blob_id stringlengths 40 40 | bodies listlengths 2 6 | bodies_text stringlengths 196 7.73k | class_docstring stringlengths 0 700 | class_name stringlengths 1 86 | detected_licenses listlengths 0 45 | format_version stringclasses 1
value | full_text stringlengths 467 8.64k | id stringlengths 40 40 | length_bytes int64 515 49.7k | license_type stringclasses 2
values | methods listlengths 2 6 | n_methods int64 2 6 | original_id stringlengths 38 40 ⌀ | prompt stringlengths 160 3.93k | prompted_full_text stringlengths 681 10.7k | revision_id stringlengths 40 40 | skeleton stringlengths 162 4.09k | snapshot_name stringclasses 1
value | snapshot_source_dir stringclasses 1
value | solution stringlengths 331 8.3k | source stringclasses 1
value | source_path stringlengths 5 177 | source_repo stringlengths 6 88 | split stringclasses 1
value | star_events_count int64 0 209k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
b3a6eac109954d03992f938dc52c1c7431ba60a8 | [
"ret_head = head.next if head and head.next else head\npp_head = None\nwhile head:\n if not head.next:\n break\n pre_head = head\n cur_head = head.next\n next_head = cur_head.next\n cur_head.next = pre_head\n pre_head.next = next_head\n if pp_head:\n pp_head.next = cur_head\n p... | <|body_start_0|>
ret_head = head.next if head and head.next else head
pp_head = None
while head:
if not head.next:
break
pre_head = head
cur_head = head.next
next_head = cur_head.next
cur_head.next = pre_head
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def swapPairs(self, head):
""":type head: ListNode :rtype: ListNode"""
<|body_0|>
def rewrite(self, head):
""":type head: ListNode :rtype: ListNode"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
ret_head = head.next if head and head.next ... | stack_v2_sparse_classes_10k_train_003200 | 2,173 | no_license | [
{
"docstring": ":type head: ListNode :rtype: ListNode",
"name": "swapPairs",
"signature": "def swapPairs(self, head)"
},
{
"docstring": ":type head: ListNode :rtype: ListNode",
"name": "rewrite",
"signature": "def rewrite(self, head)"
}
] | 2 | stack_v2_sparse_classes_30k_train_000953 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def swapPairs(self, head): :type head: ListNode :rtype: ListNode
- def rewrite(self, head): :type head: ListNode :rtype: ListNode | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def swapPairs(self, head): :type head: ListNode :rtype: ListNode
- def rewrite(self, head): :type head: ListNode :rtype: ListNode
<|skeleton|>
class Solution:
def swapPairs... | 6350568d16b0f8c49a020f055bb6d72e2705ea56 | <|skeleton|>
class Solution:
def swapPairs(self, head):
""":type head: ListNode :rtype: ListNode"""
<|body_0|>
def rewrite(self, head):
""":type head: ListNode :rtype: ListNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def swapPairs(self, head):
""":type head: ListNode :rtype: ListNode"""
ret_head = head.next if head and head.next else head
pp_head = None
while head:
if not head.next:
break
pre_head = head
cur_head = head.next
... | the_stack_v2_python_sparse | co_ms/24_Swap_Nodes_in_Pairs.py | vsdrun/lc_public | train | 6 | |
fbe6330197adcf0c74bd6917a81d1e4de6597b7d | [
"skeinforge_profile.addListsToCraftTypeRepository('skeinforge_application.skeinforge.html', self)\nself.fileNameInput = settings.FileNameInput().getFromFileName(fabmetheus_interpret.getGNUTranslatorGcodeFileTypeTuples(), 'Open File for Skeinforge', self, '')\nself.profileType = settings.MenuButtonDisplay().getFromN... | <|body_start_0|>
skeinforge_profile.addListsToCraftTypeRepository('skeinforge_application.skeinforge.html', self)
self.fileNameInput = settings.FileNameInput().getFromFileName(fabmetheus_interpret.getGNUTranslatorGcodeFileTypeTuples(), 'Open File for Skeinforge', self, '')
self.profileType = set... | A class to handle the skeinforge settings. | SkeinforgeRepository | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SkeinforgeRepository:
"""A class to handle the skeinforge settings."""
def __init__(self):
"""Set the default settings, execute title & settings fileName."""
<|body_0|>
def execute(self):
"""Skeinforge button has been clicked."""
<|body_1|>
def save(... | stack_v2_sparse_classes_10k_train_003201 | 29,747 | no_license | [
{
"docstring": "Set the default settings, execute title & settings fileName.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Skeinforge button has been clicked.",
"name": "execute",
"signature": "def execute(self)"
},
{
"docstring": "Profile has been sa... | 3 | stack_v2_sparse_classes_30k_train_003816 | Implement the Python class `SkeinforgeRepository` described below.
Class description:
A class to handle the skeinforge settings.
Method signatures and docstrings:
- def __init__(self): Set the default settings, execute title & settings fileName.
- def execute(self): Skeinforge button has been clicked.
- def save(self... | Implement the Python class `SkeinforgeRepository` described below.
Class description:
A class to handle the skeinforge settings.
Method signatures and docstrings:
- def __init__(self): Set the default settings, execute title & settings fileName.
- def execute(self): Skeinforge button has been clicked.
- def save(self... | c1b00a76f1550df2cbb457248205159e51fd4308 | <|skeleton|>
class SkeinforgeRepository:
"""A class to handle the skeinforge settings."""
def __init__(self):
"""Set the default settings, execute title & settings fileName."""
<|body_0|>
def execute(self):
"""Skeinforge button has been clicked."""
<|body_1|>
def save(... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SkeinforgeRepository:
"""A class to handle the skeinforge settings."""
def __init__(self):
"""Set the default settings, execute title & settings fileName."""
skeinforge_profile.addListsToCraftTypeRepository('skeinforge_application.skeinforge.html', self)
self.fileNameInput = setti... | the_stack_v2_python_sparse | skeinforge_application/skeinforge.py | amsler/skeinforge | train | 10 |
267e2d41e316ca9da35178d18f9b95b644442539 | [
"if not self.base:\n raise AttributeError('Factory.base must be set to a Component')\nsuper().__init__(config=config, parent=tool, **kwargs)\nself.kwargs = copy(kwargs)",
"if self.product:\n return self.product\nelse:\n raise AttributeError('The user has not specified a product for {}'.format(self.__clas... | <|body_start_0|>
if not self.base:
raise AttributeError('Factory.base must be set to a Component')
super().__init__(config=config, parent=tool, **kwargs)
self.kwargs = copy(kwargs)
<|end_body_0|>
<|body_start_1|>
if self.product:
return self.product
else:... | A base class for all class factories that exist in the `Tools`/`Components` frameworks. To create a Factory, inherit this class and set `base` to the base-class of the Factory. The traits of the sub-classes are automatically added to the Factory (and are included in the help message). The traits and kwargsthat correctl... | Factory | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Factory:
"""A base class for all class factories that exist in the `Tools`/`Components` frameworks. To create a Factory, inherit this class and set `base` to the base-class of the Factory. The traits of the sub-classes are automatically added to the Factory (and are included in the help message).... | stack_v2_sparse_classes_10k_train_003202 | 8,843 | no_license | [
{
"docstring": "Base Factory class Parameters ---------- config : traitlets.loader.Config Configuration specified by config file or cmdline arguments. Used to set traitlet values. Set to None if no configuration to pass. tool : ctapipe.core.Tool Tool executable that is calling this component. Passes the correct... | 5 | stack_v2_sparse_classes_30k_train_007114 | Implement the Python class `Factory` described below.
Class description:
A base class for all class factories that exist in the `Tools`/`Components` frameworks. To create a Factory, inherit this class and set `base` to the base-class of the Factory. The traits of the sub-classes are automatically added to the Factory ... | Implement the Python class `Factory` described below.
Class description:
A base class for all class factories that exist in the `Tools`/`Components` frameworks. To create a Factory, inherit this class and set `base` to the base-class of the Factory. The traits of the sub-classes are automatically added to the Factory ... | 1cb6f215f3a9c34e18f2d49bd36bbf9e757f5847 | <|skeleton|>
class Factory:
"""A base class for all class factories that exist in the `Tools`/`Components` frameworks. To create a Factory, inherit this class and set `base` to the base-class of the Factory. The traits of the sub-classes are automatically added to the Factory (and are included in the help message).... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Factory:
"""A base class for all class factories that exist in the `Tools`/`Components` frameworks. To create a Factory, inherit this class and set `base` to the base-class of the Factory. The traits of the sub-classes are automatically added to the Factory (and are included in the help message). The traits a... | the_stack_v2_python_sparse | ctapipe/core/factory.py | 18333/ctapipe | train | 1 |
2093a28f0be7675b204dab7f6fa01d38bb512cc3 | [
"self.inletNode = inletNode\nself.idealinletNode = idealinletNode\nself.outletNode = outletNode",
"\"\"\"the cycle based on compressor inlet\"\"\"\n'node outelt = state 1'\n'Exp'\n'State 1, P1,T1 known'\n'pressure loss and heat exchange parameters'\nself.dp = node[self.inletNode].p - node[self.idealinletNode].p\n... | <|body_start_0|>
self.inletNode = inletNode
self.idealinletNode = idealinletNode
self.outletNode = outletNode
<|end_body_0|>
<|body_start_1|>
"""the cycle based on compressor inlet"""
'node outelt = state 1'
'Exp'
'State 1, P1,T1 known'
'pressure loss and... | evaporator component | Evaporator | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Evaporator:
"""evaporator component"""
def __init__(self, inletNode, outletNode, idealinletNode):
"""init evaporator node"""
<|body_0|>
def simulate(self, node, mdot_a, cp, Ta_in, Ta_out):
"""ideal"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_10k_train_003203 | 3,605 | no_license | [
{
"docstring": "init evaporator node",
"name": "__init__",
"signature": "def __init__(self, inletNode, outletNode, idealinletNode)"
},
{
"docstring": "ideal",
"name": "simulate",
"signature": "def simulate(self, node, mdot_a, cp, Ta_in, Ta_out)"
}
] | 2 | stack_v2_sparse_classes_30k_test_000029 | Implement the Python class `Evaporator` described below.
Class description:
evaporator component
Method signatures and docstrings:
- def __init__(self, inletNode, outletNode, idealinletNode): init evaporator node
- def simulate(self, node, mdot_a, cp, Ta_in, Ta_out): ideal | Implement the Python class `Evaporator` described below.
Class description:
evaporator component
Method signatures and docstrings:
- def __init__(self, inletNode, outletNode, idealinletNode): init evaporator node
- def simulate(self, node, mdot_a, cp, Ta_in, Ta_out): ideal
<|skeleton|>
class Evaporator:
"""evapo... | 6843fd139ff2355b98eac0ac9cf09aee6fede7cd | <|skeleton|>
class Evaporator:
"""evaporator component"""
def __init__(self, inletNode, outletNode, idealinletNode):
"""init evaporator node"""
<|body_0|>
def simulate(self, node, mdot_a, cp, Ta_in, Ta_out):
"""ideal"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Evaporator:
"""evaporator component"""
def __init__(self, inletNode, outletNode, idealinletNode):
"""init evaporator node"""
self.inletNode = inletNode
self.idealinletNode = idealinletNode
self.outletNode = outletNode
def simulate(self, node, mdot_a, cp, Ta_in, Ta_out... | the_stack_v2_python_sparse | original/component.py | Nathanzhn/GA4 | train | 0 |
f0d84f8bd3334c01e032974b70b19aa3fc15485f | [
"self.files_downloaded = 0\nself.files_processed = 0\nself.exception_count = 0\nself.now = time_utils.get_utc_now()\nself.grib_processor = GribFileProcessor(station_source)\nself.model_type: ModelEnum = model_type\nif self.model_type == ModelEnum.GDPS:\n self.projection = ProjectionEnum.LATLON_15X_15\nelif self.... | <|body_start_0|>
self.files_downloaded = 0
self.files_processed = 0
self.exception_count = 0
self.now = time_utils.get_utc_now()
self.grib_processor = GribFileProcessor(station_source)
self.model_type: ModelEnum = model_type
if self.model_type == ModelEnum.GDPS:
... | Class that orchestrates downloading and processing of weather model grib files from environment Canada. | EnvCanada | [
"Apache-2.0",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EnvCanada:
"""Class that orchestrates downloading and processing of weather model grib files from environment Canada."""
def __init__(self, model_type: ModelEnum, station_source: StationSourceEnum=StationSourceEnum.UNSPECIFIED):
"""Prep variables"""
<|body_0|>
def proces... | stack_v2_sparse_classes_10k_train_003204 | 17,429 | permissive | [
{
"docstring": "Prep variables",
"name": "__init__",
"signature": "def __init__(self, model_type: ModelEnum, station_source: StationSourceEnum=StationSourceEnum.UNSPECIFIED)"
},
{
"docstring": "Process the urls for a model run.",
"name": "process_model_run_urls",
"signature": "def proces... | 4 | null | Implement the Python class `EnvCanada` described below.
Class description:
Class that orchestrates downloading and processing of weather model grib files from environment Canada.
Method signatures and docstrings:
- def __init__(self, model_type: ModelEnum, station_source: StationSourceEnum=StationSourceEnum.UNSPECIFI... | Implement the Python class `EnvCanada` described below.
Class description:
Class that orchestrates downloading and processing of weather model grib files from environment Canada.
Method signatures and docstrings:
- def __init__(self, model_type: ModelEnum, station_source: StationSourceEnum=StationSourceEnum.UNSPECIFI... | 0ba707b0eddc280240964efa481988df92046e6a | <|skeleton|>
class EnvCanada:
"""Class that orchestrates downloading and processing of weather model grib files from environment Canada."""
def __init__(self, model_type: ModelEnum, station_source: StationSourceEnum=StationSourceEnum.UNSPECIFIED):
"""Prep variables"""
<|body_0|>
def proces... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class EnvCanada:
"""Class that orchestrates downloading and processing of weather model grib files from environment Canada."""
def __init__(self, model_type: ModelEnum, station_source: StationSourceEnum=StationSourceEnum.UNSPECIFIED):
"""Prep variables"""
self.files_downloaded = 0
self.... | the_stack_v2_python_sparse | api/app/jobs/env_canada.py | bcgov/wps | train | 35 |
f1a40cb215256b2e6979a718ebf614e2bb2a7611 | [
"self.config_map = config_map\nself.events = events\nself._test = None\nself._commands = None\nreturn",
"if self._commands is None:\n self._commands = IperfCommandBuilder(config_map=self.config_map)\nreturn self._commands",
"if self._test is None:\n self._test = iperftest.IperfTest(receiver_command=self.c... | <|body_start_0|>
self.config_map = config_map
self.events = events
self._test = None
self._commands = None
return
<|end_body_0|>
<|body_start_1|>
if self._commands is None:
self._commands = IperfCommandBuilder(config_map=self.config_map)
return self._... | A builder of iperf tests | IperfTestBuilder | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IperfTestBuilder:
"""A builder of iperf tests"""
def __init__(self, config_map, events=None):
""":param: - `config_map`: a pre-loaded configuration map - `events`: a list of events to wait for"""
<|body_0|>
def commands(self):
""":return: an iperf command builder... | stack_v2_sparse_classes_10k_train_003205 | 1,538 | permissive | [
{
"docstring": ":param: - `config_map`: a pre-loaded configuration map - `events`: a list of events to wait for",
"name": "__init__",
"signature": "def __init__(self, config_map, events=None)"
},
{
"docstring": ":return: an iperf command builder",
"name": "commands",
"signature": "def co... | 3 | stack_v2_sparse_classes_30k_train_003649 | Implement the Python class `IperfTestBuilder` described below.
Class description:
A builder of iperf tests
Method signatures and docstrings:
- def __init__(self, config_map, events=None): :param: - `config_map`: a pre-loaded configuration map - `events`: a list of events to wait for
- def commands(self): :return: an ... | Implement the Python class `IperfTestBuilder` described below.
Class description:
A builder of iperf tests
Method signatures and docstrings:
- def __init__(self, config_map, events=None): :param: - `config_map`: a pre-loaded configuration map - `events`: a list of events to wait for
- def commands(self): :return: an ... | b4d1c77e1d611fe2b30768b42bdc7493afb0ea95 | <|skeleton|>
class IperfTestBuilder:
"""A builder of iperf tests"""
def __init__(self, config_map, events=None):
""":param: - `config_map`: a pre-loaded configuration map - `events`: a list of events to wait for"""
<|body_0|>
def commands(self):
""":return: an iperf command builder... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class IperfTestBuilder:
"""A builder of iperf tests"""
def __init__(self, config_map, events=None):
""":param: - `config_map`: a pre-loaded configuration map - `events`: a list of events to wait for"""
self.config_map = config_map
self.events = events
self._test = None
s... | the_stack_v2_python_sparse | apetools/builders/subbuilders/iperftestbuilder.py | russell-n/oldape | train | 0 |
70a62820f27c2fc4d322d550e02390e60d5ec830 | [
"try:\n return phonenumbers.formatnumber(obj, phonenumbers.PhoneNumberFormat.NATIONAL)\nexcept Exception as e:\n return None",
"try:\n obj = phonenumbers.parse(text, 'CA')\n return phonenumbers.formatnumber(obj, phonenumbers.PhoneNumberFormat.NATIONAL)\nexcept Exception as e:\n return None"
] | <|body_start_0|>
try:
return phonenumbers.formatnumber(obj, phonenumbers.PhoneNumberFormat.NATIONAL)
except Exception as e:
return None
<|end_body_0|>
<|body_start_1|>
try:
obj = phonenumbers.parse(text, 'CA')
return phonenumbers.formatnumber(obj,... | Class used to convert the "PhoneNumber" objects "to" and "from" strings. This objects is from the "python-phonenumbers" library. | PhoneNumberField | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PhoneNumberField:
"""Class used to convert the "PhoneNumber" objects "to" and "from" strings. This objects is from the "python-phonenumbers" library."""
def to_representation(self, obj):
"""Function used to convert the PhoneNumber object to text string representation."""
<|bo... | stack_v2_sparse_classes_10k_train_003206 | 1,103 | permissive | [
{
"docstring": "Function used to convert the PhoneNumber object to text string representation.",
"name": "to_representation",
"signature": "def to_representation(self, obj)"
},
{
"docstring": "Function used to conver the text into the PhoneNumber object representation.",
"name": "to_internal... | 2 | stack_v2_sparse_classes_30k_train_005102 | Implement the Python class `PhoneNumberField` described below.
Class description:
Class used to convert the "PhoneNumber" objects "to" and "from" strings. This objects is from the "python-phonenumbers" library.
Method signatures and docstrings:
- def to_representation(self, obj): Function used to convert the PhoneNum... | Implement the Python class `PhoneNumberField` described below.
Class description:
Class used to convert the "PhoneNumber" objects "to" and "from" strings. This objects is from the "python-phonenumbers" library.
Method signatures and docstrings:
- def to_representation(self, obj): Function used to convert the PhoneNum... | cf58cf216d377ea97a2676cd594f96fb9d602a46 | <|skeleton|>
class PhoneNumberField:
"""Class used to convert the "PhoneNumber" objects "to" and "from" strings. This objects is from the "python-phonenumbers" library."""
def to_representation(self, obj):
"""Function used to convert the PhoneNumber object to text string representation."""
<|bo... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class PhoneNumberField:
"""Class used to convert the "PhoneNumber" objects "to" and "from" strings. This objects is from the "python-phonenumbers" library."""
def to_representation(self, obj):
"""Function used to convert the PhoneNumber object to text string representation."""
try:
... | the_stack_v2_python_sparse | academicstoday/shared_api/custom_fields.py | abhijitdalavi/Django-paas | train | 0 |
dfbbaf512e227a1294b7175591d6e7f421c44fd6 | [
"self.cleaned.barcode = room.barcode\nself.cleaned.title = room.title\nself.cleaned.x = room.x\nself.cleaned.y = room.y\nself.cleaned.z = room.z\nself.cleaned.description = room.description.text\nself.cleaned.exits = []\nfor exit in room.exits:\n definition = {}\n definition['name'] = exit.name_for(room)\n ... | <|body_start_0|>
self.cleaned.barcode = room.barcode
self.cleaned.title = room.title
self.cleaned.x = room.x
self.cleaned.y = room.y
self.cleaned.z = room.z
self.cleaned.description = room.description.text
self.cleaned.exits = []
for exit in room.exits:
... | Room document to add rooms in blueprints. | RoomDocument | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RoomDocument:
"""Room document to add rooms in blueprints."""
def fill_from_object(self, room):
"""Draw the document from an object."""
<|body_0|>
def add_neighbor(self, barcode: str, title: str, x: Optional[int]=None, y: Optional[int]=None, z: Optional[int]=None, descri... | stack_v2_sparse_classes_10k_train_003207 | 8,190 | permissive | [
{
"docstring": "Draw the document from an object.",
"name": "fill_from_object",
"signature": "def fill_from_object(self, room)"
},
{
"docstring": "Add a room, optionally connected to the current room. Args: barcode (str): the new room's barcode. title (str): the new room's title. x (int, optiona... | 4 | stack_v2_sparse_classes_30k_train_006181 | Implement the Python class `RoomDocument` described below.
Class description:
Room document to add rooms in blueprints.
Method signatures and docstrings:
- def fill_from_object(self, room): Draw the document from an object.
- def add_neighbor(self, barcode: str, title: str, x: Optional[int]=None, y: Optional[int]=Non... | Implement the Python class `RoomDocument` described below.
Class description:
Room document to add rooms in blueprints.
Method signatures and docstrings:
- def fill_from_object(self, room): Draw the document from an object.
- def add_neighbor(self, barcode: str, title: str, x: Optional[int]=None, y: Optional[int]=Non... | fb7f98d331e47e2032ee1e51bf3e4b2592807fdf | <|skeleton|>
class RoomDocument:
"""Room document to add rooms in blueprints."""
def fill_from_object(self, room):
"""Draw the document from an object."""
<|body_0|>
def add_neighbor(self, barcode: str, title: str, x: Optional[int]=None, y: Optional[int]=None, z: Optional[int]=None, descri... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class RoomDocument:
"""Room document to add rooms in blueprints."""
def fill_from_object(self, room):
"""Draw the document from an object."""
self.cleaned.barcode = room.barcode
self.cleaned.title = room.title
self.cleaned.x = room.x
self.cleaned.y = room.y
self.... | the_stack_v2_python_sparse | src/data/blueprints/room.py | vincent-lg/avenew.one | train | 0 |
ad1eb218fbcc53177f2804fdd0dcd615b10debc5 | [
"if 'w' not in self.mode:\n raise IOError('FileStoreImage %s is not in write mode.', self.urn)\npredicate = ('index:target:%s' % target).lower()\ndata_store.DB.MultiSet(self.urn, {predicate: target}, token=self.token, replace=True, sync=False)",
"regex = ['index:target:.*%s.*' % target_regex.lower()]\nif isins... | <|body_start_0|>
if 'w' not in self.mode:
raise IOError('FileStoreImage %s is not in write mode.', self.urn)
predicate = ('index:target:%s' % target).lower()
data_store.DB.MultiSet(self.urn, {predicate: target}, token=self.token, replace=True, sync=False)
<|end_body_0|>
<|body_start... | The AFF4 files that are stored in the file store area. Files in the file store are essentially blob images, containing indexes to the client files which matches their hash. It is possible to query for all clients which match a specific hash or a regular expression of the aff4 path to the files on these clients. e.g. on... | FileStoreImage | [
"Apache-2.0",
"DOC"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FileStoreImage:
"""The AFF4 files that are stored in the file store area. Files in the file store are essentially blob images, containing indexes to the client files which matches their hash. It is possible to query for all clients which match a specific hash or a regular expression of the aff4 p... | stack_v2_sparse_classes_10k_train_003208 | 24,878 | permissive | [
{
"docstring": "Adds an indexed reference to the target URN.",
"name": "AddIndex",
"signature": "def AddIndex(self, target)"
},
{
"docstring": "Search the index for matches to the file specified by the regex. Args: target_regex: The regular expression to match against the index. limit: Either a ... | 2 | stack_v2_sparse_classes_30k_train_004851 | Implement the Python class `FileStoreImage` described below.
Class description:
The AFF4 files that are stored in the file store area. Files in the file store are essentially blob images, containing indexes to the client files which matches their hash. It is possible to query for all clients which match a specific has... | Implement the Python class `FileStoreImage` described below.
Class description:
The AFF4 files that are stored in the file store area. Files in the file store are essentially blob images, containing indexes to the client files which matches their hash. It is possible to query for all clients which match a specific has... | ba1648b97a76f844ffb8e1891cc9e2680f9b1c6e | <|skeleton|>
class FileStoreImage:
"""The AFF4 files that are stored in the file store area. Files in the file store are essentially blob images, containing indexes to the client files which matches their hash. It is possible to query for all clients which match a specific hash or a regular expression of the aff4 p... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class FileStoreImage:
"""The AFF4 files that are stored in the file store area. Files in the file store are essentially blob images, containing indexes to the client files which matches their hash. It is possible to query for all clients which match a specific hash or a regular expression of the aff4 path to the fi... | the_stack_v2_python_sparse | lib/aff4_objects/filestore.py | defaultnamehere/grr | train | 3 |
7f32d1a6f18eab2d7c3d505ed61740b43e6b7ca7 | [
"import build.api\nimport company.api\nimport order.api\nimport part.api\nimport stock.api\nreturn {'build': build.api.BuildList, 'company': company.api.CompanyList, 'manufacturerpart': company.api.ManufacturerPartList, 'supplierpart': company.api.SupplierPartList, 'part': part.api.PartList, 'partcategory': part.ap... | <|body_start_0|>
import build.api
import company.api
import order.api
import part.api
import stock.api
return {'build': build.api.BuildList, 'company': company.api.CompanyList, 'manufacturerpart': company.api.ManufacturerPartList, 'supplierpart': company.api.SupplierPartL... | A general-purpose 'search' API endpoint Returns hits against a number of different models simultaneously, to consolidate multiple API requests into a single query. Is much more efficient and simplifies code! | APISearchView | [
"MIT",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class APISearchView:
"""A general-purpose 'search' API endpoint Returns hits against a number of different models simultaneously, to consolidate multiple API requests into a single query. Is much more efficient and simplifies code!"""
def get_result_types(self):
"""Construct a list of sear... | stack_v2_sparse_classes_10k_train_003209 | 11,757 | permissive | [
{
"docstring": "Construct a list of search types we can return",
"name": "get_result_types",
"signature": "def get_result_types(self)"
},
{
"docstring": "Perform search query against available models",
"name": "post",
"signature": "def post(self, request, *args, **kwargs)"
}
] | 2 | null | Implement the Python class `APISearchView` described below.
Class description:
A general-purpose 'search' API endpoint Returns hits against a number of different models simultaneously, to consolidate multiple API requests into a single query. Is much more efficient and simplifies code!
Method signatures and docstring... | Implement the Python class `APISearchView` described below.
Class description:
A general-purpose 'search' API endpoint Returns hits against a number of different models simultaneously, to consolidate multiple API requests into a single query. Is much more efficient and simplifies code!
Method signatures and docstring... | e88a8e99a5f0b201c67a95cba097c729f090d5e2 | <|skeleton|>
class APISearchView:
"""A general-purpose 'search' API endpoint Returns hits against a number of different models simultaneously, to consolidate multiple API requests into a single query. Is much more efficient and simplifies code!"""
def get_result_types(self):
"""Construct a list of sear... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class APISearchView:
"""A general-purpose 'search' API endpoint Returns hits against a number of different models simultaneously, to consolidate multiple API requests into a single query. Is much more efficient and simplifies code!"""
def get_result_types(self):
"""Construct a list of search types we c... | the_stack_v2_python_sparse | InvenTree/InvenTree/api.py | inventree/InvenTree | train | 3,077 |
971bd0c1781199c4c3585355cfefe61a4bc02c9a | [
"try:\n group = await get_data_from_req(self.request).groups.get(group_id)\nexcept ResourceNotFoundError:\n raise NotFound()\nreturn json_response(GroupResponse.parse_obj(group))",
"try:\n group = await get_data_from_req(self.request).groups.update(group_id, data)\nexcept ResourceNotFoundError:\n rais... | <|body_start_0|>
try:
group = await get_data_from_req(self.request).groups.get(group_id)
except ResourceNotFoundError:
raise NotFound()
return json_response(GroupResponse.parse_obj(group))
<|end_body_0|>
<|body_start_1|>
try:
group = await get_data_fr... | GroupView | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GroupView:
async def get(self, group_id: str, /) -> Union[r200[GroupResponse], r404]:
"""Get a group. Fetches the complete representation of a single user group including its permissions. Status Codes: 200: Successful operation 404: Group not found"""
<|body_0|>
async def pa... | stack_v2_sparse_classes_10k_train_003210 | 3,996 | permissive | [
{
"docstring": "Get a group. Fetches the complete representation of a single user group including its permissions. Status Codes: 200: Successful operation 404: Group not found",
"name": "get",
"signature": "async def get(self, group_id: str, /) -> Union[r200[GroupResponse], r404]"
},
{
"docstrin... | 3 | stack_v2_sparse_classes_30k_train_003036 | Implement the Python class `GroupView` described below.
Class description:
Implement the GroupView class.
Method signatures and docstrings:
- async def get(self, group_id: str, /) -> Union[r200[GroupResponse], r404]: Get a group. Fetches the complete representation of a single user group including its permissions. St... | Implement the Python class `GroupView` described below.
Class description:
Implement the GroupView class.
Method signatures and docstrings:
- async def get(self, group_id: str, /) -> Union[r200[GroupResponse], r404]: Get a group. Fetches the complete representation of a single user group including its permissions. St... | 1d17d2ba570cf5487e7514bec29250a5b368bb0a | <|skeleton|>
class GroupView:
async def get(self, group_id: str, /) -> Union[r200[GroupResponse], r404]:
"""Get a group. Fetches the complete representation of a single user group including its permissions. Status Codes: 200: Successful operation 404: Group not found"""
<|body_0|>
async def pa... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class GroupView:
async def get(self, group_id: str, /) -> Union[r200[GroupResponse], r404]:
"""Get a group. Fetches the complete representation of a single user group including its permissions. Status Codes: 200: Successful operation 404: Group not found"""
try:
group = await get_data_fr... | the_stack_v2_python_sparse | virtool/groups/api.py | virtool/virtool | train | 45 | |
48c4f3611ffc55cdc3a205da40acae304b5aa69e | [
"if os.path.isfile(path):\n with open(path, 'rb') as file:\n return (file.read(), True)\nif save:\n return (cls.fetch_and_save(url, path), False)\nreturn (cls.fetch_with_retry(url), False)",
"content = cls.fetch_with_retry(url)\nif not content:\n return False\nwith open(path, 'wb') as file:\n f... | <|body_start_0|>
if os.path.isfile(path):
with open(path, 'rb') as file:
return (file.read(), True)
if save:
return (cls.fetch_and_save(url, path), False)
return (cls.fetch_with_retry(url), False)
<|end_body_0|>
<|body_start_1|>
content = cls.fetc... | Fetcher | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Fetcher:
def fetch_maybe(cls, url, path, save=False):
"""Fetch from url or from file if it has been cached previously"""
<|body_0|>
def fetch_and_save(cls, url, path):
"""Fetch file and save to disk"""
<|body_1|>
def fetch_with_retry(cls, url):
"... | stack_v2_sparse_classes_10k_train_003211 | 2,471 | no_license | [
{
"docstring": "Fetch from url or from file if it has been cached previously",
"name": "fetch_maybe",
"signature": "def fetch_maybe(cls, url, path, save=False)"
},
{
"docstring": "Fetch file and save to disk",
"name": "fetch_and_save",
"signature": "def fetch_and_save(cls, url, path)"
... | 4 | stack_v2_sparse_classes_30k_train_006649 | Implement the Python class `Fetcher` described below.
Class description:
Implement the Fetcher class.
Method signatures and docstrings:
- def fetch_maybe(cls, url, path, save=False): Fetch from url or from file if it has been cached previously
- def fetch_and_save(cls, url, path): Fetch file and save to disk
- def fe... | Implement the Python class `Fetcher` described below.
Class description:
Implement the Fetcher class.
Method signatures and docstrings:
- def fetch_maybe(cls, url, path, save=False): Fetch from url or from file if it has been cached previously
- def fetch_and_save(cls, url, path): Fetch file and save to disk
- def fe... | 31f29e374d8668c92f1b1c48b2d38c967f5e145f | <|skeleton|>
class Fetcher:
def fetch_maybe(cls, url, path, save=False):
"""Fetch from url or from file if it has been cached previously"""
<|body_0|>
def fetch_and_save(cls, url, path):
"""Fetch file and save to disk"""
<|body_1|>
def fetch_with_retry(cls, url):
"... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Fetcher:
def fetch_maybe(cls, url, path, save=False):
"""Fetch from url or from file if it has been cached previously"""
if os.path.isfile(path):
with open(path, 'rb') as file:
return (file.read(), True)
if save:
return (cls.fetch_and_save(url, p... | the_stack_v2_python_sparse | fetcher.py | mideind/thesis-corpus | train | 0 | |
c3e876561c8e5375d108e5ecc706a11f192da1c6 | [
"try:\n x = cls.get_list_val(x)\nexcept AssertionError:\n return False\nreturn x == cls.OK",
"try:\n x = cls.get_list_val(x)\nexcept AssertionError:\n return False\nreturn cls.has(x) and x != cls.OK",
"val1 = cls.get_list_val(val1)\nval2 = cls.get_list_val(val2)\nreturn cls.has(val1) and cls.has(val... | <|body_start_0|>
try:
x = cls.get_list_val(x)
except AssertionError:
return False
return x == cls.OK
<|end_body_0|>
<|body_start_1|>
try:
x = cls.get_list_val(x)
except AssertionError:
return False
return cls.has(x) and x !... | Error codes generated by instrument drivers and agents | InstErrorCode | [
"BSD-3-Clause",
"LicenseRef-scancode-unknown-license-reference",
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InstErrorCode:
"""Error codes generated by instrument drivers and agents"""
def is_ok(cls, x):
"""Success test functional synonym. Will need iterable type checking if success codes get additional info in the future. @param x a str, tuple or list to match to an error code success valu... | stack_v2_sparse_classes_10k_train_003212 | 9,909 | permissive | [
{
"docstring": "Success test functional synonym. Will need iterable type checking if success codes get additional info in the future. @param x a str, tuple or list to match to an error code success value. @retval True if x is a success value, False otherwise.",
"name": "is_ok",
"signature": "def is_ok(c... | 5 | stack_v2_sparse_classes_30k_train_002418 | Implement the Python class `InstErrorCode` described below.
