blob_id stringlengths 40 40 | bodies listlengths 2 6 | bodies_text stringlengths 196 7.73k | class_docstring stringlengths 0 700 | class_name stringlengths 1 86 | detected_licenses listlengths 0 45 | format_version stringclasses 1
value | full_text stringlengths 378 8.64k | id stringlengths 44 44 | length_bytes int64 505 50k | license_type stringclasses 2
values | methods listlengths 2 6 | n_methods int64 2 6 | original_id stringlengths 38 40 ⌀ | prompt stringlengths 153 4.88k | prompted_full_text stringlengths 565 12.5k | revision_id stringlengths 40 40 | skeleton stringlengths 162 5.05k | snapshot_name stringclasses 1
value | snapshot_source_dir stringclasses 1
value | snapshot_total_rows int64 75.8k 75.8k | solution stringlengths 242 8.3k | source stringclasses 1
value | source_path stringlengths 4 177 | source_repo stringlengths 6 110 | split stringclasses 1
value | star_events_count int64 0 209k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
e022d1c38b7ae99228b04a60e8d822d739f5c3fb | [
"try:\n uid = force_text(urlsafe_base64_decode(attrs['uidb64']))\n user = User.objects.get(pk=uid)\nexcept (TypeError, ValueError, OverflowError, User.DoesNotExist):\n user = None\nif not user or not account_activation_token.check_token(user, attrs['token']):\n raise serializers.ValidationError('Invalid... | <|body_start_0|>
try:
uid = force_text(urlsafe_base64_decode(attrs['uidb64']))
user = User.objects.get(pk=uid)
except (TypeError, ValueError, OverflowError, User.DoesNotExist):
user = None
if not user or not account_activation_token.check_token(user, attrs['to... | Serializer for account confirmation feature. Confirmation link http(s)://domain/uidb64/token/ is generated after successful registration. uidb64: user id in base64 encoding token: user token created after registration | AccountConfirmationSerializer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AccountConfirmationSerializer:
"""Serializer for account confirmation feature. Confirmation link http(s)://domain/uidb64/token/ is generated after successful registration. uidb64: user id in base64 encoding token: user token created after registration"""
def validate(self, attrs):
""... | stack_v2_sparse_classes_75kplus_train_002500 | 6,320 | no_license | [
{
"docstring": "Validate uidb64 and token are bound to the same user.",
"name": "validate",
"signature": "def validate(self, attrs)"
},
{
"docstring": "Setting is_active field to True, make the account active.",
"name": "save",
"signature": "def save(self, **kwargs)"
}
] | 2 | stack_v2_sparse_classes_30k_train_050313 | Implement the Python class `AccountConfirmationSerializer` described below.
Class description:
Serializer for account confirmation feature. Confirmation link http(s)://domain/uidb64/token/ is generated after successful registration. uidb64: user id in base64 encoding token: user token created after registration
Metho... | Implement the Python class `AccountConfirmationSerializer` described below.
Class description:
Serializer for account confirmation feature. Confirmation link http(s)://domain/uidb64/token/ is generated after successful registration. uidb64: user id in base64 encoding token: user token created after registration
Metho... | 4cbf70e66c49087498b6bf58971ad58b8330994d | <|skeleton|>
class AccountConfirmationSerializer:
"""Serializer for account confirmation feature. Confirmation link http(s)://domain/uidb64/token/ is generated after successful registration. uidb64: user id in base64 encoding token: user token created after registration"""
def validate(self, attrs):
""... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AccountConfirmationSerializer:
"""Serializer for account confirmation feature. Confirmation link http(s)://domain/uidb64/token/ is generated after successful registration. uidb64: user id in base64 encoding token: user token created after registration"""
def validate(self, attrs):
"""Validate uid... | the_stack_v2_python_sparse | ETWeb/accounts/api/serializers.py | adarsharegmi/employeeMS | train | 1 |
d1b44ca52c4023bd2e955b51da5a13d1a4488c55 | [
"self.name = 'ec'\nself._n_e = n_e\nself.targets = targets\nself.ssa = ssa\nspectral_pars = get_spectral_parameters_from_n_e(self._n_e, backend='sherpa', modelname=self.name)\nemission_region_pars = make_emission_region_parameters_dict('ec', backend='sherpa', modelname=self.name)\ntargets_pars = make_targets_parame... | <|body_start_0|>
self.name = 'ec'
self._n_e = n_e
self.targets = targets
self.ssa = ssa
spectral_pars = get_spectral_parameters_from_n_e(self._n_e, backend='sherpa', modelname=self.name)
emission_region_pars = make_emission_region_parameters_dict('ec', backend='sherpa', m... | ExternalComptonRegriddableModel1D | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ExternalComptonRegriddableModel1D:
def __init__(self, n_e, targets, ssa=False):
"""sherpa wrapper for a source emitting Synchrotron, SSC, and EC on a list of targets. Parameters ---------- n_e : `~agnpy.spectra.ElectronDistribution` electron distribution to be used for this modelling tar... | stack_v2_sparse_classes_75kplus_train_002501 | 14,627 | permissive | [
{
"docstring": "sherpa wrapper for a source emitting Synchrotron, SSC, and EC on a list of targets. Parameters ---------- n_e : `~agnpy.spectra.ElectronDistribution` electron distribution to be used for this modelling targets : list of strings [\"blr\", \"dt\"] targets to be considered for external Compton typi... | 4 | stack_v2_sparse_classes_30k_train_050529 | Implement the Python class `ExternalComptonRegriddableModel1D` described below.
Class description:
Implement the ExternalComptonRegriddableModel1D class.
Method signatures and docstrings:
- def __init__(self, n_e, targets, ssa=False): sherpa wrapper for a source emitting Synchrotron, SSC, and EC on a list of targets.... | Implement the Python class `ExternalComptonRegriddableModel1D` described below.
Class description:
Implement the ExternalComptonRegriddableModel1D class.
Method signatures and docstrings:
- def __init__(self, n_e, targets, ssa=False): sherpa wrapper for a source emitting Synchrotron, SSC, and EC on a list of targets.... | b72c94fa5c205284e0e3ee7a37072f3ccfc97c7b | <|skeleton|>
class ExternalComptonRegriddableModel1D:
def __init__(self, n_e, targets, ssa=False):
"""sherpa wrapper for a source emitting Synchrotron, SSC, and EC on a list of targets. Parameters ---------- n_e : `~agnpy.spectra.ElectronDistribution` electron distribution to be used for this modelling tar... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ExternalComptonRegriddableModel1D:
def __init__(self, n_e, targets, ssa=False):
"""sherpa wrapper for a source emitting Synchrotron, SSC, and EC on a list of targets. Parameters ---------- n_e : `~agnpy.spectra.ElectronDistribution` electron distribution to be used for this modelling targets : list of... | the_stack_v2_python_sparse | agnpy/fit/sherpa_wrapper.py | cosimoNigro/agnpy | train | 49 | |
e1880ad05e6eb8e04a90d77deebb111cd5ce871c | [
"self.ago_string = listing.get('config_specified_ago_string')\nself.city = listing.get('city')\nself.cluster_expansion_url = listing.get('cluster_expansion_url')\nself.company = listing.get('company_name')\nself.description = listing.get('description_clip') if listing.get('description_clip') else ''\nself.descripti... | <|body_start_0|>
self.ago_string = listing.get('config_specified_ago_string')
self.city = listing.get('city')
self.cluster_expansion_url = listing.get('cluster_expansion_url')
self.company = listing.get('company_name')
self.description = listing.get('description_clip') if listing... | Job object to store job information. | Job | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Job:
"""Job object to store job information."""
def __init__(self, listing, bridge_search_query):
"""Initialize a Job object."""
<|body_0|>
def is_new(self):
"""Returns true if job is less than a specified number of days old."""
<|body_1|>
<|end_skeleton... | stack_v2_sparse_classes_75kplus_train_002502 | 5,331 | no_license | [
{
"docstring": "Initialize a Job object.",
"name": "__init__",
"signature": "def __init__(self, listing, bridge_search_query)"
},
{
"docstring": "Returns true if job is less than a specified number of days old.",
"name": "is_new",
"signature": "def is_new(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_026487 | Implement the Python class `Job` described below.
Class description:
Job object to store job information.
Method signatures and docstrings:
- def __init__(self, listing, bridge_search_query): Initialize a Job object.
- def is_new(self): Returns true if job is less than a specified number of days old. | Implement the Python class `Job` described below.
Class description:
Job object to store job information.
Method signatures and docstrings:
- def __init__(self, listing, bridge_search_query): Initialize a Job object.
- def is_new(self): Returns true if job is less than a specified number of days old.
<|skeleton|>
cl... | da3073eec6d676dfe0164502b80d2a1c75e89575 | <|skeleton|>
class Job:
"""Job object to store job information."""
def __init__(self, listing, bridge_search_query):
"""Initialize a Job object."""
<|body_0|>
def is_new(self):
"""Returns true if job is less than a specified number of days old."""
<|body_1|>
<|end_skeleton... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Job:
"""Job object to store job information."""
def __init__(self, listing, bridge_search_query):
"""Initialize a Job object."""
self.ago_string = listing.get('config_specified_ago_string')
self.city = listing.get('city')
self.cluster_expansion_url = listing.get('cluster_e... | the_stack_v2_python_sparse | web-serpng/code/serpng/jobs/services/search/job.py | alyago/django-web | train | 0 |
b03d8e77889d78d07471cbc646ced16102682277 | [
"value = '<div>'\nclase = 'actions'\nurl_cont = './' + str(obj.id_tipo_item)\nid_tipo = UrlParser.parse_id(request.url, 'tipositems')\nif id_tipo:\n url_cont = '../' + str(obj.id_tipo_item)\nif UrlParser.parse_nombre(request.url, 'post_buscar'):\n url_cont = '../' + str(obj.id_tipo_item)\npp = PoseePermiso('r... | <|body_start_0|>
value = '<div>'
clase = 'actions'
url_cont = './' + str(obj.id_tipo_item)
id_tipo = UrlParser.parse_id(request.url, 'tipositems')
if id_tipo:
url_cont = '../' + str(obj.id_tipo_item)
if UrlParser.parse_nombre(request.url, 'post_buscar'):
... | TipoItemTableFiller | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TipoItemTableFiller:
def __actions__(self, obj):
"""Links de acciones para un registro dado"""
<|body_0|>
def _do_get_provider_count_and_objs(self, id_fase=None, id_tipo=None, **kw):
"""Se muestra la lista de tipos de item para la fase en cuestión"""
<|body_1... | stack_v2_sparse_classes_75kplus_train_002503 | 21,979 | no_license | [
{
"docstring": "Links de acciones para un registro dado",
"name": "__actions__",
"signature": "def __actions__(self, obj)"
},
{
"docstring": "Se muestra la lista de tipos de item para la fase en cuestión",
"name": "_do_get_provider_count_and_objs",
"signature": "def _do_get_provider_coun... | 2 | stack_v2_sparse_classes_30k_train_021314 | Implement the Python class `TipoItemTableFiller` described below.
Class description:
Implement the TipoItemTableFiller class.
Method signatures and docstrings:
- def __actions__(self, obj): Links de acciones para un registro dado
- def _do_get_provider_count_and_objs(self, id_fase=None, id_tipo=None, **kw): Se muestr... | Implement the Python class `TipoItemTableFiller` described below.
Class description:
Implement the TipoItemTableFiller class.
