.
- def validate_force_delete(self, data): Validate that assignees cannot be deleted if the... | a92faabf73fb93b5bfd94fd465eafc3e29aa6d8e | <|skeleton|>
class OrderAssigneeListSerializer:
"""DRF List serializer for OrderAssignee(s)."""
def validate(self, data):
"""Validate the list of assignees."""
<|body_0|>
def validate_force_delete(self, data):
"""Validate that assignees cannot be deleted if the order.status == paid... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class OrderAssigneeListSerializer:
"""DRF List serializer for OrderAssignee(s)."""
def validate(self, data):
"""Validate the list of assignees."""
self.validate_only_one_lead(data)
self.validate_force_delete(data)
return data
def validate_force_delete(self, data):
"... | the_stack_v2_python_sparse | datahub/omis/order/serializers.py | cgsunkel/data-hub-api | train | 0 |
ee915f61ab1415e4035b9d0ebebe89163c0bbcbf | [
"if style != None:\n options = {'bright': '1', 'dim': '2', 'underline': '4', 'black': '30', 'red': '31', 'green': '32', 'yellow': '33', 'blue': '34', 'magenta': '35', 'cyan': '36', 'white': '37'}\n code = options[style]\n if bold:\n code = '1;%s' % code\n return '\\x1b[' + code + 'm%s\\x1b[0m'\ne... | <|body_start_0|>
if style != None:
options = {'bright': '1', 'dim': '2', 'underline': '4', 'black': '30', 'red': '31', 'green': '32', 'yellow': '33', 'blue': '34', 'magenta': '35', 'cyan': '36', 'white': '37'}
code = options[style]
if bold:
code = '1;%s' % cod... | Print2Console | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Print2Console:
def get_format_options(style, bold):
"""Define the ANSI escape sequences for modifying the style of the output"""
<|body_0|>
def p(format_str, var, first_col_w=24, line_width=72, style=None, bold=False, decimals=2):
"""The variables to be printed ('var... | stack_v2_sparse_classes_36k_train_033997 | 2,722 | permissive | [
{
"docstring": "Define the ANSI escape sequences for modifying the style of the output",
"name": "get_format_options",
"signature": "def get_format_options(style, bold)"
},
{
"docstring": "The variables to be printed ('var') must be added inside a list. First colum width is selected 24 character... | 2 | null | Implement the Python class `Print2Console` described below.
Class description:
Implement the Print2Console class.
Method signatures and docstrings:
- def get_format_options(style, bold): Define the ANSI escape sequences for modifying the style of the output
- def p(format_str, var, first_col_w=24, line_width=72, styl... | Implement the Python class `Print2Console` described below.
Class description:
Implement the Print2Console class.
Method signatures and docstrings:
- def get_format_options(style, bold): Define the ANSI escape sequences for modifying the style of the output
- def p(format_str, var, first_col_w=24, line_width=72, styl... | 2b0e44b166d699ace2b103d064e45e8da997bdb5 | <|skeleton|>
class Print2Console:
def get_format_options(style, bold):
"""Define the ANSI escape sequences for modifying the style of the output"""
<|body_0|>
def p(format_str, var, first_col_w=24, line_width=72, style=None, bold=False, decimals=2):
"""The variables to be printed ('var... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Print2Console:
def get_format_options(style, bold):
"""Define the ANSI escape sequences for modifying the style of the output"""
if style != None:
options = {'bright': '1', 'dim': '2', 'underline': '4', 'black': '30', 'red': '31', 'green': '32', 'yellow': '33', 'blue': '34', 'magen... | the_stack_v2_python_sparse | p3iv_utils/src/p3iv_utils/consoleprint.py | philippbrusius/P3IV | train | 0 | |
53f36807f85cb5c6de0e623b2795c303145f83d3 | [
"super().__init__()\nself.hidden_channels = hidden_channels\nself.num_filters = num_filters\nself.num_interactions = num_interactions\nself.cutoff = cutoff\nself.embedding = Embedding(100, hidden_channels, max_norm=10.0)\nself.interactions = ModuleList()\nfor _ in range(num_interactions):\n block = InteractionBl... | <|body_start_0|>
super().__init__()
self.hidden_channels = hidden_channels
self.num_filters = num_filters
self.num_interactions = num_interactions
self.cutoff = cutoff
self.embedding = Embedding(100, hidden_channels, max_norm=10.0)
self.interactions = ModuleList()... | SchNet encoder. | SchNetEncoder | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SchNetEncoder:
"""SchNet encoder."""
def __init__(self, hidden_channels: int=128, num_filters: int=128, num_interactions: int=6, edge_channels: int=100, cutoff: float=10.0, smooth: bool=False) -> None:
"""Construct a SchNet encoder. Args: hidden_channels: number of hidden channels. n... | stack_v2_sparse_classes_36k_train_033998 | 15,380 | permissive | [
{
"docstring": "Construct a SchNet encoder. Args: hidden_channels: number of hidden channels. num_filters: number of filters. num_interactions: number of interactions. edge_channels: number of edge channels. cutoff: cutoff distance. smooth: whether to use smooth cutoff.",
"name": "__init__",
"signature"... | 2 | stack_v2_sparse_classes_30k_train_014910 | Implement the Python class `SchNetEncoder` described below.