Class description:
Error codes generated by instrument drivers and agents
Method signatures and docstrings:
- def is_ok(cls, x): Success test functional synonym. Will need iterable type checking if success codes get additional info in the future. @param x a ... | Implement the Python class `InstErrorCode` described below.
Class description:
Error codes generated by instrument drivers and agents
Method signatures and docstrings:
- def is_ok(cls, x): Success test functional synonym. Will need iterable type checking if success codes get additional info in the future. @param x a ... | 122c629290d27f32f2f41dafd5c12469295e8acf | <|skeleton|>
class InstErrorCode:
"""Error codes generated by instrument drivers and agents"""
def is_ok(cls, x):
"""Success test functional synonym. Will need iterable type checking if success codes get additional info in the future. @param x a str, tuple or list to match to an error code success valu... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class InstErrorCode:
"""Error codes generated by instrument drivers and agents"""
def is_ok(cls, x):
"""Success test functional synonym. Will need iterable type checking if success codes get additional info in the future. @param x a str, tuple or list to match to an error code success value. @retval Tr... | the_stack_v2_python_sparse | pyon/agent/common.py | ooici/pyon | train | 9 |
366f3f0d1f986e2295e98e43040a59f550e8ce43 | [
"path = urls.TRAIL_LOG['GET_ALL']\nparams = {'limit': limit, 'offset': offset}\nif username:\n params['username'] = username\nif start_time:\n params['start_time'] = start_time\nif end_time:\n params['end_time'] = end_time\nif description:\n params['description'] = description\nif target:\n params['t... | <|body_start_0|>
path = urls.TRAIL_LOG['GET_ALL']
params = {'limit': limit, 'offset': offset}
if username:
params['username'] = username
if start_time:
params['start_time'] = start_time
if end_time:
params['end_time'] = end_time
if desc... | Get the audit logs and event logs with the functions in this class. | Audit | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Audit:
"""Get the audit logs and event logs with the functions in this class."""
def get_traillogs(self, conn, limit=100, offset=0, username=None, start_time=None, end_time=None, description=None, target=None, classification=None, customer_name=None, ip_address=None, app_id=None):
""... | stack_v2_sparse_classes_10k_train_003213 | 7,915 | permissive | [
{
"docstring": "Get audit logs, sort by time in in reverse chronological order. This API returns the first 10,000 results only. Please use filter in the API for more relevant results. MSP Customer Would see logs of MSP's and tenants as well. :param conn: Instance of class:`pycentral.ArubaCentralBase` to make an... | 4 | stack_v2_sparse_classes_30k_val_000209 | Implement the Python class `Audit` described below.
Class description:
Get the audit logs and event logs with the functions in this class.
Method signatures and docstrings:
- def get_traillogs(self, conn, limit=100, offset=0, username=None, start_time=None, end_time=None, description=None, target=None, classification... | Implement the Python class `Audit` described below.
Class description:
Get the audit logs and event logs with the functions in this class.
Method signatures and docstrings:
- def get_traillogs(self, conn, limit=100, offset=0, username=None, start_time=None, end_time=None, description=None, target=None, classification... | d938396a18193473afbe54e6cc6697d2bd4954a7 | <|skeleton|>
class Audit:
"""Get the audit logs and event logs with the functions in this class."""
def get_traillogs(self, conn, limit=100, offset=0, username=None, start_time=None, end_time=None, description=None, target=None, classification=None, customer_name=None, ip_address=None, app_id=None):
""... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Audit:
"""Get the audit logs and event logs with the functions in this class."""
def get_traillogs(self, conn, limit=100, offset=0, username=None, start_time=None, end_time=None, description=None, target=None, classification=None, customer_name=None, ip_address=None, app_id=None):
"""Get audit lo... | the_stack_v2_python_sparse | pycentral/audit_logs.py | jayp193/pycentral | train | 0 |
b12f3ded460bd861d96e6c39c5e81eed204ef662 | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn MacOSGeneralDeviceConfiguration()",
"from .app_list_item import AppListItem\nfrom .app_list_type import AppListType\nfrom .device_configuration import DeviceConfiguration\nfrom .required_password_type import RequiredPasswordType\nfrom ... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return MacOSGeneralDeviceConfiguration()
<|end_body_0|>
<|body_start_1|>
from .app_list_item import AppListItem
from .app_list_type import AppListType
from .device_configuration import ... | This topic provides descriptions of the declared methods, properties and relationships exposed by the macOSGeneralDeviceConfiguration resource. | MacOSGeneralDeviceConfiguration | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MacOSGeneralDeviceConfiguration:
"""This topic provides descriptions of the declared methods, properties and relationships exposed by the macOSGeneralDeviceConfiguration resource."""
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> MacOSGeneralDeviceConfiguration:... | stack_v2_sparse_classes_10k_train_003214 | 6,806 | 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: MacOSGeneralDeviceConfiguration",
"name": "create_from_discriminator_value",
"signature": "def create_from_d... | 3 | stack_v2_sparse_classes_30k_train_005982 | Implement the Python class `MacOSGeneralDeviceConfiguration` described below.
Class description:
This topic provides descriptions of the declared methods, properties and relationships exposed by the macOSGeneralDeviceConfiguration resource.
Method signatures and docstrings:
- def create_from_discriminator_value(parse... | Implement the Python class `MacOSGeneralDeviceConfiguration` described below.
Class description:
This topic provides descriptions of the declared methods, properties and relationships exposed by the macOSGeneralDeviceConfiguration resource.
Method signatures and docstrings:
- def create_from_discriminator_value(parse... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class MacOSGeneralDeviceConfiguration:
"""This topic provides descriptions of the declared methods, properties and relationships exposed by the macOSGeneralDeviceConfiguration resource."""
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> MacOSGeneralDeviceConfiguration:... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class MacOSGeneralDeviceConfiguration:
"""This topic provides descriptions of the declared methods, properties and relationships exposed by the macOSGeneralDeviceConfiguration resource."""
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> MacOSGeneralDeviceConfiguration:
"""C... | the_stack_v2_python_sparse | msgraph/generated/models/mac_o_s_general_device_configuration.py | microsoftgraph/msgraph-sdk-python | train | 135 |
641545540bcfb7496d5a8ce06bae2ef61738eee0 | [
"tp = type(e)\ntb = e.__traceback__\ntraceback_str = 'Traceback (most recent call last):\\n' + ''.join(traceback.format_tb(tb))\ntry:\n attributes = e.get_attributes()\nexcept AttributeError:\n attributes = {}\nreturn (tp.__name__, traceback_str, sy.serde.msgpack.serde._simplify(worker, attributes))",
"erro... | <|body_start_0|>
tp = type(e)
tb = e.__traceback__
traceback_str = 'Traceback (most recent call last):\n' + ''.join(traceback.format_tb(tb))
try:
attributes = e.get_attributes()
except AttributeError:
attributes = {}
return (tp.__name__, traceback_... | Raised when calling send on a tensor which does not allow send to be called on it. This can happen do to sensitivity being too high | SendNotPermittedError | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SendNotPermittedError:
"""Raised when calling send on a tensor which does not allow send to be called on it. This can happen do to sensitivity being too high"""
def simplify(worker: 'sy.workers.AbstractWorker', e):
"""Serialize information about an Exception which was raised to forwa... | stack_v2_sparse_classes_10k_train_003215 | 15,166 | permissive | [
{
"docstring": "Serialize information about an Exception which was raised to forward it",
"name": "simplify",
"signature": "def simplify(worker: 'sy.workers.AbstractWorker', e)"
},
{
"docstring": "Detail and re-raise an Exception forwarded by another worker",
"name": "detail",
"signature... | 2 | stack_v2_sparse_classes_30k_train_006424 | Implement the Python class `SendNotPermittedError` described below.
Class description:
Raised when calling send on a tensor which does not allow send to be called on it. This can happen do to sensitivity being too high
Method signatures and docstrings:
- def simplify(worker: 'sy.workers.AbstractWorker', e): Serialize... | Implement the Python class `SendNotPermittedError` described below.
Class description:
Raised when calling send on a tensor which does not allow send to be called on it. This can happen do to sensitivity being too high
Method signatures and docstrings:
- def simplify(worker: 'sy.workers.AbstractWorker', e): Serialize... | cc4765bed880ad38a02505834f63df39e0815328 | <|skeleton|>
class SendNotPermittedError:
"""Raised when calling send on a tensor which does not allow send to be called on it. This can happen do to sensitivity being too high"""
def simplify(worker: 'sy.workers.AbstractWorker', e):
"""Serialize information about an Exception which was raised to forwa... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SendNotPermittedError:
"""Raised when calling send on a tensor which does not allow send to be called on it. This can happen do to sensitivity being too high"""
def simplify(worker: 'sy.workers.AbstractWorker', e):
"""Serialize information about an Exception which was raised to forward it"""
... | the_stack_v2_python_sparse | syft/exceptions.py | tudorcebere/PySyft | train | 2 |
472ff4ef152cd76d3430fd4f7f11710d92ca1950 | [
"self.width = width\nself.height = height\nself.board = []\nfor i in range(height):\n row = []\n for j in range(width):\n row.append('.')\n self.board.append(row)",
"random.seed(seed_number)\nfor i in range(self.height):\n for j in range(self.width):\n random_number = random.randint(0, 1... | <|body_start_0|>
self.width = width
self.height = height
self.board = []
for i in range(height):
row = []
for j in range(width):
row.append('.')
self.board.append(row)
<|end_body_0|>
<|body_start_1|>
random.seed(seed_number)
... | Describes the world of Conway's Game of Life. Attribute width: the width of the game world in number of cells. Invariant: width is a non-negative integer. Attribute height: the height of the game world in number of cells. Invariant: height is a non-negative integer. Attribute board: the board of the game world. Invaria... | Life | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Life:
"""Describes the world of Conway's Game of Life. Attribute width: the width of the game world in number of cells. Invariant: width is a non-negative integer. Attribute height: the height of the game world in number of cells. Invariant: height is a non-negative integer. Attribute board: the ... | stack_v2_sparse_classes_10k_train_003216 | 4,872 | no_license | [
{
"docstring": "Initializes the Game of Life with the given width and height. Also initializes the attribute board to be of the right size, and with all cells dead. Precondition: width and height are nonnegative integers.",
"name": "__init__",
"signature": "def __init__(self, width, height)"
},
{
... | 5 | stack_v2_sparse_classes_30k_train_004484 | Implement the Python class `Life` described below.
Class description:
Describes the world of Conway's Game of Life. Attribute width: the width of the game world in number of cells. Invariant: width is a non-negative integer. Attribute height: the height of the game world in number of cells. Invariant: height is a non-... | Implement the Python class `Life` described below.
Class description:
Describes the world of Conway's Game of Life. Attribute width: the width of the game world in number of cells. Invariant: width is a non-negative integer. Attribute height: the height of the game world in number of cells. Invariant: height is a non-... | 0b4b957720710d7ace0c12dffda5331fadbe2653 | <|skeleton|>
class Life:
"""Describes the world of Conway's Game of Life. Attribute width: the width of the game world in number of cells. Invariant: width is a non-negative integer. Attribute height: the height of the game world in number of cells. Invariant: height is a non-negative integer. Attribute board: the ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Life:
"""Describes the world of Conway's Game of Life. Attribute width: the width of the game world in number of cells. Invariant: width is a non-negative integer. Attribute height: the height of the game world in number of cells. Invariant: height is a non-negative integer. Attribute board: the board of the ... | the_stack_v2_python_sparse | Assignments/a5/skeleton/a5.py | futuregoogle/CS1110 | train | 0 |
3f43c8f6d08095bb6513e38db8d0828238a58008 | [
"super(STFTLoss, self).__init__()\nself.fft_size = fft_size\nself.hop_size = hop_size\nself.win_length = win_length\nself.window = getattr(torch, window)(win_length).cuda()\nself.amp_floor = 1e-05\nself.mse_loss = torch.nn.MSELoss()",
"x_stft = torch.stft(x, self.fft_size, self.hop_size, self.win_length, window=s... | <|body_start_0|>
super(STFTLoss, self).__init__()
self.fft_size = fft_size
self.hop_size = hop_size
self.win_length = win_length
self.window = getattr(torch, window)(win_length).cuda()
self.amp_floor = 1e-05
self.mse_loss = torch.nn.MSELoss()
<|end_body_0|>
<|bod... | STFT loss module. | STFTLoss | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class STFTLoss:
"""STFT loss module."""
def __init__(self, fft_size, hop_size, win_length, window):
"""Initialize STFT loss module."""
<|body_0|>
def forward(self, x, y):
"""Calculate forward propagation. Args: x (Tensor): Predicted signal (B, T). y (Tensor): Groundtru... | stack_v2_sparse_classes_10k_train_003217 | 2,811 | permissive | [
{
"docstring": "Initialize STFT loss module.",
"name": "__init__",
"signature": "def __init__(self, fft_size, hop_size, win_length, window)"
},
{
"docstring": "Calculate forward propagation. Args: x (Tensor): Predicted signal (B, T). y (Tensor): Groundtruth signal (B, T). Returns: Tensor: Logari... | 2 | stack_v2_sparse_classes_30k_train_003499 | Implement the Python class `STFTLoss` described below.
Class description:
STFT loss module.
Method signatures and docstrings:
- def __init__(self, fft_size, hop_size, win_length, window): Initialize STFT loss module.
- def forward(self, x, y): Calculate forward propagation. Args: x (Tensor): Predicted signal (B, T). ... | Implement the Python class `STFTLoss` described below.
Class description:
STFT loss module.
Method signatures and docstrings:
- def __init__(self, fft_size, hop_size, win_length, window): Initialize STFT loss module.
- def forward(self, x, y): Calculate forward propagation. Args: x (Tensor): Predicted signal (B, T). ... | 67331ddb5d6a7227120818842c61b6e07de52ba7 | <|skeleton|>
class STFTLoss:
"""STFT loss module."""
def __init__(self, fft_size, hop_size, win_length, window):
"""Initialize STFT loss module."""
<|body_0|>
def forward(self, x, y):
"""Calculate forward propagation. Args: x (Tensor): Predicted signal (B, T). y (Tensor): Groundtru... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class STFTLoss:
"""STFT loss module."""
def __init__(self, fft_size, hop_size, win_length, window):
"""Initialize STFT loss module."""
super(STFTLoss, self).__init__()
self.fft_size = fft_size
self.hop_size = hop_size
self.win_length = win_length
self.window = ge... | the_stack_v2_python_sparse | usfgan/losses/stft_loss.py | hendrikTpl/UnifiedSourceFilterGAN | train | 0 |
e8df151a2ee23dee3e567e2be58f85352d6ffcc7 | [
"if opt_options is None:\n opt_options = {'maxiter': 100, 'disp': True, 'iprint': 2, 'ftol': 1e-12, 'eps': 0.1}\nsuper().__init__(fi=fi, minimum_yaw_angle=minimum_yaw_angle, maximum_yaw_angle=maximum_yaw_angle, yaw_angles_baseline=yaw_angles_baseline, x0=x0, turbine_weights=turbine_weights, normalize_control_var... | <|body_start_0|>
if opt_options is None:
opt_options = {'maxiter': 100, 'disp': True, 'iprint': 2, 'ftol': 1e-12, 'eps': 0.1}
super().__init__(fi=fi, minimum_yaw_angle=minimum_yaw_angle, maximum_yaw_angle=maximum_yaw_angle, yaw_angles_baseline=yaw_angles_baseline, x0=x0, turbine_weights=turb... | YawOptimizationScipy is a subclass of :py:class:`floris.tools.optimization.general_library.YawOptimization` that is used to optimize the yaw angles of all turbines in a Floris Farm for a single set of inflow conditions using the SciPy optimize package. | YawOptimizationScipy | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class YawOptimizationScipy:
"""YawOptimizationScipy is a subclass of :py:class:`floris.tools.optimization.general_library.YawOptimization` that is used to optimize the yaw angles of all turbines in a Floris Farm for a single set of inflow conditions using the SciPy optimize package."""
def __init_... | stack_v2_sparse_classes_10k_train_003218 | 5,455 | permissive | [
{
"docstring": "Instantiate YawOptimizationScipy object with a FlorisInterface object and assign parameter values.",
"name": "__init__",
"signature": "def __init__(self, fi, minimum_yaw_angle=0.0, maximum_yaw_angle=25.0, yaw_angles_baseline=None, x0=None, opt_method='SLSQP', opt_options=None, turbine_we... | 2 | stack_v2_sparse_classes_30k_train_000348 | Implement the Python class `YawOptimizationScipy` described below.
Class description:
YawOptimizationScipy is a subclass of :py:class:`floris.tools.optimization.general_library.YawOptimization` that is used to optimize the yaw angles of all turbines in a Floris Farm for a single set of inflow conditions using the SciP... | Implement the Python class `YawOptimizationScipy` described below.
Class description:
YawOptimizationScipy is a subclass of :py:class:`floris.tools.optimization.general_library.YawOptimization` that is used to optimize the yaw angles of all turbines in a Floris Farm for a single set of inflow conditions using the SciP... | 59e53a66aef134a3c9e912f9468ca667b599d4e5 | <|skeleton|>
class YawOptimizationScipy:
"""YawOptimizationScipy is a subclass of :py:class:`floris.tools.optimization.general_library.YawOptimization` that is used to optimize the yaw angles of all turbines in a Floris Farm for a single set of inflow conditions using the SciPy optimize package."""
def __init_... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class YawOptimizationScipy:
"""YawOptimizationScipy is a subclass of :py:class:`floris.tools.optimization.general_library.YawOptimization` that is used to optimize the yaw angles of all turbines in a Floris Farm for a single set of inflow conditions using the SciPy optimize package."""
def __init__(self, fi, m... | the_stack_v2_python_sparse | floris/tools/optimization/yaw_optimization/yaw_optimizer_scipy.py | NREL/floris | train | 151 |
7901472b6deb477ea926f86f2b9ab766476ea1ae | [
"super(Machines, self).__init__(url=url, gis=gis, portaladmin=portaladmin)\ninitialize = kwargs.pop('initialize', False)\nself._url = url\nself._pa = portaladmin\nif initialize:\n self._init()",
"machines = []\nfor m in self.properties.machines:\n machines.append(Machine(name=m['machineName'], url=self._url... | <|body_start_0|>
super(Machines, self).__init__(url=url, gis=gis, portaladmin=portaladmin)
initialize = kwargs.pop('initialize', False)
self._url = url
self._pa = portaladmin
if initialize:
self._init()
<|end_body_0|>
<|body_start_1|>
machines = []
fo... | This resource lists all the portal machines in a site. Each portal machine has a status that indicates whether the machine is ready to accept requests. | Machines | [
"Python-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Machines:
"""This resource lists all the portal machines in a site. Each portal machine has a status that indicates whether the machine is ready to accept requests."""
def __init__(self, url, gis, portaladmin, **kwargs):
"""Constructor"""
<|body_0|>
def list(self):
... | stack_v2_sparse_classes_10k_train_003219 | 4,901 | permissive | [
{
"docstring": "Constructor",
"name": "__init__",
"signature": "def __init__(self, url, gis, portaladmin, **kwargs)"
},
{
"docstring": "provides a list of all registered machines with the local GIS",
"name": "list",
"signature": "def list(self)"
},
{
"docstring": "allows for retr... | 3 | null | Implement the Python class `Machines` described below.
Class description:
This resource lists all the portal machines in a site. Each portal machine has a status that indicates whether the machine is ready to accept requests.
Method signatures and docstrings:
- def __init__(self, url, gis, portaladmin, **kwargs): Con... | Implement the Python class `Machines` described below.
Class description:
This resource lists all the portal machines in a site. Each portal machine has a status that indicates whether the machine is ready to accept requests.
Method signatures and docstrings:
- def __init__(self, url, gis, portaladmin, **kwargs): Con... | a874fe7e5c95196e4de68db2da0e2a05eb70e5d8 | <|skeleton|>
class Machines:
"""This resource lists all the portal machines in a site. Each portal machine has a status that indicates whether the machine is ready to accept requests."""
def __init__(self, url, gis, portaladmin, **kwargs):
"""Constructor"""
<|body_0|>
def list(self):
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Machines:
"""This resource lists all the portal machines in a site. Each portal machine has a status that indicates whether the machine is ready to accept requests."""
def __init__(self, url, gis, portaladmin, **kwargs):
"""Constructor"""
super(Machines, self).__init__(url=url, gis=gis, p... | the_stack_v2_python_sparse | arcpyenv/arcgispro-py3-clone/Lib/site-packages/arcgis/gis/admin/_machines.py | SherbazHashmi/HackathonServer | train | 3 |
fdf52c53e8c01d13ae12d342deb658977903b435 | [
"self.host = host\nself.username = username\nself.password = password\nself.port = port\nself.phonebook_id = phonebook_id\nself.phonebook_dict = None\nself.number_dict = None\nself.prefixes = prefixes or []\nself.fph = FritzPhonebook(address=self.host, user=self.username, password=self.password)\nif self.phonebook_... | <|body_start_0|>
self.host = host
self.username = username
self.password = password
self.port = port
self.phonebook_id = phonebook_id
self.phonebook_dict = None
self.number_dict = None
self.prefixes = prefixes or []
self.fph = FritzPhonebook(addres... | This connects to a FritzBox router and downloads its phone book. | FritzBoxPhonebook | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FritzBoxPhonebook:
"""This connects to a FritzBox router and downloads its phone book."""
def __init__(self, host, port, username, password, phonebook_id=0, prefixes=None):
"""Initialize the class."""
<|body_0|>
def update_phonebook(self):
"""Update the phone boo... | stack_v2_sparse_classes_10k_train_003220 | 9,842 | permissive | [
{
"docstring": "Initialize the class.",
"name": "__init__",
"signature": "def __init__(self, host, port, username, password, phonebook_id=0, prefixes=None)"
},
{
"docstring": "Update the phone book dictionary.",
"name": "update_phonebook",
"signature": "def update_phonebook(self)"
},
... | 3 | null | Implement the Python class `FritzBoxPhonebook` described below.
Class description:
This connects to a FritzBox router and downloads its phone book.
Method signatures and docstrings:
- def __init__(self, host, port, username, password, phonebook_id=0, prefixes=None): Initialize the class.
- def update_phonebook(self):... | Implement the Python class `FritzBoxPhonebook` described below.
Class description:
This connects to a FritzBox router and downloads its phone book.
Method signatures and docstrings:
- def __init__(self, host, port, username, password, phonebook_id=0, prefixes=None): Initialize the class.
- def update_phonebook(self):... | ed4ab403deaed9e8c95e0db728477fcb012bf4fa | <|skeleton|>
class FritzBoxPhonebook:
"""This connects to a FritzBox router and downloads its phone book."""
def __init__(self, host, port, username, password, phonebook_id=0, prefixes=None):
"""Initialize the class."""
<|body_0|>
def update_phonebook(self):
"""Update the phone boo... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class FritzBoxPhonebook:
"""This connects to a FritzBox router and downloads its phone book."""
def __init__(self, host, port, username, password, phonebook_id=0, prefixes=None):
"""Initialize the class."""
self.host = host
self.username = username
self.password = password
... | the_stack_v2_python_sparse | homeassistant/components/fritzbox_callmonitor/sensor.py | tchellomello/home-assistant | train | 8 |
2ff5b6ee6db9c2697aad5021343f01c1469c48cc | [
"f = open(os.path.join(self.path, filename), 'rb')\nlines = f.readlines()\nf.close()\nreturn lines",
"if filename not in self.db_config:\n f = open(os.path.join(self.path, 'db', filename), 'rb')\n self.db_config[filename] = f.readlines()\n f.close()\nreturn self.db_config[filename]",
"if name is None:\... | <|body_start_0|>
f = open(os.path.join(self.path, filename), 'rb')
lines = f.readlines()
f.close()
return lines
<|end_body_0|>
<|body_start_1|>
if filename not in self.db_config:
f = open(os.path.join(self.path, 'db', filename), 'rb')
self.db_config[filen... | Encapsulates key information of a repository: its NAME, PATH, SHARD_SIZE, HEAD revision and MIN_UNPACKED_REV. | Repository | [
"BSD-3-Clause",
"LicenseRef-scancode-generic-cla",
"LicenseRef-scancode-other-permissive",
"X11",
"BSD-2-Clause",
"LicenseRef-scancode-unknown-license-reference",
"MIT",
"HPND-Markus-Kuhn",
"LicenseRef-scancode-unicode",
"Apache-2.0",
"FSFAP"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Repository:
"""Encapsulates key information of a repository: its NAME, PATH, SHARD_SIZE, HEAD revision and MIN_UNPACKED_REV."""
def _read_repo_file(self, filename):
"""Read and return all lines from FILENAME in REPO."""
<|body_0|>
def _read_config(self, filename):
... | stack_v2_sparse_classes_10k_train_003221 | 6,496 | permissive | [
{
"docstring": "Read and return all lines from FILENAME in REPO.",
"name": "_read_repo_file",
"signature": "def _read_repo_file(self, filename)"
},
{
"docstring": "Read and return all lines from FILENAME. This will be used to read 'format', 'current' etc. .",
"name": "_read_config",
"sig... | 5 | stack_v2_sparse_classes_30k_train_004394 | Implement the Python class `Repository` described below.
Class description:
Encapsulates key information of a repository: its NAME, PATH, SHARD_SIZE, HEAD revision and MIN_UNPACKED_REV.
Method signatures and docstrings:
- def _read_repo_file(self, filename): Read and return all lines from FILENAME in REPO.
- def _rea... | Implement the Python class `Repository` described below.
Class description:
Encapsulates key information of a repository: its NAME, PATH, SHARD_SIZE, HEAD revision and MIN_UNPACKED_REV.
Method signatures and docstrings:
- def _read_repo_file(self, filename): Read and return all lines from FILENAME in REPO.
- def _rea... | dd957c4991e61bde23cc60d13449ea8b65f80c43 | <|skeleton|>
class Repository:
"""Encapsulates key information of a repository: its NAME, PATH, SHARD_SIZE, HEAD revision and MIN_UNPACKED_REV."""
def _read_repo_file(self, filename):
"""Read and return all lines from FILENAME in REPO."""
<|body_0|>
def _read_config(self, filename):
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Repository:
"""Encapsulates key information of a repository: its NAME, PATH, SHARD_SIZE, HEAD revision and MIN_UNPACKED_REV."""
def _read_repo_file(self, filename):
"""Read and return all lines from FILENAME in REPO."""
f = open(os.path.join(self.path, filename), 'rb')
lines = f.r... | the_stack_v2_python_sparse | contrib/server-side/fsfsfixer/fixer/find_good_id.py | apache/subversion | train | 520 |
d81b0b3aa6a3e97f4112567e8547e45c97af5634 | [
"SinglePanelPlot.__init__(self)\nself.__triggername = triggername\nself.__triggereff = triggerefficiency",
"self._OpenCanvas('trgEffSumm', 'Summed trigger efficiency')\npad = self._GetFramedPad()\npad.DrawFrame(TriggerEfficiencyFrame('tframe'))\npad.DrawGraphicsObject(GraphicsObject(self.__triggereff.GetEfficienc... | <|body_start_0|>
SinglePanelPlot.__init__(self)
self.__triggername = triggername
self.__triggereff = triggerefficiency
<|end_body_0|>
<|body_start_1|>
self._OpenCanvas('trgEffSumm', 'Summed trigger efficiency')
pad = self._GetFramedPad()
pad.DrawFrame(TriggerEfficiencyFr... | Plot the summed trigger efficiency from different pt-hard bins | TriggerEfficiencySumPlot | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TriggerEfficiencySumPlot:
"""Plot the summed trigger efficiency from different pt-hard bins"""
def __init__(self, triggername, triggerefficiency):
"""Constructor"""
<|body_0|>
def Create(self):
"""Create the plot"""
<|body_1|>
<|end_skeleton|>
<|body_st... | stack_v2_sparse_classes_10k_train_003222 | 5,978 | permissive | [
{
"docstring": "Constructor",
"name": "__init__",
"signature": "def __init__(self, triggername, triggerefficiency)"
},
{
"docstring": "Create the plot",
"name": "Create",
"signature": "def Create(self)"
}
] | 2 | stack_v2_sparse_classes_30k_test_000316 | Implement the Python class `TriggerEfficiencySumPlot` described below.
Class description:
Plot the summed trigger efficiency from different pt-hard bins
Method signatures and docstrings:
- def __init__(self, triggername, triggerefficiency): Constructor
- def Create(self): Create the plot | Implement the Python class `TriggerEfficiencySumPlot` described below.
Class description:
Plot the summed trigger efficiency from different pt-hard bins
Method signatures and docstrings:
- def __init__(self, triggername, triggerefficiency): Constructor
- def Create(self): Create the plot
<|skeleton|>
class TriggerEf... | 5df28b2b415e78e81273b0d9bf5c1b99feda3348 | <|skeleton|>
class TriggerEfficiencySumPlot:
"""Plot the summed trigger efficiency from different pt-hard bins"""
def __init__(self, triggername, triggerefficiency):
"""Constructor"""
<|body_0|>
def Create(self):
"""Create the plot"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TriggerEfficiencySumPlot:
"""Plot the summed trigger efficiency from different pt-hard bins"""
def __init__(self, triggername, triggerefficiency):
"""Constructor"""
SinglePanelPlot.__init__(self)
self.__triggername = triggername
self.__triggereff = triggerefficiency
d... | the_stack_v2_python_sparse | PWGJE/EMCALJetTasks/Tracks/analysis/plots/TriggerEfficiencyPlotMC.py | alisw/AliPhysics | train | 129 |
437da607e5e27f70750f22b4e1fbb1a8614e60f0 | [
"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... | Manages knowledge bases. Allows users to setup and maintain knowledge bases with their knowledge data. | KnowledgeBasesServicer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class KnowledgeBasesServicer:
"""Manages knowledge bases. Allows users to setup and maintain knowledge bases with their knowledge data."""
def ListKnowledgeBases(self, request, context):
"""Returns the list of all knowledge bases of the specified agent."""
<|body_0|>
def GetKn... | stack_v2_sparse_classes_10k_train_003223 | 5,251 | permissive | [
{
"docstring": "Returns the list of all knowledge bases of the specified agent.",
"name": "ListKnowledgeBases",
"signature": "def ListKnowledgeBases(self, request, context)"
},
{
"docstring": "Retrieves the specified knowledge base.",
"name": "GetKnowledgeBase",
"signature": "def GetKnow... | 4 | stack_v2_sparse_classes_30k_train_007257 | Implement the Python class `KnowledgeBasesServicer` described below.
Class description:
Manages knowledge bases. Allows users to setup and maintain knowledge bases with their knowledge data.
Method signatures and docstrings:
- def ListKnowledgeBases(self, request, context): Returns the list of all knowledge bases of ... | Implement the Python class `KnowledgeBasesServicer` described below.
Class description:
Manages knowledge bases. Allows users to setup and maintain knowledge bases with their knowledge data.
Method signatures and docstrings:
- def ListKnowledgeBases(self, request, context): Returns the list of all knowledge bases of ... | c9c830feb6b66c2e362f8fb5d147ef0c4f4a08cf | <|skeleton|>
class KnowledgeBasesServicer:
"""Manages knowledge bases. Allows users to setup and maintain knowledge bases with their knowledge data."""
def ListKnowledgeBases(self, request, context):
"""Returns the list of all knowledge bases of the specified agent."""
<|body_0|>
def GetKn... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class KnowledgeBasesServicer:
"""Manages knowledge bases. Allows users to setup and maintain knowledge bases with their knowledge data."""
def ListKnowledgeBases(self, request, context):
"""Returns the list of all knowledge bases of the specified agent."""
context.set_code(grpc.StatusCode.UNIMP... | the_stack_v2_python_sparse | pyenv/lib/python3.6/site-packages/dialogflow_v2beta1/proto/knowledge_base_pb2_grpc.py | ronald-rgr/ai-chatbot-smartguide | train | 0 |
04c9e321302ed20e361babd26f733f857436c8c1 | [
"if len(matrix) == 0 or len(matrix[0]) == 0:\n return 0\nmaxSide = 0\nrows, columns = (len(matrix), len(matrix[0]))\ndp = [[0] * columns for _ in range(rows)]\nfor i in range(rows):\n for j in range(columns):\n if matrix[i][j] == '1':\n if i == 0 or j == 0:\n dp[i][j] = 1\n ... | <|body_start_0|>
if len(matrix) == 0 or len(matrix[0]) == 0:
return 0
maxSide = 0
rows, columns = (len(matrix), len(matrix[0]))
dp = [[0] * columns for _ in range(rows)]
for i in range(rows):
for j in range(columns):
if matrix[i][j] == '1':... | Solution | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maximalSquare(self, matrix: List[List[str]]) -> int:
"""方法二：动态规划 时间复杂度：O(mn) 空间复杂度：O(mn) :param matrix: :return:"""
<|body_0|>
def maximalSquare_optimize(self, matrix: List[List[str]]) -> int:
"""方法二：动态规划 时间复杂度：O(mn) 空间复杂度：O(0) :param matrix: :return:""... | stack_v2_sparse_classes_10k_train_003224 | 2,226 | permissive | [
{
"docstring": "方法二：动态规划 时间复杂度：O(mn) 空间复杂度：O(mn) :param matrix: :return:",
"name": "maximalSquare",
"signature": "def maximalSquare(self, matrix: List[List[str]]) -> int"
},
{
"docstring": "方法二：动态规划 时间复杂度：O(mn) 空间复杂度：O(0) :param matrix: :return:",
"name": "maximalSquare_optimize",
"signa... | 2 | stack_v2_sparse_classes_30k_train_005322 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maximalSquare(self, matrix: List[List[str]]) -> int: 方法二：动态规划 时间复杂度：O(mn) 空间复杂度：O(mn) :param matrix: :return:
- def maximalSquare_optimize(self, matrix: List[List[str]]) -> i... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maximalSquare(self, matrix: List[List[str]]) -> int: 方法二：动态规划 时间复杂度：O(mn) 空间复杂度：O(mn) :param matrix: :return:
- def maximalSquare_optimize(self, matrix: List[List[str]]) -> i... | 62419b49000e79962bcdc99cd98afd2fb82ea345 | <|skeleton|>
class Solution:
def maximalSquare(self, matrix: List[List[str]]) -> int:
"""方法二：动态规划 时间复杂度：O(mn) 空间复杂度：O(mn) :param matrix: :return:"""
<|body_0|>
def maximalSquare_optimize(self, matrix: List[List[str]]) -> int:
"""方法二：动态规划 时间复杂度：O(mn) 空间复杂度：O(0) :param matrix: :return:""... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def maximalSquare(self, matrix: List[List[str]]) -> int:
"""方法二：动态规划 时间复杂度：O(mn) 空间复杂度：O(mn) :param matrix: :return:"""
if len(matrix) == 0 or len(matrix[0]) == 0:
return 0
maxSide = 0
rows, columns = (len(matrix), len(matrix[0]))
dp = [[0] * colum... | the_stack_v2_python_sparse | LeetCode 热题 HOT 100/maximalSquare.py | MaoningGuan/LeetCode | train | 3 | |
037d5658e5e85f09b18e9b0cab84902de5aed6fe | [
"super().__init__()\nself.average_by_layers = average_by_layers\nself.average_by_discriminators = average_by_discriminators\nself.include_final_outputs = include_final_outputs",
"feat_match_loss = 0.0\nfor i, (feats_hat_, feats_) in enumerate(zip(feats_hat, feats)):\n feat_match_loss_ = 0.0\n if not self.in... | <|body_start_0|>
super().__init__()
self.average_by_layers = average_by_layers
self.average_by_discriminators = average_by_discriminators
self.include_final_outputs = include_final_outputs
<|end_body_0|>
<|body_start_1|>
feat_match_loss = 0.0
for i, (feats_hat_, feats_) ... | Feature matching loss module. | FeatureMatchLoss | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FeatureMatchLoss:
"""Feature matching loss module."""
def __init__(self, average_by_layers=True, average_by_discriminators=True, include_final_outputs=False):
"""Initialize FeatureMatchLoss module."""