Method signatures and docstrings:
- def __actions__(self, obj): Links de acciones para un registro dado
- def _do_get_provider_count_and_objs(self, id_fase=None, id_tipo=None, **kw): Se muestr... | 997531e130d1951b483f4a6a67f2df7467cd9fd1 | <|skeleton|>
class TipoItemTableFiller:
def __actions__(self, obj):
"""Links de acciones para un registro dado"""
<|body_0|>
def _do_get_provider_count_and_objs(self, id_fase=None, id_tipo=None, **kw):
"""Se muestra la lista de tipos de item para la fase en cuestión"""
<|body_1... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TipoItemTableFiller:
def __actions__(self, obj):
"""Links de acciones para un registro dado"""
value = '<div>'
clase = 'actions'
url_cont = './' + str(obj.id_tipo_item)
id_tipo = UrlParser.parse_id(request.url, 'tipositems')
if id_tipo:
url_cont = '.... | the_stack_v2_python_sparse | lpm/controllers/tipoitem.py | jorgeramirez/LPM | train | 1 | |
6a68650d966d969a7c94ce5fd26414d6f7fe2cf7 | [
"times = -(-len(B) // len(A))\nfor i in range(2):\n if B in A * (times + i):\n return times + i\nreturn -1",
"al = len(A)\nbl = len(B)\nif bl <= al:\n if len(A.replace(B, '')) != al:\n return 1\n elif len((A * 2).replace(B, '')) != 2 * al:\n return 2\n else:\n return -1\nel... | <|body_start_0|>
times = -(-len(B) // len(A))
for i in range(2):
if B in A * (times + i):
return times + i
return -1
<|end_body_0|>
<|body_start_1|>
al = len(A)
bl = len(B)
if bl <= al:
if len(A.replace(B, '')) != al:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def repeatedStringMatch_1(self, A, B):
""":type A: str :type B: str :rtype: int 206ms"""
<|body_0|>
def repeatedStringMatch(self, A, B):
""":type A: str :type B: str :rtype: int 499ms"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
times =... | stack_v2_sparse_classes_75kplus_train_002504 | 1,654 | no_license | [
{
"docstring": ":type A: str :type B: str :rtype: int 206ms",
"name": "repeatedStringMatch_1",
"signature": "def repeatedStringMatch_1(self, A, B)"
},
{
"docstring": ":type A: str :type B: str :rtype: int 499ms",
"name": "repeatedStringMatch",
"signature": "def repeatedStringMatch(self, ... | 2 | stack_v2_sparse_classes_30k_val_002879 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def repeatedStringMatch_1(self, A, B): :type A: str :type B: str :rtype: int 206ms
- def repeatedStringMatch(self, A, B): :type A: str :type B: str :rtype: int 499ms | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def repeatedStringMatch_1(self, A, B): :type A: str :type B: str :rtype: int 206ms
- def repeatedStringMatch(self, A, B): :type A: str :type B: str :rtype: int 499ms
<|skeleton|... | 679a2b246b8b6bb7fc55ed1c8096d3047d6d4461 | <|skeleton|>
class Solution:
def repeatedStringMatch_1(self, A, B):
""":type A: str :type B: str :rtype: int 206ms"""
<|body_0|>
def repeatedStringMatch(self, A, B):
""":type A: str :type B: str :rtype: int 499ms"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def repeatedStringMatch_1(self, A, B):
""":type A: str :type B: str :rtype: int 206ms"""
times = -(-len(B) // len(A))
for i in range(2):
if B in A * (times + i):
return times + i
return -1
def repeatedStringMatch(self, A, B):
"... | the_stack_v2_python_sparse | RepeatedStringMatch_686.py | 953250587/leetcode-python | train | 2 | |
04b36993816d3dc4dd4677e53d65f2e4e1bfc992 | [
"display = NanpyCharDisplay(self.mudpi, config)\nif display:\n node = self.extension.nodes[config['node']]\n if node:\n display.node = node\n self.add_component(display)\n else:\n raise MudPiError(f\"Nanpy node {config['node']} not found trying to connect {config['key']}.\")\nreturn Tr... | <|body_start_0|>
display = NanpyCharDisplay(self.mudpi, config)
if display:
node = self.extension.nodes[config['node']]
if node:
display.node = node
self.add_component(display)
else:
raise MudPiError(f"Nanpy node {config... | Interface | [
"BSD-4-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Interface:
def load(self, config):
"""Load Nanpy display components from configs"""
<|body_0|>
def validate(self, config):
"""Validate the Nanpy display config"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
display = NanpyCharDisplay(self.mudpi, co... | stack_v2_sparse_classes_75kplus_train_002505 | 5,336 | permissive | [
{
"docstring": "Load Nanpy display components from configs",
"name": "load",
"signature": "def load(self, config)"
},
{
"docstring": "Validate the Nanpy display config",
"name": "validate",
"signature": "def validate(self, config)"
}
] | 2 | stack_v2_sparse_classes_30k_train_047269 | Implement the Python class `Interface` described below.
Class description:
Implement the Interface class.
Method signatures and docstrings:
- def load(self, config): Load Nanpy display components from configs
- def validate(self, config): Validate the Nanpy display config | Implement the Python class `Interface` described below.
Class description:
Implement the Interface class.
Method signatures and docstrings:
- def load(self, config): Load Nanpy display components from configs
- def validate(self, config): Validate the Nanpy display config
<|skeleton|>
class Interface:
def load(... | fb206b1136f529c7197f1e6b29629ed05630d377 | <|skeleton|>
class Interface:
def load(self, config):
"""Load Nanpy display components from configs"""
<|body_0|>
def validate(self, config):
"""Validate the Nanpy display config"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Interface:
def load(self, config):
"""Load Nanpy display components from configs"""
display = NanpyCharDisplay(self.mudpi, config)
if display:
node = self.extension.nodes[config['node']]
if node:
display.node = node
self.add_compo... | the_stack_v2_python_sparse | mudpi/extensions/nanpy/char_display.py | mistasp0ck/mudpi-core | train | 0 | |
d50c138a63f88fd0f10ea7701b215792431be025 | [
"if os.path.exists(file):\n self.file = file\nelse:\n sys.exit('Invalid or missing file.')\nself.delimiter = delimiter",
"counter = 0\ncounter_snv = 0\ncounter_indel = 0\ncounter_indel_triplet = 0\nwith open(self.file) as file_p:\n variant_reader = csv.DictReader(file_p, delimiter=self.delimiter)\n fo... | <|body_start_0|>
if os.path.exists(file):
self.file = file
else:
sys.exit('Invalid or missing file.')
self.delimiter = delimiter
<|end_body_0|>
<|body_start_1|>
counter = 0
counter_snv = 0
counter_indel = 0
counter_indel_triplet = 0
... | The Variants class to handle the variants.tsv file. | Variants | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Variants:
"""The Variants class to handle the variants.tsv file."""
def __init__(self, file, delimiter='\t'):
"""Initialize the object with the variants.tsv file"""
<|body_0|>
def get_total_variants(self, indel=True):
"""A method that parses the iVar variants fil... | stack_v2_sparse_classes_75kplus_train_002506 | 2,703 | permissive | [
{
"docstring": "Initialize the object with the variants.tsv file",
"name": "__init__",
"signature": "def __init__(self, file, delimiter='\\t')"
},
{
"docstring": "A method that parses the iVar variants file and returns the total number of variants. Arguments: * indel: a boolean to determine whet... | 2 | stack_v2_sparse_classes_30k_train_016776 | Implement the Python class `Variants` described below.
Class description:
The Variants class to handle the variants.tsv file.
Method signatures and docstrings:
- def __init__(self, file, delimiter='\t'): Initialize the object with the variants.tsv file
- def get_total_variants(self, indel=True): A method that parses ... | Implement the Python class `Variants` described below.
Class description:
The Variants class to handle the variants.tsv file.
Method signatures and docstrings:
- def __init__(self, file, delimiter='\t'): Initialize the object with the variants.tsv file
- def get_total_variants(self, indel=True): A method that parses ... | 9f81f4bda3d1581e666fedebb9f31b066ceefb70 | <|skeleton|>
class Variants:
"""The Variants class to handle the variants.tsv file."""
def __init__(self, file, delimiter='\t'):
"""Initialize the object with the variants.tsv file"""
<|body_0|>
def get_total_variants(self, indel=True):
"""A method that parses the iVar variants fil... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Variants:
"""The Variants class to handle the variants.tsv file."""
def __init__(self, file, delimiter='\t'):
"""Initialize the object with the variants.tsv file"""
if os.path.exists(file):
self.file = file
else:
sys.exit('Invalid or missing file.')
... | the_stack_v2_python_sparse | parser/ncov/parser/Variants.py | connor-lab/ncov-tools | train | 3 |
17a66a715d80643625a3a165067f4002c28641f4 | [
"self.username = username\nself.password = password\nself.et_build_version = et_build_version\nself.title = title\nself.space = space\nself.parent_page = parent_page",
"generator = auto_testing_CI.CI3_module.confluence.generate_build_report_for_all_testings.GenerateAllReports(self.username, self.password, self.et... | <|body_start_0|>
self.username = username
self.password = password
self.et_build_version = et_build_version
self.title = title
self.space = space
self.parent_page = parent_page
<|end_body_0|>
<|body_start_1|>
generator = auto_testing_CI.CI3_module.confluence.gene... | Collect all testing reports and update them to the Confluence | CollectAllReportsAndUpdateToConfluence | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CollectAllReportsAndUpdateToConfluence:
"""Collect all testing reports and update them to the Confluence"""
def __init__(self, username, password, et_build_version, title, space, parent_page):
""":param username: string username to connect with Confulence then create/update testing r... | stack_v2_sparse_classes_75kplus_train_002507 | 1,844 | no_license | [
{
"docstring": ":param username: string username to connect with Confulence then create/update testing reports :param password: string password to the above username: :param et_build_version: string the current Errata Tool version of the build, like 3354 and so on :param title: string the title of the testing r... | 2 | stack_v2_sparse_classes_30k_train_016137 | Implement the Python class `CollectAllReportsAndUpdateToConfluence` described below.
Class description:
Collect all testing reports and update them to the Confluence
Method signatures and docstrings:
- def __init__(self, username, password, et_build_version, title, space, parent_page): :param username: string usernam... | Implement the Python class `CollectAllReportsAndUpdateToConfluence` described below.
Class description:
Collect all testing reports and update them to the Confluence
Method signatures and docstrings:
- def __init__(self, username, password, et_build_version, title, space, parent_page): :param username: string usernam... | 4d9e3e68c826ea44a6ddbbf72f18d54e68f6aa43 | <|skeleton|>
class CollectAllReportsAndUpdateToConfluence:
"""Collect all testing reports and update them to the Confluence"""
def __init__(self, username, password, et_build_version, title, space, parent_page):
""":param username: string username to connect with Confulence then create/update testing r... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CollectAllReportsAndUpdateToConfluence:
"""Collect all testing reports and update them to the Confluence"""
def __init__(self, username, password, et_build_version, title, space, parent_page):
""":param username: string username to connect with Confulence then create/update testing reports :param... | the_stack_v2_python_sparse | CI3_module/confluence/collect_all_reports_and_update_to_confluence.py | testcara/CI_3 | train | 0 |
be630830af53ef6855daaba6fb9247e991ad63a9 | [
"request = self.context['request']\npath = self.context['view'].kwargs.get('path')\nreturn reverse('filebrowserpath', request=request, kwargs={'path': path})",
"request = self.context['request']\npath = self.context['view'].kwargs.get('path')\nreturn reverse('filebrowserpathfile-list', request=request, kwargs={'p... | <|body_start_0|>
request = self.context['request']
path = self.context['view'].kwargs.get('path')
return reverse('filebrowserpath', request=request, kwargs={'path': path})
<|end_body_0|>
<|body_start_1|>
request = self.context['request']
path = self.context['view'].kwargs.get('p... | FileBrowserPathSerializer | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FileBrowserPathSerializer:
def get_url(self, obj):
"""Overriden to get the url of the path."""
<|body_0|>
def get_files(self, obj):
"""Custom method to get the hyperlink to the list of files directly under the path."""
<|body_1|>
<|end_skeleton|>
<|body_sta... | stack_v2_sparse_classes_75kplus_train_002508 | 2,034 | permissive | [
{
"docstring": "Overriden to get the url of the path.",
"name": "get_url",
"signature": "def get_url(self, obj)"
},
{
"docstring": "Custom method to get the hyperlink to the list of files directly under the path.",
"name": "get_files",
"signature": "def get_files(self, obj)"
}
] | 2 | stack_v2_sparse_classes_30k_train_024825 | Implement the Python class `FileBrowserPathSerializer` described below.
Class description:
Implement the FileBrowserPathSerializer class.
Method signatures and docstrings:
- def get_url(self, obj): Overriden to get the url of the path.
- def get_files(self, obj): Custom method to get the hyperlink to the list of file... | Implement the Python class `FileBrowserPathSerializer` described below.
Class description:
Implement the FileBrowserPathSerializer class.
Method signatures and docstrings:
- def get_url(self, obj): Overriden to get the url of the path.
- def get_files(self, obj): Custom method to get the hyperlink to the list of file... | 20d3eedf20610af9182f6cca8db8f0b3546b5336 | <|skeleton|>
class FileBrowserPathSerializer:
def get_url(self, obj):
"""Overriden to get the url of the path."""
<|body_0|>
def get_files(self, obj):
"""Custom method to get the hyperlink to the list of files directly under the path."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class FileBrowserPathSerializer:
def get_url(self, obj):
"""Overriden to get the url of the path."""
request = self.context['request']
path = self.context['view'].kwargs.get('path')
return reverse('filebrowserpath', request=request, kwargs={'path': path})
def get_files(self, obj... | the_stack_v2_python_sparse | chris_backend/filebrowser/serializers.py | FNNDSC/ChRIS_ultron_backEnd | train | 36 | |
92858f4c6c8b2f078572f95837dccfd0bf4b6cfa | [
"self.component_name = component_name\nself.component_type = component_type\nself.indent = None if ndjson else 4\nself.separators = (',', ':') if ndjson else (', ', ': ')\nsuper(StructuredFormatter, self).__init__()",
"data: Dict[str, Union[str, List[str]]] = {'timestamp': datetime.utcnow().isoformat(), 'message'... | <|body_start_0|>
self.component_name = component_name
self.component_type = component_type
self.indent = None if ndjson else 4
self.separators = (',', ':') if ndjson else (', ', ': ')
super(StructuredFormatter, self).__init__()
<|end_body_0|>
<|body_start_1|>
data: Dict[... | StructuredFormatter is a Formatter for structured logging. LogRecord objects are formatted as JSON. Under the default configuration, a StructuredFormatter will render these as NDJSON (http://ndjson.org/) | StructuredFormatter | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StructuredFormatter:
"""StructuredFormatter is a Formatter for structured logging. LogRecord objects are formatted as JSON. Under the default configuration, a StructuredFormatter will render these as NDJSON (http://ndjson.org/)"""
def __init__(self, component_name: Optional[str]=None, compon... | stack_v2_sparse_classes_75kplus_train_002509 | 3,202 | permissive | [
{
"docstring": "Create a StructuredFormatter object. component_name: Optional[str] - The name of the software component component_type: Optional[str] - The type of the software component ndjson: bool - Output as NDJSON; defaults to True.",
"name": "__init__",
"signature": "def __init__(self, component_n... | 2 | stack_v2_sparse_classes_30k_train_032555 | Implement the Python class `StructuredFormatter` described below.