Class description:
SchNet encoder.
Method signatures and docstrings:
- def __init__(self, hidden_channels: int=128, num_filters: int=128, num_interactions: int=6, edge_channels: int=100, cutoff: float=10.0, smooth: bool=False) -> None: Construct a SchNet enc... | Implement the Python class `SchNetEncoder` described below.
Class description:
SchNet encoder.
Method signatures and docstrings:
- def __init__(self, hidden_channels: int=128, num_filters: int=128, num_interactions: int=6, edge_channels: int=100, cutoff: float=10.0, smooth: bool=False) -> None: Construct a SchNet enc... | 0b69b7d5b261f2f9af3984793c1295b9b80cd01a | <|skeleton|>
class SchNetEncoder:
"""SchNet encoder."""
def __init__(self, hidden_channels: int=128, num_filters: int=128, num_interactions: int=6, edge_channels: int=100, cutoff: float=10.0, smooth: bool=False) -> None:
"""Construct a SchNet encoder. Args: hidden_channels: number of hidden channels. n... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SchNetEncoder:
"""SchNet encoder."""
def __init__(self, hidden_channels: int=128, num_filters: int=128, num_interactions: int=6, edge_channels: int=100, cutoff: float=10.0, smooth: bool=False) -> None:
"""Construct a SchNet encoder. Args: hidden_channels: number of hidden channels. num_filters: n... | the_stack_v2_python_sparse | src/gt4sd/algorithms/generation/diffusion/geodiff/model/layers.py | GT4SD/gt4sd-core | train | 239 |
65e234d719cc214e5dc0196fa270295bbff27cd2 | [
"params = {'action': 'query', 'meta': 'notifications', 'notformat': 'special'}\nfor key, value in kwargs.items():\n params['not' + key] = value\ndata = self.simple_request(**params).submit()\nnotifications = data['query']['notifications']['list']\nreturn (Notification.fromJSON(self, notification) for notificatio... | <|body_start_0|>
params = {'action': 'query', 'meta': 'notifications', 'notformat': 'special'}
for key, value in kwargs.items():
params['not' + key] = value
data = self.simple_request(**params).submit()
notifications = data['query']['notifications']['list']
return (No... | APISite mixin for Echo extension. | EchoMixin | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EchoMixin:
"""APISite mixin for Echo extension."""
def notifications(self, **kwargs):
"""Yield Notification objects from the Echo extension. :keyword Optional[str] format: If specified, notifications will be returned formatted this way. Its value is either ``model``, ``special`` or `... | stack_v2_sparse_classes_36k_train_033999 | 28,091 | permissive | [
{
"docstring": "Yield Notification objects from the Echo extension. :keyword Optional[str] format: If specified, notifications will be returned formatted this way. Its value is either ``model``, ``special`` or ``None``. Default is ``special``. .. seealso:: :api:`Notifications` for other keywords.",
"name": ... | 2 | null | Implement the Python class `EchoMixin` described below.
Class description:
APISite mixin for Echo extension.
Method signatures and docstrings:
- def notifications(self, **kwargs): Yield Notification objects from the Echo extension. :keyword Optional[str] format: If specified, notifications will be returned formatted ... | Implement the Python class `EchoMixin` described below.
Class description:
APISite mixin for Echo extension.
Method signatures and docstrings:
- def notifications(self, **kwargs): Yield Notification objects from the Echo extension. :keyword Optional[str] format: If specified, notifications will be returned formatted ... | 5c01e6bfcd328bc6eae643e661f1a0ae57612808 | <|skeleton|>
class EchoMixin:
"""APISite mixin for Echo extension."""
def notifications(self, **kwargs):
"""Yield Notification objects from the Echo extension. :keyword Optional[str] format: If specified, notifications will be returned formatted this way. Its value is either ``model``, ``special`` or `... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EchoMixin:
"""APISite mixin for Echo extension."""
def notifications(self, **kwargs):
"""Yield Notification objects from the Echo extension. :keyword Optional[str] format: If specified, notifications will be returned formatted this way. Its value is either ``model``, ``special`` or ``None``. Defa... | the_stack_v2_python_sparse | pywikibot/site/_extensions.py | wikimedia/pywikibot | train | 432 |
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