<|body_0|>
def forward(self, feats_hat, feats):
"""Calcualate ... | stack_v2_sparse_classes_10k_train_003225 | 46,210 | permissive | [
{
"docstring": "Initialize FeatureMatchLoss module.",
"name": "__init__",
"signature": "def __init__(self, average_by_layers=True, average_by_discriminators=True, include_final_outputs=False)"
},
{
"docstring": "Calcualate feature matching loss. Args: feats_hat(list): List of list of discriminat... | 2 | stack_v2_sparse_classes_30k_train_002752 | Implement the Python class `FeatureMatchLoss` described below.
Class description:
Feature matching loss module.
Method signatures and docstrings:
- def __init__(self, average_by_layers=True, average_by_discriminators=True, include_final_outputs=False): Initialize FeatureMatchLoss module.
- def forward(self, feats_hat... | Implement the Python class `FeatureMatchLoss` described below.
Class description:
Feature matching loss module.
Method signatures and docstrings:
- def __init__(self, average_by_layers=True, average_by_discriminators=True, include_final_outputs=False): Initialize FeatureMatchLoss module.
- def forward(self, feats_hat... | 17854a04d43c231eff66bfed9d6aa55e94a29e79 | <|skeleton|>
class FeatureMatchLoss:
"""Feature matching loss module."""
def __init__(self, average_by_layers=True, average_by_discriminators=True, include_final_outputs=False):
"""Initialize FeatureMatchLoss module."""
<|body_0|>
def forward(self, feats_hat, feats):
"""Calcualate ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class FeatureMatchLoss:
"""Feature matching loss module."""
def __init__(self, average_by_layers=True, average_by_discriminators=True, include_final_outputs=False):
"""Initialize FeatureMatchLoss module."""
super().__init__()
self.average_by_layers = average_by_layers
self.avera... | the_stack_v2_python_sparse | paddlespeech/t2s/modules/losses.py | anniyanvr/DeepSpeech-1 | train | 0 |
01d74009f652435a584d412cb72f39071a096ce0 | [
"self._targets_and_priorities = targets_and_priorities\nself._queue_name = queue_name\nsuper(NotificationPikaPoller, self).__init__(pika_engine, batch_size, batch_timeout, prefetch_count, pika_drv_msg.PikaIncomingMessage)",
"queues_to_consume = []\nfor target, priority in self._targets_and_priorities:\n routin... | <|body_start_0|>
self._targets_and_priorities = targets_and_priorities
self._queue_name = queue_name
super(NotificationPikaPoller, self).__init__(pika_engine, batch_size, batch_timeout, prefetch_count, pika_drv_msg.PikaIncomingMessage)
<|end_body_0|>
<|body_start_1|>
queues_to_consume =... | PikaPoller implementation for polling Notification messages. Overrides base functionality according to Notification specific | NotificationPikaPoller | [
"Python-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NotificationPikaPoller:
"""PikaPoller implementation for polling Notification messages. Overrides base functionality according to Notification specific"""
def __init__(self, pika_engine, targets_and_priorities, batch_size, batch_timeout, prefetch_count, queue_name=None):
"""Adds targ... | stack_v2_sparse_classes_10k_train_003226 | 22,231 | permissive | [
{
"docstring": "Adds targets_and_priorities and queue_name parameter for declaring exchanges and queues used for notification delivery :param pika_engine: PikaEngine, shared object with configuration and shared driver functionality :param targets_and_priorities: list of (target, priority), defines default queue... | 2 | stack_v2_sparse_classes_30k_test_000361 | Implement the Python class `NotificationPikaPoller` described below.
Class description:
PikaPoller implementation for polling Notification messages. Overrides base functionality according to Notification specific
Method signatures and docstrings:
- def __init__(self, pika_engine, targets_and_priorities, batch_size, b... | Implement the Python class `NotificationPikaPoller` described below.
Class description:
PikaPoller implementation for polling Notification messages. Overrides base functionality according to Notification specific
Method signatures and docstrings:
- def __init__(self, pika_engine, targets_and_priorities, batch_size, b... | c01951b33e278de9e769c2d0609c0be61d2cb26b | <|skeleton|>
class NotificationPikaPoller:
"""PikaPoller implementation for polling Notification messages. Overrides base functionality according to Notification specific"""
def __init__(self, pika_engine, targets_and_priorities, batch_size, batch_timeout, prefetch_count, queue_name=None):
"""Adds targ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class NotificationPikaPoller:
"""PikaPoller implementation for polling Notification messages. Overrides base functionality according to Notification specific"""
def __init__(self, pika_engine, targets_and_priorities, batch_size, batch_timeout, prefetch_count, queue_name=None):
"""Adds targets_and_prior... | the_stack_v2_python_sparse | filesystems/vnx_rootfs_lxc_ubuntu64-16.04-v025-openstack-compute/rootfs/usr/lib/python2.7/dist-packages/oslo_messaging/_drivers/pika_driver/pika_poller.py | juancarlosdiaztorres/Ansible-OpenStack | train | 0 |
4cbb13cea2166ce462e8ddd8c8520c6fb94f7974 | [
"self.max_width = max_width\nself.closed = False\nsuper().__init__(visible=False, vsync=False, resizable=True)",
"assert isinstance(x, np.ndarray), f'expected numpy array dtype, got {type(x)}'\nassert x.ndim == 3, f'expected ndim=3, got {x.ndim}'\nassert x.shape[-1] == 3, f'expected 3 color channel, got {x.shape[... | <|body_start_0|>
self.max_width = max_width
self.closed = False
super().__init__(visible=False, vsync=False, resizable=True)
<|end_body_0|>
<|body_start_1|>
assert isinstance(x, np.ndarray), f'expected numpy array dtype, got {type(x)}'
assert x.ndim == 3, f'expected ndim=3, got ... | Display an image from an RGB array in an OpenGL window. Example:: imageviewer = ImageViewer(max_width=500) image = np.asarray(Image.open('x.jpg')) imageviewer(image) | ImageViewer | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ImageViewer:
"""Display an image from an RGB array in an OpenGL window. Example:: imageviewer = ImageViewer(max_width=500) image = np.asarray(Image.open('x.jpg')) imageviewer(image)"""
def __init__(self, max_width=500):
"""Initialize the OpenGL window. Args: max_width (int): maximum ... | stack_v2_sparse_classes_10k_train_003227 | 3,097 | permissive | [
{
"docstring": "Initialize the OpenGL window. Args: max_width (int): maximum width of the window.",
"name": "__init__",
"signature": "def __init__(self, max_width=500)"
},
{
"docstring": "Create an image from the given RGB array and display to the window. Args: x (ndarray): RGB array",
"name... | 3 | stack_v2_sparse_classes_30k_train_002761 | Implement the Python class `ImageViewer` described below.
Class description:
Display an image from an RGB array in an OpenGL window. Example:: imageviewer = ImageViewer(max_width=500) image = np.asarray(Image.open('x.jpg')) imageviewer(image)
Method signatures and docstrings:
- def __init__(self, max_width=500): Init... | Implement the Python class `ImageViewer` described below.
Class description:
Display an image from an RGB array in an OpenGL window. Example:: imageviewer = ImageViewer(max_width=500) image = np.asarray(Image.open('x.jpg')) imageviewer(image)
Method signatures and docstrings:
- def __init__(self, max_width=500): Init... | 273bb7f5babb1f250f6dba0b5f62c6614f301719 | <|skeleton|>
class ImageViewer:
"""Display an image from an RGB array in an OpenGL window. Example:: imageviewer = ImageViewer(max_width=500) image = np.asarray(Image.open('x.jpg')) imageviewer(image)"""
def __init__(self, max_width=500):
"""Initialize the OpenGL window. Args: max_width (int): maximum ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ImageViewer:
"""Display an image from an RGB array in an OpenGL window. Example:: imageviewer = ImageViewer(max_width=500) image = np.asarray(Image.open('x.jpg')) imageviewer(image)"""
def __init__(self, max_width=500):
"""Initialize the OpenGL window. Args: max_width (int): maximum width of the ... | the_stack_v2_python_sparse | lagom/vis/image_viewer.py | LorinChen/lagom | train | 1 |
8dec117412f8275c66f7246110daf7d506cf2fcf | [
"DataMatrixGuiXYProbe.__init__(self, plot_title=plot_title, id_is_strain=id_is_strain)\nself.app1.set_title(plot_title)\nself.id2NA_mismatch_rate = id2NA_mismatch_rate\nself.plot_title = plot_title\nself.id2info = id2info\nself.id2index = id2index\nself.id_is_strain = id_is_strain\nself.header = header\nself.strain... | <|body_start_0|>
DataMatrixGuiXYProbe.__init__(self, plot_title=plot_title, id_is_strain=id_is_strain)
self.app1.set_title(plot_title)
self.id2NA_mismatch_rate = id2NA_mismatch_rate
self.plot_title = plot_title
self.id2info = id2info
self.id2index = id2index
self.... | 2009-3-24 trunk moved to indepedent DataMatrixGuiXYProbe.py and inherits from it 2008-02-05 embed it into a bigger gnome app, add more buttons, and change the __init__() 2008-01-01 class to visualize the results from QualityControl.py | QCVisualize | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class QCVisualize:
"""2009-3-24 trunk moved to indepedent DataMatrixGuiXYProbe.py and inherits from it 2008-02-05 embed it into a bigger gnome app, add more buttons, and change the __init__() 2008-01-01 class to visualize the results from QualityControl.py"""
def __init__(self, id2NA_mismatch_rate... | stack_v2_sparse_classes_10k_train_003228 | 3,098 | no_license | [
{
"docstring": "2008-01-10 use a paned window to wrap the scrolledwindow and the canvas so that the relative size of canvas to the scrolledwindow could be adjusted by the user.",
"name": "__init__",
"signature": "def __init__(self, id2NA_mismatch_rate, plot_title='', id2info={}, id2index={}, id_is_strai... | 2 | stack_v2_sparse_classes_30k_train_003423 | Implement the Python class `QCVisualize` described below.
Class description:
2009-3-24 trunk moved to indepedent DataMatrixGuiXYProbe.py and inherits from it 2008-02-05 embed it into a bigger gnome app, add more buttons, and change the __init__() 2008-01-01 class to visualize the results from QualityControl.py
Method... | Implement the Python class `QCVisualize` described below.
Class description:
2009-3-24 trunk moved to indepedent DataMatrixGuiXYProbe.py and inherits from it 2008-02-05 embed it into a bigger gnome app, add more buttons, and change the __init__() 2008-01-01 class to visualize the results from QualityControl.py
Method... | 7b402496aae81665e6a915b5021b94d56e034c9d | <|skeleton|>
class QCVisualize:
"""2009-3-24 trunk moved to indepedent DataMatrixGuiXYProbe.py and inherits from it 2008-02-05 embed it into a bigger gnome app, add more buttons, and change the __init__() 2008-01-01 class to visualize the results from QualityControl.py"""
def __init__(self, id2NA_mismatch_rate... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class QCVisualize:
"""2009-3-24 trunk moved to indepedent DataMatrixGuiXYProbe.py and inherits from it 2008-02-05 embed it into a bigger gnome app, add more buttons, and change the __init__() 2008-01-01 class to visualize the results from QualityControl.py"""
def __init__(self, id2NA_mismatch_rate, plot_title=... | the_stack_v2_python_sparse | pymodule/trunk/QCVisualize.py | polyactis/repos | train | 1 |
8f08a3634154cb2bc8caada8c7b81685d16f84bf | [
"provinces = 0\nvisited = set()\nq = deque()\nfor left in range(len(is_connected)):\n if left not in visited:\n q.append(left)\n while q:\n curr = q.popleft()\n if curr not in visited:\n visited.add(curr)\n for neighbor in range(len(is_connected)):\n ... | <|body_start_0|>
provinces = 0
visited = set()
q = deque()
for left in range(len(is_connected)):
if left not in visited:
q.append(left)
while q:
curr = q.popleft()
if curr not in visited:
... | City | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class City:
def number_of_provinces_bfs(self, is_connected: List[List[int]]) -> int:
"""Approach: BFS Time Complexity: O(N^2) Space Complexity: O(N) :param is_connected: :return:"""
<|body_0|>
def number_of_provinces_dfs(self, is_connected: List[List[int]]) -> int:
"""Appr... | stack_v2_sparse_classes_10k_train_003229 | 2,443 | no_license | [
{
"docstring": "Approach: BFS Time Complexity: O(N^2) Space Complexity: O(N) :param is_connected: :return:",
"name": "number_of_provinces_bfs",
"signature": "def number_of_provinces_bfs(self, is_connected: List[List[int]]) -> int"
},
{
"docstring": "Approach: DFS Time Complexity: O(N^2) Space Co... | 2 | null | Implement the Python class `City` described below.
Class description:
Implement the City class.
Method signatures and docstrings:
- def number_of_provinces_bfs(self, is_connected: List[List[int]]) -> int: Approach: BFS Time Complexity: O(N^2) Space Complexity: O(N) :param is_connected: :return:
- def number_of_provin... | Implement the Python class `City` described below.
Class description:
Implement the City class.
Method signatures and docstrings:
- def number_of_provinces_bfs(self, is_connected: List[List[int]]) -> int: Approach: BFS Time Complexity: O(N^2) Space Complexity: O(N) :param is_connected: :return:
- def number_of_provin... | 65cc78b5afa0db064f9fe8f06597e3e120f7363d | <|skeleton|>
class City:
def number_of_provinces_bfs(self, is_connected: List[List[int]]) -> int:
"""Approach: BFS Time Complexity: O(N^2) Space Complexity: O(N) :param is_connected: :return:"""
<|body_0|>
def number_of_provinces_dfs(self, is_connected: List[List[int]]) -> int:
"""Appr... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class City:
def number_of_provinces_bfs(self, is_connected: List[List[int]]) -> int:
"""Approach: BFS Time Complexity: O(N^2) Space Complexity: O(N) :param is_connected: :return:"""
provinces = 0
visited = set()
q = deque()
for left in range(len(is_connected)):
if... | the_stack_v2_python_sparse | goldman_sachs/number_of_provinces.py | Shiv2157k/leet_code | train | 1 | |
2d9b5a2a11b4b00364cf6b322e06001133bc0c98 | [
"qe = Queue.Queue(maxsize=0)\nqe.put(root)\ndata = []\nwhile not qe.empty():\n node = qe.get()\n if node:\n data.append(str(node.val))\n qe.put(node.left)\n qe.put(node.right)\n else:\n data.append('null')\nreturn ' '.join(data)",
"myiter = iter(data.split())\nqe = Queue.Queue... | <|body_start_0|>
qe = Queue.Queue(maxsize=0)
qe.put(root)
data = []
while not qe.empty():
node = qe.get()
if node:
data.append(str(node.val))
qe.put(node.left)
qe.put(node.right)
else:
dat... | Codec | [
"MIT"
] | 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_10k_train_003230 | 1,528 | permissive | [
{
"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_001505 | 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:... | c8bf33af30569177c5276ffcd72a8d93ba4c402a | <|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_10k | data/stack_v2_sparse_classes_30k | class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
qe = Queue.Queue(maxsize=0)
qe.put(root)
data = []
while not qe.empty():
node = qe.get()
if node:
data.append(str(node.val... | the_stack_v2_python_sparse | 201-300/291-300/297-serializeAndDeserializeBinaryTree/serializeAndDeserializeBinaryTree.py | xuychen/Leetcode | train | 0 | |
f8bcf9c38da426f45171d975250c44d716df0c5f | [
"super().__init__()\nself.label_arr = np.asarray(['NULL'] + classes)\npath_to_ckpt = inference_graph\nself.detection_graph = tf.Graph()\nwith self.detection_graph.as_default():\n od_graph_def = tf.GraphDef()\n with tf.gfile.GFile(path_to_ckpt, 'rb') as fid:\n serialized_graph = fid.read()\n od_g... | <|body_start_0|>
super().__init__()
self.label_arr = np.asarray(['NULL'] + classes)
path_to_ckpt = inference_graph
self.detection_graph = tf.Graph()
with self.detection_graph.as_default():
od_graph_def = tf.GraphDef()
with tf.gfile.GFile(path_to_ckpt, 'rb'... | TFDetector | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TFDetector:
def __init__(self, classes, inference_graph='frozen_graph.pb'):
"""Initialize Detector Object"""
<|body_0|>
def predict(self, images_data, batch_size=10, min_confidence=0.7):
"""Predict results from list of images to list of boxes"""
<|body_1|>
<... | stack_v2_sparse_classes_10k_train_003231 | 2,196 | permissive | [
{
"docstring": "Initialize Detector Object",
"name": "__init__",
"signature": "def __init__(self, classes, inference_graph='frozen_graph.pb')"
},
{
"docstring": "Predict results from list of images to list of boxes",
"name": "predict",
"signature": "def predict(self, images_data, batch_s... | 2 | stack_v2_sparse_classes_30k_train_002781 | Implement the Python class `TFDetector` described below.
Class description:
Implement the TFDetector class.
Method signatures and docstrings:
- def __init__(self, classes, inference_graph='frozen_graph.pb'): Initialize Detector Object
- def predict(self, images_data, batch_size=10, min_confidence=0.7): Predict result... | Implement the Python class `TFDetector` described below.
Class description:
Implement the TFDetector class.
Method signatures and docstrings:
- def __init__(self, classes, inference_graph='frozen_graph.pb'): Initialize Detector Object
- def predict(self, images_data, batch_size=10, min_confidence=0.7): Predict result... | 7a20d4350c630017d11f964a4996dce8b9a8251b | <|skeleton|>
class TFDetector:
def __init__(self, classes, inference_graph='frozen_graph.pb'):
"""Initialize Detector Object"""
<|body_0|>
def predict(self, images_data, batch_size=10, min_confidence=0.7):
"""Predict results from list of images to list of boxes"""
<|body_1|>
<... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TFDetector:
def __init__(self, classes, inference_graph='frozen_graph.pb'):
"""Initialize Detector Object"""
super().__init__()
self.label_arr = np.asarray(['NULL'] + classes)
path_to_ckpt = inference_graph
self.detection_graph = tf.Graph()
with self.detection_g... | the_stack_v2_python_sparse | train/tf_detector.py | CatalystCode/active-learning-detect | train | 5 | |
f58c08ea38b41ddea754e06fbbbcca2488828904 | [
"for k in list(orig_dict.keys()):\n if k not in keys_whitelist:\n del orig_dict[k]\nfor v in orig_dict.values():\n if isinstance(v, dict):\n self.delete_keys_from_dict(v, keys_whitelist)\nreturn orig_dict",
"if not self.fields:\n raise ImproperlyConfigured('fields attribute must be specifie... | <|body_start_0|>
for k in list(orig_dict.keys()):
if k not in keys_whitelist:
del orig_dict[k]
for v in orig_dict.values():
if isinstance(v, dict):
self.delete_keys_from_dict(v, keys_whitelist)
return orig_dict
<|end_body_0|>
<|body_start_... | GenericCSVRenderer | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GenericCSVRenderer:
def delete_keys_from_dict(self, orig_dict, keys_whitelist):
"""recursively delete keys which are not in whitelist from dict"""
<|body_0|>
def render(self, data, media_type=None, renderer_context=None, writer_opts=None):
"""extract the array from r... | stack_v2_sparse_classes_10k_train_003232 | 1,211 | permissive | [
{
"docstring": "recursively delete keys which are not in whitelist from dict",
"name": "delete_keys_from_dict",
"signature": "def delete_keys_from_dict(self, orig_dict, keys_whitelist)"
},
{
"docstring": "extract the array from results field & remove fields which were not specified in whitelist"... | 2 | stack_v2_sparse_classes_30k_train_004872 | Implement the Python class `GenericCSVRenderer` described below.
Class description:
Implement the GenericCSVRenderer class.
Method signatures and docstrings:
- def delete_keys_from_dict(self, orig_dict, keys_whitelist): recursively delete keys which are not in whitelist from dict
- def render(self, data, media_type=N... | Implement the Python class `GenericCSVRenderer` described below.
Class description:
Implement the GenericCSVRenderer class.
Method signatures and docstrings:
- def delete_keys_from_dict(self, orig_dict, keys_whitelist): recursively delete keys which are not in whitelist from dict
- def render(self, data, media_type=N... | cf9ab30c67523062e1a3e0b8ff1b7b5ba4c8586f | <|skeleton|>
class GenericCSVRenderer:
def delete_keys_from_dict(self, orig_dict, keys_whitelist):
"""recursively delete keys which are not in whitelist from dict"""
<|body_0|>
def render(self, data, media_type=None, renderer_context=None, writer_opts=None):
"""extract the array from r... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class GenericCSVRenderer:
def delete_keys_from_dict(self, orig_dict, keys_whitelist):
"""recursively delete keys which are not in whitelist from dict"""
for k in list(orig_dict.keys()):
if k not in keys_whitelist:
del orig_dict[k]
for v in orig_dict.values():
... | the_stack_v2_python_sparse | server/server/utils/renderers.py | jeremyhakoune/connective | train | 0 | |
ee310356b759caa9cd866ebc52212b8533a0dc33 | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn Reminder()",
"from .date_time_time_zone import DateTimeTimeZone\nfrom .location import Location\nfrom .date_time_time_zone import DateTimeTimeZone\nfrom .location import Location\nfields: Dict[str, Callable[[Any], None]] = {'changeKey'... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return Reminder()
<|end_body_0|>
<|body_start_1|>
from .date_time_time_zone import DateTimeTimeZone
from .location import Location
from .date_time_time_zone import DateTimeTimeZone
... | Reminder | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Reminder:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Reminder:
"""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: Reminder... | stack_v2_sparse_classes_10k_train_003233 | 4,994 | 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: Reminder",
"name": "create_from_discriminator_value",
"signature": "def create_from_discriminator_value(pars... | 3 | stack_v2_sparse_classes_30k_train_006280 | Implement the Python class `Reminder` described below.
Class description:
Implement the Reminder class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Reminder: Creates a new instance of the appropriate class based on discriminator value Args: parse_no... | Implement the Python class `Reminder` described below.
Class description:
Implement the Reminder class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Reminder: Creates a new instance of the appropriate class based on discriminator value Args: parse_no... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class Reminder:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Reminder:
"""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: Reminder... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Reminder:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Reminder:
"""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: Reminder"""
if... | the_stack_v2_python_sparse | msgraph/generated/models/reminder.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
89aff1c7f830d2af2833704660c9d395c210f07c | [
"super().__init__()\nself.yaml_file_path = yaml_file_path\nself.key = key\nself.expected = expected",
"base_message = self.base_message.format(filename=self.yaml_file_path)\nerror_message = ERROR_MESSAGE.format(key=self.key, expected=self.expected)\nreturn base_message + error_message"
] | <|body_start_0|>
super().__init__()
self.yaml_file_path = yaml_file_path
self.key = key
self.expected = expected
<|end_body_0|>
<|body_start_1|>
base_message = self.base_message.format(filename=self.yaml_file_path)
error_message = ERROR_MESSAGE.format(key=self.key, expec... | Custom error for invalid config file value. | InvalidYAMLValueError | [
"CC-BY-NC-SA-4.0",
"BSD-3-Clause",
"CC0-1.0",
"ISC",
"Unlicense",
"LicenseRef-scancode-secret-labs-2011",
"WTFPL",
"Apache-2.0",
"LGPL-3.0-only",
"MIT",
"CC-BY-SA-4.0",
"LicenseRef-scancode-public-domain",
"CC-BY-NC-2.5",
"LicenseRef-scancode-other-copyleft",
"LicenseRef-scancode-unknown... | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InvalidYAMLValueError:
"""Custom error for invalid config file value."""
def __init__(self, yaml_file_path, key, expected):
"""Create error for invalid config file value."""
<|body_0|>
def __str__(self):
"""Override default error string. Returns: Error message fo... | stack_v2_sparse_classes_10k_train_003234 | 859 | permissive | [
{
"docstring": "Create error for invalid config file value.",
"name": "__init__",
"signature": "def __init__(self, yaml_file_path, key, expected)"
},
{
"docstring": "Override default error string. Returns: Error message for invalid config file value.",
"name": "__str__",
"signature": "de... | 2 | stack_v2_sparse_classes_30k_train_000773 | Implement the Python class `InvalidYAMLValueError` described below.
Class description:
Custom error for invalid config file value.
Method signatures and docstrings:
- def __init__(self, yaml_file_path, key, expected): Create error for invalid config file value.
- def __str__(self): Override default error string. Retu... | Implement the Python class `InvalidYAMLValueError` described below.
Class description:
Custom error for invalid config file value.
Method signatures and docstrings:
- def __init__(self, yaml_file_path, key, expected): Create error for invalid config file value.
- def __str__(self): Override default error string. Retu... | ea3281ec6f4d17538f6d3cf6f88d74fa54581b34 | <|skeleton|>
class InvalidYAMLValueError:
"""Custom error for invalid config file value."""
def __init__(self, yaml_file_path, key, expected):
"""Create error for invalid config file value."""
<|body_0|>
def __str__(self):
"""Override default error string. Returns: Error message fo... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class InvalidYAMLValueError:
"""Custom error for invalid config file value."""
def __init__(self, yaml_file_path, key, expected):
"""Create error for invalid config file value."""
super().__init__()
self.yaml_file_path = yaml_file_path
self.key = key
self.expected = expe... | the_stack_v2_python_sparse | csfieldguide/utils/errors/InvalidYAMLValueError.py | uccser/cs-field-guide | train | 364 |
be76ad3d413e402df7e6ac137d0d26a444ef98f9 | [
"super().__init__(max_number=max_number, min_number=min_number, seed=seed)\nself.stamp_size = stamp_size\nself.max_shift = max_shift if max_shift is not None else self.stamp_size / 10.0\nself.min_mag, self.max_mag = (min_mag, max_mag)\nself.mag_name = mag_name",
"if self.mag_name not in table.colnames:\n raise... | <|body_start_0|>
super().__init__(max_number=max_number, min_number=min_number, seed=seed)
self.stamp_size = stamp_size
self.max_shift = max_shift if max_shift is not None else self.stamp_size / 10.0
self.min_mag, self.max_mag = (min_mag, max_mag)
self.mag_name = mag_name
<|end_b... | Default sampling function used for producing blend catalogs. | DefaultSampling | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DefaultSampling:
"""Default sampling function used for producing blend catalogs."""
def __init__(self, max_number: int=2, min_number: int=1, stamp_size: float=24.0, max_shift: Optional[float]=None, seed: int=DEFAULT_SEED, max_mag: float=25.3, min_mag: float=-np.inf, mag_name: str='i_ab'):
... | stack_v2_sparse_classes_10k_train_003235 | 12,943 | permissive | [
{
"docstring": "Initializes default sampling function. Args: max_number: Defined in parent class min_number: Defined in parent class stamp_size: Size of the desired stamp. max_shift: Magnitude of maximum value of shift. If None then it is set as one-tenth the stamp size. (in arcseconds) seed: Seed to initialize... | 2 | stack_v2_sparse_classes_30k_train_005306 | Implement the Python class `DefaultSampling` described below.
Class description:
Default sampling function used for producing blend catalogs.
Method signatures and docstrings:
- def __init__(self, max_number: int=2, min_number: int=1, stamp_size: float=24.0, max_shift: Optional[float]=None, seed: int=DEFAULT_SEED, ma... | Implement the Python class `DefaultSampling` described below.
Class description:
Default sampling function used for producing blend catalogs.
Method signatures and docstrings:
- def __init__(self, max_number: int=2, min_number: int=1, stamp_size: float=24.0, max_shift: Optional[float]=None, seed: int=DEFAULT_SEED, ma... | f5b716a373f130238100db8980aa0d282822983a | <|skeleton|>
class DefaultSampling:
"""Default sampling function used for producing blend catalogs."""
def __init__(self, max_number: int=2, min_number: int=1, stamp_size: float=24.0, max_shift: Optional[float]=None, seed: int=DEFAULT_SEED, max_mag: float=25.3, min_mag: float=-np.inf, mag_name: str='i_ab'):
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class DefaultSampling:
"""Default sampling function used for producing blend catalogs."""
def __init__(self, max_number: int=2, min_number: int=1, stamp_size: float=24.0, max_shift: Optional[float]=None, seed: int=DEFAULT_SEED, max_mag: float=25.3, min_mag: float=-np.inf, mag_name: str='i_ab'):
"""Init... | the_stack_v2_python_sparse | btk/sampling_functions.py | LSSTDESC/BlendingToolKit | train | 22 |
87ba21ab4977176f06a9a27646d4a9ccd241fdf8 | [
"layer = QgsMapLayerRegistry.instance().mapLayersByName(layerName)[0]\nlayer.setCustomProperty('labeling', 'pal')\nlayer.setCustomProperty('labeling/enabled', 'True')\nlayer.setCustomProperty('labeling/fieldName', fieldName)\nlayer.setCustomProperty('labeling/fontFamily', fontFamily)\nlayer.setCustomProperty('label... | <|body_start_0|>
layer = QgsMapLayerRegistry.instance().mapLayersByName(layerName)[0]
layer.setCustomProperty('labeling', 'pal')
layer.setCustomProperty('labeling/enabled', 'True')
layer.setCustomProperty('labeling/fieldName', fieldName)
layer.setCustomProperty('labeling/fontFami... | Class that deals with vector layer labels | Label | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Label:
"""Class that deals with vector layer labels"""
def nameLabel(self, layerName, fieldName, fontFamily='Arial', fontSize=8, fontWeight=50, fontItalic=False, fontUnderline=False, fontStrikeout=False):
"""Set label and format based on the parameters passed"""
<|body_0|>
... | stack_v2_sparse_classes_10k_train_003236 | 2,279 | no_license | [
{
"docstring": "Set label and format based on the parameters passed",
"name": "nameLabel",
"signature": "def nameLabel(self, layerName, fieldName, fontFamily='Arial', fontSize=8, fontWeight=50, fontItalic=False, fontUnderline=False, fontStrikeout=False)"
},
{
"docstring": "Show font dialog and p... | 3 | stack_v2_sparse_classes_30k_train_006215 | Implement the Python class `Label` described below.
Class description:
Class that deals with vector layer labels
Method signatures and docstrings:
- def nameLabel(self, layerName, fieldName, fontFamily='Arial', fontSize=8, fontWeight=50, fontItalic=False, fontUnderline=False, fontStrikeout=False): Set label and forma... | Implement the Python class `Label` described below.
Class description:
Class that deals with vector layer labels
Method signatures and docstrings:
- def nameLabel(self, layerName, fieldName, fontFamily='Arial', fontSize=8, fontWeight=50, fontItalic=False, fontUnderline=False, fontStrikeout=False): Set label and forma... | ba1fd3a139580e00eca4aa87ad8e49f46718d58a | <|skeleton|>
class Label:
"""Class that deals with vector layer labels"""
def nameLabel(self, layerName, fieldName, fontFamily='Arial', fontSize=8, fontWeight=50, fontItalic=False, fontUnderline=False, fontStrikeout=False):
"""Set label and format based on the parameters passed"""
<|body_0|>
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Label:
"""Class that deals with vector layer labels"""
def nameLabel(self, layerName, fieldName, fontFamily='Arial', fontSize=8, fontWeight=50, fontItalic=False, fontUnderline=False, fontStrikeout=False):
"""Set label and format based on the parameters passed"""
layer = QgsMapLayerRegistr... | the_stack_v2_python_sparse | labels.py | Charlotteg/QGISforSchools | train | 1 |
605f20002a174659c4cf9f6defb33d98d55a291e | [
"super().__init__(order=CallbackOrder.external, node=CallbackNode.all)\nself.best_score = None\nself.metric = metric\nself.patience = patience\nself.num_bad_epochs = 0\nself.is_better = None\nif minimize:\n self.is_better = lambda score, best: score <= best - min_delta\nelse:\n self.is_better = lambda score, ... | <|body_start_0|>
super().__init__(order=CallbackOrder.external, node=CallbackNode.all)
self.best_score = None
self.metric = metric
self.patience = patience
self.num_bad_epochs = 0
self.is_better = None
if minimize:
self.is_better = lambda score, best: ... | Early exit based on metric. Minimal working example (Notebook API): .. code-block:: python import torch from torch.utils.data import DataLoader, TensorDataset from catalyst import dl # data num_samples, num_features = int(1e4), int(1e1) X, y = torch.rand(num_samples, num_features), torch.rand(num_samples) dataset = Ten... | EarlyStoppingCallback | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EarlyStoppingCallback:
"""Early exit based on metric. Minimal working example (Notebook API): .. code-block:: python import torch from torch.utils.data import DataLoader, TensorDataset from catalyst import dl # data num_samples, num_features = int(1e4), int(1e1) X, y = torch.rand(num_samples, num... | stack_v2_sparse_classes_10k_train_003237 | 6,187 | permissive | [
{
"docstring": "Args: patience: number of epochs with no improvement after which training will be stopped. metric: metric name to use for early stopping, default is ``\"loss\"``. minimize: if ``True`` then expected that metric should decrease and early stopping will be performed only when metric stops decreasin... | 2 | stack_v2_sparse_classes_30k_train_006277 | Implement the Python class `EarlyStoppingCallback` described below.