Class description:
StructuredFormatter is a Formatter for structured logging. LogRecord objects are formatted as JSON. Under the default configuration, a StructuredFormatter will render these as NDJSON (http://ndjson.org/)
Method signatures and docstri... | Implement the Python class `StructuredFormatter` described below.
Class description:
StructuredFormatter is a Formatter for structured logging. LogRecord objects are formatted as JSON. Under the default configuration, a StructuredFormatter will render these as NDJSON (http://ndjson.org/)
Method signatures and docstri... | 12719efa84be2281debe98a18c69bbe7a6d0f399 | <|skeleton|>
class StructuredFormatter:
"""StructuredFormatter is a Formatter for structured logging. LogRecord objects are formatted as JSON. Under the default configuration, a StructuredFormatter will render these as NDJSON (http://ndjson.org/)"""
def __init__(self, component_name: Optional[str]=None, compon... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class StructuredFormatter:
"""StructuredFormatter is a Formatter for structured logging. LogRecord objects are formatted as JSON. Under the default configuration, a StructuredFormatter will render these as NDJSON (http://ndjson.org/)"""
def __init__(self, component_name: Optional[str]=None, component_type: Opt... | the_stack_v2_python_sparse | lta/log_format.py | blinkdog/lta | train | 0 |
57afabfaf156351e8508aa1f86d0a664f6549914 | [
"if not root:\n return False\nif not root.left and (not root.right):\n return root.val == sum\nreturn self.hasPathSum(root.left, sum - root.val) or self.hasPathSum(root.right, sum - root.val)",
"if not root:\n return False\nstack = [(root.val, root)]\nwhile stack:\n value, node = stack.pop()\n if n... | <|body_start_0|>
if not root:
return False
if not root.left and (not root.right):
return root.val == sum
return self.hasPathSum(root.left, sum - root.val) or self.hasPathSum(root.right, sum - root.val)
<|end_body_0|>
<|body_start_1|>
if not root:
retu... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def hasPathSum(self, root: TreeNode, sum: int) -> bool:
"""递归 到某个节点时，判断其是否是叶子节点并且值是否等于sum 若不是，则递归判断左右子树 注： 递归判断时，需要减去当前root的值"""
<|body_0|>
def hasPathSum_1(self, root: TreeNode, sum: int) -> bool:
"""迭代 每次把之前节点的值加起来"""
<|body_1|>
<|end_skeleton|>
... | stack_v2_sparse_classes_75kplus_train_002510 | 1,824 | no_license | [
{
"docstring": "递归 到某个节点时，判断其是否是叶子节点并且值是否等于sum 若不是，则递归判断左右子树 注： 递归判断时，需要减去当前root的值",
"name": "hasPathSum",
"signature": "def hasPathSum(self, root: TreeNode, sum: int) -> bool"
},
{
"docstring": "迭代 每次把之前节点的值加起来",
"name": "hasPathSum_1",
"signature": "def hasPathSum_1(self, root: TreeNod... | 2 | stack_v2_sparse_classes_30k_train_005809 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def hasPathSum(self, root: TreeNode, sum: int) -> bool: 递归 到某个节点时，判断其是否是叶子节点并且值是否等于sum 若不是，则递归判断左右子树 注： 递归判断时，需要减去当前root的值
- def hasPathSum_1(self, root: TreeNode, sum: int) -> b... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def hasPathSum(self, root: TreeNode, sum: int) -> bool: 递归 到某个节点时，判断其是否是叶子节点并且值是否等于sum 若不是，则递归判断左右子树 注： 递归判断时，需要减去当前root的值
- def hasPathSum_1(self, root: TreeNode, sum: int) -> b... | 3508e1ce089131b19603c3206aab4cf43023bb19 | <|skeleton|>
class Solution:
def hasPathSum(self, root: TreeNode, sum: int) -> bool:
"""递归 到某个节点时，判断其是否是叶子节点并且值是否等于sum 若不是，则递归判断左右子树 注： 递归判断时，需要减去当前root的值"""
<|body_0|>
def hasPathSum_1(self, root: TreeNode, sum: int) -> bool:
"""迭代 每次把之前节点的值加起来"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def hasPathSum(self, root: TreeNode, sum: int) -> bool:
"""递归 到某个节点时，判断其是否是叶子节点并且值是否等于sum 若不是，则递归判断左右子树 注： 递归判断时，需要减去当前root的值"""
if not root:
return False
if not root.left and (not root.right):
return root.val == sum
return self.hasPathSum(root... | the_stack_v2_python_sparse | algorithm/leetcode/tree/17-路径总和.py | lxconfig/UbuntuCode_bak | train | 0 | |
e295d5f0cdad55195150c6f0cff1042453777252 | [
"if self.iterations in ['infinite']:\n while True:\n project = self.implement(project=project, **kwargs)\nelse:\n for iteration in range(self.iterations):\n project = self.implement(project=project, **kwargs)\nreturn project",
"if self.parameters:\n parameters = self.parameters\n paramet... | <|body_start_0|>
if self.iterations in ['infinite']:
while True:
project = self.implement(project=project, **kwargs)
else:
for iteration in range(self.iterations):
project = self.implement(project=project, **kwargs)
return project
<|end_bod... | Base class for parts of a sourdough Workflow. Args: name (str): designates the name of a class instance that is used for internal referencing throughout siMpLify. For example, if a siMpLify instance needs options from a Settings instance, 'name' should match the appropriate section name in a Settings instance. Defaults... | SimpleProcess | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SimpleProcess:
"""Base class for parts of a sourdough Workflow. Args: name (str): designates the name of a class instance that is used for internal referencing throughout siMpLify. For example, if a siMpLify instance needs options from a Settings instance, 'name' should match the appropriate sect... | stack_v2_sparse_classes_75kplus_train_002511 | 32,679 | permissive | [
{
"docstring": "[summary] Args: project (sourdough.Project): [description] Returns: sourdough.Project: [description]",
"name": "execute",
"signature": "def execute(self, project: sourdough.Project, **kwargs) -> sourdough.Project"
},
{
"docstring": "[summary] Args: project (sourdough.Project): [d... | 2 | stack_v2_sparse_classes_30k_train_049109 | Implement the Python class `SimpleProcess` described below.
Class description:
Base class for parts of a sourdough Workflow. Args: name (str): designates the name of a class instance that is used for internal referencing throughout siMpLify. For example, if a siMpLify instance needs options from a Settings instance, '... | Implement the Python class `SimpleProcess` described below.
Class description:
Base class for parts of a sourdough Workflow. Args: name (str): designates the name of a class instance that is used for internal referencing throughout siMpLify. For example, if a siMpLify instance needs options from a Settings instance, '... | 5302da8bf4944ac518d22cc37c181e5a09baaabe | <|skeleton|>
class SimpleProcess:
"""Base class for parts of a sourdough Workflow. Args: name (str): designates the name of a class instance that is used for internal referencing throughout siMpLify. For example, if a siMpLify instance needs options from a Settings instance, 'name' should match the appropriate sect... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SimpleProcess:
"""Base class for parts of a sourdough Workflow. Args: name (str): designates the name of a class instance that is used for internal referencing throughout siMpLify. For example, if a siMpLify instance needs options from a Settings instance, 'name' should match the appropriate section name in a... | the_stack_v2_python_sparse | simplify/core/components.py | WithPrecedent/simplify | train | 1 |
07b96c93f87a7ee435316625171e7f7271168ba5 | [
"super().__init__()\nself.attention = AttentionLayer(config)\nself.conv = ConvLayer(config)\nself.classify_layer = nn.Linear(config.qa_conv_out_channel * 3, 2, bias=True)",
"embedded_value = self.attention(x, token_type_ids)\nconcat_output = self.conv(embedded_value)\nlogits = self.classify_layer(concat_output)\n... | <|body_start_0|>
super().__init__()
self.attention = AttentionLayer(config)
self.conv = ConvLayer(config)
self.classify_layer = nn.Linear(config.qa_conv_out_channel * 3, 2, bias=True)
<|end_body_0|>
<|body_start_1|>
embedded_value = self.attention(x, token_type_ids)
conc... | QA conv head with attention | QAConvHeadWithAttention | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class QAConvHeadWithAttention:
"""QA conv head with attention"""
def __init__(self, config):
"""Args: config (ModelArguments): ModelArguments"""
<|body_0|>
def forward(self, x, token_type_ids):
"""Args: x (torch.Tensor): Head input token_type_ids (torch.Tensor): Token ... | stack_v2_sparse_classes_75kplus_train_002512 | 2,582 | permissive | [
{
"docstring": "Args: config (ModelArguments): ModelArguments",
"name": "__init__",
"signature": "def __init__(self, config)"
},
{
"docstring": "Args: x (torch.Tensor): Head input token_type_ids (torch.Tensor): Token type ids of input_ids Returns: torch.Tensor: output logits (batch_size * max_se... | 2 | stack_v2_sparse_classes_30k_train_048236 | Implement the Python class `QAConvHeadWithAttention` described below.
Class description:
QA conv head with attention
Method signatures and docstrings:
- def __init__(self, config): Args: config (ModelArguments): ModelArguments
- def forward(self, x, token_type_ids): Args: x (torch.Tensor): Head input token_type_ids (... | Implement the Python class `QAConvHeadWithAttention` described below.
Class description:
QA conv head with attention
Method signatures and docstrings:
- def __init__(self, config): Args: config (ModelArguments): ModelArguments
- def forward(self, x, token_type_ids): Args: x (torch.Tensor): Head input token_type_ids (... | ea60d7a7b0f22c9e2e3b71d1d80cc2f00805e3fa | <|skeleton|>
class QAConvHeadWithAttention:
"""QA conv head with attention"""
def __init__(self, config):
"""Args: config (ModelArguments): ModelArguments"""
<|body_0|>
def forward(self, x, token_type_ids):
"""Args: x (torch.Tensor): Head input token_type_ids (torch.Tensor): Token ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class QAConvHeadWithAttention:
"""QA conv head with attention"""
def __init__(self, config):
"""Args: config (ModelArguments): ModelArguments"""
super().__init__()
self.attention = AttentionLayer(config)
self.conv = ConvLayer(config)
self.classify_layer = nn.Linear(confi... | the_stack_v2_python_sparse | solution/reader/architectures/modeling_heads.py | boostcampaitech2/mrc-level2-nlp-14 | train | 7 |
df47a704453146077e9bead3fea13a260001fa80 | [
"requested_size = Size(0, 0)\nfor child in children:\n requested_size |= child.requested_size\nreturn requested_size",
"for child in cells:\n cell_size = SizeAllocation((0, 0), allocated_size.size)\n child.allocateSize(cell_size)"
] | <|body_start_0|>
requested_size = Size(0, 0)
for child in children:
requested_size |= child.requested_size
return requested_size
<|end_body_0|>
<|body_start_1|>
for child in cells:
cell_size = SizeAllocation((0, 0), allocated_size.size)
child.allocate... | A WindowLayout manages only one cell and sets its position to (0, 0). The idea of a window is that the children they contain have their position relative to that window and not the screen or anything else. The WindowLayout layout is made for Bin objects: objects that have only one cell. Therefore, the position of the c... | WindowLayout | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WindowLayout:
"""A WindowLayout manages only one cell and sets its position to (0, 0). The idea of a window is that the children they contain have their position relative to that window and not the screen or anything else. The WindowLayout layout is made for Bin objects: objects that have only on... | stack_v2_sparse_classes_75kplus_train_002513 | 1,173 | no_license | [
{
"docstring": "Return the max.",
"name": "requestSize",
"signature": "def requestSize(self, children)"
},
{
"docstring": "Windows subtract their position from the child's position. As a result, the position of the child is always (0, 0).",
"name": "allocateSize",
"signature": "def alloc... | 2 | null | Implement the Python class `WindowLayout` described below.
Class description:
A WindowLayout manages only one cell and sets its position to (0, 0). The idea of a window is that the children they contain have their position relative to that window and not the screen or anything else. The WindowLayout layout is made for... | Implement the Python class `WindowLayout` described below.
Class description:
A WindowLayout manages only one cell and sets its position to (0, 0). The idea of a window is that the children they contain have their position relative to that window and not the screen or anything else. The WindowLayout layout is made for... | 69cab98eed820c52e5e7e99dd3abe67286821e68 | <|skeleton|>
class WindowLayout:
"""A WindowLayout manages only one cell and sets its position to (0, 0). The idea of a window is that the children they contain have their position relative to that window and not the screen or anything else. The WindowLayout layout is made for Bin objects: objects that have only on... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class WindowLayout:
"""A WindowLayout manages only one cell and sets its position to (0, 0). The idea of a window is that the children they contain have their position relative to that window and not the screen or anything else. The WindowLayout layout is made for Bin objects: objects that have only one cell. There... | the_stack_v2_python_sparse | src/pynguin/layout/windowlayout.py | Niriel/pynguin | train | 1 |
369a3bda6190d22bc2b60b448833673d54ca405d | [
"self.key = key\nself._set_key_parms(['type'])\nself._set_prhb_parms(['type'])",
"if 'conf' not in self.__dict__:\n self.conf = self.get_view_obj(self.key)\nreturn self.conf.get('type')"
] | <|body_start_0|>
self.key = key
self._set_key_parms(['type'])
self._set_prhb_parms(['type'])
<|end_body_0|>
<|body_start_1|>
if 'conf' not in self.__dict__:
self.conf = self.get_view_obj(self.key)
return self.conf.get('type')
<|end_body_1|>
| WorkFlowEvalConfig | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WorkFlowEvalConfig:
def __init__(self, key=None):
"""init key variable :param key: :return:"""
<|body_0|>
def get_eval_type(self):
"""get eval type ( regression, classification.. ) :return:"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.key = ... | stack_v2_sparse_classes_75kplus_train_002514 | 632 | permissive | [
{
"docstring": "init key variable :param key: :return:",
"name": "__init__",
"signature": "def __init__(self, key=None)"
},
{
"docstring": "get eval type ( regression, classification.. ) :return:",
"name": "get_eval_type",
"signature": "def get_eval_type(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_054393 | Implement the Python class `WorkFlowEvalConfig` described below.