Class description:
Early exit based on metric. Minimal working example (Notebook API): .. code-block:: python import torch from torch.utils.data import DataLoader, TensorDataset from catalyst import dl # data num_samples, num_features = int(1e4), int(... | Implement the Python class `EarlyStoppingCallback` described below.
Class description:
Early exit based on metric. Minimal working example (Notebook API): .. code-block:: python import torch from torch.utils.data import DataLoader, TensorDataset from catalyst import dl # data num_samples, num_features = int(1e4), int(... | 8ce39fc31635eabc348b055a2df8ec8bc5700dce | <|skeleton|>
class EarlyStoppingCallback:
"""Early exit based on metric. Minimal working example (Notebook API): .. code-block:: python import torch from torch.utils.data import DataLoader, TensorDataset from catalyst import dl # data num_samples, num_features = int(1e4), int(1e1) X, y = torch.rand(num_samples, num... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class EarlyStoppingCallback:
"""Early exit based on metric. Minimal working example (Notebook API): .. code-block:: python import torch from torch.utils.data import DataLoader, TensorDataset from catalyst import dl # data num_samples, num_features = int(1e4), int(1e1) X, y = torch.rand(num_samples, num_features), t... | the_stack_v2_python_sparse | catalyst/callbacks/early_stop.py | 418sec/catalyst | train | 0 |
68e64a0b50e48ffba72ec442b8031f578f210cea | [
"params = dict(((key, val) for key, val in request.QUERY_PARAMS.iteritems()))\nparams['image_id'] = image_id\nparams['tag_group_id'] = tag_group_id\nparams['tag_id'] = tag_id\nform = MultiGetForm(params)\nif not form.is_valid():\n raise BadRequestException()\nreturn Response(form.submit(request))",
"params = d... | <|body_start_0|>
params = dict(((key, val) for key, val in request.QUERY_PARAMS.iteritems()))
params['image_id'] = image_id
params['tag_group_id'] = tag_group_id
params['tag_id'] = tag_id
form = MultiGetForm(params)
if not form.is_valid():
raise BadRequestExce... | Class for rendering the view for creating GeneLinks and searching through the GeneLinks. | GeneLinkList | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GeneLinkList:
"""Class for rendering the view for creating GeneLinks and searching through the GeneLinks."""
def get(self, request, image_id, tag_group_id, tag_id):
"""Method for getting multiple GeneLinks either through search or general listing."""
<|body_0|>
def post(... | stack_v2_sparse_classes_10k_train_003238 | 2,768 | no_license | [
{
"docstring": "Method for getting multiple GeneLinks either through search or general listing.",
"name": "get",
"signature": "def get(self, request, image_id, tag_group_id, tag_id)"
},
{
"docstring": "Method for creating a new GeneLink.",
"name": "post",
"signature": "def post(self, req... | 2 | stack_v2_sparse_classes_30k_train_006137 | Implement the Python class `GeneLinkList` described below.
Class description:
Class for rendering the view for creating GeneLinks and searching through the GeneLinks.
Method signatures and docstrings:
- def get(self, request, image_id, tag_group_id, tag_id): Method for getting multiple GeneLinks either through search... | Implement the Python class `GeneLinkList` described below.
Class description:
Class for rendering the view for creating GeneLinks and searching through the GeneLinks.
Method signatures and docstrings:
- def get(self, request, image_id, tag_group_id, tag_id): Method for getting multiple GeneLinks either through search... | 22c1ce3c5a8e4ed99c2f014672d60ad3c5a4003c | <|skeleton|>
class GeneLinkList:
"""Class for rendering the view for creating GeneLinks and searching through the GeneLinks."""
def get(self, request, image_id, tag_group_id, tag_id):
"""Method for getting multiple GeneLinks either through search or general listing."""
<|body_0|>
def post(... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class GeneLinkList:
"""Class for rendering the view for creating GeneLinks and searching through the GeneLinks."""
def get(self, request, image_id, tag_group_id, tag_id):
"""Method for getting multiple GeneLinks either through search or general listing."""
params = dict(((key, val) for key, val... | the_stack_v2_python_sparse | biodig/rest/v2/GeneLinks/views.py | asmariyaz23/BioDIG | train | 0 |
5c6d1ecab9c2806da2262d58ed9ffa15499e9708 | [
"super().__init__()\nself.args = quant_arc_interface.args\nself.q_params = nn.Parameter(self.args.q_delta * torch.randn(self.args.q_depth * self.args.n_qubits))\nself.qai = quant_arc_interface",
"q_in = torch.tanh(input_features) * np.pi / 2.0\nq_in = q_in.to(self.args.device)\nq_out = torch.Tensor(0, self.qai.se... | <|body_start_0|>
super().__init__()
self.args = quant_arc_interface.args
self.q_params = nn.Parameter(self.args.q_delta * torch.randn(self.args.q_depth * self.args.n_qubits))
self.qai = quant_arc_interface
<|end_body_0|>
<|body_start_1|>
q_in = torch.tanh(input_features) * np.pi... | Torch module implementing the *dressed* quantum net. | QNet_1 | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class QNet_1:
"""Torch module implementing the *dressed* quantum net."""
def __init__(self, quant_arc_interface):
"""Definition of the *dressed* layout."""
<|body_0|>
def forward(self, input_features):
"""Defining how tensors are supposed to move through the *dressed* ... | stack_v2_sparse_classes_10k_train_003239 | 2,951 | permissive | [
{
"docstring": "Definition of the *dressed* layout.",
"name": "__init__",
"signature": "def __init__(self, quant_arc_interface)"
},
{
"docstring": "Defining how tensors are supposed to move through the *dressed* quantum net.",
"name": "forward",
"signature": "def forward(self, input_feat... | 2 | stack_v2_sparse_classes_30k_train_005501 | Implement the Python class `QNet_1` described below.
Class description:
Torch module implementing the *dressed* quantum net.
Method signatures and docstrings:
- def __init__(self, quant_arc_interface): Definition of the *dressed* layout.
- def forward(self, input_features): Defining how tensors are supposed to move t... | Implement the Python class `QNet_1` described below.
Class description:
Torch module implementing the *dressed* quantum net.
Method signatures and docstrings:
- def __init__(self, quant_arc_interface): Definition of the *dressed* layout.
- def forward(self, input_features): Defining how tensors are supposed to move t... | 8126691b43bddc2b1a96f73ab35d04d1af200d7a | <|skeleton|>
class QNet_1:
"""Torch module implementing the *dressed* quantum net."""
def __init__(self, quant_arc_interface):
"""Definition of the *dressed* layout."""
<|body_0|>
def forward(self, input_features):
"""Defining how tensors are supposed to move through the *dressed* ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class QNet_1:
"""Torch module implementing the *dressed* quantum net."""
def __init__(self, quant_arc_interface):
"""Definition of the *dressed* layout."""
super().__init__()
self.args = quant_arc_interface.args
self.q_params = nn.Parameter(self.args.q_delta * torch.randn(self.a... | the_stack_v2_python_sparse | model/dvqc_layers.py | zzh237/quanthmc | train | 0 |
2723fb1ad8050a2b1f8a90964f12661e0e0ca92a | [
"super(EncoderBlock, self).__init__()\nself.mha = MultiHeadAttention(dm, h)\nself.dense_hidden = tf.keras.layers.Dense(units=hidden, activation='relu')\nself.dense_output = tf.keras.layers.Dense(units=dm)\nself.layernorm1 = tf.keras.layers.LayerNormalization(epsilon=1e-06)\nself.layernorm2 = tf.keras.layers.LayerNo... | <|body_start_0|>
super(EncoderBlock, self).__init__()
self.mha = MultiHeadAttention(dm, h)
self.dense_hidden = tf.keras.layers.Dense(units=hidden, activation='relu')
self.dense_output = tf.keras.layers.Dense(units=dm)
self.layernorm1 = tf.keras.layers.LayerNormalization(epsilon=1... | Class MultiHeadAttention | EncoderBlock | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EncoderBlock:
"""Class MultiHeadAttention"""
def __init__(self, dm, h, hidden, drop_rate=0.1):
"""Constructor Class constructor dm - the dimensionality of the model h - the number of heads hidden - the number of hidden units in the fully connected layer drop_rate - the dropout rate S... | stack_v2_sparse_classes_10k_train_003240 | 2,302 | permissive | [
{
"docstring": "Constructor Class constructor dm - the dimensionality of the model h - the number of heads hidden - the number of hidden units in the fully connected layer drop_rate - the dropout rate Sets the following public instance attributes: mha - a MultiHeadAttention layer dense_hidden - the hidden dense... | 2 | stack_v2_sparse_classes_30k_train_003766 | Implement the Python class `EncoderBlock` described below.
Class description:
Class MultiHeadAttention
Method signatures and docstrings:
- def __init__(self, dm, h, hidden, drop_rate=0.1): Constructor Class constructor dm - the dimensionality of the model h - the number of heads hidden - the number of hidden units in... | Implement the Python class `EncoderBlock` described below.
Class description:
Class MultiHeadAttention
Method signatures and docstrings:
- def __init__(self, dm, h, hidden, drop_rate=0.1): Constructor Class constructor dm - the dimensionality of the model h - the number of heads hidden - the number of hidden units in... | eaf23423ec0f412f103f5931d6610fdd67bcc5be | <|skeleton|>
class EncoderBlock:
"""Class MultiHeadAttention"""
def __init__(self, dm, h, hidden, drop_rate=0.1):
"""Constructor Class constructor dm - the dimensionality of the model h - the number of heads hidden - the number of hidden units in the fully connected layer drop_rate - the dropout rate S... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class EncoderBlock:
"""Class MultiHeadAttention"""
def __init__(self, dm, h, hidden, drop_rate=0.1):
"""Constructor Class constructor dm - the dimensionality of the model h - the number of heads hidden - the number of hidden units in the fully connected layer drop_rate - the dropout rate Sets the follo... | the_stack_v2_python_sparse | supervised_learning/0x11-attention/7-transformer_encoder_block.py | ledbagholberton/holbertonschool-machine_learning | train | 1 |
b6a22bbc93ed7230e59269637a75b0a0a3282fae | [
"if mode == Mode.PLAYER:\n return True\nreturn False",
"if mode == Mode.RANDOM_AI or mode == Mode.AI_WITHOUT_FLAGS or mode == Mode.AI_WITH_FLAGS or (mode == Mode.AI_WITH_FLAGS2):\n return True\nreturn False"
] | <|body_start_0|>
if mode == Mode.PLAYER:
return True
return False
<|end_body_0|>
<|body_start_1|>
if mode == Mode.RANDOM_AI or mode == Mode.AI_WITHOUT_FLAGS or mode == Mode.AI_WITH_FLAGS or (mode == Mode.AI_WITH_FLAGS2):
return True
return False
<|end_body_1|>
| Mode | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Mode:
def is_player_mode(cls, mode):
"""Allow to know if a mode is a player mode or not. :mode: The mode. :return: True if the mode is a player mode, False otherwise."""
<|body_0|>
def is_ai_mode(cls, mode):
"""Allow to know if a mode is an artificial intelligence mo... | stack_v2_sparse_classes_10k_train_003241 | 5,674 | no_license | [
{
"docstring": "Allow to know if a mode is a player mode or not. :mode: The mode. :return: True if the mode is a player mode, False otherwise.",
"name": "is_player_mode",
"signature": "def is_player_mode(cls, mode)"
},
{
"docstring": "Allow to know if a mode is an artificial intelligence mode or... | 2 | stack_v2_sparse_classes_30k_train_005877 | Implement the Python class `Mode` described below.
Class description:
Implement the Mode class.
Method signatures and docstrings:
- def is_player_mode(cls, mode): Allow to know if a mode is a player mode or not. :mode: The mode. :return: True if the mode is a player mode, False otherwise.
- def is_ai_mode(cls, mode):... | Implement the Python class `Mode` described below.
Class description:
Implement the Mode class.
Method signatures and docstrings:
- def is_player_mode(cls, mode): Allow to know if a mode is a player mode or not. :mode: The mode. :return: True if the mode is a player mode, False otherwise.
- def is_ai_mode(cls, mode):... | e4601fbdd9f7cfdef6774f26c2850ec8cf3c562e | <|skeleton|>
class Mode:
def is_player_mode(cls, mode):
"""Allow to know if a mode is a player mode or not. :mode: The mode. :return: True if the mode is a player mode, False otherwise."""
<|body_0|>
def is_ai_mode(cls, mode):
"""Allow to know if a mode is an artificial intelligence mo... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Mode:
def is_player_mode(cls, mode):
"""Allow to know if a mode is a player mode or not. :mode: The mode. :return: True if the mode is a player mode, False otherwise."""
if mode == Mode.PLAYER:
return True
return False
def is_ai_mode(cls, mode):
"""Allow to kno... | the_stack_v2_python_sparse | source/main.py | roundsace/Minesweeper_deep_learning | train | 0 | |
311a746fe3d5b3743c6fa746747ff0b0b40aa907 | [
"self.wifi_mac = wifi_mac\nself.id = id\nself.serial = serial\nself.device_fields = device_fields",
"if dictionary is None:\n return None\ndevice_fields = meraki_sdk.models.device_fields_model.DeviceFieldsModel.from_dictionary(dictionary.get('deviceFields')) if dictionary.get('deviceFields') else None\nwifi_ma... | <|body_start_0|>
self.wifi_mac = wifi_mac
self.id = id
self.serial = serial
self.device_fields = device_fields
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
device_fields = meraki_sdk.models.device_fields_model.DeviceFieldsModel.from_dict... | Implementation of the 'updateNetworkSmDeviceFields' model. TODO: type model description here. Attributes: wifi_mac (string): The wifiMac of the device to be modified. id (string): The id of the device to be modified. serial (string): The serial of the device to be modified. device_fields (DeviceFieldsModel): The new fi... | UpdateNetworkSmDeviceFieldsModel | [
"MIT",
"Python-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UpdateNetworkSmDeviceFieldsModel:
"""Implementation of the 'updateNetworkSmDeviceFields' model. TODO: type model description here. Attributes: wifi_mac (string): The wifiMac of the device to be modified. id (string): The id of the device to be modified. serial (string): The serial of the device t... | stack_v2_sparse_classes_10k_train_003242 | 2,396 | permissive | [
{
"docstring": "Constructor for the UpdateNetworkSmDeviceFieldsModel class",
"name": "__init__",
"signature": "def __init__(self, device_fields=None, wifi_mac=None, id=None, serial=None)"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: dictionary (dictionary): A dict... | 2 | null | Implement the Python class `UpdateNetworkSmDeviceFieldsModel` described below.
Class description:
Implementation of the 'updateNetworkSmDeviceFields' model. TODO: type model description here. Attributes: wifi_mac (string): The wifiMac of the device to be modified. id (string): The id of the device to be modified. seri... | Implement the Python class `UpdateNetworkSmDeviceFieldsModel` described below.
Class description:
Implementation of the 'updateNetworkSmDeviceFields' model. TODO: type model description here. Attributes: wifi_mac (string): The wifiMac of the device to be modified. id (string): The id of the device to be modified. seri... | 9894089eb013318243ae48869cc5130eb37f80c0 | <|skeleton|>
class UpdateNetworkSmDeviceFieldsModel:
"""Implementation of the 'updateNetworkSmDeviceFields' model. TODO: type model description here. Attributes: wifi_mac (string): The wifiMac of the device to be modified. id (string): The id of the device to be modified. serial (string): The serial of the device t... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class UpdateNetworkSmDeviceFieldsModel:
"""Implementation of the 'updateNetworkSmDeviceFields' model. TODO: type model description here. Attributes: wifi_mac (string): The wifiMac of the device to be modified. id (string): The id of the device to be modified. serial (string): The serial of the device to be modified... | the_stack_v2_python_sparse | meraki_sdk/models/update_network_sm_device_fields_model.py | RaulCatalano/meraki-python-sdk | train | 1 |
d9ef052d16d7b36802860900ca45255b0f81bc5b | [
"values = np.random.choice(trade_rets, scenarios_length * num_of_scenarios)\nvalues = np.reshape(values, (scenarios_length, num_of_scenarios))\nreturn SimpleReturnsDataFrame(values)",
"assert 0.0 <= time_in_the_market <= 1.0, 'time_in_the_market should belong to the [0.0, 1.0] range'\ndates_index = date_range(sta... | <|body_start_0|>
values = np.random.choice(trade_rets, scenarios_length * num_of_scenarios)
values = np.reshape(values, (scenarios_length, num_of_scenarios))
return SimpleReturnsDataFrame(values)
<|end_body_0|>
<|body_start_1|>
assert 0.0 <= time_in_the_market <= 1.0, 'time_in_the_marke... | Class used for generating different scenarios for Trades. | ScenariosGenerator | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ScenariosGenerator:
"""Class used for generating different scenarios for Trades."""
def make_scenarios(self, trade_rets: Sequence[float], scenarios_length: int=100, num_of_scenarios: int=10000) -> SimpleReturnsDataFrame:
"""Utility function to generate different trades scenarios, whe... | stack_v2_sparse_classes_10k_train_003243 | 7,119 | permissive | [
{
"docstring": "Utility function to generate different trades scenarios, where each scenario is a series of returns for a given investment strategy. The scenarios of a given length are created by randomly choosing (with replacement) returns from the original sequence of a Trade's returns. The result is the Simp... | 3 | stack_v2_sparse_classes_30k_train_003983 | Implement the Python class `ScenariosGenerator` described below.
Class description:
Class used for generating different scenarios for Trades.
Method signatures and docstrings:
- def make_scenarios(self, trade_rets: Sequence[float], scenarios_length: int=100, num_of_scenarios: int=10000) -> SimpleReturnsDataFrame: Uti... | Implement the Python class `ScenariosGenerator` described below.
Class description:
Class used for generating different scenarios for Trades.
Method signatures and docstrings:
- def make_scenarios(self, trade_rets: Sequence[float], scenarios_length: int=100, num_of_scenarios: int=10000) -> SimpleReturnsDataFrame: Uti... | f707e51bc2ff45f6e46dcdd24d59d83ce7dc4f94 | <|skeleton|>
class ScenariosGenerator:
"""Class used for generating different scenarios for Trades."""
def make_scenarios(self, trade_rets: Sequence[float], scenarios_length: int=100, num_of_scenarios: int=10000) -> SimpleReturnsDataFrame:
"""Utility function to generate different trades scenarios, whe... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ScenariosGenerator:
"""Class used for generating different scenarios for Trades."""
def make_scenarios(self, trade_rets: Sequence[float], scenarios_length: int=100, num_of_scenarios: int=10000) -> SimpleReturnsDataFrame:
"""Utility function to generate different trades scenarios, where each scena... | the_stack_v2_python_sparse | qf_lib/backtesting/fast_alpha_model_tester/scenarios_generator.py | quarkfin/qf-lib | train | 379 |
3ff7e70aa485703fae7a45994d389a1748ee8250 | [
"ret = []\n\ndef preorder(node):\n if node:\n ret.append(str(node.val))\n preorder(node.left)\n preorder(node.right)\npreorder(root)\nreturn ' '.join(ret)",
"tree = collections.deque(map(int, data.split()))\n\ndef construct(lower, upper):\n if tree and lower <= tree[0] <= upper:\n ... | <|body_start_0|>
ret = []
def preorder(node):
if node:
ret.append(str(node.val))
preorder(node.left)
preorder(node.right)
preorder(root)
return ' '.join(ret)
<|end_body_0|>
<|body_start_1|>
tree = collections.deque(map... | Codec | [
"Apache-2.0"
] | 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|>
ret = []
... | stack_v2_sparse_classes_10k_train_003244 | 1,354 | permissive | [
{
"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... | 2419a7d720bea1fd6ff3b75c38342a0ace18b205 | <|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_10k | data/stack_v2_sparse_classes_30k | class Codec:
def serialize(self, root: TreeNode) -> str:
"""Encodes a tree to a single string."""
ret = []
def preorder(node):
if node:
ret.append(str(node.val))
preorder(node.left)
preorder(node.right)
preorder(root)
... | the_stack_v2_python_sparse | LeetCode/0449. Serialize and Deserialize BST/solution.py | InnoFang/algo-set | train | 23 | |
2309190c4f5e0fa139b10ed7a0d76c461bd5a1a8 | [
"self.sensor = Sensor('127.0.0.1', '1111')\nself.pump = Pump('127.0.0.1', '2222')\nself.decider = Decider(100, 0.05)\nself.controller = Controller(self.sensor, self.pump, self.decider)\nself.actions = {'PUMP_IN': self.pump.PUMP_IN, 'PUMP_OUT': self.pump.PUMP_OUT, 'PUMP_OFF': self.pump.PUMP_OFF}",
"cur_height = 50... | <|body_start_0|>
self.sensor = Sensor('127.0.0.1', '1111')
self.pump = Pump('127.0.0.1', '2222')
self.decider = Decider(100, 0.05)
self.controller = Controller(self.sensor, self.pump, self.decider)
self.actions = {'PUMP_IN': self.pump.PUMP_IN, 'PUMP_OUT': self.pump.PUMP_OUT, 'PUM... | Module tests for the water-regulation module | ModuleTests | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ModuleTests:
"""Module tests for the water-regulation module"""
def setUp(self):
"""Create Dummy instance"""
<|body_0|>
def test_module(self):
"""Basic integration test for waterregulation module"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
s... | stack_v2_sparse_classes_10k_train_003245 | 1,354 | no_license | [
{
"docstring": "Create Dummy instance",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "Basic integration test for waterregulation module",
"name": "test_module",
"signature": "def test_module(self)"
}
] | 2 | null | Implement the Python class `ModuleTests` described below.
Class description:
Module tests for the water-regulation module
Method signatures and docstrings:
- def setUp(self): Create Dummy instance
- def test_module(self): Basic integration test for waterregulation module | Implement the Python class `ModuleTests` described below.
Class description:
Module tests for the water-regulation module
Method signatures and docstrings:
- def setUp(self): Create Dummy instance
- def test_module(self): Basic integration test for waterregulation module
<|skeleton|>
class ModuleTests:
"""Module... | b1fea0309b3495b3e1dc167d7029bc9e4b6f00f1 | <|skeleton|>
class ModuleTests:
"""Module tests for the water-regulation module"""
def setUp(self):
"""Create Dummy instance"""
<|body_0|>
def test_module(self):
"""Basic integration test for waterregulation module"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ModuleTests:
"""Module tests for the water-regulation module"""
def setUp(self):
"""Create Dummy instance"""
self.sensor = Sensor('127.0.0.1', '1111')
self.pump = Pump('127.0.0.1', '2222')
self.decider = Decider(100, 0.05)
self.controller = Controller(self.sensor, ... | the_stack_v2_python_sparse | students/tbrackney/Lesson6/water-regulation/waterregulation/integrationtest.py | UWPCE-PythonCert-ClassRepos/SP_Online_Course2_2018 | train | 4 |
7b3c781f4f856c73ed66f12062d410f8e51b69dc | [
"size = len(nums)\ndp = [1] * size\nfor x in range(size):\n for y in range(x):\n if nums[x] > nums[y]:\n dp[x] = max(dp[x], dp[y] + 1)\nreturn max(dp) if dp else 0",
"size = len(nums)\nl = 0\ndp = []\nfor x in range(size):\n low, high = (0, len(dp) - 1)\n while low <= high:\n mid... | <|body_start_0|>
size = len(nums)
dp = [1] * size
for x in range(size):
for y in range(x):
if nums[x] > nums[y]:
dp[x] = max(dp[x], dp[y] + 1)
return max(dp) if dp else 0
<|end_body_0|>
<|body_start_1|>
size = len(nums)
l =... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def lengthOfLIS1(self, nums):
""":type nums: List[int] :rtype: int 时间复杂度O(N^2) dp状态方程： dp[0] = 1 dp[i] = max(dp[i], dp[j]+biger(nums[i], nums[j])) 其中0 <= j < i, biger函数返回1／0"""
<|body_0|>
def lengthOfLIS(self, nums):
""":type nums: List[int] :rtype: int 时间复... | stack_v2_sparse_classes_10k_train_003246 | 1,814 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: int 时间复杂度O(N^2) dp状态方程： dp[0] = 1 dp[i] = max(dp[i], dp[j]+biger(nums[i], nums[j])) 其中0 <= j < i, biger函数返回1／0",
"name": "lengthOfLIS1",
"signature": "def lengthOfLIS1(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: int 时间复杂度O(NlogN) dp... | 2 | stack_v2_sparse_classes_30k_train_001161 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def lengthOfLIS1(self, nums): :type nums: List[int] :rtype: int 时间复杂度O(N^2) dp状态方程： dp[0] = 1 dp[i] = max(dp[i], dp[j]+biger(nums[i], nums[j])) 其中0 <= j < i, biger函数返回1／0
- def l... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def lengthOfLIS1(self, nums): :type nums: List[int] :rtype: int 时间复杂度O(N^2) dp状态方程： dp[0] = 1 dp[i] = max(dp[i], dp[j]+biger(nums[i], nums[j])) 其中0 <= j < i, biger函数返回1／0
- def l... | 9687f8e743a8b6396fff192f22b5256d1025f86b | <|skeleton|>
class Solution:
def lengthOfLIS1(self, nums):
""":type nums: List[int] :rtype: int 时间复杂度O(N^2) dp状态方程： dp[0] = 1 dp[i] = max(dp[i], dp[j]+biger(nums[i], nums[j])) 其中0 <= j < i, biger函数返回1／0"""
<|body_0|>
def lengthOfLIS(self, nums):
""":type nums: List[int] :rtype: int 时间复... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def lengthOfLIS1(self, nums):
""":type nums: List[int] :rtype: int 时间复杂度O(N^2) dp状态方程： dp[0] = 1 dp[i] = max(dp[i], dp[j]+biger(nums[i], nums[j])) 其中0 <= j < i, biger函数返回1／0"""
size = len(nums)
dp = [1] * size
for x in range(size):
for y in range(x):
... | the_stack_v2_python_sparse | 2017/dp/Longest_Increasing_Subsequence.py | buhuipao/LeetCode | train | 5 | |
6cfc05d815b3101fc3193c8137ffc2066cbbd215 | [
"if l1 or l2:\n if l1 is None:\n return l2\n if l2 is None:\n return l1\nhead = ListNode()\nnode = head\nwhile l1 or l2:\n if l1 and l2:\n if l1.val <= l2.val:\n node.next = l1\n l1 = l1.next\n else:\n node.next = l2\n l2 = l2.next\n ... | <|body_start_0|>
if l1 or l2:
if l1 is None:
return l2
if l2 is None:
return l1
head = ListNode()
node = head
while l1 or l2:
if l1 and l2:
if l1.val <= l2.val:
node.next = l1
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def mergeTwoLists(self, l1, l2):
""":type l1: ListNode :type l2: ListNode :rtype: ListNode"""
<|body_0|>
def mergeKLists(self, lists):
""":type lists: List[ListNode] :rtype: ListNode"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if l1 or... | stack_v2_sparse_classes_10k_train_003247 | 2,364 | no_license | [
{
"docstring": ":type l1: ListNode :type l2: ListNode :rtype: ListNode",
"name": "mergeTwoLists",
"signature": "def mergeTwoLists(self, l1, l2)"
},
{
"docstring": ":type lists: List[ListNode] :rtype: ListNode",
"name": "mergeKLists",
"signature": "def mergeKLists(self, lists)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def mergeTwoLists(self, l1, l2): :type l1: ListNode :type l2: ListNode :rtype: ListNode
- def mergeKLists(self, lists): :type lists: List[ListNode] :rtype: ListNode | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def mergeTwoLists(self, l1, l2): :type l1: ListNode :type l2: ListNode :rtype: ListNode
- def mergeKLists(self, lists): :type lists: List[ListNode] :rtype: ListNode
<|skeleton|>... | df7d2229c50aa5134d297cc5599f7df9e64780c1 | <|skeleton|>
class Solution:
def mergeTwoLists(self, l1, l2):
""":type l1: ListNode :type l2: ListNode :rtype: ListNode"""
<|body_0|>
def mergeKLists(self, lists):
""":type lists: List[ListNode] :rtype: ListNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def mergeTwoLists(self, l1, l2):
""":type l1: ListNode :type l2: ListNode :rtype: ListNode"""
if l1 or l2:
if l1 is None:
return l2
if l2 is None:
return l1
head = ListNode()
node = head
while l1 or l2:
... | the_stack_v2_python_sparse | 23.合并k个升序链表.py | libowei1213/LeetCode | train | 0 | |
7ab4c02a258c75c71d36646af7990d9d92d6a655 | [
"gtk.Fixed.__init__(self)\nself._lst_labels = [u'λ<sub>b</sub>:', u'π<sub>Q</sub>:', u'π<sub>E</sub>:']\nself._dtc_data_controller = controller\nself._hardware_id = kwargs['hardware_id']\nself._subcategory_id = kwargs['subcategory_id']\nself._lblModel = ramstk.RAMSTKLabel('', tooltip=_(u'The assessment model used t... | <|body_start_0|>
gtk.Fixed.__init__(self)
self._lst_labels = [u'λ<sub>b</sub>:', u'π<sub>Q</sub>:', u'π<sub>E</sub>:']
self._dtc_data_controller = controller
self._hardware_id = kwargs['hardware_id']
self._subcategory_id = kwargs['subcategory_id']
self._lblModel = ramstk.... | Display Hardware assessment results attribute data in the RAMSTK Work Book. The Hardware assessment result view displays all the assessment results for the selected hardware item. This includes, currently, results for MIL-HDBK-217FN2 parts count and MIL-HDBK-217FN2 part stress methods. The attributes of a Hardware asse... | AssessmentResults | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AssessmentResults:
"""Display Hardware assessment results attribute data in the RAMSTK Work Book. The Hardware assessment result view displays all the assessment results for the selected hardware item. This includes, currently, results for MIL-HDBK-217FN2 parts count and MIL-HDBK-217FN2 part stre... | stack_v2_sparse_classes_10k_train_003248 | 35,514 | permissive | [
{
"docstring": "Initialize an instance of the Hardware assessment result view. :param controller: the hardware data controller instance. :type controller: :class:`ramstk.hardware.Controller.HardwareBoMDataController` :param int hardware_id: the hardware ID of the currently selected hardware item. :param int sub... | 4 | stack_v2_sparse_classes_30k_train_000473 | Implement the Python class `AssessmentResults` described below.
Class description:
Display Hardware assessment results attribute data in the RAMSTK Work Book. The Hardware assessment result view displays all the assessment results for the selected hardware item. This includes, currently, results for MIL-HDBK-217FN2 pa... | Implement the Python class `AssessmentResults` described below.
Class description:
Display Hardware assessment results attribute data in the RAMSTK Work Book. The Hardware assessment result view displays all the assessment results for the selected hardware item. This includes, currently, results for MIL-HDBK-217FN2 pa... | 488ffed8b842399ddcae93007de6c6f1dda23d05 | <|skeleton|>
class AssessmentResults:
"""Display Hardware assessment results attribute data in the RAMSTK Work Book. The Hardware assessment result view displays all the assessment results for the selected hardware item. This includes, currently, results for MIL-HDBK-217FN2 parts count and MIL-HDBK-217FN2 part stre... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class AssessmentResults:
"""Display Hardware assessment results attribute data in the RAMSTK Work Book. The Hardware assessment result view displays all the assessment results for the selected hardware item. This includes, currently, results for MIL-HDBK-217FN2 parts count and MIL-HDBK-217FN2 part stress methods. T... | the_stack_v2_python_sparse | src/ramstk/gui/gtk/workviews/components/Component.py | JmiXIII/ramstk | train | 0 |
a90e539c2706efb69424b6cce74bc0ff28e522ca | [
"if not configs_file:\n dir_path = os.path.dirname(os.path.realpath(__file__))\n configs_file = os.path.join(dir_path, 'my_bb_configs.ini')\nprint('Loading configs: ' + configs_file)",
"if io.is_file(f_configs) is False:\n warn.warn('configs (INI) file does not exist: ' + f_configs)\n return None",
... | <|body_start_0|>
if not configs_file:
dir_path = os.path.dirname(os.path.realpath(__file__))
configs_file = os.path.join(dir_path, 'my_bb_configs.ini')
print('Loading configs: ' + configs_file)
<|end_body_0|>
<|body_start_1|>
if io.is_file(f_configs) is False:
... | Simple class made-up of static methods for handling INI configuration files used in LOKI API. | Configurations | [
"MIT",
"LicenseRef-scancode-proprietary-license"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Configurations:
"""Simple class made-up of static methods for handling INI configuration files used in LOKI API."""
def parse(configs_file):
"""Instantiates parser for INI (config) file :param cfconfigs_fileile: absolute path to config INI file :return: ConfigParser object with confi... | stack_v2_sparse_classes_10k_train_003249 | 6,802 | permissive | [
{
"docstring": "Instantiates parser for INI (config) file :param cfconfigs_fileile: absolute path to config INI file :return: ConfigParser object with configurations loaded",
"name": "parse",
"signature": "def parse(configs_file)"
},
{
"docstring": "Top-level function that reads & stores all (or... | 4 | stack_v2_sparse_classes_30k_train_002022 | Implement the Python class `Configurations` described below.