Class description:
Implement the WorkFlowEvalConfig class.
Method signatures and docstrings:
- def __init__(self, key=None): init key variable :param key: :return:
- def get_eval_type(self): get eval type ( regression, classification.. ) :return: | Implement the Python class `WorkFlowEvalConfig` described below.
Class description:
Implement the WorkFlowEvalConfig class.
Method signatures and docstrings:
- def __init__(self, key=None): init key variable :param key: :return:
- def get_eval_type(self): get eval type ( regression, classification.. ) :return:
<|ske... | 6ad2fbc7384e4dbe7e3e63bdb44c8ce0387f4b7f | <|skeleton|>
class WorkFlowEvalConfig:
def __init__(self, key=None):
"""init key variable :param key: :return:"""
<|body_0|>
def get_eval_type(self):
"""get eval type ( regression, classification.. ) :return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class WorkFlowEvalConfig:
def __init__(self, key=None):
"""init key variable :param key: :return:"""
self.key = key
self._set_key_parms(['type'])
self._set_prhb_parms(['type'])
def get_eval_type(self):
"""get eval type ( regression, classification.. ) :return:"""
... | the_stack_v2_python_sparse | master/workflow/evalconf/workflow_evalconf.py | yurimkoo/tensormsa | train | 1 | |
86a23761fe225c0ed5b4ff994425ba711939678e | [
"self.name = 'ext_grad'\nself.scaler = scaler\nself.batch_size = batch_size",
"grads = mainloop.grads\n'\\n for p, g in grads.items():\\n grads[p] = g / self.batch_size\\n g_norm = 0.\\n for g in grads.values():\\n g_norm += (g**2).sum()\\n '\ng_norm = 0.0\nfor p,... | <|body_start_0|>
self.name = 'ext_grad'
self.scaler = scaler
self.batch_size = batch_size
<|end_body_0|>
<|body_start_1|>
grads = mainloop.grads
'\n for p, g in grads.items():\n grads[p] = g / self.batch_size\n g_norm = 0.\n for g in grads.values(... | GradientClipping | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GradientClipping:
def __init__(self, scaler=5, batch_size=1):
""".. todo:: WRITEME"""
<|body_0|>
def exe(self, mainloop):
""".. todo:: WRITEME"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.name = 'ext_grad'
self.scaler = scaler
... | stack_v2_sparse_classes_75kplus_train_002515 | 8,905 | no_license | [
{
"docstring": ".. todo:: WRITEME",
"name": "__init__",
"signature": "def __init__(self, scaler=5, batch_size=1)"
},
{
"docstring": ".. todo:: WRITEME",
"name": "exe",
"signature": "def exe(self, mainloop)"
}
] | 2 | stack_v2_sparse_classes_30k_train_028345 | Implement the Python class `GradientClipping` described below.
Class description:
Implement the GradientClipping class.
Method signatures and docstrings:
- def __init__(self, scaler=5, batch_size=1): .. todo:: WRITEME
- def exe(self, mainloop): .. todo:: WRITEME | Implement the Python class `GradientClipping` described below.
Class description:
Implement the GradientClipping class.
Method signatures and docstrings:
- def __init__(self, scaler=5, batch_size=1): .. todo:: WRITEME
- def exe(self, mainloop): .. todo:: WRITEME
<|skeleton|>
class GradientClipping:
def __init__... | 94fe4208f6450d603d37e5a376dc85d988c9f639 | <|skeleton|>
class GradientClipping:
def __init__(self, scaler=5, batch_size=1):
""".. todo:: WRITEME"""
<|body_0|>
def exe(self, mainloop):
""".. todo:: WRITEME"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class GradientClipping:
def __init__(self, scaler=5, batch_size=1):
""".. todo:: WRITEME"""
self.name = 'ext_grad'
self.scaler = scaler
self.batch_size = batch_size
def exe(self, mainloop):
""".. todo:: WRITEME"""
grads = mainloop.grads
'\n for p, ... | the_stack_v2_python_sparse | cle/train/ext.py | kyunghyuncho/cle | train | 1 | |
4e4983b22a77a1b1b2e49d0b769a275e4683f201 | [
"if len(lipids) != len(ref_rt) or len(lipids) != len(meas_rt):\n m = 'RTCalibration: __init__: lipids, ref_rt, and meas_rt must all be the same length ({}, {}, {})'\n raise ValueError(m.format(len(lipids), len(ref_rt), len(meas_rt)))\nself.meas_rt, self.ref_rt, self.lipids = (list(t) for t in zip(*sorted(zip(... | <|body_start_0|>
if len(lipids) != len(ref_rt) or len(lipids) != len(meas_rt):
m = 'RTCalibration: __init__: lipids, ref_rt, and meas_rt must all be the same length ({}, {}, {})'
raise ValueError(m.format(len(lipids), len(ref_rt), len(meas_rt)))
self.meas_rt, self.ref_rt, self.li... | RTCalibration description: An object for performing HILIC retention time calibration | RTCalibration | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RTCalibration:
"""RTCalibration description: An object for performing HILIC retention time calibration"""
def __init__(self, lipids, meas_rt, ref_rt):
"""RTCalibration.__init__ description: Stores lists of lipid calibrants and their reference/measured retention times, lists are sorte... | stack_v2_sparse_classes_75kplus_train_002516 | 5,954 | permissive | [
{
"docstring": "RTCalibration.__init__ description: Stores lists of lipid calibrants and their reference/measured retention times, lists are sorted together by measured retention time parameters: lipids (list(str)) -- lipid calibrants meas_rt (list(float)) -- measured retention times ref_rt (list(float)) -- ref... | 4 | stack_v2_sparse_classes_30k_val_002295 | Implement the Python class `RTCalibration` described below.
Class description:
RTCalibration description: An object for performing HILIC retention time calibration
Method signatures and docstrings:
- def __init__(self, lipids, meas_rt, ref_rt): RTCalibration.__init__ description: Stores lists of lipid calibrants and ... | Implement the Python class `RTCalibration` described below.
Class description:
RTCalibration description: An object for performing HILIC retention time calibration
Method signatures and docstrings:
- def __init__(self, lipids, meas_rt, ref_rt): RTCalibration.__init__ description: Stores lists of lipid calibrants and ... | c7c3b72d4549a1a9937f287f3b314eff8e7ed054 | <|skeleton|>
class RTCalibration:
"""RTCalibration description: An object for performing HILIC retention time calibration"""
def __init__(self, lipids, meas_rt, ref_rt):
"""RTCalibration.__init__ description: Stores lists of lipid calibrants and their reference/measured retention times, lists are sorte... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class RTCalibration:
"""RTCalibration description: An object for performing HILIC retention time calibration"""
def __init__(self, lipids, meas_rt, ref_rt):
"""RTCalibration.__init__ description: Stores lists of lipid calibrants and their reference/measured retention times, lists are sorted together by... | the_stack_v2_python_sparse | lipydomics/identification/rt_calibration.py | kaitlin-rempfert/lipydomics | train | 0 |
f04b963678034be216f3d1ca4e27e56e795926cb | [
"for track_data_sample in data_samples:\n video_data_samples = track_data_sample['video_data_samples']\n ori_video_len = video_data_samples[0].ori_video_length\n if ori_video_len == len(video_data_samples):\n self.process_video(video_data_samples)\n else:\n self.process_image(video_data_sa... | <|body_start_0|>
for track_data_sample in data_samples:
video_data_samples = track_data_sample['video_data_samples']
ori_video_len = video_data_samples[0].ori_video_length
if ori_video_len == len(video_data_samples):
self.process_video(video_data_samples)
... | Base class for a metric in video task. The metric first processes each batch of data_samples and predictions, and appends the processed results to the results list. Then it collects all results together from all ranks if distributed training is used. Finally, it computes the metrics of the entire dataset. A subclass of... | BaseVideoMetric | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BaseVideoMetric:
"""Base class for a metric in video task. The metric first processes each batch of data_samples and predictions, and appends the processed results to the results list. Then it collects all results together from all ranks if distributed training is used. Finally, it computes the m... | stack_v2_sparse_classes_75kplus_train_002517 | 6,513 | permissive | [
{
"docstring": "Process one batch of data samples and predictions. The processed results should be stored in ``self.results``, which will be used to compute the metrics when all batches have been processed. Args: data_batch (dict): A batch of data from the dataloader. data_samples (Sequence[dict]): A batch of d... | 2 | stack_v2_sparse_classes_30k_train_012686 | Implement the Python class `BaseVideoMetric` described below.
Class description:
Base class for a metric in video task. The metric first processes each batch of data_samples and predictions, and appends the processed results to the results list. Then it collects all results together from all ranks if distributed train... | Implement the Python class `BaseVideoMetric` described below.
Class description:
Base class for a metric in video task. The metric first processes each batch of data_samples and predictions, and appends the processed results to the results list. Then it collects all results together from all ranks if distributed train... | f78af7785ada87f1ced75a2313746e4ba3149760 | <|skeleton|>
class BaseVideoMetric:
"""Base class for a metric in video task. The metric first processes each batch of data_samples and predictions, and appends the processed results to the results list. Then it collects all results together from all ranks if distributed training is used. Finally, it computes the m... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class BaseVideoMetric:
"""Base class for a metric in video task. The metric first processes each batch of data_samples and predictions, and appends the processed results to the results list. Then it collects all results together from all ranks if distributed training is used. Finally, it computes the metrics of the... | the_stack_v2_python_sparse | mmdet/evaluation/metrics/base_video_metric.py | wencheng256/mmdetection | train | 0 |
631de2942d6f0b78ea75799a7cdf87ae27958f39 | [
"super().__init__()\nif not isinstance(volumes, Volumes):\n raise ValueError(\"'volumes' have to be an instance of the 'Volumes' class.\")\nself._volumes = volumes\nself._sample_mode = sample_mode",
"world2local = self._volumes.get_world_to_local_coords_transform().get_matrix()\ndirections_transform_matrix = e... | <|body_start_0|>
super().__init__()
if not isinstance(volumes, Volumes):
raise ValueError("'volumes' have to be an instance of the 'Volumes' class.")
self._volumes = volumes
self._sample_mode = sample_mode
<|end_body_0|>
<|body_start_1|>
world2local = self._volumes.g... | A module to sample a batch of volumes `Volumes` at 3D points sampled along projection rays. | VolumeSampler | [
"MIT",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VolumeSampler:
"""A module to sample a batch of volumes `Volumes` at 3D points sampled along projection rays."""
def __init__(self, volumes: Volumes, sample_mode: str='bilinear') -> None:
"""Args: volumes: An instance of the `Volumes` class representing a batch of volumes that are be... | stack_v2_sparse_classes_75kplus_train_002518 | 17,111 | permissive | [
{
"docstring": "Args: volumes: An instance of the `Volumes` class representing a batch of volumes that are being rendered. sample_mode: Defines the algorithm used to sample the volumetric voxel grid. Can be either \"bilinear\" or \"nearest\".",
"name": "__init__",
"signature": "def __init__(self, volume... | 3 | stack_v2_sparse_classes_30k_train_015072 | Implement the Python class `VolumeSampler` described below.
Class description:
A module to sample a batch of volumes `Volumes` at 3D points sampled along projection rays.
Method signatures and docstrings:
- def __init__(self, volumes: Volumes, sample_mode: str='bilinear') -> None: Args: volumes: An instance of the `V... | Implement the Python class `VolumeSampler` described below.
Class description:
A module to sample a batch of volumes `Volumes` at 3D points sampled along projection rays.