Class description:
Simple class made-up of static methods for handling INI configuration files used in LOKI API.
Method signatures and docstrings:
- def parse(configs_file): Instantiates parser for INI (config) file :param cfconfigs_fileile: absolute path t... | Implement the Python class `Configurations` described below.
Class description:
Simple class made-up of static methods for handling INI configuration files used in LOKI API.
Method signatures and docstrings:
- def parse(configs_file): Instantiates parser for INI (config) file :param cfconfigs_fileile: absolute path t... | bc07ba242ccaf762a55c80204d7da05d55847ec5 | <|skeleton|>
class Configurations:
"""Simple class made-up of static methods for handling INI configuration files used in LOKI API."""
def parse(configs_file):
"""Instantiates parser for INI (config) file :param cfconfigs_fileile: absolute path to config INI file :return: ConfigParser object with confi... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Configurations:
"""Simple class made-up of static methods for handling INI configuration files used in LOKI API."""
def parse(configs_file):
"""Instantiates parser for INI (config) file :param cfconfigs_fileile: absolute path to config INI file :return: ConfigParser object with configurations loa... | the_stack_v2_python_sparse | src/fiwtools/utils/common.py | visionjo/FIW_KRT | train | 28 |
f3a1af44d78f155a2bb836d7c6e6df5183895472 | [
"if platform.platform().lower().startswith('windows'):\n cmd = 'ping -n 1 -w 1 '\nelse:\n cmd = 'ping -c 1 -W 1 '\nprocess = subprocess.Popen(cmd + ip_address, shell=True, stdout=subprocess.PIPE)\ntime.sleep(1.2)\nprocess.stdout.close()\nprocess.wait()\nreturn process.returncode",
"if ip_address in Ping.unr... | <|body_start_0|>
if platform.platform().lower().startswith('windows'):
cmd = 'ping -n 1 -w 1 '
else:
cmd = 'ping -c 1 -W 1 '
process = subprocess.Popen(cmd + ip_address, shell=True, stdout=subprocess.PIPE)
time.sleep(1.2)
process.stdout.close()
pro... | Platform-independent ping support. | Ping | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Ping:
"""Platform-independent ping support."""
def ping(ip_address):
"""Send a ping (ICMP ECHO request) to the given host. SpiNNaker boards support ICMP ECHO when booted. :param str ip_address: The IP address to ping. Hostnames can be used, but are not recommended. :return: return co... | stack_v2_sparse_classes_10k_train_003250 | 2,321 | permissive | [
{
"docstring": "Send a ping (ICMP ECHO request) to the given host. SpiNNaker boards support ICMP ECHO when booted. :param str ip_address: The IP address to ping. Hostnames can be used, but are not recommended. :return: return code of subprocess; 0 for success, anything else for failure :rtype: int",
"name":... | 2 | stack_v2_sparse_classes_30k_train_006151 | Implement the Python class `Ping` described below.
Class description:
Platform-independent ping support.
Method signatures and docstrings:
- def ping(ip_address): Send a ping (ICMP ECHO request) to the given host. SpiNNaker boards support ICMP ECHO when booted. :param str ip_address: The IP address to ping. Hostnames... | Implement the Python class `Ping` described below.
Class description:
Platform-independent ping support.
Method signatures and docstrings:
- def ping(ip_address): Send a ping (ICMP ECHO request) to the given host. SpiNNaker boards support ICMP ECHO when booted. :param str ip_address: The IP address to ping. Hostnames... | 9d87f324f91eb49795825f77d663f6ac46a1c5f4 | <|skeleton|>
class Ping:
"""Platform-independent ping support."""
def ping(ip_address):
"""Send a ping (ICMP ECHO request) to the given host. SpiNNaker boards support ICMP ECHO when booted. :param str ip_address: The IP address to ping. Hostnames can be used, but are not recommended. :return: return co... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Ping:
"""Platform-independent ping support."""
def ping(ip_address):
"""Send a ping (ICMP ECHO request) to the given host. SpiNNaker boards support ICMP ECHO when booted. :param str ip_address: The IP address to ping. Hostnames can be used, but are not recommended. :return: return code of subproc... | the_stack_v2_python_sparse | spinn_utilities/ping.py | SpiNNakerManchester/SpiNNUtils | train | 1 |
defce6771f3c747bb26af5b3e0de29b0f1874a5e | [
"cross = tensor([[[0, 1, 0], [1, 1, 1], [0, 1, 0]]])\nbound = tensor([[[0, 0, 0], [0, 1, 0], [0, 0, 0]]])\nkernel = stack([bound, cross, bound], 1) * (1 / 7)\nreturn kernel[None]",
"if pred.dim() != 5:\n raise ValueError(f'Only 3D images supported. Got {pred.dim()}.')\nreturn super().forward(pred, target)"
] | <|body_start_0|>
cross = tensor([[[0, 1, 0], [1, 1, 1], [0, 1, 0]]])
bound = tensor([[[0, 0, 0], [0, 1, 0], [0, 0, 0]]])
kernel = stack([bound, cross, bound], 1) * (1 / 7)
return kernel[None]
<|end_body_0|>
<|body_start_1|>
if pred.dim() != 5:
raise ValueError(f'Only... | Binary 3D Hausdorff loss based on morphological erosion. Hausdorff Distance loss measures the maximum distance of a predicted segmentation boundary to the nearest ground-truth edge pixel. For two segmentation point sets X and Y , the one-sided HD from X to Y is defined as: .. math:: hd(X,Y) = \\max_{x \\in X} \\min_{y ... | HausdorffERLoss3D | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HausdorffERLoss3D:
"""Binary 3D Hausdorff loss based on morphological erosion. Hausdorff Distance loss measures the maximum distance of a predicted segmentation boundary to the nearest ground-truth edge pixel. For two segmentation point sets X and Y , the one-sided HD from X to Y is defined as: .... | stack_v2_sparse_classes_10k_train_003251 | 9,826 | permissive | [
{
"docstring": "Get kernel for image morphology convolution.",
"name": "get_kernel",
"signature": "def get_kernel(self) -> Tensor"
},
{
"docstring": "Compute 3D Hausdorff loss. Args: pred: predicted tensor with a shape of :math:`(B, C, D, H, W)`. Each channel is as binary as: 1 -> fg, 0 -> bg. t... | 2 | null | Implement the Python class `HausdorffERLoss3D` described below.
Class description:
Binary 3D Hausdorff loss based on morphological erosion. Hausdorff Distance loss measures the maximum distance of a predicted segmentation boundary to the nearest ground-truth edge pixel. For two segmentation point sets X and Y , the on... | Implement the Python class `HausdorffERLoss3D` described below.
Class description:
Binary 3D Hausdorff loss based on morphological erosion. Hausdorff Distance loss measures the maximum distance of a predicted segmentation boundary to the nearest ground-truth edge pixel. For two segmentation point sets X and Y , the on... | 1e0f8baa7318c05b17ea6dbb48605691bca8972f | <|skeleton|>
class HausdorffERLoss3D:
"""Binary 3D Hausdorff loss based on morphological erosion. Hausdorff Distance loss measures the maximum distance of a predicted segmentation boundary to the nearest ground-truth edge pixel. For two segmentation point sets X and Y , the one-sided HD from X to Y is defined as: .... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class HausdorffERLoss3D:
"""Binary 3D Hausdorff loss based on morphological erosion. Hausdorff Distance loss measures the maximum distance of a predicted segmentation boundary to the nearest ground-truth edge pixel. For two segmentation point sets X and Y , the one-sided HD from X to Y is defined as: .. math:: hd(X... | the_stack_v2_python_sparse | kornia/losses/hausdorff.py | kornia/kornia | train | 7,351 |
27e590d51b42eab4a3c102ba3912e4e14c95447d | [
"A = []\nB = []\nfor k in range(len(guess)):\n if k not in A and guess[k] == secret[k]:\n A.append(k)\n B.append(k)\nal = len(A)\nfor k, s in enumerate(secret):\n if k not in B:\n for _k, g in enumerate(guess):\n if _k not in A and k not in B and (s == g):\n B.ap... | <|body_start_0|>
A = []
B = []
for k in range(len(guess)):
if k not in A and guess[k] == secret[k]:
A.append(k)
B.append(k)
al = len(A)
for k, s in enumerate(secret):
if k not in B:
for _k, g in enumerate(gue... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def getHint1(self, secret, guess):
""":type secret: str :type guess: str :rtype: str"""
<|body_0|>
def getHint2(self, secret, guess):
""":type secret: str :type guess: str :rtype: str"""
<|body_1|>
def getHint(self, secret, guess):
""":... | stack_v2_sparse_classes_10k_train_003252 | 1,974 | no_license | [
{
"docstring": ":type secret: str :type guess: str :rtype: str",
"name": "getHint1",
"signature": "def getHint1(self, secret, guess)"
},
{
"docstring": ":type secret: str :type guess: str :rtype: str",
"name": "getHint2",
"signature": "def getHint2(self, secret, guess)"
},
{
"doc... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def getHint1(self, secret, guess): :type secret: str :type guess: str :rtype: str
- def getHint2(self, secret, guess): :type secret: str :type guess: str :rtype: str
- def getHin... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def getHint1(self, secret, guess): :type secret: str :type guess: str :rtype: str
- def getHint2(self, secret, guess): :type secret: str :type guess: str :rtype: str
- def getHin... | e5b018493bbd12edcdcd0434f35d9c358106d391 | <|skeleton|>
class Solution:
def getHint1(self, secret, guess):
""":type secret: str :type guess: str :rtype: str"""
<|body_0|>
def getHint2(self, secret, guess):
""":type secret: str :type guess: str :rtype: str"""
<|body_1|>
def getHint(self, secret, guess):
""":... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def getHint1(self, secret, guess):
""":type secret: str :type guess: str :rtype: str"""
A = []
B = []
for k in range(len(guess)):
if k not in A and guess[k] == secret[k]:
A.append(k)
B.append(k)
al = len(A)
f... | the_stack_v2_python_sparse | py/leetcode/299.py | wfeng1991/learnpy | train | 0 | |
7c2685859a31cb7cb635fb74b4549625d5749252 | [
"if user.is_government_user and user.has_perm('DOCUMENTS_GOVERNMENT_REVIEW') and (document.status.status in ['Received', 'Submitted']):\n return True\nif not user.is_government_user and (not privileged) and (document.status.status in ['Draft', 'Submitted']):\n return True\nreturn False",
"current_status = c... | <|body_start_0|>
if user.is_government_user and user.has_perm('DOCUMENTS_GOVERNMENT_REVIEW') and (document.status.status in ['Received', 'Submitted']):
return True
if not user.is_government_user and (not privileged) and (document.status.status in ['Draft', 'Submitted']):
return T... | Used by Viewset to check permissions for API requests | DocumentCommentPermissions | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DocumentCommentPermissions:
"""Used by Viewset to check permissions for API requests"""
def user_can_comment(user, document, privileged):
"""Check whether the user should have authority to add a comment. Government Users with abilities to review the documents should always have autho... | stack_v2_sparse_classes_10k_train_003253 | 4,753 | permissive | [
{
"docstring": "Check whether the user should have authority to add a comment. Government Users with abilities to review the documents should always have authority to add a comment, unless it's archived. Fuel Suppliers with abilities to add or submit can add a comment if the document is either in draft or submi... | 4 | stack_v2_sparse_classes_30k_train_005767 | Implement the Python class `DocumentCommentPermissions` described below.
Class description:
Used by Viewset to check permissions for API requests
Method signatures and docstrings:
- def user_can_comment(user, document, privileged): Check whether the user should have authority to add a comment. Government Users with a... | Implement the Python class `DocumentCommentPermissions` described below.
Class description:
Used by Viewset to check permissions for API requests
Method signatures and docstrings:
- def user_can_comment(user, document, privileged): Check whether the user should have authority to add a comment. Government Users with a... | 80ae1ef5938ef5e580128ed0c622071b307fc7e1 | <|skeleton|>
class DocumentCommentPermissions:
"""Used by Viewset to check permissions for API requests"""
def user_can_comment(user, document, privileged):
"""Check whether the user should have authority to add a comment. Government Users with abilities to review the documents should always have autho... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class DocumentCommentPermissions:
"""Used by Viewset to check permissions for API requests"""
def user_can_comment(user, document, privileged):
"""Check whether the user should have authority to add a comment. Government Users with abilities to review the documents should always have authority to add a... | the_stack_v2_python_sparse | backend/api/permissions/DocumentComment.py | kuanfandevops/tfrs | train | 0 |
7a2b1549ea151dd40cdd291b77560b516a478ab2 | [
"context = {}\ntry:\n build = Build.objects.get(id=self.kwargs['pk'])\n context['build'] = build\n context['allocations'] = build.getAutoAllocations()\nexcept Build.DoesNotExist:\n context['error'] = _('No matching build found')\nreturn context",
"build = self.get_object()\nform = self.get_form()\ncon... | <|body_start_0|>
context = {}
try:
build = Build.objects.get(id=self.kwargs['pk'])
context['build'] = build
context['allocations'] = build.getAutoAllocations()
except Build.DoesNotExist:
context['error'] = _('No matching build found')
retur... | View to auto-allocate parts for a build. Follows a simple set of rules to automatically allocate StockItem objects. Ref: build.models.Build.getAutoAllocations() | BuildAutoAllocate | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BuildAutoAllocate:
"""View to auto-allocate parts for a build. Follows a simple set of rules to automatically allocate StockItem objects. Ref: build.models.Build.getAutoAllocations()"""
def get_context_data(self, *args, **kwargs):
"""Get the context data for form rendering."""
... | stack_v2_sparse_classes_10k_train_003254 | 19,285 | permissive | [
{
"docstring": "Get the context data for form rendering.",
"name": "get_context_data",
"signature": "def get_context_data(self, *args, **kwargs)"
},
{
"docstring": "Handle POST request. Perform auto allocations. - If the form validation passes, perform allocations - Otherwise, the form is passed... | 2 | stack_v2_sparse_classes_30k_train_002282 | Implement the Python class `BuildAutoAllocate` described below.
Class description:
View to auto-allocate parts for a build. Follows a simple set of rules to automatically allocate StockItem objects. Ref: build.models.Build.getAutoAllocations()
Method signatures and docstrings:
- def get_context_data(self, *args, **kw... | Implement the Python class `BuildAutoAllocate` described below.
Class description:
View to auto-allocate parts for a build. Follows a simple set of rules to automatically allocate StockItem objects. Ref: build.models.Build.getAutoAllocations()
Method signatures and docstrings:
- def get_context_data(self, *args, **kw... | daab81fa2cf6f3ce1760e31d8cd94951c6dffdd2 | <|skeleton|>
class BuildAutoAllocate:
"""View to auto-allocate parts for a build. Follows a simple set of rules to automatically allocate StockItem objects. Ref: build.models.Build.getAutoAllocations()"""
def get_context_data(self, *args, **kwargs):
"""Get the context data for form rendering."""
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class BuildAutoAllocate:
"""View to auto-allocate parts for a build. Follows a simple set of rules to automatically allocate StockItem objects. Ref: build.models.Build.getAutoAllocations()"""
def get_context_data(self, *args, **kwargs):
"""Get the context data for form rendering."""
context = {... | the_stack_v2_python_sparse | InvenTree/build/views.py | fritzlim/InvenTree | train | 1 |
84ae46d51a4f49aef9c34b60b4fc4206fb1a16a5 | [
"self._hardware_api = hardware_api\nself._state_store = state_store\nself._thermocycler_plate_lifter = thermocycler_plate_lifter or ThermocyclerPlateLifter(state_store=self._state_store, equipment=equipment, movement=movement)\nself._tc_movement_flagger = thermocycler_movement_flagger or ThermocyclerMovementFlagger... | <|body_start_0|>
self._hardware_api = hardware_api
self._state_store = state_store
self._thermocycler_plate_lifter = thermocycler_plate_lifter or ThermocyclerPlateLifter(state_store=self._state_store, equipment=equipment, movement=movement)
self._tc_movement_flagger = thermocycler_moveme... | Implementation logic for labware movement. | LabwareMovementHandler | [
"LicenseRef-scancode-warranty-disclaimer",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LabwareMovementHandler:
"""Implementation logic for labware movement."""
def __init__(self, hardware_api: HardwareControlAPI, state_store: StateStore, equipment: EquipmentHandler, movement: MovementHandler, thermocycler_plate_lifter: Optional[ThermocyclerPlateLifter]=None, thermocycler_movem... | stack_v2_sparse_classes_10k_train_003255 | 7,087 | permissive | [
{
"docstring": "Initialize a LabwareMovementHandler instance.",
"name": "__init__",
"signature": "def __init__(self, hardware_api: HardwareControlAPI, state_store: StateStore, equipment: EquipmentHandler, movement: MovementHandler, thermocycler_plate_lifter: Optional[ThermocyclerPlateLifter]=None, therm... | 3 | stack_v2_sparse_classes_30k_train_003723 | Implement the Python class `LabwareMovementHandler` described below.
Class description:
Implementation logic for labware movement.
Method signatures and docstrings:
- def __init__(self, hardware_api: HardwareControlAPI, state_store: StateStore, equipment: EquipmentHandler, movement: MovementHandler, thermocycler_plat... | Implement the Python class `LabwareMovementHandler` described below.
Class description:
Implementation logic for labware movement.
Method signatures and docstrings:
- def __init__(self, hardware_api: HardwareControlAPI, state_store: StateStore, equipment: EquipmentHandler, movement: MovementHandler, thermocycler_plat... | 026b523c8c9e5d45910c490efb89194d72595be9 | <|skeleton|>
class LabwareMovementHandler:
"""Implementation logic for labware movement."""
def __init__(self, hardware_api: HardwareControlAPI, state_store: StateStore, equipment: EquipmentHandler, movement: MovementHandler, thermocycler_plate_lifter: Optional[ThermocyclerPlateLifter]=None, thermocycler_movem... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class LabwareMovementHandler:
"""Implementation logic for labware movement."""
def __init__(self, hardware_api: HardwareControlAPI, state_store: StateStore, equipment: EquipmentHandler, movement: MovementHandler, thermocycler_plate_lifter: Optional[ThermocyclerPlateLifter]=None, thermocycler_movement_flagger: ... | the_stack_v2_python_sparse | api/src/opentrons/protocol_engine/execution/labware_movement.py | Opentrons/opentrons | train | 326 |
6fb8102d093237d7fae68bf6523a4e94eb2c7044 | [
"self.k = k\nself.kheap = []\nheapq.heapify(self.kheap)\nfor i in nums:\n self.add(i)",
"heapq.heappush(self.kheap, val)\nif len(self.kheap) > self.k:\n heapq.heappop(self.kheap)\nreturn self.kheap[0]"
] | <|body_start_0|>
self.k = k
self.kheap = []
heapq.heapify(self.kheap)
for i in nums:
self.add(i)
<|end_body_0|>
<|body_start_1|>
heapq.heappush(self.kheap, val)
if len(self.kheap) > self.k:
heapq.heappop(self.kheap)
return self.kheap[0]
<|... | KthLargest | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class KthLargest:
def __init__(self, k, nums):
""":type k: int :type nums: List[int]"""
<|body_0|>
def add(self, val):
""":type val: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.k = k
self.kheap = []
heapq.heapify(s... | stack_v2_sparse_classes_10k_train_003256 | 650 | no_license | [
{
"docstring": ":type k: int :type nums: List[int]",
"name": "__init__",
"signature": "def __init__(self, k, nums)"
},
{
"docstring": ":type val: int :rtype: int",
"name": "add",
"signature": "def add(self, val)"
}
] | 2 | stack_v2_sparse_classes_30k_test_000232 | Implement the Python class `KthLargest` described below.
Class description:
Implement the KthLargest class.
Method signatures and docstrings:
- def __init__(self, k, nums): :type k: int :type nums: List[int]
- def add(self, val): :type val: int :rtype: int | Implement the Python class `KthLargest` described below.
Class description:
Implement the KthLargest class.
Method signatures and docstrings:
- def __init__(self, k, nums): :type k: int :type nums: List[int]
- def add(self, val): :type val: int :rtype: int
<|skeleton|>
class KthLargest:
def __init__(self, k, nu... | 70d8827f430b484fd3407001e02107b2545ef787 | <|skeleton|>
class KthLargest:
def __init__(self, k, nums):
""":type k: int :type nums: List[int]"""
<|body_0|>
def add(self, val):
""":type val: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class KthLargest:
def __init__(self, k, nums):
""":type k: int :type nums: List[int]"""
self.k = k
self.kheap = []
heapq.heapify(self.kheap)
for i in nums:
self.add(i)
def add(self, val):
""":type val: int :rtype: int"""
heapq.heappush(self.kh... | the_stack_v2_python_sparse | leetcode/algorithms/heap/kth-largest-element-in-a-stream.py | AnujPancholi/codingQuestionSolutions | train | 1 | |
a98739f7c75f284ac2417610ba5fda18d9fea6e5 | [
"category_id = request.query_params['category_id']\nsearch = request.query_params['search']\nqueryset = self.get_queryset().filter(category_id=category_id)\nif search != '':\n queryset = queryset.filter(name__contains=search)\npagination_queryset = self.paginate_queryset(queryset)\nserializer = self.get_serializ... | <|body_start_0|>
category_id = request.query_params['category_id']
search = request.query_params['search']
queryset = self.get_queryset().filter(category_id=category_id)
if search != '':
queryset = queryset.filter(name__contains=search)
pagination_queryset = self.pagi... | API操作视图 | ApiViewSet | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ApiViewSet:
"""API操作视图"""
def list(self, request):
"""接口列表 { classify_id: int, }"""
<|body_0|>
def add(self, request):
"""新增一个接口"""
<|body_1|>
def update(self, request, **kwargs):
"""更新接口"""
<|body_2|>
<|end_skeleton|>
<|body_start_... | stack_v2_sparse_classes_10k_train_003257 | 6,485 | no_license | [
{
"docstring": "接口列表 { classify_id: int, }",
"name": "list",
"signature": "def list(self, request)"
},
{
"docstring": "新增一个接口",
"name": "add",
"signature": "def add(self, request)"
},
{
"docstring": "更新接口",
"name": "update",
"signature": "def update(self, request, **kwarg... | 3 | stack_v2_sparse_classes_30k_train_003461 | Implement the Python class `ApiViewSet` described below.
Class description:
API操作视图
Method signatures and docstrings:
- def list(self, request): 接口列表 { classify_id: int, }
- def add(self, request): 新增一个接口
- def update(self, request, **kwargs): 更新接口 | Implement the Python class `ApiViewSet` described below.
Class description:
API操作视图
Method signatures and docstrings:
- def list(self, request): 接口列表 { classify_id: int, }
- def add(self, request): 新增一个接口
- def update(self, request, **kwargs): 更新接口
<|skeleton|>
class ApiViewSet:
"""API操作视图"""
def list(self,... | e8407fdd97e821779f2abb4c2debfb246f44e4ed | <|skeleton|>
class ApiViewSet:
"""API操作视图"""
def list(self, request):
"""接口列表 { classify_id: int, }"""
<|body_0|>
def add(self, request):
"""新增一个接口"""
<|body_1|>
def update(self, request, **kwargs):
"""更新接口"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ApiViewSet:
"""API操作视图"""
def list(self, request):
"""接口列表 { classify_id: int, }"""
category_id = request.query_params['category_id']
search = request.query_params['search']
queryset = self.get_queryset().filter(category_id=category_id)
if search != '':
... | the_stack_v2_python_sparse | begin/views1/api.py | aaas19920513/ApiDemo | train | 0 |
792244baeaa9e7bccfc5bf7e7dde918344244f09 | [
"easy = set()\nfor i in nums:\n easy.add(i)\nfor i in xrange(len(nums)):\n if i not in easy:\n return i\nreturn len(nums)",
"missing = len(nums)\nfor i, num in enumerate(nums):\n missing ^= i ^ num\nreturn missing"
] | <|body_start_0|>
easy = set()
for i in nums:
easy.add(i)
for i in xrange(len(nums)):
if i not in easy:
return i
return len(nums)
<|end_body_0|>
<|body_start_1|>
missing = len(nums)
for i, num in enumerate(nums):
missing... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def missingNumber(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def missingNumberConstantMemory(self, nums):
"""if we initialize an integer to nn and XOR it with every index and value, we will be left with the missing number. :type nums: L... | stack_v2_sparse_classes_10k_train_003258 | 881 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "missingNumber",
"signature": "def missingNumber(self, nums)"
},
{
"docstring": "if we initialize an integer to nn and XOR it with every index and value, we will be left with the missing number. :type nums: List[int] :rtype: int",
"... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def missingNumber(self, nums): :type nums: List[int] :rtype: int
- def missingNumberConstantMemory(self, nums): if we initialize an integer to nn and XOR it with every index and ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def missingNumber(self, nums): :type nums: List[int] :rtype: int
- def missingNumberConstantMemory(self, nums): if we initialize an integer to nn and XOR it with every index and ... | 2f7df25d0d735f726b7012e4aa2417dee50526d9 | <|skeleton|>
class Solution:
def missingNumber(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def missingNumberConstantMemory(self, nums):
"""if we initialize an integer to nn and XOR it with every index and value, we will be left with the missing number. :type nums: L... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def missingNumber(self, nums):
""":type nums: List[int] :rtype: int"""
easy = set()
for i in nums:
easy.add(i)
for i in xrange(len(nums)):
if i not in easy:
return i
return len(nums)
def missingNumberConstantMemory(... | the_stack_v2_python_sparse | leetcode/arrays/missing_number.py | marquesarthur/programming_problems | train | 2 | |
bdde02442a5825b7a207dbde5f7aa11518d34df6 | [
"super().__init__(surepetcare_id, coordinator)\nself._attr_name = f'{self._device_name} Battery Level'\nself._attr_unique_id = f'{self._device_id}-battery'",
"state = surepy_entity.raw_data()['status']\ntry:\n per_battery_voltage = state['battery'] / 4\n voltage_diff = per_battery_voltage - SURE_BATT_VOLTAG... | <|body_start_0|>
super().__init__(surepetcare_id, coordinator)
self._attr_name = f'{self._device_name} Battery Level'
self._attr_unique_id = f'{self._device_id}-battery'
<|end_body_0|>
<|body_start_1|>
state = surepy_entity.raw_data()['status']
try:
per_battery_volta... | A sensor implementation for Sure Petcare batteries. | SureBattery | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SureBattery:
"""A sensor implementation for Sure Petcare batteries."""
def __init__(self, surepetcare_id: int, coordinator: SurePetcareDataCoordinator) -> None:
"""Initialize a Sure Petcare battery sensor."""
<|body_0|>
def _update_attr(self, surepy_entity: SurepyEntity)... | stack_v2_sparse_classes_10k_train_003259 | 3,867 | permissive | [
{
"docstring": "Initialize a Sure Petcare battery sensor.",
"name": "__init__",
"signature": "def __init__(self, surepetcare_id: int, coordinator: SurePetcareDataCoordinator) -> None"
},
{
"docstring": "Update the state and attributes.",
"name": "_update_attr",
"signature": "def _update_... | 2 | null | Implement the Python class `SureBattery` described below.
Class description:
A sensor implementation for Sure Petcare batteries.
Method signatures and docstrings:
- def __init__(self, surepetcare_id: int, coordinator: SurePetcareDataCoordinator) -> None: Initialize a Sure Petcare battery sensor.
- def _update_attr(se... | Implement the Python class `SureBattery` described below.
Class description:
A sensor implementation for Sure Petcare batteries.
Method signatures and docstrings:
- def __init__(self, surepetcare_id: int, coordinator: SurePetcareDataCoordinator) -> None: Initialize a Sure Petcare battery sensor.
- def _update_attr(se... | 80caeafcb5b6e2f9da192d0ea6dd1a5b8244b743 | <|skeleton|>
class SureBattery:
"""A sensor implementation for Sure Petcare batteries."""
def __init__(self, surepetcare_id: int, coordinator: SurePetcareDataCoordinator) -> None:
"""Initialize a Sure Petcare battery sensor."""
<|body_0|>
def _update_attr(self, surepy_entity: SurepyEntity)... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SureBattery:
"""A sensor implementation for Sure Petcare batteries."""
def __init__(self, surepetcare_id: int, coordinator: SurePetcareDataCoordinator) -> None:
"""Initialize a Sure Petcare battery sensor."""
super().__init__(surepetcare_id, coordinator)
self._attr_name = f'{self.... | the_stack_v2_python_sparse | homeassistant/components/surepetcare/sensor.py | home-assistant/core | train | 35,501 |
07e2da94704646ac1328a6ad17e5dded1f02556c | [
"R1 = array([[1, 4, 5], [-4, 2, 6], [-5, -6, 3]], float64)\nR2 = array([[0, 1, 0], [0, 0, 0], [0, 0, 0]], float64)\neR1 = array([[-1.242955024379687, -3.178944439554645, 6.804083368075889], [-6.545353831891249, -2.604941866769356, 1.228233941393001], [0.975355249080821, -7.711099455690256, -3.318642157729292]], flo... | <|body_start_0|>
R1 = array([[1, 4, 5], [-4, 2, 6], [-5, -6, 3]], float64)
R2 = array([[0, 1, 0], [0, 0, 0], [0, 0, 0]], float64)
eR1 = array([[-1.242955024379687, -3.178944439554645, 6.804083368075889], [-6.545353831891249, -2.604941866769356, 1.228233941393001], [0.975355249080821, -7.71109945... | Unit tests for the lib.linear_algebra.matrix_exponential relax module. | Test_matrix_exponential | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Test_matrix_exponential:
"""Unit tests for the lib.linear_algebra.matrix_exponential relax module."""
def test_matrix_exponential(self):
"""Test the matrix exponential function matrix_exponential() with real matrices."""
<|body_0|>
def test_matrix_exponential2(self):
... | stack_v2_sparse_classes_10k_train_003260 | 4,601 | no_license | [
{
"docstring": "Test the matrix exponential function matrix_exponential() with real matrices.",
"name": "test_matrix_exponential",
"signature": "def test_matrix_exponential(self)"
},
{
"docstring": "Test the matrix exponential function matrix_exponential() with complex matrices.",
"name": "t... | 2 | null | Implement the Python class `Test_matrix_exponential` described below.
Class description:
Unit tests for the lib.linear_algebra.matrix_exponential relax module.
Method signatures and docstrings:
- def test_matrix_exponential(self): Test the matrix exponential function matrix_exponential() with real matrices.
- def tes... | Implement the Python class `Test_matrix_exponential` described below.
Class description:
Unit tests for the lib.linear_algebra.matrix_exponential relax module.
Method signatures and docstrings:
- def test_matrix_exponential(self): Test the matrix exponential function matrix_exponential() with real matrices.
- def tes... | c317326ddeacd1a1c608128769676899daeae531 | <|skeleton|>
class Test_matrix_exponential:
"""Unit tests for the lib.linear_algebra.matrix_exponential relax module."""
def test_matrix_exponential(self):
"""Test the matrix exponential function matrix_exponential() with real matrices."""
<|body_0|>
def test_matrix_exponential2(self):
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Test_matrix_exponential:
"""Unit tests for the lib.linear_algebra.matrix_exponential relax module."""
def test_matrix_exponential(self):
"""Test the matrix exponential function matrix_exponential() with real matrices."""
R1 = array([[1, 4, 5], [-4, 2, 6], [-5, -6, 3]], float64)
R2... | the_stack_v2_python_sparse | test_suite/unit_tests/_lib/_linear_algebra/test_matrix_exponential.py | jlec/relax | train | 4 |
d33f5928e4414fbed5d4a09ae32baa2c6f413c19 | [
"super(Decoder, self).__init__()\nself.input_size = input_size\nself.hidden_size = hidden_size\nself.num_layers = num_layers\nself.proba_output = proba_output\nif rnn_type == 'LSTM':\n self.model = nn.LSTM(input_size=self.input_size, hidden_size=self.hidden_size, num_layers=self.num_layers, batch_first=batch_fir... | <|body_start_0|>
super(Decoder, self).__init__()
self.input_size = input_size
self.hidden_size = hidden_size
self.num_layers = num_layers
self.proba_output = proba_output
if rnn_type == 'LSTM':
self.model = nn.LSTM(input_size=self.input_size, hidden_size=self.... | Decoder Network | Decoder | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Decoder:
"""Decoder Network"""
def __init__(self, input_size, hidden_size, num_layers, dropout=0, batch_first=True, rnn_type='LSTM', proba_output=False):
"""Create Encoder Args: input_size (int): number of features per time step hidden_size (int): number of hidden nodes per time step... | stack_v2_sparse_classes_10k_train_003261 | 14,969 | permissive | [
{
"docstring": "Create Encoder Args: input_size (int): number of features per time step hidden_size (int): number of hidden nodes per time step num_layers (int): number of layers dropout (float, optional): percentage of nodes that should switched out at any term. Defaults to 0. batch_first (bool, optional): if ... | 2 | stack_v2_sparse_classes_30k_train_004200 | Implement the Python class `Decoder` described below.
Class description:
Decoder Network
Method signatures and docstrings:
- def __init__(self, input_size, hidden_size, num_layers, dropout=0, batch_first=True, rnn_type='LSTM', proba_output=False): Create Encoder Args: input_size (int): number of features per time ste... | Implement the Python class `Decoder` described below.