Method signatures and docstrings:
- def __init__(self, volumes: Volumes, sample_mode: str='bilinear') -> None: Args: volumes: An instance of the `V... | a3d99cab6bf5eb69be8d5eb48895da6edd859565 | <|skeleton|>
class VolumeSampler:
"""A module to sample a batch of volumes `Volumes` at 3D points sampled along projection rays."""
def __init__(self, volumes: Volumes, sample_mode: str='bilinear') -> None:
"""Args: volumes: An instance of the `Volumes` class representing a batch of volumes that are be... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class VolumeSampler:
"""A module to sample a batch of volumes `Volumes` at 3D points sampled along projection rays."""
def __init__(self, volumes: Volumes, sample_mode: str='bilinear') -> None:
"""Args: volumes: An instance of the `Volumes` class representing a batch of volumes that are being rendered.... | the_stack_v2_python_sparse | pytorch3d/renderer/implicit/renderer.py | facebookresearch/pytorch3d | train | 7,964 |
2e063e64cb40c8bb17694cfa47e4dd61338e6d70 | [
"self.value_list = value_list\nself.function = function\nself.name = name if isinstance(name, str) else str(name)",
"if self.function.value == 1:\n return self.get_truth_or(restaurant)\nelif self.function.value == 0:\n return self.get_truth_and(restaurant)\nelif self.function.value == -1:\n if self.value... | <|body_start_0|>
self.value_list = value_list
self.function = function
self.name = name if isinstance(name, str) else str(name)
<|end_body_0|>
<|body_start_1|>
if self.function.value == 1:
return self.get_truth_or(restaurant)
elif self.function.value == 0:
... | Feature | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Feature:
def __init__(self, name, value_list: list, function: Function):
"""Initialises a new Feature that can be used as antecedent for an Implication. A Feature has multiple FeatureValues or Features that are united with a Function (logical operator) An example of a Feature is: A && B,... | stack_v2_sparse_classes_75kplus_train_002519 | 16,699 | no_license | [
{
"docstring": "Initialises a new Feature that can be used as antecedent for an Implication. A Feature has multiple FeatureValues or Features that are united with a Function (logical operator) An example of a Feature is: A && B, where A/B can be a Feature or a FeatureValue Parameters ---------- name : str the n... | 4 | null | Implement the Python class `Feature` described below.
Class description:
Implement the Feature class.
Method signatures and docstrings:
- def __init__(self, name, value_list: list, function: Function): Initialises a new Feature that can be used as antecedent for an Implication. A Feature has multiple FeatureValues or... | Implement the Python class `Feature` described below.
Class description:
Implement the Feature class.
Method signatures and docstrings:
- def __init__(self, name, value_list: list, function: Function): Initialises a new Feature that can be used as antecedent for an Implication. A Feature has multiple FeatureValues or... | 152027e4be258f77cb082a5c5a3cc72013c93ca4 | <|skeleton|>
class Feature:
def __init__(self, name, value_list: list, function: Function):
"""Initialises a new Feature that can be used as antecedent for an Implication. A Feature has multiple FeatureValues or Features that are united with a Function (logical operator) An example of a Feature is: A && B,... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Feature:
def __init__(self, name, value_list: list, function: Function):
"""Initialises a new Feature that can be used as antecedent for an Implication. A Feature has multiple FeatureValues or Features that are united with a Function (logical operator) An example of a Feature is: A && B, where A/B can... | the_stack_v2_python_sparse | implication_classes.py | GuidoBekkers/textClassifier | train | 1 | |
ace172f63a77ad562b78c539a092ae3791b8ae7d | [
"if name == 'BaseModel':\n return super(PropertiedClassWithDjango, cls).__new__(cls, name, bases, attrs)\nnew_class = super(PropertiedClassWithDjango, cls).__new__(cls, name, bases, attrs)\nnew_class._meta = ModelOptions(new_class)\nnew_class.objects = ModelManager(new_class)\nnew_class._default_manager = new_cl... | <|body_start_0|>
if name == 'BaseModel':
return super(PropertiedClassWithDjango, cls).__new__(cls, name, bases, attrs)
new_class = super(PropertiedClassWithDjango, cls).__new__(cls, name, bases, attrs)
new_class._meta = ModelOptions(new_class)
new_class.objects = ModelManager... | Metaclass for the combined Django + App Engine model class. This metaclass inherits from db.PropertiedClass in the appengine library. This metaclass has two additional purposes: 1) Register each model class created with Django (the parent class will take care of registering it with the appengine libraries). 2) Add the ... | PropertiedClassWithDjango | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PropertiedClassWithDjango:
"""Metaclass for the combined Django + App Engine model class. This metaclass inherits from db.PropertiedClass in the appengine library. This metaclass has two additional purposes: 1) Register each model class created with Django (the parent class will take care of regi... | stack_v2_sparse_classes_75kplus_train_002520 | 6,077 | permissive | [
{
"docstring": "Creates a combined appengine and Django model. The resulting model will be known to both the appengine libraries and Django.",
"name": "__new__",
"signature": "def __new__(cls, name, bases, attrs)"
},
{
"docstring": "Initialises the list of Django properties. This method takes ca... | 2 | stack_v2_sparse_classes_30k_train_028370 | Implement the Python class `PropertiedClassWithDjango` described below.
Class description:
Metaclass for the combined Django + App Engine model class. This metaclass inherits from db.PropertiedClass in the appengine library. This metaclass has two additional purposes: 1) Register each model class created with Django (... | Implement the Python class `PropertiedClassWithDjango` described below.
Class description:
Metaclass for the combined Django + App Engine model class. This metaclass inherits from db.PropertiedClass in the appengine library. This metaclass has two additional purposes: 1) Register each model class created with Django (... | f7582ac0944932455e99cf54643c553e7641225c | <|skeleton|>
class PropertiedClassWithDjango:
"""Metaclass for the combined Django + App Engine model class. This metaclass inherits from db.PropertiedClass in the appengine library. This metaclass has two additional purposes: 1) Register each model class created with Django (the parent class will take care of regi... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PropertiedClassWithDjango:
"""Metaclass for the combined Django + App Engine model class. This metaclass inherits from db.PropertiedClass in the appengine library. This metaclass has two additional purposes: 1) Register each model class created with Django (the parent class will take care of registering it wi... | the_stack_v2_python_sparse | appengine_django/models.py | babybunny/rebuildingtogethercaptain | train | 5 |
4a0978c96700ce9bed0eab343272b9747366f6a1 | [
"cleaned_data = self.cleaned_data\nitem = cleaned_data.get('item')\nlocation = cleaned_data.get('location')\ntype = cleaned_data.get('type')\nif not item:\n raise forms.ValidationError(self.error_messages['item_error'], code='item_error')\nif not location:\n raise forms.ValidationError(self.error_messages['lo... | <|body_start_0|>
cleaned_data = self.cleaned_data
item = cleaned_data.get('item')
location = cleaned_data.get('location')
type = cleaned_data.get('type')
if not item:
raise forms.ValidationError(self.error_messages['item_error'], code='item_error')
if not loca... | Form for items' movements | ItemMoveForm | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ItemMoveForm:
"""Form for items' movements"""
def clean_quantity(self):
"""Method to clean quantity"""
<|body_0|>
def __init__(self, *args, **kwargs):
"""Method for initial values and functions"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
cle... | stack_v2_sparse_classes_75kplus_train_002521 | 8,200 | permissive | [
{
"docstring": "Method to clean quantity",
"name": "clean_quantity",
"signature": "def clean_quantity(self)"
},
{
"docstring": "Method for initial values and functions",
"name": "__init__",
"signature": "def __init__(self, *args, **kwargs)"
}
] | 2 | stack_v2_sparse_classes_30k_train_026974 | Implement the Python class `ItemMoveForm` described below.
Class description:
Form for items' movements
Method signatures and docstrings:
- def clean_quantity(self): Method to clean quantity
- def __init__(self, *args, **kwargs): Method for initial values and functions | Implement the Python class `ItemMoveForm` described below.
Class description:
Form for items' movements
Method signatures and docstrings:
- def clean_quantity(self): Method to clean quantity
- def __init__(self, *args, **kwargs): Method for initial values and functions
<|skeleton|>
class ItemMoveForm:
"""Form fo... | f3f8354bf164fcfe86d597cdbc28b0e3b7b73bd1 | <|skeleton|>
class ItemMoveForm:
"""Form for items' movements"""
def clean_quantity(self):
"""Method to clean quantity"""
<|body_0|>
def __init__(self, *args, **kwargs):
"""Method for initial values and functions"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ItemMoveForm:
"""Form for items' movements"""
def clean_quantity(self):
"""Method to clean quantity"""
cleaned_data = self.cleaned_data
item = cleaned_data.get('item')
location = cleaned_data.get('location')
type = cleaned_data.get('type')
if not item:
... | the_stack_v2_python_sparse | seshat/stock/forms.py | XecusM/SESHAT | train | 0 |
9427d6600bbc0fed4ba2078f66cff819d9ba124a | [
"self.npart = npart\nself.ndim = ndim\nself.bounds = bounds",
"if self.bounds == None:\n self.swarm = np.random.random((self.npart, self.ndim))\nelse:\n self.swarm = np.zeros((self.npart, self.ndim))\n lo = self.bounds.Lower()\n hi = self.bounds.Upper()\n for i in range(self.npart):\n for j ... | <|body_start_0|>
self.npart = npart
self.ndim = ndim
self.bounds = bounds
<|end_body_0|>
<|body_start_1|>
if self.bounds == None:
self.swarm = np.random.random((self.npart, self.ndim))
else:
self.swarm = np.zeros((self.npart, self.ndim))
lo = ... | Initialize a swarm uniformly | RandomInitializer | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RandomInitializer:
"""Initialize a swarm uniformly"""
def __init__(self, npart=10, ndim=3, bounds=None):
"""Constructor"""
<|body_0|>
def InitializeSwarm(self):
"""Return a randomly initialized swarm"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_75kplus_train_002522 | 1,422 | permissive | [
{
"docstring": "Constructor",
"name": "__init__",
"signature": "def __init__(self, npart=10, ndim=3, bounds=None)"
},
{
"docstring": "Return a randomly initialized swarm",
"name": "InitializeSwarm",
"signature": "def InitializeSwarm(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_013492 | Implement the Python class `RandomInitializer` described below.
Class description:
Initialize a swarm uniformly
Method signatures and docstrings:
- def __init__(self, npart=10, ndim=3, bounds=None): Constructor
- def InitializeSwarm(self): Return a randomly initialized swarm | Implement the Python class `RandomInitializer` described below.
Class description:
Initialize a swarm uniformly
Method signatures and docstrings:
- def __init__(self, npart=10, ndim=3, bounds=None): Constructor
- def InitializeSwarm(self): Return a randomly initialized swarm
<|skeleton|>
class RandomInitializer:
... | 5445b6f90ab49339ca0fdb71e98d44e6827c95a8 | <|skeleton|>
class RandomInitializer:
"""Initialize a swarm uniformly"""
def __init__(self, npart=10, ndim=3, bounds=None):
"""Constructor"""
<|body_0|>
def InitializeSwarm(self):
"""Return a randomly initialized swarm"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class RandomInitializer:
"""Initialize a swarm uniformly"""
def __init__(self, npart=10, ndim=3, bounds=None):
"""Constructor"""
self.npart = npart
self.ndim = ndim
self.bounds = bounds
def InitializeSwarm(self):
"""Return a randomly initialized swarm"""
if ... | the_stack_v2_python_sparse | RandomInitializer.py | dayoladejo/SwarmOptimization | train | 0 |
9cdb059585a0c8cc794f4e7c24d6d7a451e7e21b | [
"population_size = param_value(graph, parameters, Parameter.POPULATION_SIZE)\nno_of_processes = param_value(graph, parameters, Parameter.NO_OF_PROCESSES)\nindividuals = generate_individuals(graph, parameters)\npopulations = []\nchunks = ChainChunkFactory._list_chunks(individuals, population_size, no_of_processes)\n... | <|body_start_0|>
population_size = param_value(graph, parameters, Parameter.POPULATION_SIZE)
no_of_processes = param_value(graph, parameters, Parameter.NO_OF_PROCESSES)
individuals = generate_individuals(graph, parameters)
populations = []
chunks = ChainChunkFactory._list_chunks(... | ChainChunkFactory | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ChainChunkFactory:
def create(graph: Graph, parameters: Dict[str, Any]=None) -> Optional[List[Population]]:
"""Returns a list of no_of_processes populations that have approximately population_size / no_of_processes individuals."""
<|body_0|>
def _list_chunks(individuals: Lis... | stack_v2_sparse_classes_75kplus_train_002523 | 5,463 | permissive | [
{
"docstring": "Returns a list of no_of_processes populations that have approximately population_size / no_of_processes individuals.",
"name": "create",
"signature": "def create(graph: Graph, parameters: Dict[str, Any]=None) -> Optional[List[Population]]"
},
{
"docstring": "Splits a list into eq... | 2 | stack_v2_sparse_classes_30k_train_048663 | Implement the Python class `ChainChunkFactory` described below.
Class description:
Implement the ChainChunkFactory class.
Method signatures and docstrings:
- def create(graph: Graph, parameters: Dict[str, Any]=None) -> Optional[List[Population]]: Returns a list of no_of_processes populations that have approximately p... | Implement the Python class `ChainChunkFactory` described below.
Class description:
Implement the ChainChunkFactory class.
Method signatures and docstrings:
- def create(graph: Graph, parameters: Dict[str, Any]=None) -> Optional[List[Population]]: Returns a list of no_of_processes populations that have approximately p... | 69f0242aceb47fc383d0e56077f08b2b061273b5 | <|skeleton|>
class ChainChunkFactory:
def create(graph: Graph, parameters: Dict[str, Any]=None) -> Optional[List[Population]]:
"""Returns a list of no_of_processes populations that have approximately population_size / no_of_processes individuals."""
<|body_0|>
def _list_chunks(individuals: Lis... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ChainChunkFactory:
def create(graph: Graph, parameters: Dict[str, Any]=None) -> Optional[List[Population]]:
"""Returns a list of no_of_processes populations that have approximately population_size / no_of_processes individuals."""
population_size = param_value(graph, parameters, Parameter.POPU... | the_stack_v2_python_sparse | python/mage/graph_coloring_module/components/chain_chunk.py | gitbuda/mage | train | 0 | |
33be6e97c6a62b3b1f24ae91a504f2b1da9170e1 | [
"self.K = k\nself.X = self.file_to_vec(filename)\nself.SIZE, self.dimension = self.X.shape\nself.weights = [1.0 / k] * (k - 1)\nself.weights.append(1.0 - sum(self.weights))\nself.mu = self.X[[random.randint(1, self.SIZE) for x in range(self.K)]]\nself.sigma = [np.identity(self.dimension) for i in range(k)]\nself.p_... | <|body_start_0|>
self.K = k
self.X = self.file_to_vec(filename)
self.SIZE, self.dimension = self.X.shape
self.weights = [1.0 / k] * (k - 1)
self.weights.append(1.0 - sum(self.weights))
self.mu = self.X[[random.randint(1, self.SIZE) for x in range(self.K)]]
self.si... | GMM | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GMM:
def __init__(self, k=2, filename='2gaussian.txt'):
""":param k: int number of gaussian mixture :param filename: FILENAMES for the data file"""
<|body_0|>
def file_to_vec(filename):
""":type filename: string take FILENAMES and converts to numpy vectors"""
... | stack_v2_sparse_classes_75kplus_train_002524 | 4,712 | no_license | [
{
"docstring": ":param k: int number of gaussian mixture :param filename: FILENAMES for the data file",
"name": "__init__",
"signature": "def __init__(self, k=2, filename='2gaussian.txt')"
},
{
"docstring": ":type filename: string take FILENAMES and converts to numpy vectors",
"name": "file_... | 5 | stack_v2_sparse_classes_30k_train_033762 | Implement the Python class `GMM` described below.
Class description:
Implement the GMM class.
Method signatures and docstrings:
- def __init__(self, k=2, filename='2gaussian.txt'): :param k: int number of gaussian mixture :param filename: FILENAMES for the data file
- def file_to_vec(filename): :type filename: string... | Implement the Python class `GMM` described below.
Class description:
Implement the GMM class.
Method signatures and docstrings:
- def __init__(self, k=2, filename='2gaussian.txt'): :param k: int number of gaussian mixture :param filename: FILENAMES for the data file
- def file_to_vec(filename): :type filename: string... | ab455e0f236e63e19f5d222f48bbfc9c83338b6b | <|skeleton|>
class GMM:
def __init__(self, k=2, filename='2gaussian.txt'):
""":param k: int number of gaussian mixture :param filename: FILENAMES for the data file"""
<|body_0|>
def file_to_vec(filename):
""":type filename: string take FILENAMES and converts to numpy vectors"""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class GMM:
def __init__(self, k=2, filename='2gaussian.txt'):
""":param k: int number of gaussian mixture :param filename: FILENAMES for the data file"""
self.K = k
self.X = self.file_to_vec(filename)
self.SIZE, self.dimension = self.X.shape
self.weights = [1.0 / k] * (k - 1)... | the_stack_v2_python_sparse | HW2/gmm.py | malliksunkara/Unsupervised-ML | train | 0 | |
cb45201393807138cd6afb8704970b72f6b2267a | [
"self.source: str = source\nself.content: str = content\nself.is_error: bool = is_error",
"pad = len(self.source) if len(self.source) > source_len else source_len\ncolor_code = '\\x1b[31;1m' if self.is_error and colorize else ''\nreset_code = '\\x1b[0m' if self.is_error and colorize else ''\nreturn f'[ {self.sour... | <|body_start_0|>
self.source: str = source
self.content: str = content
self.is_error: bool = is_error
<|end_body_0|>
<|body_start_1|>
pad = len(self.source) if len(self.source) > source_len else source_len
color_code = '\x1b[31;1m' if self.is_error and colorize else ''
r... | Helper class for managing messages. | Message | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Message:
"""Helper class for managing messages."""
def __init__(self, source: str, content: str, is_error: bool=False) -> None:
"""Initialize a Message object. Args: source: The source of the message, eg 'dftimewolf' or a runtime name. content: The content of the message. is_error: T... | stack_v2_sparse_classes_75kplus_train_002525 | 17,020 | permissive | [
{
"docstring": "Initialize a Message object. Args: source: The source of the message, eg 'dftimewolf' or a runtime name. content: The content of the message. is_error: True if the message is an error message, False otherwise.",
"name": "__init__",
"signature": "def __init__(self, source: str, content: s... | 2 | stack_v2_sparse_classes_30k_train_038310 | Implement the Python class `Message` described below.
Class description:
Helper class for managing messages.
Method signatures and docstrings:
- def __init__(self, source: str, content: str, is_error: bool=False) -> None: Initialize a Message object. Args: source: The source of the message, eg 'dftimewolf' or a runti... | Implement the Python class `Message` described below.
Class description:
Helper class for managing messages.
Method signatures and docstrings:
- def __init__(self, source: str, content: str, is_error: bool=False) -> None: Initialize a Message object. Args: source: The source of the message, eg 'dftimewolf' or a runti... | bcea85b1ce7a0feb2aa28b5be4fc6ae124e8ca3c | <|skeleton|>
class Message:
"""Helper class for managing messages."""
def __init__(self, source: str, content: str, is_error: bool=False) -> None:
"""Initialize a Message object. Args: source: The source of the message, eg 'dftimewolf' or a runtime name. content: The content of the message. is_error: T... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Message:
"""Helper class for managing messages."""
def __init__(self, source: str, content: str, is_error: bool=False) -> None:
"""Initialize a Message object. Args: source: The source of the message, eg 'dftimewolf' or a runtime name. content: The content of the message. is_error: True if the me... | the_stack_v2_python_sparse | dftimewolf/cli/curses_display_manager.py | log2timeline/dftimewolf | train | 248 |
c5b9268498dbe86bc0cad1bb43c5aa751520dd76 | [
"\"\"\"\n 解法2：动态规划。\n a[j] += [a[j-i] + [i]]\n \"\"\"\nA = [[[]]] + [[] for i in range(target)]\nfor c in candidates:\n for n in range(c, target + 1):\n A[n] += [comb + [c] for comb in A[n - c]]\nreturn A[target]\n'\\n 组合总和 II\\n 给定一个数组\\xa0candidates\\xa0和一个目标数\\xa0target\\xa0，... | <|body_start_0|>
"""
解法2：动态规划。
a[j] += [a[j-i] + [i]]
"""
A = [[[]]] + [[] for i in range(target)]
for c in candidates:
for n in range(c, target + 1):
A[n] += [comb + [c] for comb in A[n - c]]
return A[target]
... | 组合总和 I 给定一个无重复元素的数组 candidates 和一个目标数 target ，找出 candidates 中所有可以使数字和为 target 的组合。 candidates 中的数字可以无限制重复被选取。 说明： 所有数字（包括 target）都是正整数。 解集不能包含重复的组合。 示例 1: 输入: candidates = [2,3,6,7], target = 7, 所求解集为: [ [7], [2,2,3] ] 示例 2: 输入: candidates = [2,3,5], target = 8, 所求解集为: [ [2,2,2,2], [2,3,3], [3,5] ] 链接：https://leetcode-... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
"""组合总和 I 给定一个无重复元素的数组 candidates 和一个目标数 target ，找出 candidates 中所有可以使数字和为 target 的组合。 candidates 中的数字可以无限制重复被选取。 说明： 所有数字（包括 target）都是正整数。 解集不能包含重复的组合。 示例 1: 输入: candidates = [2,3,6,7], target = 7, 所求解集为: [ [7], [2,2,3] ] 示例 2: 输入: candidates = [2,3,5], target = 8, 所求解集为: [ [2,2,2,2], [... | stack_v2_sparse_classes_75kplus_train_002526 | 7,247 | no_license | [
{
"docstring": "解法1：回溯+剪枝",
"name": "combinationSum",
"signature": "def combinationSum(self, candidates: list, target: int) -> list"
},
{
"docstring": "解法1：回溯，同1的解法1",
"name": "combinationSum2",
"signature": "def combinationSum2(self, candidates: list, target: int) -> list"
},
{
... | 4 | stack_v2_sparse_classes_30k_train_039661 | Implement the Python class `Solution` described below.
Class description:
组合总和 I 给定一个无重复元素的数组 candidates 和一个目标数 target ，找出 candidates 中所有可以使数字和为 target 的组合。 candidates 中的数字可以无限制重复被选取。 说明： 所有数字（包括 target）都是正整数。 解集不能包含重复的组合。 示例 1: 输入: candidates = [2,3,6,7], target = 7, 所求解集为: [ [7], [2,2,3] ] 示例 2: 输入: candidates = [2,... | Implement the Python class `Solution` described below.
Class description:
组合总和 I 给定一个无重复元素的数组 candidates 和一个目标数 target ，找出 candidates 中所有可以使数字和为 target 的组合。 candidates 中的数字可以无限制重复被选取。 说明： 所有数字（包括 target）都是正整数。 解集不能包含重复的组合。 示例 1: 输入: candidates = [2,3,6,7], target = 7, 所求解集为: [ [7], [2,2,3] ] 示例 2: 输入: candidates = [2,... | ad25281be49dfb9de211ba324b398e946e49025d | <|skeleton|>
class Solution:
"""组合总和 I 给定一个无重复元素的数组 candidates 和一个目标数 target ，找出 candidates 中所有可以使数字和为 target 的组合。 candidates 中的数字可以无限制重复被选取。 说明： 所有数字（包括 target）都是正整数。 解集不能包含重复的组合。 示例 1: 输入: candidates = [2,3,6,7], target = 7, 所求解集为: [ [7], [2,2,3] ] 示例 2: 输入: candidates = [2,3,5], target = 8, 所求解集为: [ [2,2,2,2], [... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
"""组合总和 I 给定一个无重复元素的数组 candidates 和一个目标数 target ，找出 candidates 中所有可以使数字和为 target 的组合。 candidates 中的数字可以无限制重复被选取。 说明： 所有数字（包括 target）都是正整数。 解集不能包含重复的组合。 示例 1: 输入: candidates = [2,3,6,7], target = 7, 所求解集为: [ [7], [2,2,3] ] 示例 2: 输入: candidates = [2,3,5], target = 8, 所求解集为: [ [2,2,2,2], [2,3,3], [3,5]... | the_stack_v2_python_sparse | 人生苦短/组合总和（1-4）.py | Jsonlmy/leetcode | train | 0 |
604c426677bef406b1e6851c6fc60321b3f8583b | [
"self.payment_facilitator_code = payment_facilitator_code\nself.code = code\nself.name = name\nself.merchant_category_code = merchant_category_code\nself.document = document\nself.mtype = mtype\nself.phone = phone\nself.address = address",
"if dictionary is None:\n return None\npayment_facilitator_code = dicti... | <|body_start_0|>
self.payment_facilitator_code = payment_facilitator_code
self.code = code
self.name = name
self.merchant_category_code = merchant_category_code
self.document = document
self.mtype = mtype
self.phone = phone
self.address = address
<|end_bod... | Implementation of the 'CreateSubMerchantRequest' model. SubMerchant Attributes: payment_facilitator_code (string): Payment Facilitator Code code (string): Code name (string): Name merchant_category_code (string): Merchant Category Code document (string): Document number. Only numbers, no special characters. mtype (stri... | CreateSubMerchantRequest | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CreateSubMerchantRequest:
"""Implementation of the 'CreateSubMerchantRequest' model. SubMerchant Attributes: payment_facilitator_code (string): Payment Facilitator Code code (string): Code name (string): Name merchant_category_code (string): Merchant Category Code document (string): Document numb... | stack_v2_sparse_classes_75kplus_train_002527 | 3,482 | permissive | [
{
"docstring": "Constructor for the CreateSubMerchantRequest class",
"name": "__init__",
"signature": "def __init__(self, payment_facilitator_code=None, code=None, name=None, merchant_category_code=None, document=None, mtype=None, phone=None, address=None)"
},
{
"docstring": "Creates an instance... | 2 | null | Implement the Python class `CreateSubMerchantRequest` described below.
Class description:
Implementation of the 'CreateSubMerchantRequest' model. SubMerchant Attributes: payment_facilitator_code (string): Payment Facilitator Code code (string): Code name (string): Name merchant_category_code (string): Merchant Categor... | Implement the Python class `CreateSubMerchantRequest` described below.
Class description:
Implementation of the 'CreateSubMerchantRequest' model. SubMerchant Attributes: payment_facilitator_code (string): Payment Facilitator Code code (string): Code name (string): Name merchant_category_code (string): Merchant Categor... | 95c80c35dd57bb2a238faeaf30d1e3b4544d2298 | <|skeleton|>
class CreateSubMerchantRequest:
"""Implementation of the 'CreateSubMerchantRequest' model. SubMerchant Attributes: payment_facilitator_code (string): Payment Facilitator Code code (string): Code name (string): Name merchant_category_code (string): Merchant Category Code document (string): Document numb... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CreateSubMerchantRequest:
"""Implementation of the 'CreateSubMerchantRequest' model. SubMerchant Attributes: payment_facilitator_code (string): Payment Facilitator Code code (string): Code name (string): Name merchant_category_code (string): Merchant Category Code document (string): Document number. Only numb... | the_stack_v2_python_sparse | mundiapi/models/create_sub_merchant_request.py | mundipagg/MundiAPI-PYTHON | train | 10 |
68fbd986055ee502f867c05d45835f5956ef2b8f | [
"self.registeredPlates = open('registeredPlates.txt').read().splitlines()\nif string in self.registeredPlates:\n return True\nelse:\n return False",
"self.restrictedWords = open('restrictedWords.txt').read().splitlines()\nif string in self.restrictedWords:\n return True\nelse:\n return False",
"self... | <|body_start_0|>
self.registeredPlates = open('registeredPlates.txt').read().splitlines()
if string in self.registeredPlates:
return True
else:
return False
<|end_body_0|>
<|body_start_1|>
self.restrictedWords = open('restrictedWords.txt').read().splitlines()
... | check | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class check:
def registered(self, string):
"""Checks if string is in registered plates file; returns boolean"""
<|body_0|>
def restricted(self, string):
"""Checks if string is in restricted plates file; returns boolean"""
<|body_1|>
def word(self, string):
... | stack_v2_sparse_classes_75kplus_train_002528 | 3,194 | permissive | [
{
"docstring": "Checks if string is in registered plates file; returns boolean",
"name": "registered",
"signature": "def registered(self, string)"
},
{
"docstring": "Checks if string is in restricted plates file; returns boolean",
"name": "restricted",
"signature": "def restricted(self, ... | 3 | stack_v2_sparse_classes_30k_train_006650 | Implement the Python class `check` described below.