Class description:
Decoder Network
Method signatures and docstrings:
- def __init__(self, input_size, hidden_size, num_layers, dropout=0, batch_first=True, rnn_type='LSTM', proba_output=False): Create Encoder Args: input_size (int): number of features per time ste... | 5b4a61b5dd0bc259ffe68223877949ef4ebfa5e3 | <|skeleton|>
class Decoder:
"""Decoder Network"""
def __init__(self, input_size, hidden_size, num_layers, dropout=0, batch_first=True, rnn_type='LSTM', proba_output=False):
"""Create Encoder Args: input_size (int): number of features per time step hidden_size (int): number of hidden nodes per time step... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Decoder:
"""Decoder Network"""
def __init__(self, input_size, hidden_size, num_layers, dropout=0, batch_first=True, rnn_type='LSTM', proba_output=False):
"""Create Encoder Args: input_size (int): number of features per time step hidden_size (int): number of hidden nodes per time step num_layers (... | the_stack_v2_python_sparse | src/models/anomalia/layers.py | maurony/ts-vrae | train | 1 |
e4e0075fd82a9e6b5e0310956b9b5406ba7681b5 | [
"del mock_cloud_build, mock_google_auth\nmock_upload_log.return_value = True\nbuilds = [{'build_id': '1', 'finishTime': 'test_time', 'status': 'SUCCESS'}]\nmock_get_build = MockGetBuild(builds)\nupdate_build_status.BuildGetter.get_build = mock_get_build.get_build\nexpected_projects = {'history': [{'build_id': '1', ... | <|body_start_0|>
del mock_cloud_build, mock_google_auth
mock_upload_log.return_value = True
builds = [{'build_id': '1', 'finishTime': 'test_time', 'status': 'SUCCESS'}]
mock_get_build = MockGetBuild(builds)
update_build_status.BuildGetter.get_build = mock_get_build.get_build
... | Unit tests for get_build_history. | TestGetBuildHistory | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestGetBuildHistory:
"""Unit tests for get_build_history."""
def test_get_build_history(self, mock_upload_log, mock_cloud_build, mock_google_auth):
"""Test for get_build_steps."""
<|body_0|>
def test_get_build_history_no_last_success(self, mock_upload_log, mock_cloud_bui... | stack_v2_sparse_classes_10k_train_003262 | 10,717 | permissive | [
{
"docstring": "Test for get_build_steps.",
"name": "test_get_build_history",
"signature": "def test_get_build_history(self, mock_upload_log, mock_cloud_build, mock_google_auth)"
},
{
"docstring": "Test when there is no last successful build.",
"name": "test_get_build_history_no_last_success... | 2 | null | Implement the Python class `TestGetBuildHistory` described below.
Class description:
Unit tests for get_build_history.
Method signatures and docstrings:
- def test_get_build_history(self, mock_upload_log, mock_cloud_build, mock_google_auth): Test for get_build_steps.
- def test_get_build_history_no_last_success(self,... | Implement the Python class `TestGetBuildHistory` described below.
Class description:
Unit tests for get_build_history.
Method signatures and docstrings:
- def test_get_build_history(self, mock_upload_log, mock_cloud_build, mock_google_auth): Test for get_build_steps.
- def test_get_build_history_no_last_success(self,... | f0275421f84b8f80ee767fb9230134ac97cb687b | <|skeleton|>
class TestGetBuildHistory:
"""Unit tests for get_build_history."""
def test_get_build_history(self, mock_upload_log, mock_cloud_build, mock_google_auth):
"""Test for get_build_steps."""
<|body_0|>
def test_get_build_history_no_last_success(self, mock_upload_log, mock_cloud_bui... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TestGetBuildHistory:
"""Unit tests for get_build_history."""
def test_get_build_history(self, mock_upload_log, mock_cloud_build, mock_google_auth):
"""Test for get_build_steps."""
del mock_cloud_build, mock_google_auth
mock_upload_log.return_value = True
builds = [{'build_... | the_stack_v2_python_sparse | infra/build/build_status/update_build_status_test.py | google/oss-fuzz | train | 9,438 |
6205c91bb619671c31dc660dc46228a7e40313e4 | [
"super().__init__()\nself.recorder = recorder\nself.params = MethodParameters(recorder=recorder)\nself.rval = MethodReturn(recorder=recorder)\nself.exception = MethodException(recorder=recorder)\nself.repository = MethodRepository(recorder=recorder)\nself.pass_recorder = MethodPassRecorder(recorder=recorder)\nself.... | <|body_start_0|>
super().__init__()
self.recorder = recorder
self.params = MethodParameters(recorder=recorder)
self.rval = MethodReturn(recorder=recorder)
self.exception = MethodException(recorder=recorder)
self.repository = MethodRepository(recorder=recorder)
sel... | Record interesting things about methods. Usage: @rekorder.method.param(when=When.AROUND) @rekorder.method.rval @rekorder.method.exception @rekorder.method.repository(paths=['some/path']) def some_func(...) Alternate Usage: Method can also be used as a decorator. This usage delegates to the param, rval and exception Dev... | Method | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Method:
"""Record interesting things about methods. Usage: @rekorder.method.param(when=When.AROUND) @rekorder.method.rval @rekorder.method.exception @rekorder.method.repository(paths=['some/path']) def some_func(...) Alternate Usage: Method can also be used as a decorator. This usage delegates to... | stack_v2_sparse_classes_10k_train_003263 | 2,717 | no_license | [
{
"docstring": "Construct the Method with a reference to the Recorder capable of recording the tunes created by our Recordable devices. Args: recorder (Recorder): Recorder instance.",
"name": "__init__",
"signature": "def __init__(self, recorder)"
},
{
"docstring": "Use this decorator to pass th... | 3 | stack_v2_sparse_classes_30k_train_006448 | Implement the Python class `Method` described below.
Class description:
Record interesting things about methods. Usage: @rekorder.method.param(when=When.AROUND) @rekorder.method.rval @rekorder.method.exception @rekorder.method.repository(paths=['some/path']) def some_func(...) Alternate Usage: Method can also be used ... | Implement the Python class `Method` described below.
Class description:
Record interesting things about methods. Usage: @rekorder.method.param(when=When.AROUND) @rekorder.method.rval @rekorder.method.exception @rekorder.method.repository(paths=['some/path']) def some_func(...) Alternate Usage: Method can also be used ... | 8135438b5785e1e9f23b44f5b93130b73196ea8f | <|skeleton|>
class Method:
"""Record interesting things about methods. Usage: @rekorder.method.param(when=When.AROUND) @rekorder.method.rval @rekorder.method.exception @rekorder.method.repository(paths=['some/path']) def some_func(...) Alternate Usage: Method can also be used as a decorator. This usage delegates to... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Method:
"""Record interesting things about methods. Usage: @rekorder.method.param(when=When.AROUND) @rekorder.method.rval @rekorder.method.exception @rekorder.method.repository(paths=['some/path']) def some_func(...) Alternate Usage: Method can also be used as a decorator. This usage delegates to the param, r... | the_stack_v2_python_sparse | rekorder/lib/method/method.py | jcejohnson/rekorder | train | 0 |
b503371719c19983f130de0cad10ad51b0deb2c8 | [
"rules = [['(?i)(quiz)$', '\\\\1zes'], ['^(?i)(ox)$', '\\\\1en'], ['(?i)([m|l])ouse$', '\\\\1ice'], ['(?i)(matr|vert|ind)ix|ex$', '\\\\1ices'], ['(?i)(x|ch|ss|sh)$', '\\\\1es'], ['(?i)([^aeiouy]|qu)ies$', '\\\\1y'], ['(?i)([^aeiouy]|qu)y$', '\\\\1ies'], ['(?i)(hive)$', '\\\\1s'], ['(?i)(?:([^f])fe|([lr])f)$', '\\\\... | <|body_start_0|>
rules = [['(?i)(quiz)$', '\\1zes'], ['^(?i)(ox)$', '\\1en'], ['(?i)([m|l])ouse$', '\\1ice'], ['(?i)(matr|vert|ind)ix|ex$', '\\1ices'], ['(?i)(x|ch|ss|sh)$', '\\1es'], ['(?i)([^aeiouy]|qu)ies$', '\\1y'], ['(?i)([^aeiouy]|qu)y$', '\\1ies'], ['(?i)(hive)$', '\\1s'], ['(?i)(?:([^f])fe|([lr])f)$', '... | Inflector for pluralize and singularize English nouns. This is the default Inflector for the Inflector obj | English | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class English:
"""Inflector for pluralize and singularize English nouns. This is the default Inflector for the Inflector obj"""
def pluralize(self, word):
"""Pluralizes English nouns."""
<|body_0|>
def singularize(self, word):
"""Singularizes English nouns."""
... | stack_v2_sparse_classes_10k_train_003264 | 36,915 | no_license | [
{
"docstring": "Pluralizes English nouns.",
"name": "pluralize",
"signature": "def pluralize(self, word)"
},
{
"docstring": "Singularizes English nouns.",
"name": "singularize",
"signature": "def singularize(self, word)"
}
] | 2 | stack_v2_sparse_classes_30k_train_000506 | Implement the Python class `English` described below.
Class description:
Inflector for pluralize and singularize English nouns. This is the default Inflector for the Inflector obj
Method signatures and docstrings:
- def pluralize(self, word): Pluralizes English nouns.
- def singularize(self, word): Singularizes Engli... | Implement the Python class `English` described below.
Class description:
Inflector for pluralize and singularize English nouns. This is the default Inflector for the Inflector obj
Method signatures and docstrings:
- def pluralize(self, word): Pluralizes English nouns.
- def singularize(self, word): Singularizes Engli... | 0ac6653219c2701c13c508c5c4fc9bc3437eea06 | <|skeleton|>
class English:
"""Inflector for pluralize and singularize English nouns. This is the default Inflector for the Inflector obj"""
def pluralize(self, word):
"""Pluralizes English nouns."""
<|body_0|>
def singularize(self, word):
"""Singularizes English nouns."""
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class English:
"""Inflector for pluralize and singularize English nouns. This is the default Inflector for the Inflector obj"""
def pluralize(self, word):
"""Pluralizes English nouns."""
rules = [['(?i)(quiz)$', '\\1zes'], ['^(?i)(ox)$', '\\1en'], ['(?i)([m|l])ouse$', '\\1ice'], ['(?i)(matr|ver... | the_stack_v2_python_sparse | repoData/noklesta-SublimeRailsNav/allPythonContent.py | aCoffeeYin/pyreco | train | 0 |
a845898fa5edfc140140448855f78767fd63d1d0 | [
"assert start <= end\nif array[start] != target:\n return -1\nelif start == end:\n return start\ni = start\nstep = 1\nwhile True:\n if i == end:\n return i\n j = i + step\n step *= 2\n if j > end or array[j] != target:\n candidate = self.lastIndexOf(array, target, i + 1, end)\n ... | <|body_start_0|>
assert start <= end
if array[start] != target:
return -1
elif start == end:
return start
i = start
step = 1
while True:
if i == end:
return i
j = i + step
step *= 2
if... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def lastIndexOf(self, array, target, start, end):
"""Finds the last index of target in range [start...end] of array. Returns -1 if the target does not exist. The array is expected to be sorted in ascending order and array[start] must be the target for the search to continue."""... | stack_v2_sparse_classes_10k_train_003265 | 2,903 | permissive | [
{
"docstring": "Finds the last index of target in range [start...end] of array. Returns -1 if the target does not exist. The array is expected to be sorted in ascending order and array[start] must be the target for the search to continue.",
"name": "lastIndexOf",
"signature": "def lastIndexOf(self, arra... | 2 | stack_v2_sparse_classes_30k_train_001287 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def lastIndexOf(self, array, target, start, end): Finds the last index of target in range [start...end] of array. Returns -1 if the target does not exist. The array is expected t... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def lastIndexOf(self, array, target, start, end): Finds the last index of target in range [start...end] of array. Returns -1 if the target does not exist. The array is expected t... | 363848b7870c8d90f5be0d345204c0bf8eb45daa | <|skeleton|>
class Solution:
def lastIndexOf(self, array, target, start, end):
"""Finds the last index of target in range [start...end] of array. Returns -1 if the target does not exist. The array is expected to be sorted in ascending order and array[start] must be the target for the search to continue."""... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def lastIndexOf(self, array, target, start, end):
"""Finds the last index of target in range [start...end] of array. Returns -1 if the target does not exist. The array is expected to be sorted in ascending order and array[start] must be the target for the search to continue."""
asser... | the_stack_v2_python_sparse | leetcode/algorithms/remove-duplicates-from-sorted-array-ii/solution.py | kgashok/algorithms | train | 1 | |
cbb68f037ae229abc9c7ed04ac115f7dc54e1a4d | [
"def help(root):\n if not root:\n res.append('#')\n return ','.join(res)\n res.append(str(root.val))\n help(root.left)\n help(root.right)\n return ','.join(res)\nres = []\nreturn help(root)",
"def help(nodes):\n value = nodes.pop(0)\n if value == '#':\n return None\n r... | <|body_start_0|>
def help(root):
if not root:
res.append('#')
return ','.join(res)
res.append(str(root.val))
help(root.left)
help(root.right)
return ','.join(res)
res = []
return help(root)
<|end_body_0|>... | 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_10k_train_003266 | 1,378 | 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_007190 | 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:... | 7f4917bd2c0581d02f68a6407fdb5d3a5926fd4e | <|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_10k | 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 help(root):
if not root:
res.append('#')
return ','.join(res)
res.append(str(root.val))
help(root.left)
... | the_stack_v2_python_sparse | 297.二叉树的序列化与反序列化.py | icevivian/Hello_offer | train | 0 | |
c052853d0526608f97cfc4e2e0129cf21672b283 | [
"super(GeneralizedMLP, self).__init__(name=name)\nif layers is not None:\n self._layers = layers\nelse:\n self._layers = [64, 64, 1]\nif regularizer_weight:\n self._regularizers = {'w': tf.contrib.layers.l2_regularizer(scale=regularizer_weight)}\nelse:\n self._regularizers = None\nself._use_batchnorm = ... | <|body_start_0|>
super(GeneralizedMLP, self).__init__(name=name)
if layers is not None:
self._layers = layers
else:
self._layers = [64, 64, 1]
if regularizer_weight:
self._regularizers = {'w': tf.contrib.layers.l2_regularizer(scale=regularizer_weight)}... | A multilayer, fully-connected discriminator. | GeneralizedMLP | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GeneralizedMLP:
"""A multilayer, fully-connected discriminator."""
def __init__(self, name='fc_discriminator', regularizer_weight=0.0, use_batchnorm=False, layers=None, final_activation=None):
"""Constructs a GeneralizedMLP."""
<|body_0|>
def _build(self, input, is_train... | stack_v2_sparse_classes_10k_train_003267 | 2,866 | no_license | [
{
"docstring": "Constructs a GeneralizedMLP.",
"name": "__init__",
"signature": "def __init__(self, name='fc_discriminator', regularizer_weight=0.0, use_batchnorm=False, layers=None, final_activation=None)"
},
{
"docstring": "Adds the network into the graph.",
"name": "_build",
"signatur... | 2 | stack_v2_sparse_classes_30k_train_000462 | Implement the Python class `GeneralizedMLP` described below.
Class description:
A multilayer, fully-connected discriminator.
Method signatures and docstrings:
- def __init__(self, name='fc_discriminator', regularizer_weight=0.0, use_batchnorm=False, layers=None, final_activation=None): Constructs a GeneralizedMLP.
- ... | Implement the Python class `GeneralizedMLP` described below.
Class description:
A multilayer, fully-connected discriminator.
Method signatures and docstrings:
- def __init__(self, name='fc_discriminator', regularizer_weight=0.0, use_batchnorm=False, layers=None, final_activation=None): Constructs a GeneralizedMLP.
- ... | 358a09d491aab0794df9cc7f3f8064430a78fbc3 | <|skeleton|>
class GeneralizedMLP:
"""A multilayer, fully-connected discriminator."""
def __init__(self, name='fc_discriminator', regularizer_weight=0.0, use_batchnorm=False, layers=None, final_activation=None):
"""Constructs a GeneralizedMLP."""
<|body_0|>
def _build(self, input, is_train... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class GeneralizedMLP:
"""A multilayer, fully-connected discriminator."""
def __init__(self, name='fc_discriminator', regularizer_weight=0.0, use_batchnorm=False, layers=None, final_activation=None):
"""Constructs a GeneralizedMLP."""
super(GeneralizedMLP, self).__init__(name=name)
if la... | the_stack_v2_python_sparse | architectures/mlp_architectures.py | zwbgood6/temporal-hierarchy | train | 0 |
0b51bdfc86a1777bcfb0a20b37203f295e515230 | [
"left = 0\nright = x\nmid = (left + right) / 2\nwhile left <= right:\n if mid ** 2 > x:\n right = mid - 1\n else:\n left = mid + 1\n mid = (left + right) / 2\nreturn mid",
"left = 0\nright = x\nmid = (left + right) // 2\nwhile left <= right:\n if mid ** 2 == x:\n return mid\n e... | <|body_start_0|>
left = 0
right = x
mid = (left + right) / 2
while left <= right:
if mid ** 2 > x:
right = mid - 1
else:
left = mid + 1
mid = (left + right) / 2
return mid
<|end_body_0|>
<|body_start_1|>
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def mySqrt(self, x):
""":type x: int :rtype: int"""
<|body_0|>
def yourSqrt(self, x):
""":type x: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
left = 0
right = x
mid = (left + right) / 2
while lef... | stack_v2_sparse_classes_10k_train_003268 | 1,501 | no_license | [
{
"docstring": ":type x: int :rtype: int",
"name": "mySqrt",
"signature": "def mySqrt(self, x)"
},
{
"docstring": ":type x: int :rtype: int",
"name": "yourSqrt",
"signature": "def yourSqrt(self, x)"
}
] | 2 | stack_v2_sparse_classes_30k_train_005136 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def mySqrt(self, x): :type x: int :rtype: int
- def yourSqrt(self, x): :type x: int :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def mySqrt(self, x): :type x: int :rtype: int
- def yourSqrt(self, x): :type x: int :rtype: int
<|skeleton|>
class Solution:
def mySqrt(self, x):
""":type x: int :r... | 2d5fa4cd696d5035ea8859befeadc5cc436959c9 | <|skeleton|>
class Solution:
def mySqrt(self, x):
""":type x: int :rtype: int"""
<|body_0|>
def yourSqrt(self, x):
""":type x: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def mySqrt(self, x):
""":type x: int :rtype: int"""
left = 0
right = x
mid = (left + right) / 2
while left <= right:
if mid ** 2 > x:
right = mid - 1
else:
left = mid + 1
mid = (left + right) ... | the_stack_v2_python_sparse | SourceCode/Python/Problem/00069.Sqrt x.py | roger6blog/LeetCode | train | 0 | |
0eadfbfa1e83c474a949ac72b99f3851e324c0f4 | [
"is_app_engine_target_set = app_engine_http_queue is not None and app_engine_http_queue.appEngineRoutingOverride is not None\nis_http_target_set = http_target is not None\nif is_app_engine_target_set and is_http_target_set:\n raise CreatingHttpAndAppEngineQueueError('Attempting to send multiple queue target type... | <|body_start_0|>
is_app_engine_target_set = app_engine_http_queue is not None and app_engine_http_queue.appEngineRoutingOverride is not None
is_http_target_set = http_target is not None
if is_app_engine_target_set and is_http_target_set:
raise CreatingHttpAndAppEngineQueueError('Atte... | Client for queues service in the Cloud Tasks API. | BetaQueues | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BetaQueues:
"""Client for queues service in the Cloud Tasks API."""
def Create(self, parent_ref, queue_ref, retry_config=None, rate_limits=None, app_engine_http_queue=None, stackdriver_logging_config=None, queue_type=None, http_target=None):
"""Prepares and sends a Create request for... | stack_v2_sparse_classes_10k_train_003269 | 19,528 | permissive | [
{
"docstring": "Prepares and sends a Create request for creating a queue.",
"name": "Create",
"signature": "def Create(self, parent_ref, queue_ref, retry_config=None, rate_limits=None, app_engine_http_queue=None, stackdriver_logging_config=None, queue_type=None, http_target=None)"
},
{
"docstrin... | 2 | null | Implement the Python class `BetaQueues` described below.
Class description:
Client for queues service in the Cloud Tasks API.
Method signatures and docstrings:
- def Create(self, parent_ref, queue_ref, retry_config=None, rate_limits=None, app_engine_http_queue=None, stackdriver_logging_config=None, queue_type=None, h... | Implement the Python class `BetaQueues` described below.
Class description:
Client for queues service in the Cloud Tasks API.
Method signatures and docstrings:
- def Create(self, parent_ref, queue_ref, retry_config=None, rate_limits=None, app_engine_http_queue=None, stackdriver_logging_config=None, queue_type=None, h... | 392abf004b16203030e6efd2f0af24db7c8d669e | <|skeleton|>
class BetaQueues:
"""Client for queues service in the Cloud Tasks API."""
def Create(self, parent_ref, queue_ref, retry_config=None, rate_limits=None, app_engine_http_queue=None, stackdriver_logging_config=None, queue_type=None, http_target=None):
"""Prepares and sends a Create request for... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class BetaQueues:
"""Client for queues service in the Cloud Tasks API."""
def Create(self, parent_ref, queue_ref, retry_config=None, rate_limits=None, app_engine_http_queue=None, stackdriver_logging_config=None, queue_type=None, http_target=None):
"""Prepares and sends a Create request for creating a q... | the_stack_v2_python_sparse | lib/googlecloudsdk/api_lib/tasks/queues.py | google-cloud-sdk-unofficial/google-cloud-sdk | train | 9 |
54d6176378b1eb8ffbaccc3418d212a6be389e56 | [
"def backtrack(nums, temp_list, result):\n if len(temp_list) == len(nums):\n result.append(list(temp_list))\n else:\n for num in nums:\n if num not in temp_list:\n temp_list.append(num)\n backtrack(nums, temp_list, result)\n temp_list.pop()... | <|body_start_0|>
def backtrack(nums, temp_list, result):
if len(temp_list) == len(nums):
result.append(list(temp_list))
else:
for num in nums:
if num not in temp_list:
temp_list.append(num)
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def permute(self, nums):
""":type nums: List[int] :rtype: List[List[int]]"""
<|body_0|>
def permute_2(self, nums):
""":type nums: List[int] :rtype: List[List[int]]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
def backtrack(nums, temp_li... | stack_v2_sparse_classes_10k_train_003270 | 1,439 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: List[List[int]]",
"name": "permute",
"signature": "def permute(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: List[List[int]]",
"name": "permute_2",
"signature": "def permute_2(self, nums)"
}
] | 2 | stack_v2_sparse_classes_30k_train_002106 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def permute(self, nums): :type nums: List[int] :rtype: List[List[int]]
- def permute_2(self, nums): :type nums: List[int] :rtype: List[List[int]] | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def permute(self, nums): :type nums: List[int] :rtype: List[List[int]]
- def permute_2(self, nums): :type nums: List[int] :rtype: List[List[int]]
<|skeleton|>
class Solution:
... | 9d9e0c08992ef7dbd9ac517821faa9de17f49b0e | <|skeleton|>
class Solution:
def permute(self, nums):
""":type nums: List[int] :rtype: List[List[int]]"""
<|body_0|>
def permute_2(self, nums):
""":type nums: List[int] :rtype: List[List[int]]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def permute(self, nums):
""":type nums: List[int] :rtype: List[List[int]]"""
def backtrack(nums, temp_list, result):
if len(temp_list) == len(nums):
result.append(list(temp_list))
else:
for num in nums:
if nu... | the_stack_v2_python_sparse | 046-permutations.py | floydchenchen/leetcode | train | 0 | |
10c7f89af6aa692e7519621ce91e1cb7cc1a66a8 | [
"import heapq\nh1 = QueueNode(3)\nh2 = QueueNode(5)\nh3 = QueueNode(7)\nheap = [h1, h2, h3]\nheapq.heapify(heap)\nfor cnt in xrange(k - 1):\n h = heapq.heappop(heap)\n if h == h1:\n h1.q.append(h1.val * 3)\n h2.q.append(h1.val * 5)\n h3.q.append(h1.val * 7)\n elif h == h2:\n h2.... | <|body_start_0|>
import heapq
h1 = QueueNode(3)
h2 = QueueNode(5)
h3 = QueueNode(7)
heap = [h1, h2, h3]
heapq.heapify(heap)
for cnt in xrange(k - 1):
h = heapq.heappop(heap)
if h == h1:
h1.q.append(h1.val * 3)
... | Solution | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def kthPrimeNumber(self, k):
"""heap and queue :param k: :return:"""
<|body_0|>
def kthPrimeNumber_error(self, k):
"""heap and queue Erroneous on re-appending the next items on the same queue Example of errors: 45 is repeated, 45 = 3*3*5 and 45 = 3*5*3 :par... | stack_v2_sparse_classes_10k_train_003271 | 2,413 | permissive | [
{
"docstring": "heap and queue :param k: :return:",
"name": "kthPrimeNumber",
"signature": "def kthPrimeNumber(self, k)"
},
{
"docstring": "heap and queue Erroneous on re-appending the next items on the same queue Example of errors: 45 is repeated, 45 = 3*3*5 and 45 = 3*5*3 :param k: :return:",
... | 2 | stack_v2_sparse_classes_30k_train_000877 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def kthPrimeNumber(self, k): heap and queue :param k: :return:
- def kthPrimeNumber_error(self, k): heap and queue Erroneous on re-appending the next items on the same queue Exam... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def kthPrimeNumber(self, k): heap and queue :param k: :return:
- def kthPrimeNumber_error(self, k): heap and queue Erroneous on re-appending the next items on the same queue Exam... | 4629a3857b2c57418b86a3b3a7180ecb15e763e3 | <|skeleton|>
class Solution:
def kthPrimeNumber(self, k):
"""heap and queue :param k: :return:"""
<|body_0|>
def kthPrimeNumber_error(self, k):
"""heap and queue Erroneous on re-appending the next items on the same queue Example of errors: 45 is repeated, 45 = 3*3*5 and 45 = 3*5*3 :par... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def kthPrimeNumber(self, k):
"""heap and queue :param k: :return:"""
import heapq
h1 = QueueNode(3)
h2 = QueueNode(5)
h3 = QueueNode(7)
heap = [h1, h2, h3]
heapq.heapify(heap)
for cnt in xrange(k - 1):
h = heapq.heappop(heap... | the_stack_v2_python_sparse | Kth Prime Number.py | RijuDasgupta9116/LintCode | train | 0 | |
f3853432fb03d2156f017c26e3788b82d4517541 | [
"self.res = 0\nvisited = [[False for _ in range(n)] for _ in range(m)]\nself.dfs(m, n, k, 0, 0, visited)\nreturn self.res",
"if row < 0 or row >= m or col < 0 or (col >= n) or visited[row][col] or (not self.valid(row, col, k)):\n return\nvisited[row][col] = True\nself.res += 1\nself.dfs(m, n, k, row + 1, col, ... | <|body_start_0|>
self.res = 0
visited = [[False for _ in range(n)] for _ in range(m)]
self.dfs(m, n, k, 0, 0, visited)
return self.res
<|end_body_0|>
<|body_start_1|>
if row < 0 or row >= m or col < 0 or (col >= n) or visited[row][col] or (not self.valid(row, col, k)):
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def movingCount(self, m, n, k):
"""Args: m: int n: int k: int Return: int"""
<|body_0|>
def dfs(self, m, n, k, row, col, visited):
"""Args: m: int n: int k: int row: int col: int visited: list[bool]"""
<|body_1|>
def valid(self, row, col, k):
... | stack_v2_sparse_classes_10k_train_003272 | 1,346 | no_license | [
{
"docstring": "Args: m: int n: int k: int Return: int",
"name": "movingCount",
"signature": "def movingCount(self, m, n, k)"
},
{
"docstring": "Args: m: int n: int k: int row: int col: int visited: list[bool]",
"name": "dfs",
"signature": "def dfs(self, m, n, k, row, col, visited)"
},... | 3 | stack_v2_sparse_classes_30k_train_001737 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def movingCount(self, m, n, k): Args: m: int n: int k: int Return: int
- def dfs(self, m, n, k, row, col, visited): Args: m: int n: int k: int row: int col: int visited: list[boo... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def movingCount(self, m, n, k): Args: m: int n: int k: int Return: int
- def dfs(self, m, n, k, row, col, visited): Args: m: int n: int k: int row: int col: int visited: list[boo... | 101bce2fac8b188a4eb2f5e017293d21ad0ecb21 | <|skeleton|>
class Solution:
def movingCount(self, m, n, k):
"""Args: m: int n: int k: int Return: int"""
<|body_0|>
def dfs(self, m, n, k, row, col, visited):
"""Args: m: int n: int k: int row: int col: int visited: list[bool]"""
<|body_1|>
def valid(self, row, col, k):
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def movingCount(self, m, n, k):
"""Args: m: int n: int k: int Return: int"""
self.res = 0
visited = [[False for _ in range(n)] for _ in range(m)]
self.dfs(m, n, k, 0, 0, visited)
return self.res
def dfs(self, m, n, k, row, col, visited):
"""Args: ... | the_stack_v2_python_sparse | 剑指offer/剑指 Offer 13. 机器人的运动范围.py | AiZhanghan/Leetcode | train | 0 | |
7845a3d22d173f515479e3b4513b816c29be1400 | [
"if not arr:\n return True\nif arr.count(0) > 1:\n return True\nfor item in arr:\n if item == 0:\n continue\n if 2 * item in arr:\n return True\nreturn False",
"for i, a in enumerate(arr):\n for j, b in enumerate(arr):\n if i != j and a == b:\n return True\nreturn Fa... | <|body_start_0|>
if not arr:
return True
if arr.count(0) > 1:
return True
for item in arr:
if item == 0:
continue
if 2 * item in arr:
return True
return False
<|end_body_0|>
<|body_start_1|>
for i, a... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def checkIfExist(self, arr):
""":type arr: List[int] :rtype: bool"""
<|body_0|>
def checkIfExist2(self, arr):
""":type arr: List[int] :rtype: bool"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not arr:
return True
... | stack_v2_sparse_classes_10k_train_003273 | 1,116 | no_license | [
{
"docstring": ":type arr: List[int] :rtype: bool",
"name": "checkIfExist",
"signature": "def checkIfExist(self, arr)"
},
{
"docstring": ":type arr: List[int] :rtype: bool",
"name": "checkIfExist2",
"signature": "def checkIfExist2(self, arr)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def checkIfExist(self, arr): :type arr: List[int] :rtype: bool
- def checkIfExist2(self, arr): :type arr: List[int] :rtype: bool | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def checkIfExist(self, arr): :type arr: List[int] :rtype: bool
- def checkIfExist2(self, arr): :type arr: List[int] :rtype: bool
<|skeleton|>
class Solution:
def checkIfExi... | 690b685048c8e89d26047b6bc48b5f9af7d59cbb | <|skeleton|>
class Solution:
def checkIfExist(self, arr):
""":type arr: List[int] :rtype: bool"""
<|body_0|>
def checkIfExist2(self, arr):
""":type arr: List[int] :rtype: bool"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def checkIfExist(self, arr):
""":type arr: List[int] :rtype: bool"""
if not arr:
return True
if arr.count(0) > 1:
return True
for item in arr:
if item == 0:
continue
if 2 * item in arr:
re... | the_stack_v2_python_sparse | 数组/1346. 检查整数及其两倍数是否存在.py | SimmonsChen/LeetCode | train | 0 | |
759af17b3cec5520d59c86c400b7b48220a404d0 | [
"count = 0\nwhile head:\n count += 1\n head = head.next\nreturn count",
"if headA is None or headB is None:\n return None\nlength1 = self.length(headA)\nlength2 = self.length(headB)\nif length1 > length2:\n steps = length1 - length2\n slower = headB\n faster = headA\nelse:\n steps = length2 -... | <|body_start_0|>
count = 0
while head:
count += 1
head = head.next
return count
<|end_body_0|>
<|body_start_1|>
if headA is None or headB is None:
return None
length1 = self.length(headA)
length2 = self.length(headB)
if length1... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def length(self, head):
""">>> s = Solution() >>> s.length(None) 0 >>> head = LinkedList.fromList([1]) >>> s.length(head) 1 >>> head = LinkedList.fromList([1, 2, 3]) >>> s.length(head) 3"""
<|body_0|>
def getIntersectionNode(self, headA, headB):
""":type he... | stack_v2_sparse_classes_10k_train_003274 | 1,786 | no_license | [
{
"docstring": ">>> s = Solution() >>> s.length(None) 0 >>> head = LinkedList.fromList([1]) >>> s.length(head) 1 >>> head = LinkedList.fromList([1, 2, 3]) >>> s.length(head) 3",
"name": "length",
"signature": "def length(self, head)"
},
{
"docstring": ":type head1, head1: ListNode :rtype: ListNo... | 2 | stack_v2_sparse_classes_30k_train_006170 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def length(self, head): >>> s = Solution() >>> s.length(None) 0 >>> head = LinkedList.fromList([1]) >>> s.length(head) 1 >>> head = LinkedList.fromList([1, 2, 3]) >>> s.length(he... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def length(self, head): >>> s = Solution() >>> s.length(None) 0 >>> head = LinkedList.fromList([1]) >>> s.length(head) 1 >>> head = LinkedList.fromList([1, 2, 3]) >>> s.length(he... | 3b13a02f9c8273f9794a57b948d2655792707f37 | <|skeleton|>
class Solution:
def length(self, head):
""">>> s = Solution() >>> s.length(None) 0 >>> head = LinkedList.fromList([1]) >>> s.length(head) 1 >>> head = LinkedList.fromList([1, 2, 3]) >>> s.length(head) 3"""
<|body_0|>
def getIntersectionNode(self, headA, headB):
""":type he... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def length(self, head):
""">>> s = Solution() >>> s.length(None) 0 >>> head = LinkedList.fromList([1]) >>> s.length(head) 1 >>> head = LinkedList.fromList([1, 2, 3]) >>> s.length(head) 3"""
count = 0
while head:
count += 1
head = head.next
retu... | the_stack_v2_python_sparse | insection_of_lists.py | gsy/leetcode | train | 1 | |
5f40abcf24075df92de65ecfda0a9ccd20c87bd4 | [
"def inorder(node):\n if node:\n yield from inorder(node.left)\n yield node.val\n yield from inorder(node.right)\nfor i in inorder(root):\n if k > 1:\n k -= 1\n else:\n return i",
"cnt = 0\nstack = []\ntmp = root\nwhile tmp is not None or len(stack) > 0:\n if tmp is ... | <|body_start_0|>
def inorder(node):
if node:
yield from inorder(node.left)
yield node.val
yield from inorder(node.right)
for i in inorder(root):
if k > 1:
k -= 1
else:
return i
<|end_body_... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def kthSmallest2(self, root: Optional[TreeNode], k: int) -> int:
"""Runtime: 44 ms, faster than 98.45% Memory Usage: 18 MB, less than 48.12% The number of nodes in the tree is n. 1 <= k <= n <= 10^4 0 <= Node.val <= 10^4"""
<|body_0|>
def kthSmallest(self, root: Op... | stack_v2_sparse_classes_10k_train_003275 | 2,102 | permissive | [
{
"docstring": "Runtime: 44 ms, faster than 98.45% Memory Usage: 18 MB, less than 48.12% The number of nodes in the tree is n. 1 <= k <= n <= 10^4 0 <= Node.val <= 10^4",
"name": "kthSmallest2",
"signature": "def kthSmallest2(self, root: Optional[TreeNode], k: int) -> int"
},
{
"docstring": "93 ... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def kthSmallest2(self, root: Optional[TreeNode], k: int) -> int: Runtime: 44 ms, faster than 98.45% Memory Usage: 18 MB, less than 48.12% The number of nodes in the tree is n. 1 ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def kthSmallest2(self, root: Optional[TreeNode], k: int) -> int: Runtime: 44 ms, faster than 98.45% Memory Usage: 18 MB, less than 48.12% The number of nodes in the tree is n. 1 ... | 4dd1e54d8d08f7e6590bc76abd08ecaacaf775e5 | <|skeleton|>
class Solution:
def kthSmallest2(self, root: Optional[TreeNode], k: int) -> int:
"""Runtime: 44 ms, faster than 98.45% Memory Usage: 18 MB, less than 48.12% The number of nodes in the tree is n. 1 <= k <= n <= 10^4 0 <= Node.val <= 10^4"""
<|body_0|>
def kthSmallest(self, root: Op... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def kthSmallest2(self, root: Optional[TreeNode], k: int) -> int:
"""Runtime: 44 ms, faster than 98.45% Memory Usage: 18 MB, less than 48.12% The number of nodes in the tree is n. 1 <= k <= n <= 10^4 0 <= Node.val <= 10^4"""
def inorder(node):
if node:
yiel... | the_stack_v2_python_sparse | src/230-KthSmallestElementinaBST.py | Jiezhi/myleetcode | train | 1 | |
2db7ed8951cad880e828dbb04b7ad6d53582d307 | [
"super(Head, self).__init__()\nself.action_dim = squeeze(action_dim)\nself.dueling = dueling\nhead_fn = partial(DuelingHead, a_layer_num=a_layer_num, v_layer_num=v_layer_num) if dueling else nn.Linear\nif isinstance(self.action_dim, tuple):\n self.pred = nn.ModuleList()\n for dim in self.action_dim:\n ... | <|body_start_0|>
super(Head, self).__init__()
self.action_dim = squeeze(action_dim)
self.dueling = dueling
head_fn = partial(DuelingHead, a_layer_num=a_layer_num, v_layer_num=v_layer_num) if dueling else nn.Linear
if isinstance(self.action_dim, tuple):
self.pred = nn.... | Overview: The Head used in DQN models. Receive encoded embedding tensor and use it to predict the action. Interfaces: __init__, forward | Head | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Head:
"""Overview: The Head used in DQN models. Receive encoded embedding tensor and use it to predict the action. Interfaces: __init__, forward"""
def __init__(self, action_dim: tuple, input_dim: int, dueling: bool=True, a_layer_num: int=1, v_layer_num: int=1) -> None:
"""Overview: ... | stack_v2_sparse_classes_10k_train_003276 | 9,851 | permissive | [
{
"docstring": "Overview: Init the Head according to arguments. Arguments: - action_dim (:obj:`tuple`): the num of action dim, \\\\ note that it can be a tuple containing more than one element - input_dim (:obj:`int`): input tensor dim of the head - dueling (:obj:`bool`): whether to use ``DuelingHead`` or ``nn.... | 2 | stack_v2_sparse_classes_30k_train_007331 | Implement the Python class `Head` described below.