Class description:
Implement the check class.
Method signatures and docstrings:
- def registered(self, string): Checks if string is in registered plates file; returns boolean
- def restricted(self, string): Checks if string is in restricted plates file; returns bool... | Implement the Python class `check` described below.
Class description:
Implement the check class.
Method signatures and docstrings:
- def registered(self, string): Checks if string is in registered plates file; returns boolean
- def restricted(self, string): Checks if string is in restricted plates file; returns bool... | af04f91e14492d0ddfe7b5ad00e0652e609ca1b5 | <|skeleton|>
class check:
def registered(self, string):
"""Checks if string is in registered plates file; returns boolean"""
<|body_0|>
def restricted(self, string):
"""Checks if string is in restricted plates file; returns boolean"""
<|body_1|>
def word(self, string):
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class check:
def registered(self, string):
"""Checks if string is in registered plates file; returns boolean"""
self.registeredPlates = open('registeredPlates.txt').read().splitlines()
if string in self.registeredPlates:
return True
else:
return False
def... | the_stack_v2_python_sparse | Code/Pygame Based/20140326/carPlateRegistrationSystem.py | creatingcrap/PythonPlate | train | 0 | |
962b8bec9d0698d111d953a2c4e75714a096d68a | [
"self.device = device\nself.type = 0\nself.code = 0\nself.checksum = 0\nself.hdr_length = 0",
"icmph = unpack('!BBH', packet)\nself.type = icmph[0]\nself.code = icmph[1]\nself.checksum = icmph[2]\nself.hdr_length = self.DEFAULT_LENGTH"
] | <|body_start_0|>
self.device = device
self.type = 0
self.code = 0
self.checksum = 0
self.hdr_length = 0
<|end_body_0|>
<|body_start_1|>
icmph = unpack('!BBH', packet)
self.type = icmph[0]
self.code = icmph[1]
self.checksum = icmph[2]
self.... | Description : class to store the details of ICMP protocol sample packet structure 0 1 2 3 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 +-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+ | Type | Code | Checksum | +-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+ | unuse... | IcmpHeader | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IcmpHeader:
"""Description : class to store the details of ICMP protocol sample packet structure 0 1 2 3 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 +-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+ | Type | Code | Checksum | +-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+... | stack_v2_sparse_classes_75kplus_train_002529 | 1,704 | no_license | [
{
"docstring": "Description : Initialize the ICMP header details",
"name": "__init__",
"signature": "def __init__(self, device)"
},
{
"docstring": "Description : Assigns values to the ICMP header class attributes from the details present in the given packet input_param : packet - packet received... | 2 | null | Implement the Python class `IcmpHeader` described below.
Class description:
Description : class to store the details of ICMP protocol sample packet structure 0 1 2 3 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 +-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+ | Type | Code | Checksu... | Implement the Python class `IcmpHeader` described below.
Class description:
Description : class to store the details of ICMP protocol sample packet structure 0 1 2 3 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 +-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+ | Type | Code | Checksu... | eb5c852b993ddf3e8516705f0252de41e771e731 | <|skeleton|>
class IcmpHeader:
"""Description : class to store the details of ICMP protocol sample packet structure 0 1 2 3 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 +-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+ | Type | Code | Checksum | +-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class IcmpHeader:
"""Description : class to store the details of ICMP protocol sample packet structure 0 1 2 3 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 +-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+ | Type | Code | Checksum | +-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-... | the_stack_v2_python_sparse | manager/sniffer/icmp.py | Rk85/Network-Packet-Analyzer | train | 0 |
4d33ad0395c2e3ae536a9bf6fdabf98487323eed | [
"self.utils = NSGA2Utils(problem, num_of_individuals, num_of_tour_particips, tournament_prob, crossover_param, mutation_param)\nself.population = None\nself.num_of_generations = num_of_generations\nself.on_generation_finished = []\nself.num_of_individuals = num_of_individuals",
"self.population = self.utils.creat... | <|body_start_0|>
self.utils = NSGA2Utils(problem, num_of_individuals, num_of_tour_particips, tournament_prob, crossover_param, mutation_param)
self.population = None
self.num_of_generations = num_of_generations
self.on_generation_finished = []
self.num_of_individuals = num_of_ind... | This class manages the evolutionary process of the NSGA-II algorithm. | Evolution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Evolution:
"""This class manages the evolutionary process of the NSGA-II algorithm."""
def __init__(self, problem, num_of_generations=1000, num_of_individuals=100, num_of_tour_particips=2, tournament_prob=0.9, crossover_param=2, mutation_param=5):
"""Initialize an instance of the Evo... | stack_v2_sparse_classes_75kplus_train_002530 | 5,047 | no_license | [
{
"docstring": "Initialize an instance of the Evolution class. :param problem: The problem to optimize. :param num_of_generations: The number of generations the algorithm will evolve. :param num_of_individuals: The number of individuals (solutions) in each generation. :param num_of_tour_particips: The number of... | 2 | stack_v2_sparse_classes_30k_train_044870 | Implement the Python class `Evolution` described below.
Class description:
This class manages the evolutionary process of the NSGA-II algorithm.
Method signatures and docstrings:
- def __init__(self, problem, num_of_generations=1000, num_of_individuals=100, num_of_tour_particips=2, tournament_prob=0.9, crossover_para... | Implement the Python class `Evolution` described below.
Class description:
This class manages the evolutionary process of the NSGA-II algorithm.
Method signatures and docstrings:
- def __init__(self, problem, num_of_generations=1000, num_of_individuals=100, num_of_tour_particips=2, tournament_prob=0.9, crossover_para... | 5411b64acc15a0613881e91c74d65874457bdb48 | <|skeleton|>
class Evolution:
"""This class manages the evolutionary process of the NSGA-II algorithm."""
def __init__(self, problem, num_of_generations=1000, num_of_individuals=100, num_of_tour_particips=2, tournament_prob=0.9, crossover_param=2, mutation_param=5):
"""Initialize an instance of the Evo... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Evolution:
"""This class manages the evolutionary process of the NSGA-II algorithm."""
def __init__(self, problem, num_of_generations=1000, num_of_individuals=100, num_of_tour_particips=2, tournament_prob=0.9, crossover_param=2, mutation_param=5):
"""Initialize an instance of the Evolution class.... | the_stack_v2_python_sparse | NSGA2/nsga2/evolution.py | RioKKH/pytools | train | 0 |
026fd71ee32b75fc492dd3de03f900cbd24733b8 | [
"pygame.mixer.pre_init(44100, -16, 1, 512)\npygame.init()\nctypes.windll.user32.SetProcessDPIAware()\nself.settings = Settings()\nself.screen = pygame.display.set_mode((self.settings.screen_width, self.settings.screen_height))\npygame.display.set_caption(self.settings.caption)\nself.main_menu = True\nself.play_game... | <|body_start_0|>
pygame.mixer.pre_init(44100, -16, 1, 512)
pygame.init()
ctypes.windll.user32.SetProcessDPIAware()
self.settings = Settings()
self.screen = pygame.display.set_mode((self.settings.screen_width, self.settings.screen_height))
pygame.display.set_caption(self.s... | A class representing the game. | Game | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Game:
"""A class representing the game."""
def __init__(self):
"""Initialize game."""
<|body_0|>
def run_game(self):
"""Main function for Space Invaders."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
pygame.mixer.pre_init(44100, -16, 1, 512)
... | stack_v2_sparse_classes_75kplus_train_002531 | 3,861 | permissive | [
{
"docstring": "Initialize game.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Main function for Space Invaders.",
"name": "run_game",
"signature": "def run_game(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_033664 | Implement the Python class `Game` described below.
Class description:
A class representing the game.
Method signatures and docstrings:
- def __init__(self): Initialize game.
- def run_game(self): Main function for Space Invaders. | Implement the Python class `Game` described below.
Class description:
A class representing the game.
Method signatures and docstrings:
- def __init__(self): Initialize game.
- def run_game(self): Main function for Space Invaders.
<|skeleton|>
class Game:
"""A class representing the game."""
def __init__(sel... | fad971bc651065138f51f94c4ddecdbb1cd20e86 | <|skeleton|>
class Game:
"""A class representing the game."""
def __init__(self):
"""Initialize game."""
<|body_0|>
def run_game(self):
"""Main function for Space Invaders."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Game:
"""A class representing the game."""
def __init__(self):
"""Initialize game."""
pygame.mixer.pre_init(44100, -16, 1, 512)
pygame.init()
ctypes.windll.user32.SetProcessDPIAware()
self.settings = Settings()
self.screen = pygame.display.set_mode((self.se... | the_stack_v2_python_sparse | space_invaders.py | hlynurstef/Space_Invaders | train | 0 |
2ded63d2dacd7fb8907bf91bade7a0e05c80a321 | [
"handler_names = provider_config.get_authentication_handlers() if provider_config else []\nself._authn_handlers = []\nfrom vmware.vapi.lib.load import dynamic_import\nfor handler_name in handler_names:\n handler_constructor = dynamic_import(handler_name)\n if handler_constructor is None:\n raise Import... | <|body_start_0|>
handler_names = provider_config.get_authentication_handlers() if provider_config else []
self._authn_handlers = []
from vmware.vapi.lib.load import dynamic_import
for handler_name in handler_names:
handler_constructor = dynamic_import(handler_name)
... | AuthenticationFilter in API Provider chain enforces the authentication schemes specified in the authentication metadata file | AuthenticationFilter | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AuthenticationFilter:
"""AuthenticationFilter in API Provider chain enforces the authentication schemes specified in the authentication metadata file"""
def __init__(self, next_provider=None, provider_config=None):
"""Initialize AuthenticationFilter :type next_provider: :class:`vmwar... | stack_v2_sparse_classes_75kplus_train_002532 | 5,195 | no_license | [
{
"docstring": "Initialize AuthenticationFilter :type next_provider: :class:`vmware.vapi.core.ApiProvider` :param next_provider: API Provider to invoke the requests :type provider_config: :class:`vmware.vapi.settings.config.ProviderConfig` or :class:`None` :param provider_config: Provider configuration object",... | 2 | null | Implement the Python class `AuthenticationFilter` described below.
Class description:
AuthenticationFilter in API Provider chain enforces the authentication schemes specified in the authentication metadata file
Method signatures and docstrings:
- def __init__(self, next_provider=None, provider_config=None): Initializ... | Implement the Python class `AuthenticationFilter` described below.
Class description:
AuthenticationFilter in API Provider chain enforces the authentication schemes specified in the authentication metadata file
Method signatures and docstrings:
- def __init__(self, next_provider=None, provider_config=None): Initializ... | 5d395700ab3d0d1d45b497e48beab8c366fca9f5 | <|skeleton|>
class AuthenticationFilter:
"""AuthenticationFilter in API Provider chain enforces the authentication schemes specified in the authentication metadata file"""
def __init__(self, next_provider=None, provider_config=None):
"""Initialize AuthenticationFilter :type next_provider: :class:`vmwar... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AuthenticationFilter:
"""AuthenticationFilter in API Provider chain enforces the authentication schemes specified in the authentication metadata file"""
def __init__(self, next_provider=None, provider_config=None):
"""Initialize AuthenticationFilter :type next_provider: :class:`vmware.vapi.core.A... | the_stack_v2_python_sparse | alexa-program/vmware/vapi/security/authentication_filter.py | taromurata/TDP2018_VMCAPI | train | 1 |
9e21d192e5ad693d294d851a235a2eb90007d0ed | [
"super(CustomRNN, self).__init__()\nself.hidden_size = hidden_size\nself.rnn_type = rnn_type\nself.vocab_size = vocab_size\nself.num_layers = num_layers\nself.rnn = nn.ModuleList()\nif rnn_type == 'basic_rnn':\n layer = BasicRNNCell\nelif rnn_type == 'lstm_rnn':\n layer = LSTMCell\nelse:\n print('Enter val... | <|body_start_0|>
super(CustomRNN, self).__init__()
self.hidden_size = hidden_size
self.rnn_type = rnn_type
self.vocab_size = vocab_size
self.num_layers = num_layers
self.rnn = nn.ModuleList()
if rnn_type == 'basic_rnn':
layer = BasicRNNCell
eli... | CustomRNN | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CustomRNN:
def __init__(self, vocab_size, hidden_size, num_layers=1, rnn_type='basic_rnn'):
"""Creates an recurrent neural network of type {basic_rnn, lstm_rnn} basic_rnn is an rnn whose layers implement a tanH activation function lstm_rnn is ann rnn whose layers implement an LSTM cell A... | stack_v2_sparse_classes_75kplus_train_002533 | 3,688 | no_license | [
{
"docstring": "Creates an recurrent neural network of type {basic_rnn, lstm_rnn} basic_rnn is an rnn whose layers implement a tanH activation function lstm_rnn is ann rnn whose layers implement an LSTM cell Arguments --------- vocab_size: (int), the number of unique characters in the corpus. This is the number... | 2 | stack_v2_sparse_classes_30k_train_006644 | Implement the Python class `CustomRNN` described below.