Class description:
Overview: The Head used in DQN models. Receive encoded embedding tensor and use it to predict the action. Interfaces: __init__, forward
Method signatures and docstrings:
- def __init__(self, action_dim: tuple, input_dim: int, dueling: bool=True, a_... | Implement the Python class `Head` described below.
Class description:
Overview: The Head used in DQN models. Receive encoded embedding tensor and use it to predict the action. Interfaces: __init__, forward
Method signatures and docstrings:
- def __init__(self, action_dim: tuple, input_dim: int, dueling: bool=True, a_... | 09d507c412235a2f0cf9c0b3485ec9ed15fb6421 | <|skeleton|>
class Head:
"""Overview: The Head used in DQN models. Receive encoded embedding tensor and use it to predict the action. Interfaces: __init__, forward"""
def __init__(self, action_dim: tuple, input_dim: int, dueling: bool=True, a_layer_num: int=1, v_layer_num: int=1) -> None:
"""Overview: ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Head:
"""Overview: The Head used in DQN models. Receive encoded embedding tensor and use it to predict the action. Interfaces: __init__, forward"""
def __init__(self, action_dim: tuple, input_dim: int, dueling: bool=True, a_layer_num: int=1, v_layer_num: int=1) -> None:
"""Overview: Init the Head... | the_stack_v2_python_sparse | ctools/model/dqn/dqn_network.py | LFhase/DI-star | train | 1 |
5f1fbb979033a14e2c58e2833ab1d2a1ccccc4aa | [
"inv_obj = self.pool.get('account.invoice').browse(cr, uid, invoice_id)\nres = super(account_invoice_tax, self).move_line_get(cr, uid, invoice_id)\nfor r in res:\n if inv_obj.budget_confirm_id:\n if r['price'] > 0 and r['account_id'] == inv_obj.budget_confirm_id.general_account_id.id:\n r.updat... | <|body_start_0|>
inv_obj = self.pool.get('account.invoice').browse(cr, uid, invoice_id)
res = super(account_invoice_tax, self).move_line_get(cr, uid, invoice_id)
for r in res:
if inv_obj.budget_confirm_id:
if r['price'] > 0 and r['account_id'] == inv_obj.budget_confir... | account_invoice_tax | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class account_invoice_tax:
def move_line_get(self, cr, uid, invoice_id):
"""Check the budget_confermation_id in particular invoice and update tax line move by it or set False. @param invoice_id : id for invoice @return: dictionary of values to be updated"""
<|body_0|>
def compute(... | stack_v2_sparse_classes_10k_train_003277 | 6,435 | no_license | [
{
"docstring": "Check the budget_confermation_id in particular invoice and update tax line move by it or set False. @param invoice_id : id for invoice @return: dictionary of values to be updated",
"name": "move_line_get",
"signature": "def move_line_get(self, cr, uid, invoice_id)"
},
{
"docstrin... | 2 | null | Implement the Python class `account_invoice_tax` described below.
Class description:
Implement the account_invoice_tax class.
Method signatures and docstrings:
- def move_line_get(self, cr, uid, invoice_id): Check the budget_confermation_id in particular invoice and update tax line move by it or set False. @param inv... | Implement the Python class `account_invoice_tax` described below.
Class description:
Implement the account_invoice_tax class.
Method signatures and docstrings:
- def move_line_get(self, cr, uid, invoice_id): Check the budget_confermation_id in particular invoice and update tax line move by it or set False. @param inv... | 0b997095c260d58b026440967fea3a202bef7efb | <|skeleton|>
class account_invoice_tax:
def move_line_get(self, cr, uid, invoice_id):
"""Check the budget_confermation_id in particular invoice and update tax line move by it or set False. @param invoice_id : id for invoice @return: dictionary of values to be updated"""
<|body_0|>
def compute(... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class account_invoice_tax:
def move_line_get(self, cr, uid, invoice_id):
"""Check the budget_confermation_id in particular invoice and update tax line move by it or set False. @param invoice_id : id for invoice @return: dictionary of values to be updated"""
inv_obj = self.pool.get('account.invoice')... | the_stack_v2_python_sparse | v_7/Dongola/common/account_invoice_confirmation/invoice.py | musabahmed/baba | train | 0 | |
7b05857373af0795a2cddb278e3a79c607fafa69 | [
"bsz = ys.size(0)\nseqlen = ys.size(1)\ninputs = ys.narrow(1, 0, seqlen - 1)\nif (ys[:, 0] == self.START_IDX).any():\n raise AssertionError('The Beginning of Sentence token is automatically added to the label in decode_forced, but you included it in the label. This means your model will have a double BOS token, ... | <|body_start_0|>
bsz = ys.size(0)
seqlen = ys.size(1)
inputs = ys.narrow(1, 0, seqlen - 1)
if (ys[:, 0] == self.START_IDX).any():
raise AssertionError('The Beginning of Sentence token is automatically added to the label in decode_forced, but you included it in the label. This... | Returns the latent representations in the forward pass. We need the latent representations for the multi-objective computations | TransformerGeneratorReturnLatentModel | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TransformerGeneratorReturnLatentModel:
"""Returns the latent representations in the forward pass. We need the latent representations for the multi-objective computations"""
def decode_forced(self, encoder_states: Tuple[Any], ys: torch.LongTensor) -> Tuple[torch.Tensor, torch.LongTensor, torc... | stack_v2_sparse_classes_10k_train_003278 | 37,138 | permissive | [
{
"docstring": "Override TGM.decode_forced to return latent states. Nearly copied verbatim, except for return type.",
"name": "decode_forced",
"signature": "def decode_forced(self, encoder_states: Tuple[Any], ys: torch.LongTensor) -> Tuple[torch.Tensor, torch.LongTensor, torch.Tensor, torch.BoolTensor]"... | 2 | null | Implement the Python class `TransformerGeneratorReturnLatentModel` described below.
Class description:
Returns the latent representations in the forward pass. We need the latent representations for the multi-objective computations
Method signatures and docstrings:
- def decode_forced(self, encoder_states: Tuple[Any],... | Implement the Python class `TransformerGeneratorReturnLatentModel` described below.
Class description:
Returns the latent representations in the forward pass. We need the latent representations for the multi-objective computations
Method signatures and docstrings:
- def decode_forced(self, encoder_states: Tuple[Any],... | e1d899edfb92471552bae153f59ad30aa7fca468 | <|skeleton|>
class TransformerGeneratorReturnLatentModel:
"""Returns the latent representations in the forward pass. We need the latent representations for the multi-objective computations"""
def decode_forced(self, encoder_states: Tuple[Any], ys: torch.LongTensor) -> Tuple[torch.Tensor, torch.LongTensor, torc... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TransformerGeneratorReturnLatentModel:
"""Returns the latent representations in the forward pass. We need the latent representations for the multi-objective computations"""
def decode_forced(self, encoder_states: Tuple[Any], ys: torch.LongTensor) -> Tuple[torch.Tensor, torch.LongTensor, torch.Tensor, tor... | the_stack_v2_python_sparse | projects/light_whoami/agents/multi_objective.py | facebookresearch/ParlAI | train | 10,943 |
14ee4c15847b4a84087dda703f0040f94a844ab9 | [
"transformed_input = []\ntokenized_string = nltk.word_tokenize(input_string)\npos_tagged_tokens = nltk.pos_tag(tokenized_string)\nwordnet_lemmatizer = WordNetLemmatizer()\nfor pos_tagged_token in pos_tagged_tokens:\n word, part_of_speech = pos_tagged_token\n if str(part_of_speech).startswith('N'):\n tr... | <|body_start_0|>
transformed_input = []
tokenized_string = nltk.word_tokenize(input_string)
pos_tagged_tokens = nltk.pos_tag(tokenized_string)
wordnet_lemmatizer = WordNetLemmatizer()
for pos_tagged_token in pos_tagged_tokens:
word, part_of_speech = pos_tagged_token
... | This class implements lemmatization and is based on an abstract method. | LemmatizationFilePreprocessing | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LemmatizationFilePreprocessing:
"""This class implements lemmatization and is based on an abstract method."""
def string_transformation(input_string):
"""This method returns a string array with the words of the document. It needs to be used for query preprocessing as well."""
... | stack_v2_sparse_classes_10k_train_003279 | 6,719 | no_license | [
{
"docstring": "This method returns a string array with the words of the document. It needs to be used for query preprocessing as well.",
"name": "string_transformation",
"signature": "def string_transformation(input_string)"
},
{
"docstring": "This method reads the 20 newsgroup corpus, processe... | 3 | stack_v2_sparse_classes_30k_train_004702 | Implement the Python class `LemmatizationFilePreprocessing` described below.
Class description:
This class implements lemmatization and is based on an abstract method.
Method signatures and docstrings:
- def string_transformation(input_string): This method returns a string array with the words of the document. It nee... | Implement the Python class `LemmatizationFilePreprocessing` described below.
Class description:
This class implements lemmatization and is based on an abstract method.
Method signatures and docstrings:
- def string_transformation(input_string): This method returns a string array with the words of the document. It nee... | 3192cdb4b969e461d389d2cff2063a33d79fa9e2 | <|skeleton|>
class LemmatizationFilePreprocessing:
"""This class implements lemmatization and is based on an abstract method."""
def string_transformation(input_string):
"""This method returns a string array with the words of the document. It needs to be used for query preprocessing as well."""
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class LemmatizationFilePreprocessing:
"""This class implements lemmatization and is based on an abstract method."""
def string_transformation(input_string):
"""This method returns a string array with the words of the document. It needs to be used for query preprocessing as well."""
transformed_... | the_stack_v2_python_sparse | src/preprocessing/LemmatizationFilePreprocessing.py | IR-WS-TeamProject/LatentSemanticIndexing | train | 1 |
ed94486254899116b94770c0259e0fb6dc50c06d | [
"data_list = []\nresults = self.query.all()\nformatter = date.getLocaleFormatter(self.request, 'date', 'long')\nfor result in results:\n data = {}\n data['qid'] = 'i-' + str(result.parliamentary_item_id)\n if type(result) == domain.AgendaItem:\n g = u' ' + result.group.type + u' ' + result.group.sho... | <|body_start_0|>
data_list = []
results = self.query.all()
formatter = date.getLocaleFormatter(self.request, 'date', 'long')
for result in results:
data = {}
data['qid'] = 'i-' + str(result.parliamentary_item_id)
if type(result) == domain.AgendaItem:
... | Group parliamentary items per stage e.g. action required, in progress, answered/debated, "dead" (withdrawn, elapsed, inadmissible, dropped). | OwnedItemsInStageViewlet | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OwnedItemsInStageViewlet:
"""Group parliamentary items per stage e.g. action required, in progress, answered/debated, "dead" (withdrawn, elapsed, inadmissible, dropped)."""
def _setData(self):
"""Return the data of the query."""
<|body_0|>
def update(self):
"""Re... | stack_v2_sparse_classes_10k_train_003280 | 27,657 | no_license | [
{
"docstring": "Return the data of the query.",
"name": "_setData",
"signature": "def _setData(self)"
},
{
"docstring": "Refresh the query.",
"name": "update",
"signature": "def update(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_005449 | Implement the Python class `OwnedItemsInStageViewlet` described below.
Class description:
Group parliamentary items per stage e.g. action required, in progress, answered/debated, "dead" (withdrawn, elapsed, inadmissible, dropped).
Method signatures and docstrings:
- def _setData(self): Return the data of the query.
-... | Implement the Python class `OwnedItemsInStageViewlet` described below.
Class description:
Group parliamentary items per stage e.g. action required, in progress, answered/debated, "dead" (withdrawn, elapsed, inadmissible, dropped).
Method signatures and docstrings:
- def _setData(self): Return the data of the query.
-... | 5cf0ba31dfbff8d2c1b4aa8ab6f69c7a0ae9870d | <|skeleton|>
class OwnedItemsInStageViewlet:
"""Group parliamentary items per stage e.g. action required, in progress, answered/debated, "dead" (withdrawn, elapsed, inadmissible, dropped)."""
def _setData(self):
"""Return the data of the query."""
<|body_0|>
def update(self):
"""Re... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class OwnedItemsInStageViewlet:
"""Group parliamentary items per stage e.g. action required, in progress, answered/debated, "dead" (withdrawn, elapsed, inadmissible, dropped)."""
def _setData(self):
"""Return the data of the query."""
data_list = []
results = self.query.all()
fo... | the_stack_v2_python_sparse | bungeni.main/branches/mr/bungeni/ui/viewlets/workspace.py | malangalanga/bungeni-portal | train | 0 |
d289e5547441ca375772b60e966cb0cf439913fb | [
"super().__init__()\nself.layer_norm = nn.LayerNorm(size, eps=1e-06)\nself.src_src_att = MultiHeadedAttention(num_heads, size, dropout=dropout)\nself.feed_forward = PositionwiseFeedForward(size, ff_size=ff_size, dropout=dropout, alpha=alpha, layer_norm=layer_norm, activation=activation)\nself.dropout = nn.Dropout(d... | <|body_start_0|>
super().__init__()
self.layer_norm = nn.LayerNorm(size, eps=1e-06)
self.src_src_att = MultiHeadedAttention(num_heads, size, dropout=dropout)
self.feed_forward = PositionwiseFeedForward(size, ff_size=ff_size, dropout=dropout, alpha=alpha, layer_norm=layer_norm, activation... | One Transformer encoder layer has a Multi-head attention layer plus a position-wise feed-forward layer. | TransformerEncoderLayer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TransformerEncoderLayer:
"""One Transformer encoder layer has a Multi-head attention layer plus a position-wise feed-forward layer."""
def __init__(self, size: int=0, ff_size: int=0, num_heads: int=0, dropout: float=0.1, alpha: float=1.0, layer_norm: str='post', activation: str='relu') -> No... | stack_v2_sparse_classes_10k_train_003281 | 13,169 | permissive | [
{
"docstring": "A single Transformer encoder layer. Note: don't change the name or the order of members! otherwise pretrained models cannot be loaded correctly. :param size: model dimensionality :param ff_size: size of the feed-forward intermediate layer :param num_heads: number of heads :param dropout: dropout... | 2 | stack_v2_sparse_classes_30k_train_005195 | Implement the Python class `TransformerEncoderLayer` described below.
Class description:
One Transformer encoder layer has a Multi-head attention layer plus a position-wise feed-forward layer.
Method signatures and docstrings:
- def __init__(self, size: int=0, ff_size: int=0, num_heads: int=0, dropout: float=0.1, alp... | Implement the Python class `TransformerEncoderLayer` described below.
Class description:
One Transformer encoder layer has a Multi-head attention layer plus a position-wise feed-forward layer.
Method signatures and docstrings:
- def __init__(self, size: int=0, ff_size: int=0, num_heads: int=0, dropout: float=0.1, alp... | 0968187ac0968007cabebed5e5cb6587c08dff78 | <|skeleton|>
class TransformerEncoderLayer:
"""One Transformer encoder layer has a Multi-head attention layer plus a position-wise feed-forward layer."""
def __init__(self, size: int=0, ff_size: int=0, num_heads: int=0, dropout: float=0.1, alpha: float=1.0, layer_norm: str='post', activation: str='relu') -> No... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TransformerEncoderLayer:
"""One Transformer encoder layer has a Multi-head attention layer plus a position-wise feed-forward layer."""
def __init__(self, size: int=0, ff_size: int=0, num_heads: int=0, dropout: float=0.1, alpha: float=1.0, layer_norm: str='post', activation: str='relu') -> None:
"... | the_stack_v2_python_sparse | joeynmt/transformer_layers.py | joeynmt/joeynmt | train | 668 |
fa560333820b24d62886d62643e19cecd46f93d3 | [
"if root is None:\n return None\nbroot = TreeNode(root.val)\nnode = broot\nfor i, child in enumerate(root.children):\n new_node = self.encode(child)\n if i == 0:\n broot.left = new_node\n node = broot.left\n else:\n node.right = new_node\n node = node.right\nreturn broot",
... | <|body_start_0|>
if root is None:
return None
broot = TreeNode(root.val)
node = broot
for i, child in enumerate(root.children):
new_node = self.encode(child)
if i == 0:
broot.left = new_node
node = broot.left
... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def encode(self, root):
"""Encodes an n-ary tree to a binary tree. :type root: Node :rtype: TreeNode"""
<|body_0|>
def decode(self, data):
"""Decodes your binary tree to an n-ary tree. :type data: TreeNode :rtype: Node"""
<|body_1|>
<|end_skeleton|>
... | stack_v2_sparse_classes_10k_train_003282 | 2,836 | no_license | [
{
"docstring": "Encodes an n-ary tree to a binary tree. :type root: Node :rtype: TreeNode",
"name": "encode",
"signature": "def encode(self, root)"
},
{
"docstring": "Decodes your binary tree to an n-ary tree. :type data: TreeNode :rtype: Node",
"name": "decode",
"signature": "def decode... | 2 | null | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def encode(self, root): Encodes an n-ary tree to a binary tree. :type root: Node :rtype: TreeNode
- def decode(self, data): Decodes your binary tree to an n-ary tree. :type data: TreeN... | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def encode(self, root): Encodes an n-ary tree to a binary tree. :type root: Node :rtype: TreeNode
- def decode(self, data): Decodes your binary tree to an n-ary tree. :type data: TreeN... | a5cb862f0c5a3cfd21468141800568c2dedded0a | <|skeleton|>
class Codec:
def encode(self, root):
"""Encodes an n-ary tree to a binary tree. :type root: Node :rtype: TreeNode"""
<|body_0|>
def decode(self, data):
"""Decodes your binary tree to an n-ary tree. :type data: TreeNode :rtype: Node"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Codec:
def encode(self, root):
"""Encodes an n-ary tree to a binary tree. :type root: Node :rtype: TreeNode"""
if root is None:
return None
broot = TreeNode(root.val)
node = broot
for i, child in enumerate(root.children):
new_node = self.encode(c... | the_stack_v2_python_sparse | python/leetcode/tree/431_nary_bin_tree.py | Levintsky/topcoder | train | 0 | |
8848485f64fe45a228b309280e6f28c046356aec | [
"self.table = DBFetcher(dot_t_system_dir, 'db', 'admin').fetch()\nself.ssid_hash = None\nself.password_hash = None\nself.private_key = None\nself.get_keys()",
"ssid_hash = hashlib.sha256(ssid.encode()).hexdigest()\npassword_hash = hashlib.sha256(password.encode()).hexdigest()\npublic_key = hashlib.sha256((ssid + ... | <|body_start_0|>
self.table = DBFetcher(dot_t_system_dir, 'db', 'admin').fetch()
self.ssid_hash = None
self.password_hash = None
self.private_key = None
self.get_keys()
<|end_body_0|>
<|body_start_1|>
ssid_hash = hashlib.sha256(ssid.encode()).hexdigest()
password... | Class to define an administrator for managing admin authentication keys of tracking system. This class provides necessary initiations and functions named :func:`t_system.administration.Administrator.change_keys` for changing admin entry keys. | Administrator | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Administrator:
"""Class to define an administrator for managing admin authentication keys of tracking system. This class provides necessary initiations and functions named :func:`t_system.administration.Administrator.change_keys` for changing admin entry keys."""
def __init__(self):
... | stack_v2_sparse_classes_10k_train_003283 | 4,830 | permissive | [
{
"docstring": "Initialization method of :class:`t_system.administration.Administrator` class.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "The high-level method to change keys of secret entry point for root authorized. 2 key(ssid and password) authentication uses s... | 5 | stack_v2_sparse_classes_30k_train_004100 | Implement the Python class `Administrator` described below.
Class description:
Class to define an administrator for managing admin authentication keys of tracking system. This class provides necessary initiations and functions named :func:`t_system.administration.Administrator.change_keys` for changing admin entry key... | Implement the Python class `Administrator` described below.
Class description:
Class to define an administrator for managing admin authentication keys of tracking system. This class provides necessary initiations and functions named :func:`t_system.administration.Administrator.change_keys` for changing admin entry key... | a9d63fbbdc208c578d6a6153bf2ba13142b3c7a5 | <|skeleton|>
class Administrator:
"""Class to define an administrator for managing admin authentication keys of tracking system. This class provides necessary initiations and functions named :func:`t_system.administration.Administrator.change_keys` for changing admin entry keys."""
def __init__(self):
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Administrator:
"""Class to define an administrator for managing admin authentication keys of tracking system. This class provides necessary initiations and functions named :func:`t_system.administration.Administrator.change_keys` for changing admin entry keys."""
def __init__(self):
"""Initializa... | the_stack_v2_python_sparse | t_system/administration.py | ahmetishakoglu/T_System | train | 0 |
f1bc9e874854f5453cd4abb36f23f2852c9c966a | [
"dp = [0] * (n - 1)\ndp[0] = 1\nfor i in range(3, n + 1):\n for j in range(1, i):\n if i - j < 2:\n if j * (i - j) > dp[i - 2]:\n dp[i - 2] = j * (i - j)\n elif j * dp[i - j - 2] > dp[i - 2] or j * (i - j) > dp[i - 2]:\n dp[i - 2] = j * max(dp[i - j - 2], i - j)... | <|body_start_0|>
dp = [0] * (n - 1)
dp[0] = 1
for i in range(3, n + 1):
for j in range(1, i):
if i - j < 2:
if j * (i - j) > dp[i - 2]:
dp[i - 2] = j * (i - j)
elif j * dp[i - j - 2] > dp[i - 2] or j * (i - j... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def integerBreak(self, n):
""":type n: int :rtype: int"""
<|body_0|>
def integerBreak2(self, n: int) -> int:
"""dp[i] is the maximum product for number i"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
dp = [0] * (n - 1)
dp[0] = 1
... | stack_v2_sparse_classes_10k_train_003284 | 1,299 | no_license | [
{
"docstring": ":type n: int :rtype: int",
"name": "integerBreak",
"signature": "def integerBreak(self, n)"
},
{
"docstring": "dp[i] is the maximum product for number i",
"name": "integerBreak2",
"signature": "def integerBreak2(self, n: int) -> int"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def integerBreak(self, n): :type n: int :rtype: int
- def integerBreak2(self, n: int) -> int: dp[i] is the maximum product for number i | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def integerBreak(self, n): :type n: int :rtype: int
- def integerBreak2(self, n: int) -> int: dp[i] is the maximum product for number i
<|skeleton|>
class Solution:
def int... | a5b02044ef39154b6a8d32eb57682f447e1632ba | <|skeleton|>
class Solution:
def integerBreak(self, n):
""":type n: int :rtype: int"""
<|body_0|>
def integerBreak2(self, n: int) -> int:
"""dp[i] is the maximum product for number i"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def integerBreak(self, n):
""":type n: int :rtype: int"""
dp = [0] * (n - 1)
dp[0] = 1
for i in range(3, n + 1):
for j in range(1, i):
if i - j < 2:
if j * (i - j) > dp[i - 2]:
dp[i - 2] = j * (i ... | the_stack_v2_python_sparse | algo/dp/integer_break.py | xys234/coding-problems | train | 0 | |
9565296ffe8b13b3a1d30861232a122b09913af4 | [
"super().__init__(x_ref=x_ref, p_val=p_val, x_ref_preprocessed=x_ref_preprocessed, preprocess_at_init=preprocess_at_init, update_x_ref=update_x_ref, preprocess_fn=preprocess_fn, correction=correction, n_features=n_features, input_shape=input_shape, data_type=data_type)\nself._set_config(locals())\nself.alternative ... | <|body_start_0|>
super().__init__(x_ref=x_ref, p_val=p_val, x_ref_preprocessed=x_ref_preprocessed, preprocess_at_init=preprocess_at_init, update_x_ref=update_x_ref, preprocess_fn=preprocess_fn, correction=correction, n_features=n_features, input_shape=input_shape, data_type=data_type)
self._set_config(l... | KSDrift | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class KSDrift:
def __init__(self, x_ref: Union[np.ndarray, list], p_val: float=0.05, x_ref_preprocessed: bool=False, preprocess_at_init: bool=True, update_x_ref: Optional[Dict[str, int]]=None, preprocess_fn: Optional[Callable]=None, correction: str='bonferroni', alternative: str='two-sided', n_feature... | stack_v2_sparse_classes_10k_train_003285 | 4,384 | permissive | [
{
"docstring": "Kolmogorov-Smirnov (K-S) data drift detector with Bonferroni or False Discovery Rate (FDR) correction for multivariate data. Parameters ---------- x_ref Data used as reference distribution. p_val p-value used for significance of the K-S test for each feature. If the FDR correction method is used... | 2 | stack_v2_sparse_classes_30k_train_005056 | Implement the Python class `KSDrift` described below.
Class description:
Implement the KSDrift class.
Method signatures and docstrings:
- def __init__(self, x_ref: Union[np.ndarray, list], p_val: float=0.05, x_ref_preprocessed: bool=False, preprocess_at_init: bool=True, update_x_ref: Optional[Dict[str, int]]=None, pr... | Implement the Python class `KSDrift` described below.
Class description:
Implement the KSDrift class.
Method signatures and docstrings:
- def __init__(self, x_ref: Union[np.ndarray, list], p_val: float=0.05, x_ref_preprocessed: bool=False, preprocess_at_init: bool=True, update_x_ref: Optional[Dict[str, int]]=None, pr... | 4a1b4f74a8590117965421e86c2295bff0f33e89 | <|skeleton|>
class KSDrift:
def __init__(self, x_ref: Union[np.ndarray, list], p_val: float=0.05, x_ref_preprocessed: bool=False, preprocess_at_init: bool=True, update_x_ref: Optional[Dict[str, int]]=None, preprocess_fn: Optional[Callable]=None, correction: str='bonferroni', alternative: str='two-sided', n_feature... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class KSDrift:
def __init__(self, x_ref: Union[np.ndarray, list], p_val: float=0.05, x_ref_preprocessed: bool=False, preprocess_at_init: bool=True, update_x_ref: Optional[Dict[str, int]]=None, preprocess_fn: Optional[Callable]=None, correction: str='bonferroni', alternative: str='two-sided', n_features: Optional[in... | the_stack_v2_python_sparse | alibi_detect/cd/ks.py | SeldonIO/alibi-detect | train | 1,922 | |
403ffb5ab3253633b53379f50780ec39dd120a40 | [
"self._AMPLIFIER_CHANNELS = []\nself._AUX_CHANNELS = []\nself._SUPPLY_VOLTAGE_CHANNELS = []\nself._ADC_INPUT_CHANNELS = []\nself._DIGITAL_INPUT_CHANNELS = []\nself._TEMP_SENSORS = 0\nself.rhd = rhd_file\nself.readHead()\nself.readBlocks()",
"filesize = self.rhd.tell()\nself.header_identifier = hex(np.uint32(struc... | <|body_start_0|>
self._AMPLIFIER_CHANNELS = []
self._AUX_CHANNELS = []
self._SUPPLY_VOLTAGE_CHANNELS = []
self._ADC_INPUT_CHANNELS = []
self._DIGITAL_INPUT_CHANNELS = []
self._TEMP_SENSORS = 0
self.rhd = rhd_file
self.readHead()
self.readBlocks()
<... | RHD | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RHD:
def __init__(self, rhd_file):
"""Constructor takes in open file object you can use use RHD.openRhd(file_path) to follow python convention"""
<|body_0|>
def readHead(self):
"""Reads all header data from the rhd file creates signal group and channel list"""
... | stack_v2_sparse_classes_10k_train_003286 | 12,179 | permissive | [
{
"docstring": "Constructor takes in open file object you can use use RHD.openRhd(file_path) to follow python convention",
"name": "__init__",
"signature": "def __init__(self, rhd_file)"
},
{
"docstring": "Reads all header data from the rhd file creates signal group and channel list",
"name"... | 3 | stack_v2_sparse_classes_30k_train_005973 | Implement the Python class `RHD` described below.
Class description:
Implement the RHD class.
Method signatures and docstrings:
- def __init__(self, rhd_file): Constructor takes in open file object you can use use RHD.openRhd(file_path) to follow python convention
- def readHead(self): Reads all header data from the ... | Implement the Python class `RHD` described below.
Class description:
Implement the RHD class.
Method signatures and docstrings:
- def __init__(self, rhd_file): Constructor takes in open file object you can use use RHD.openRhd(file_path) to follow python convention
- def readHead(self): Reads all header data from the ... | 0fdbe834442550117dc9d9c8f611989bb600db62 | <|skeleton|>
class RHD:
def __init__(self, rhd_file):
"""Constructor takes in open file object you can use use RHD.openRhd(file_path) to follow python convention"""
<|body_0|>
def readHead(self):
"""Reads all header data from the rhd file creates signal group and channel list"""
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class RHD:
def __init__(self, rhd_file):
"""Constructor takes in open file object you can use use RHD.openRhd(file_path) to follow python convention"""
self._AMPLIFIER_CHANNELS = []
self._AUX_CHANNELS = []
self._SUPPLY_VOLTAGE_CHANNELS = []
self._ADC_INPUT_CHANNELS = []
... | the_stack_v2_python_sparse | pyhfo/io/RHD.py | britodasilva/pyhfo | train | 4 | |
0476ae4a3911cdb57dddab65f194e3502cdc11ad | [
"content = '\\n Hi {{ taster_first_name }},\\n\\n {% if verification_code %}\\n To allow you to enjoy all that Vinely has to offer, we have created a new account for you. Follow the following steps to activate your account.\\n <h3>Activate Account:</h3>\\n <table>\\n <tr>\\... | <|body_start_0|>
content = '\n Hi {{ taster_first_name }},\n\n {% if verification_code %}\n To allow you to enjoy all that Vinely has to offer, we have created a new account for you. Follow the following steps to activate your account.\n <h3>Activate Account:</h3>\n <table>\n ... | Migration | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Migration:
def forwards(self, orm):
"""Write your forwards methods here."""
<|body_0|>
def backwards(self, orm):
"""Write your backwards methods here."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
content = '\n Hi {{ taster_first_name }},\n... | stack_v2_sparse_classes_10k_train_003287 | 4,199 | no_license | [
{
"docstring": "Write your forwards methods here.",
"name": "forwards",
"signature": "def forwards(self, orm)"
},
{
"docstring": "Write your backwards methods here.",
"name": "backwards",
"signature": "def backwards(self, orm)"
}
] | 2 | stack_v2_sparse_classes_30k_train_000404 | Implement the Python class `Migration` described below.
Class description:
Implement the Migration class.
Method signatures and docstrings:
- def forwards(self, orm): Write your forwards methods here.
- def backwards(self, orm): Write your backwards methods here. | Implement the Python class `Migration` described below.
Class description:
Implement the Migration class.
Method signatures and docstrings:
- def forwards(self, orm): Write your forwards methods here.
- def backwards(self, orm): Write your backwards methods here.
<|skeleton|>
class Migration:
def forwards(self,... | c5c7d8a0b1a297e07302870017d3fb03c5dbb009 | <|skeleton|>
class Migration:
def forwards(self, orm):
"""Write your forwards methods here."""
<|body_0|>
def backwards(self, orm):
"""Write your backwards methods here."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Migration:
def forwards(self, orm):
"""Write your forwards methods here."""
content = '\n Hi {{ taster_first_name }},\n\n {% if verification_code %}\n To allow you to enjoy all that Vinely has to offer, we have created a new account for you. Follow the following steps to a... | the_stack_v2_python_sparse | cms/migrations/0016_add_welcome_email_template.py | RSV3/nuvine | train | 0 | |
d0c44c99119ac2e02260ff2f0b0d23a3c6d45be4 | [
"super().__init__()\nself.temperature = np.sqrt(input_channels)\nself.key_projection = nn.Linear(input_channels, input_channels, bias=False)\nself.value_projection = nn.Linear(input_channels, input_channels, bias=False)\nnn.init.xavier_normal_(self.key_projection.weight)\nnn.init.xavier_normal_(self.value_projectio... | <|body_start_0|>
super().__init__()
self.temperature = np.sqrt(input_channels)
self.key_projection = nn.Linear(input_channels, input_channels, bias=False)
self.value_projection = nn.Linear(input_channels, input_channels, bias=False)
nn.init.xavier_normal_(self.key_projection.weig... | The co-attention network for MHCADDI model. | CoAttention | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CoAttention:
"""The co-attention network for MHCADDI model."""
def __init__(self, input_channels: int, output_channels: int, dropout: float=0.1):
"""Instantiate the co-attention network. :param input_channels: The number of atom features. :param output_channels: The number of output ... | stack_v2_sparse_classes_10k_train_003288 | 25,672 | no_license | [
{
"docstring": "Instantiate the co-attention network. :param input_channels: The number of atom features. :param output_channels: The number of output features. :param dropout: Dropout probability.",
"name": "__init__",
"signature": "def __init__(self, input_channels: int, output_channels: int, dropout:... | 3 | stack_v2_sparse_classes_30k_train_002971 | Implement the Python class `CoAttention` described below.
Class description:
The co-attention network for MHCADDI model.
Method signatures and docstrings:
- def __init__(self, input_channels: int, output_channels: int, dropout: float=0.1): Instantiate the co-attention network. :param input_channels: The number of ato... | Implement the Python class `CoAttention` described below.
Class description:
The co-attention network for MHCADDI model.
Method signatures and docstrings:
- def __init__(self, input_channels: int, output_channels: int, dropout: float=0.1): Instantiate the co-attention network. :param input_channels: The number of ato... | 7e55a422588c1d1e00f35a3d3a3ff896cce59e18 | <|skeleton|>
class CoAttention:
"""The co-attention network for MHCADDI model."""
def __init__(self, input_channels: int, output_channels: int, dropout: float=0.1):
"""Instantiate the co-attention network. :param input_channels: The number of atom features. :param output_channels: The number of output ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class CoAttention:
"""The co-attention network for MHCADDI model."""
def __init__(self, input_channels: int, output_channels: int, dropout: float=0.1):
"""Instantiate the co-attention network. :param input_channels: The number of atom features. :param output_channels: The number of output features. :pa... | the_stack_v2_python_sparse | generated/test_AstraZeneca_chemicalx.py | jansel/pytorch-jit-paritybench | train | 35 |
c76fba554f512659a11a840dc3882b22a4bd8eef | [
"sizes = list(input.size())\nsizes[0] = total_batch_size\noutput = input.new_zeros(*sizes)\noutput.index_copy_(0, non_pad_indices, input)\nctx.save_for_backward(non_pad_indices)\nreturn output",
"non_pad_indices, = ctx.saved_tensors\ngrad_input = output_grads.index_select(0, non_pad_indices)\nreturn (grad_input, ... | <|body_start_0|>
sizes = list(input.size())
sizes[0] = total_batch_size
output = input.new_zeros(*sizes)
output.index_copy_(0, non_pad_indices, input)
ctx.save_for_backward(non_pad_indices)
return output
<|end_body_0|>
<|body_start_1|>
non_pad_indices, = ctx.save... | This function is kinda similar to rnn pad_packed_sequence It remaps nonpadded values for a (N-1)-d tensor into a (N)-d tensor | IndexCopy | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IndexCopy:
"""This function is kinda similar to rnn pad_packed_sequence It remaps nonpadded values for a (N-1)-d tensor into a (N)-d tensor"""
def forward(ctx, input, non_pad_indices, total_batch_size):
""":param ctx: :param input: 2D [bsz x ... ] bsz is the total number of elements ... | stack_v2_sparse_classes_10k_train_003289 | 45,662 | permissive | [
{
"docstring": ":param ctx: :param input: 2D [bsz x ... ] bsz is the total number of elements after unpadding :param non_pad_indices: bsz * seq_len :param total_batch_size: (int) bsz * seq_len (before unpadding) > bsz :return: In the forward pass we create a new zero tensor and copy the inputs into it based on ... | 2 | stack_v2_sparse_classes_30k_train_003667 | Implement the Python class `IndexCopy` described below.
Class description:
This function is kinda similar to rnn pad_packed_sequence It remaps nonpadded values for a (N-1)-d tensor into a (N)-d tensor
Method signatures and docstrings:
- def forward(ctx, input, non_pad_indices, total_batch_size): :param ctx: :param in... | Implement the Python class `IndexCopy` described below.
Class description:
This function is kinda similar to rnn pad_packed_sequence It remaps nonpadded values for a (N-1)-d tensor into a (N)-d tensor
Method signatures and docstrings:
- def forward(ctx, input, non_pad_indices, total_batch_size): :param ctx: :param in... | 5e1e424d0d9c2135a456e372a2ea9ee49de5bd2c | <|skeleton|>
class IndexCopy:
"""This function is kinda similar to rnn pad_packed_sequence It remaps nonpadded values for a (N-1)-d tensor into a (N)-d tensor"""
def forward(ctx, input, non_pad_indices, total_batch_size):
""":param ctx: :param input: 2D [bsz x ... ] bsz is the total number of elements ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class IndexCopy:
"""This function is kinda similar to rnn pad_packed_sequence It remaps nonpadded values for a (N-1)-d tensor into a (N)-d tensor"""
def forward(ctx, input, non_pad_indices, total_batch_size):
""":param ctx: :param input: 2D [bsz x ... ] bsz is the total number of elements after unpaddi... | the_stack_v2_python_sparse | pretrain_module/modeling_deltalm.py | quanpn90/NMTGMinor | train | 92 |
e2e02221f82041ec26f92af88c2f8c61deb22fa2 | [
"old_namespaced_oligotype = NamespacedOligotypesModel.query.filter((NamespacedOligotypesModel.namespace == namespaced_oligotype.namespace) & (NamespacedOligotypesModel.oligotype == namespaced_oligotype.oligotype)).first()\nif old_namespaced_oligotype:\n return (False, from_dict(NamespacedOligotype, old_namespace... | <|body_start_0|>
old_namespaced_oligotype = NamespacedOligotypesModel.query.filter((NamespacedOligotypesModel.namespace == namespaced_oligotype.namespace) & (NamespacedOligotypesModel.oligotype == namespaced_oligotype.oligotype)).first()
if old_namespaced_oligotype:
return (False, from_dict(... | A manager of Namespaced Oligotypes model. | NamespacesdOligotypeRepositoryManager | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NamespacesdOligotypeRepositoryManager:
"""A manager of Namespaced Oligotypes model."""
def get_or_create(namespaced_oligotype: NamespacedOligotype) -> Tuple[bool, NamespacedOligotype]:
"""Insert a single record into database. Args: namespaced_oligotype (NamespacedOligotype): A single... | stack_v2_sparse_classes_10k_train_003290 | 3,211 | no_license | [
{
"docstring": "Insert a single record into database. Args: namespaced_oligotype (NamespacedOligotype): A single namespaced oligotype entity. Returns: Tuple[bool, NamespacesdOligotype]: A boolean indicating if the namespace was created (True) or recovered from database (False), and a instance of the created nam... | 2 | stack_v2_sparse_classes_30k_test_000180 | Implement the Python class `NamespacesdOligotypeRepositoryManager` described below.
Class description:
A manager of Namespaced Oligotypes model.
Method signatures and docstrings:
- def get_or_create(namespaced_oligotype: NamespacedOligotype) -> Tuple[bool, NamespacedOligotype]: Insert a single record into database. A... | Implement the Python class `NamespacesdOligotypeRepositoryManager` described below.
Class description:
A manager of Namespaced Oligotypes model.
Method signatures and docstrings:
- def get_or_create(namespaced_oligotype: NamespacedOligotype) -> Tuple[bool, NamespacedOligotype]: Insert a single record into database. A... | 5d240fea783a453137c9a3697b67dae67b08a73d | <|skeleton|>
class NamespacesdOligotypeRepositoryManager:
"""A manager of Namespaced Oligotypes model."""
def get_or_create(namespaced_oligotype: NamespacedOligotype) -> Tuple[bool, NamespacedOligotype]:
"""Insert a single record into database. Args: namespaced_oligotype (NamespacedOligotype): A single... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class NamespacesdOligotypeRepositoryManager:
"""A manager of Namespaced Oligotypes model."""
def get_or_create(namespaced_oligotype: NamespacedOligotype) -> Tuple[bool, NamespacedOligotype]:
"""Insert a single record into database. Args: namespaced_oligotype (NamespacedOligotype): A single namespaced o... | the_stack_v2_python_sparse | src/adapters/repositories/oligotype_link.py | sgelias/blu | train | 0 |
71810d4ab61c3807d87baae1f7679e9739d71cff | [
"test_layer = talking_heads_attention.TalkingHeadsAttention(num_heads=12, key_size=64)\nfrom_tensor = tf.keras.Input(shape=(40, 80))\nto_tensor = tf.keras.Input(shape=(20, 80))\noutput = test_layer([from_tensor, to_tensor])\nself.assertEqual(output.shape.as_list(), [None, 40, 80])",
"test_layer = talking_heads_at... | <|body_start_0|>
test_layer = talking_heads_attention.TalkingHeadsAttention(num_heads=12, key_size=64)
from_tensor = tf.keras.Input(shape=(40, 80))
to_tensor = tf.keras.Input(shape=(20, 80))
output = test_layer([from_tensor, to_tensor])
self.assertEqual(output.shape.as_list(), [N... | MultiHeadAttentionTest | [
"MIT",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MultiHeadAttentionTest:
def test_non_masked_attention(self):
"""Test that the attention layer can be created without a mask tensor."""
<|body_0|>
def test_non_masked_self_attention(self):
"""Test with one input (self-attenntion) and no mask tensor."""
<|body_... | stack_v2_sparse_classes_10k_train_003291 | 4,090 | permissive | [
{
"docstring": "Test that the attention layer can be created without a mask tensor.",
"name": "test_non_masked_attention",
"signature": "def test_non_masked_attention(self)"
},
{
"docstring": "Test with one input (self-attenntion) and no mask tensor.",
"name": "test_non_masked_self_attention... | 4 | null | Implement the Python class `MultiHeadAttentionTest` described below.
Class description:
Implement the MultiHeadAttentionTest class.
Method signatures and docstrings:
- def test_non_masked_attention(self): Test that the attention layer can be created without a mask tensor.
- def test_non_masked_self_attention(self): T... | Implement the Python class `MultiHeadAttentionTest` described below.
Class description:
Implement the MultiHeadAttentionTest class.
Method signatures and docstrings:
- def test_non_masked_attention(self): Test that the attention layer can be created without a mask tensor.
- def test_non_masked_self_attention(self): T... | a115d918f6894a69586174653172be0b5d1de952 | <|skeleton|>
class MultiHeadAttentionTest:
def test_non_masked_attention(self):
"""Test that the attention layer can be created without a mask tensor."""
<|body_0|>
def test_non_masked_self_attention(self):
"""Test with one input (self-attenntion) and no mask tensor."""
<|body_... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class MultiHeadAttentionTest:
def test_non_masked_attention(self):
"""Test that the attention layer can be created without a mask tensor."""
test_layer = talking_heads_attention.TalkingHeadsAttention(num_heads=12, key_size=64)
from_tensor = tf.keras.Input(shape=(40, 80))
to_tensor = ... | the_stack_v2_python_sparse | models/official/nlp/modeling/layers/talking_heads_attention_test.py | finnickniu/tensorflow_object_detection_tflite | train | 60 | |
fe699ee0cbe2831fdfd71707a98ae51fba00b641 | [
"logging.info('## SETUP METHOD ##')\nlogging.info('# Initializing the webdriver.')\nself.ffprofile = self.create_ffprofile()\nself.driver = webdriver.Firefox(self.ffprofile)\nself.driver.maximize_window()\nself.driver.implicitly_wait(5)\nself.driver.get('http://the-internet.herokuapp.com/')",
"logging.info('## TE... | <|body_start_0|>
logging.info('## SETUP METHOD ##')
logging.info('# Initializing the webdriver.')
self.ffprofile = self.create_ffprofile()
self.driver = webdriver.Firefox(self.ffprofile)
self.driver.maximize_window()
self.driver.implicitly_wait(5)
self.driver.get(... | This class is for instantiating web driver instances. | DriverManagerFirefox | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DriverManagerFirefox:
"""This class is for instantiating web driver instances."""
def setUp(self):
"""This method is to instantiate the web driver instance."""
<|body_0|>
def tearDown(self):
"""This is teardown method. It is to capture the screenshots for failed ... | stack_v2_sparse_classes_10k_train_003292 | 3,946 | permissive | [
{
"docstring": "This method is to instantiate the web driver instance.",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "This is teardown method. It is to capture the screenshots for failed test cases, & to remove web driver object.",
"name": "tearDown",
"signature": "... | 4 | stack_v2_sparse_classes_30k_train_003729 | Implement the Python class `DriverManagerFirefox` described below.
Class description:
This class is for instantiating web driver instances.
Method signatures and docstrings:
- def setUp(self): This method is to instantiate the web driver instance.
- def tearDown(self): This is teardown method. It is to capture the sc... | Implement the Python class `DriverManagerFirefox` described below.
Class description:
This class is for instantiating web driver instances.
Method signatures and docstrings:
- def setUp(self): This method is to instantiate the web driver instance.
- def tearDown(self): This is teardown method. It is to capture the sc... | 65513cb85eccb1ae3fae4ac3625d0e6878720ec8 | <|skeleton|>
class DriverManagerFirefox:
"""This class is for instantiating web driver instances."""
def setUp(self):
"""This method is to instantiate the web driver instance."""
<|body_0|>
def tearDown(self):
"""This is teardown method. It is to capture the screenshots for failed ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class DriverManagerFirefox:
"""This class is for instantiating web driver instances."""
def setUp(self):
"""This method is to instantiate the web driver instance."""
logging.info('## SETUP METHOD ##')
logging.info('# Initializing the webdriver.')
self.ffprofile = self.create_ffp... | the_stack_v2_python_sparse | attic/2019/contributions-2019/open/mudaliar-yptu/PWAF/utility/drivermanager.py | Agriad/devops-course | train | 0 |
8fb7a4d6d30caf511926517ede2956aeb46c728c | [
"if not self.caller.location or not self.caller.location.allow_combat:\n self.msg(\"Can't fight here!\")\n raise InterruptCommand()",
"self.args = args = self.args.strip()\nself.lhs, self.rhs = ('', '')\nif not args:\n return\nif ' on ' in args:\n lhs, rhs = args.split(' on ', 1)\nelse:\n lhs, *rhs... | <|body_start_0|>
if not self.caller.location or not self.caller.location.allow_combat:
self.msg("Can't fight here!")
raise InterruptCommand()
<|end_body_0|>
<|body_start_1|>
self.args = args = self.args.strip()
self.lhs, self.rhs = ('', '')
if not args:
... | Parent class for all twitch-combat commnads. | _BaseTwitchCombatCommand | [
"BSD-3-Clause",
"LicenseRef-scancode-unknown-license-reference",
"CC-BY-4.0",
"CC-BY-3.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class _BaseTwitchCombatCommand:
"""Parent class for all twitch-combat commnads."""
def at_pre_command(self):
"""Called before parsing."""
<|body_0|>
def parse(self):
"""Handle parsing of most supported combat syntaxes (except stunts). <action> [<target>|<item>] or <act... | stack_v2_sparse_classes_10k_train_003293 | 18,175 | permissive | [
{
"docstring": "Called before parsing.",
"name": "at_pre_command",
"signature": "def at_pre_command(self)"
},
{
"docstring": "Handle parsing of most supported combat syntaxes (except stunts). <action> [<target>|<item>] or <action> <item> [on] <target> Use 'on' to differentiate if names/items hav... | 3 | stack_v2_sparse_classes_30k_train_001154 | Implement the Python class `_BaseTwitchCombatCommand` described below.
Class description:
Parent class for all twitch-combat commnads.
Method signatures and docstrings:
- def at_pre_command(self): Called before parsing.
- def parse(self): Handle parsing of most supported combat syntaxes (except stunts). <action> [<ta... | Implement the Python class `_BaseTwitchCombatCommand` described below.
Class description:
Parent class for all twitch-combat commnads.
Method signatures and docstrings:
- def at_pre_command(self): Called before parsing.
- def parse(self): Handle parsing of most supported combat syntaxes (except stunts). <action> [<ta... | b3ca58b5c1325a3bf57051dfe23560a08d2947b7 | <|skeleton|>
class _BaseTwitchCombatCommand:
"""Parent class for all twitch-combat commnads."""
def at_pre_command(self):
"""Called before parsing."""
<|body_0|>
def parse(self):
"""Handle parsing of most supported combat syntaxes (except stunts). <action> [<target>|<item>] or <act... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class _BaseTwitchCombatCommand:
"""Parent class for all twitch-combat commnads."""
def at_pre_command(self):
"""Called before parsing."""
if not self.caller.location or not self.caller.location.allow_combat:
self.msg("Can't fight here!")
raise InterruptCommand()
def... | the_stack_v2_python_sparse | evennia/contrib/tutorials/evadventure/combat_twitch.py | evennia/evennia | train | 1,781 |
eeb63cd79be481d770dd81c851b08af8896b5f78 | [
"for i, c in enumerate(self.children):\n if c in ('elif', 'if'):\n yield self.children[i + 1]",
"start_pos = node.start_pos\nfor check_node in reversed(list(self.get_test_nodes())):\n if check_node.start_pos < start_pos:\n if start_pos < check_node.end_pos:\n return None\n el... | <|body_start_0|>
for i, c in enumerate(self.children):
if c in ('elif', 'if'):
yield self.children[i + 1]
<|end_body_0|>
<|body_start_1|>
start_pos = node.start_pos
for check_node in reversed(list(self.get_test_nodes())):
if check_node.start_pos < start_p... | IfStmt | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference",
"Python-2.0",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IfStmt:
def get_test_nodes(self):
"""E.g. returns all the `test` nodes that are named as x, below: if x: pass elif x: pass"""
<|body_0|>
def get_corresponding_test_node(self, node):
"""Searches for the branch in which the node is and returns the corresponding test no... | stack_v2_sparse_classes_10k_train_003294 | 38,111 | permissive | [
{
"docstring": "E.g. returns all the `test` nodes that are named as x, below: if x: pass elif x: pass",
"name": "get_test_nodes",
"signature": "def get_test_nodes(self)"
},
{
"docstring": "Searches for the branch in which the node is and returns the corresponding test node (see function above). ... | 3 | stack_v2_sparse_classes_30k_train_000784 | Implement the Python class `IfStmt` described below.
Class description:
Implement the IfStmt class.
Method signatures and docstrings:
- def get_test_nodes(self): E.g. returns all the `test` nodes that are named as x, below: if x: pass elif x: pass
- def get_corresponding_test_node(self, node): Searches for the branch... | Implement the Python class `IfStmt` described below.
Class description:
Implement the IfStmt class.
Method signatures and docstrings:
- def get_test_nodes(self): E.g. returns all the `test` nodes that are named as x, below: if x: pass elif x: pass
- def get_corresponding_test_node(self, node): Searches for the branch... | f5042e35b945aded77b23470ead62d7eacefde92 | <|skeleton|>
class IfStmt:
def get_test_nodes(self):
"""E.g. returns all the `test` nodes that are named as x, below: if x: pass elif x: pass"""
<|body_0|>
def get_corresponding_test_node(self, node):
"""Searches for the branch in which the node is and returns the corresponding test no... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class IfStmt:
def get_test_nodes(self):
"""E.g. returns all the `test` nodes that are named as x, below: if x: pass elif x: pass"""
for i, c in enumerate(self.children):
if c in ('elif', 'if'):
yield self.children[i + 1]
def get_corresponding_test_node(self, node):
... | the_stack_v2_python_sparse | contrib/python/parso/py2/parso/python/tree.py | catboost/catboost | train | 8,012 | |
3bc51fd4e9886015bddf3648900f7dfb567a5d2c | [
"result = empty_result()\ntry:\n result['data'] = {'interface_status': get_interface_states(hostname)}\nexcept ValueError as e:\n return (empty_result('error', 'Could not get interface states, invalid input: {}'.format(e)), 400)\nexcept Exception as e:\n return (empty_result('error', 'Could not get interfa... | <|body_start_0|>
result = empty_result()
try:
result['data'] = {'interface_status': get_interface_states(hostname)}
except ValueError as e:
return (empty_result('error', 'Could not get interface states, invalid input: {}'.format(e)), 400)
except Exception as e:
... | InterfaceStatusApi | [
"BSD-2-Clause-Views",
"BSD-2-Clause",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InterfaceStatusApi:
def get(self, hostname):
"""List all interfaces status"""
<|body_0|>
def put(self, hostname):
"""Bounce selected interfaces by appling bounce-down/bounce-up template"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
result = empty_... | stack_v2_sparse_classes_10k_train_003295 | 15,267 | permissive | [
{
"docstring": "List all interfaces status",
"name": "get",
"signature": "def get(self, hostname)"
},
{
"docstring": "Bounce selected interfaces by appling bounce-down/bounce-up template",
"name": "put",
"signature": "def put(self, hostname)"
}
] | 2 | stack_v2_sparse_classes_30k_train_002931 | Implement the Python class `InterfaceStatusApi` described below.
Class description:
Implement the InterfaceStatusApi class.
Method signatures and docstrings:
- def get(self, hostname): List all interfaces status
- def put(self, hostname): Bounce selected interfaces by appling bounce-down/bounce-up template | Implement the Python class `InterfaceStatusApi` described below.
Class description:
Implement the InterfaceStatusApi class.
Method signatures and docstrings:
- def get(self, hostname): List all interfaces status
- def put(self, hostname): Bounce selected interfaces by appling bounce-down/bounce-up template
<|skeleto... | d755dfed69bebe0c7bea66ad1802cba2cd89fec8 | <|skeleton|>
class InterfaceStatusApi:
def get(self, hostname):
"""List all interfaces status"""
<|body_0|>
def put(self, hostname):
"""Bounce selected interfaces by appling bounce-down/bounce-up template"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class InterfaceStatusApi:
def get(self, hostname):
"""List all interfaces status"""
result = empty_result()
try:
result['data'] = {'interface_status': get_interface_states(hostname)}
except ValueError as e:
return (empty_result('error', 'Could not get interfac... | the_stack_v2_python_sparse | src/cnaas_nms/api/interface.py | SUNET/cnaas-nms | train | 67 | |
29f3e0e062ddc3c18932731cc60e0b00375b22bf | [
"res = super(cost_revaluation, self).default_get(cr, uid, fields, context=context)\naccount_data = self.pool.get('account.invoice').browse(cr, uid, context.get('active_id'), context=context)\nresult = []\nfor line in account_data.invoice_line:\n if line.product_id and line.prod_lot_id:\n result.append({'i... | <|body_start_0|>
res = super(cost_revaluation, self).default_get(cr, uid, fields, context=context)
account_data = self.pool.get('account.invoice').browse(cr, uid, context.get('active_id'), context=context)
result = []
for line in account_data.invoice_line:
if line.product_id ... | cost_revaluation | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class cost_revaluation:
def default_get(self, cr, uid, fields, context=None):
"""Get the default value from invoice line ---------------------------------------- @param self: The object pointer. @param cr: A database cursor @param uid: ID of the user currently logged in @param fields: A List o... | stack_v2_sparse_classes_10k_train_003296 | 6,683 | no_license | [
{
"docstring": "Get the default value from invoice line ---------------------------------------- @param self: The object pointer. @param cr: A database cursor @param uid: ID of the user currently logged in @param fields: A List of fields @param context: A standard dictionary @return: Return a dictionary which h... | 2 | stack_v2_sparse_classes_30k_train_005206 | Implement the Python class `cost_revaluation` described below.
Class description:
Implement the cost_revaluation class.
Method signatures and docstrings:
- def default_get(self, cr, uid, fields, context=None): Get the default value from invoice line ---------------------------------------- @param self: The object poi... | Implement the Python class `cost_revaluation` described below.
Class description:
Implement the cost_revaluation class.
Method signatures and docstrings:
- def default_get(self, cr, uid, fields, context=None): Get the default value from invoice line ---------------------------------------- @param self: The object poi... | f2b44a8af0e7bee87d52d258fca012bf44ca876f | <|skeleton|>
class cost_revaluation:
def default_get(self, cr, uid, fields, context=None):
"""Get the default value from invoice line ---------------------------------------- @param self: The object pointer. @param cr: A database cursor @param uid: ID of the user currently logged in @param fields: A List o... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class cost_revaluation:
def default_get(self, cr, uid, fields, context=None):
"""Get the default value from invoice line ---------------------------------------- @param self: The object pointer. @param cr: A database cursor @param uid: ID of the user currently logged in @param fields: A List of fields @para... | the_stack_v2_python_sparse | via_lot_valuation/wizard/cost_revaluation.py | eksotama/prln-via-custom-addons | train | 0 | |
5b393a001338ee30598d34b5fa07ad5a691e7e9b | [
"with SIMPLE_FILE_PATH.open() as auth_file:\n for line in auth_file.readlines():\n match = re.match('(^STEAM_[0,1]{1}:[0,1]{1}:[0-9]+)', line)\n if match:\n self.add(match.group(0))",
"if uniqueid in self:\n return True\nreturn False"
] | <|body_start_0|>
with SIMPLE_FILE_PATH.open() as auth_file:
for line in auth_file.readlines():
match = re.match('(^STEAM_[0,1]{1}:[0,1]{1}:[0-9]+)', line)
if match:
self.add(match.group(0))
<|end_body_0|>
<|body_start_1|>
if uniqueid in se... | Class used to determine if a player is authorized | _SimpleAuth | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class _SimpleAuth:
"""Class used to determine if a player is authorized"""
def _parse_admins(self):
"""Method used to get all uniqueids that are authorized on the server"""
<|body_0|>
def is_player_authorized(self, uniqueid, level, permission, flag):
"""Method used to ... | stack_v2_sparse_classes_10k_train_003297 | 2,351 | no_license | [
{
"docstring": "Method used to get all uniqueids that are authorized on the server",
"name": "_parse_admins",
"signature": "def _parse_admins(self)"
},
{
"docstring": "Method used to check if a player is authorized",
"name": "is_player_authorized",
"signature": "def is_player_authorized(... | 2 | stack_v2_sparse_classes_30k_train_006177 | Implement the Python class `_SimpleAuth` described below.
Class description:
Class used to determine if a player is authorized
Method signatures and docstrings:
- def _parse_admins(self): Method used to get all uniqueids that are authorized on the server
- def is_player_authorized(self, uniqueid, level, permission, f... | Implement the Python class `_SimpleAuth` described below.
Class description:
Class used to determine if a player is authorized
Method signatures and docstrings:
- def _parse_admins(self): Method used to get all uniqueids that are authorized on the server
- def is_player_authorized(self, uniqueid, level, permission, f... | b84df87f67ecb0fb2487e68e8b4b6bee3944f506 | <|skeleton|>
class _SimpleAuth:
"""Class used to determine if a player is authorized"""
def _parse_admins(self):
"""Method used to get all uniqueids that are authorized on the server"""
<|body_0|>
def is_player_authorized(self, uniqueid, level, permission, flag):
"""Method used to ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class _SimpleAuth:
"""Class used to determine if a player is authorized"""
def _parse_admins(self):
"""Method used to get all uniqueids that are authorized on the server"""
with SIMPLE_FILE_PATH.open() as auth_file:
for line in auth_file.readlines():
match = re.match... | the_stack_v2_python_sparse | addons/source-python/packages/source-python/auth/providers/simple.py | aurorapar/Source.Python | train | 0 |
006f8088a3c2309deb57ba249ae1c42861322f12 | [
"m = re.search(cls.direction_symbol_regex, s)\nif m:\n symbol = m.group(0)\n if symbol[0] == '<' and symbol[-1] == '>':\n return True\n return False\nelse:\n raise MalformattedReactionDirectionSymbolException('Check the directional symbol')",
"m = re.match(cls.symbol_regex, symbol)\nif m is Non... | <|body_start_0|>
m = re.search(cls.direction_symbol_regex, s)
if m:
symbol = m.group(0)
if symbol[0] == '<' and symbol[-1] == '>':
return True
return False
else:
raise MalformattedReactionDirectionSymbolException('Check the directio... | An implementation of ExpressionParser for reading strings and forming | StringExpressionParser | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StringExpressionParser:
"""An implementation of ExpressionParser for reading strings and forming"""
def _is_bidirectional(cls, s):
"""Determines if a reaction is bi-directional based on the symbol between the reactants and products. :param s: a string which is formatted according to ... | stack_v2_sparse_classes_10k_train_003298 | 8,250 | no_license | [
{
"docstring": "Determines if a reaction is bi-directional based on the symbol between the reactants and products. :param s: a string which is formatted according to our conventions :return: True or False",
"name": "_is_bidirectional",
"signature": "def _is_bidirectional(cls, s)"
},
{
"docstring... | 5 | stack_v2_sparse_classes_30k_train_000057 | Implement the Python class `StringExpressionParser` described below.
Class description:
An implementation of ExpressionParser for reading strings and forming
Method signatures and docstrings:
- def _is_bidirectional(cls, s): Determines if a reaction is bi-directional based on the symbol between the reactants and prod... | Implement the Python class `StringExpressionParser` described below.
Class description:
An implementation of ExpressionParser for reading strings and forming
Method signatures and docstrings:
- def _is_bidirectional(cls, s): Determines if a reaction is bi-directional based on the symbol between the reactants and prod... | 4a625b0b00040a06f2b52ac74d60c636012f1dd4 | <|skeleton|>
class StringExpressionParser:
"""An implementation of ExpressionParser for reading strings and forming"""
def _is_bidirectional(cls, s):
"""Determines if a reaction is bi-directional based on the symbol between the reactants and products. :param s: a string which is formatted according to ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class StringExpressionParser:
"""An implementation of ExpressionParser for reading strings and forming"""
def _is_bidirectional(cls, s):
"""Determines if a reaction is bi-directional based on the symbol between the reactants and products. :param s: a string which is formatted according to our conventio... | the_stack_v2_python_sparse | src/parsers.py | blawney/mycalc | train | 0 |
01e8bea3c5104e64f7901f6e7a0a6688bb959d12 | [
"super().__init__()\nimport sklearn\nimport sklearn.svm\nself.model = sklearn.svm.NuSVC",
"specs = super(NuSVC, cls).getInputSpecification()\nspecs.description = 'The \\\\xmlNode{NuSVC} \\\\textit{Nu-Support Vector Classification} is an Nu-Support Vector Classification.\\n It is very si... | <|body_start_0|>
super().__init__()
import sklearn
import sklearn.svm
self.model = sklearn.svm.NuSVC
<|end_body_0|>
<|body_start_1|>
specs = super(NuSVC, cls).getInputSpecification()
specs.description = 'The \\xmlNode{NuSVC} \\textit{Nu-Support Vector Classification} is ... | Support Vector Classifier | NuSVC | [
"Apache-2.0",
"LicenseRef-scancode-warranty-disclaimer",
"BSD-2-Clause",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NuSVC:
"""Support Vector Classifier"""
def __init__(self):
"""Constructor that will appropriately initialize a supervised learning object @ In, None @ Out, None"""
<|body_0|>
def getInputSpecification(cls):
"""Method to get a reference to a class that specifies t... | stack_v2_sparse_classes_10k_train_003299 | 9,261 | permissive | [
{
"docstring": "Constructor that will appropriately initialize a supervised learning object @ In, None @ Out, None",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Method to get a reference to a class that specifies the input data for class cls. @ In, cls, the class for... | 3 | null | Implement the Python class `NuSVC` described below.
Class description:
Support Vector Classifier
Method signatures and docstrings:
- def __init__(self): Constructor that will appropriately initialize a supervised learning object @ In, None @ Out, None
- def getInputSpecification(cls): Method to get a reference to a c... | Implement the Python class `NuSVC` described below.
Class description:
Support Vector Classifier
Method signatures and docstrings:
- def __init__(self): Constructor that will appropriately initialize a supervised learning object @ In, None @ Out, None
- def getInputSpecification(cls): Method to get a reference to a c... | 2b16e7aa3325fe84cab2477947a951414c635381 | <|skeleton|>
class NuSVC:
"""Support Vector Classifier"""
def __init__(self):
"""Constructor that will appropriately initialize a supervised learning object @ In, None @ Out, None"""
<|body_0|>
def getInputSpecification(cls):
"""Method to get a reference to a class that specifies t... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class NuSVC:
"""Support Vector Classifier"""
def __init__(self):
"""Constructor that will appropriately initialize a supervised learning object @ In, None @ Out, None"""
super().__init__()
import sklearn
import sklearn.svm
self.model = sklearn.svm.NuSVC
def getInput... | the_stack_v2_python_sparse | ravenframework/SupervisedLearning/ScikitLearn/SVM/NuSVC.py | idaholab/raven | train | 201 |
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