Class description:
Implement the CustomRNN class.
Method signatures and docstrings:
- def __init__(self, vocab_size, hidden_size, num_layers=1, rnn_type='basic_rnn'): Creates an recurrent neural network of type {basic_rnn, lstm_rnn} basic_rnn is an rnn whose lay... | Implement the Python class `CustomRNN` described below.
Class description:
Implement the CustomRNN class.
Method signatures and docstrings:
- def __init__(self, vocab_size, hidden_size, num_layers=1, rnn_type='basic_rnn'): Creates an recurrent neural network of type {basic_rnn, lstm_rnn} basic_rnn is an rnn whose lay... | ca5d01dab5ba58a93b224541569c5ad2b3d943ed | <|skeleton|>
class CustomRNN:
def __init__(self, vocab_size, hidden_size, num_layers=1, rnn_type='basic_rnn'):
"""Creates an recurrent neural network of type {basic_rnn, lstm_rnn} basic_rnn is an rnn whose layers implement a tanH activation function lstm_rnn is ann rnn whose layers implement an LSTM cell A... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CustomRNN:
def __init__(self, vocab_size, hidden_size, num_layers=1, rnn_type='basic_rnn'):
"""Creates an recurrent neural network of type {basic_rnn, lstm_rnn} basic_rnn is an rnn whose layers implement a tanH activation function lstm_rnn is ann rnn whose layers implement an LSTM cell Arguments -----... | the_stack_v2_python_sparse | create_rnn.py | zhangjoe99/basic-rnn | train | 0 | |
9d471cab4d3b138c0493f73a0809a48361e25f96 | [
"self.capcity = capacity\nself.map = {}\nself.head = DNode(None)\nself.tail = self.head\nself.exist = 0",
"curNode = self.map.get(key)\nif curNode:\n tailNode = self.tail\n if curNode != tailNode:\n curNode.next.pre = curNode.pre\n curNode.pre.next = curNode.next\n tailNode.next = curNo... | <|body_start_0|>
self.capcity = capacity
self.map = {}
self.head = DNode(None)
self.tail = self.head
self.exist = 0
<|end_body_0|>
<|body_start_1|>
curNode = self.map.get(key)
if curNode:
tailNode = self.tail
if curNode != tailNode:
... | LRUCache | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LRUCache:
def __init__(self, capacity):
""":type capacity: int"""
<|body_0|>
def get(self, key):
""":type key: int :rtype: int"""
<|body_1|>
def put(self, key, value):
""":type key: int :type value: int :rtype: None"""
<|body_2|>
<|end_s... | stack_v2_sparse_classes_75kplus_train_002534 | 2,099 | no_license | [
{
"docstring": ":type capacity: int",
"name": "__init__",
"signature": "def __init__(self, capacity)"
},
{
"docstring": ":type key: int :rtype: int",
"name": "get",
"signature": "def get(self, key)"
},
{
"docstring": ":type key: int :type value: int :rtype: None",
"name": "pu... | 3 | null | Implement the Python class `LRUCache` described below.
Class description:
Implement the LRUCache class.
Method signatures and docstrings:
- def __init__(self, capacity): :type capacity: int
- def get(self, key): :type key: int :rtype: int
- def put(self, key, value): :type key: int :type value: int :rtype: None | Implement the Python class `LRUCache` described below.
Class description:
Implement the LRUCache class.
Method signatures and docstrings:
- def __init__(self, capacity): :type capacity: int
- def get(self, key): :type key: int :rtype: int
- def put(self, key, value): :type key: int :type value: int :rtype: None
<|sk... | bc67562b010397f74a2d97ced1c7863566370861 | <|skeleton|>
class LRUCache:
def __init__(self, capacity):
""":type capacity: int"""
<|body_0|>
def get(self, key):
""":type key: int :rtype: int"""
<|body_1|>
def put(self, key, value):
""":type key: int :type value: int :rtype: None"""
<|body_2|>
<|end_s... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class LRUCache:
def __init__(self, capacity):
""":type capacity: int"""
self.capcity = capacity
self.map = {}
self.head = DNode(None)
self.tail = self.head
self.exist = 0
def get(self, key):
""":type key: int :rtype: int"""
curNode = self.map.get(... | the_stack_v2_python_sparse | Design/146_LRU Cache.py | Mercyzzz/MercyLeetcode | train | 1 | |
218b5ab3a2cbdb4f1c36aee62630c2320a7ca86c | [
"try:\n book = BookInfo.objects.get(pk=pk)\nexcept BookInfo.DoesNotExist:\n return HttpResponse(status=404)\nreturn JsonResponse({'id': book.id, 'name': book.name, 'pub_date': book.pub_date, 'read_count': book.read_count, 'comment_count': book.comment_count})",
"try:\n book = BookInfo.objects.get(pk=pk)\... | <|body_start_0|>
try:
book = BookInfo.objects.get(pk=pk)
except BookInfo.DoesNotExist:
return HttpResponse(status=404)
return JsonResponse({'id': book.id, 'name': book.name, 'pub_date': book.pub_date, 'read_count': book.read_count, 'comment_count': book.comment_count})
<|... | BookAPIView | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BookAPIView:
def get(self, request, pk):
"""获取单个图书信息 路由： GET /books/<pk>/ url中则需要设置books/(?P<pk>d+)/"""
<|body_0|>
def put(self, request, pk):
"""修改图书信息 路由： PUT /books/<pk>"""
<|body_1|>
def delete(self, request, pk):
"""删除图书 路由： DELETE /books/<p... | stack_v2_sparse_classes_75kplus_train_002535 | 4,279 | permissive | [
{
"docstring": "获取单个图书信息 路由： GET /books/<pk>/ url中则需要设置books/(?P<pk>d+)/",
"name": "get",
"signature": "def get(self, request, pk)"
},
{
"docstring": "修改图书信息 路由： PUT /books/<pk>",
"name": "put",
"signature": "def put(self, request, pk)"
},
{
"docstring": "删除图书 路由： DELETE /books/<... | 3 | stack_v2_sparse_classes_30k_train_030693 | Implement the Python class `BookAPIView` described below.
Class description:
Implement the BookAPIView class.
Method signatures and docstrings:
- def get(self, request, pk): 获取单个图书信息 路由： GET /books/<pk>/ url中则需要设置books/(?P<pk>d+)/
- def put(self, request, pk): 修改图书信息 路由： PUT /books/<pk>
- def delete(self, request, pk... | Implement the Python class `BookAPIView` described below.
Class description:
Implement the BookAPIView class.
Method signatures and docstrings:
- def get(self, request, pk): 获取单个图书信息 路由： GET /books/<pk>/ url中则需要设置books/(?P<pk>d+)/
- def put(self, request, pk): 修改图书信息 路由： PUT /books/<pk>
- def delete(self, request, pk... | 771a3f44c5d0e9a7be1118b84ca89cd34c3d7293 | <|skeleton|>
class BookAPIView:
def get(self, request, pk):
"""获取单个图书信息 路由： GET /books/<pk>/ url中则需要设置books/(?P<pk>d+)/"""
<|body_0|>
def put(self, request, pk):
"""修改图书信息 路由： PUT /books/<pk>"""
<|body_1|>
def delete(self, request, pk):
"""删除图书 路由： DELETE /books/<p... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class BookAPIView:
def get(self, request, pk):
"""获取单个图书信息 路由： GET /books/<pk>/ url中则需要设置books/(?P<pk>d+)/"""
try:
book = BookInfo.objects.get(pk=pk)
except BookInfo.DoesNotExist:
return HttpResponse(status=404)
return JsonResponse({'id': book.id, 'name': book... | the_stack_v2_python_sparse | 19Django_Advanced/day01to06/demo/DRF/views.py | mumudexiaomuwu/Python24 | train | 1 | |
b8478d11bf8717ef0a79b8a88249fdf45e629821 | [
"self.name = name\nself.description = description\nself.config_scheme = config_scheme\nself.default_config = default_config\nself.default_cron = default_cron\nself.default_activated = default_activated\nself.args = args\nself.kwargs = kwargs",
"from gengine.app.registries import get_task_registry\nget_task_regist... | <|body_start_0|>
self.name = name
self.description = description
self.config_scheme = config_scheme
self.default_config = default_config
self.default_cron = default_cron
self.default_activated = default_activated
self.args = args
self.kwargs = kwargs
<|end... | EngineTask | [
"MIT",
"ZPL-2.1",
"Apache-2.0",
"BSD-3-Clause-Modification",
"LGPL-2.0-or-later"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EngineTask:
def __init__(self, name, description, config_scheme, default_config, default_cron, default_activated, *args, **kwargs):
"""Constructor just here to accept parameters for decorator"""
<|body_0|>
def __call__(self, wrapped):
"""Attach the decorator with Ven... | stack_v2_sparse_classes_75kplus_train_002536 | 2,888 | permissive | [
{
"docstring": "Constructor just here to accept parameters for decorator",
"name": "__init__",
"signature": "def __init__(self, name, description, config_scheme, default_config, default_cron, default_activated, *args, **kwargs)"
},
{
"docstring": "Attach the decorator with Venusian",
"name":... | 2 | stack_v2_sparse_classes_30k_train_005905 | Implement the Python class `EngineTask` described below.
Class description:
Implement the EngineTask class.
Method signatures and docstrings:
- def __init__(self, name, description, config_scheme, default_config, default_cron, default_activated, *args, **kwargs): Constructor just here to accept parameters for decorat... | Implement the Python class `EngineTask` described below.
Class description:
Implement the EngineTask class.
Method signatures and docstrings:
- def __init__(self, name, description, config_scheme, default_config, default_cron, default_activated, *args, **kwargs): Constructor just here to accept parameters for decorat... | b82a900f2f4a43cea463853e36d6f8237c7f255e | <|skeleton|>
class EngineTask:
def __init__(self, name, description, config_scheme, default_config, default_cron, default_activated, *args, **kwargs):
"""Constructor just here to accept parameters for decorator"""
<|body_0|>
def __call__(self, wrapped):
"""Attach the decorator with Ven... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class EngineTask:
def __init__(self, name, description, config_scheme, default_config, default_cron, default_activated, *args, **kwargs):
"""Constructor just here to accept parameters for decorator"""
self.name = name
self.description = description
self.config_scheme = config_scheme
... | the_stack_v2_python_sparse | gengine/app/tasksystem.py | ActiDoo/gamification-engine | train | 413 | |
907b93d07ed8e48bdf7b0666f76df96068f0b849 | [
"if user is not None and user.is_superuser and with_superuser:\n return self\nfilters_prefix = ''\nif self.model._meta.label == 'flow.Storage':\n filters_prefix = 'data__'\nfilters = dict()\nif user:\n filters['user'] = models.Q(**{f'{filters_prefix}permission_group__permissions__user': user, f'{filters_pr... | <|body_start_0|>
if user is not None and user.is_superuser and with_superuser:
return self
filters_prefix = ''
if self.model._meta.label == 'flow.Storage':
filters_prefix = 'data__'
filters = dict()
if user:
filters['user'] = models.Q(**{f'{fil... | Queryset with methods that simlify filtering by permissions. | PermissionQuerySet | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PermissionQuerySet:
"""Queryset with methods that simlify filtering by permissions."""
def _filter_by_permission(self, user: Optional[User], groups: models.QuerySet, permission: Permission, public: bool=True, with_superuser: bool=True) -> models.QuerySet:
"""Filter queryset by permis... | stack_v2_sparse_classes_75kplus_train_002537 | 19,789 | permissive | [
{
"docstring": "Filter queryset by permissions. This is a generic method that is called in public methods. :attr user: the user which permissions should be considered. :attr groups: the groups which permissions should be considered. :attr permission: the lowest permission entity must have. :attr public: when Tr... | 3 | stack_v2_sparse_classes_30k_train_039792 | Implement the Python class `PermissionQuerySet` described below.
Class description:
Queryset with methods that simlify filtering by permissions.
Method signatures and docstrings:
- def _filter_by_permission(self, user: Optional[User], groups: models.QuerySet, permission: Permission, public: bool=True, with_superuser:... | Implement the Python class `PermissionQuerySet` described below.
Class description:
Queryset with methods that simlify filtering by permissions.
Method signatures and docstrings:
- def _filter_by_permission(self, user: Optional[User], groups: models.QuerySet, permission: Permission, public: bool=True, with_superuser:... | 25c0c45235ef37beb45c1af4c917fbbae6282016 | <|skeleton|>
class PermissionQuerySet:
"""Queryset with methods that simlify filtering by permissions."""
def _filter_by_permission(self, user: Optional[User], groups: models.QuerySet, permission: Permission, public: bool=True, with_superuser: bool=True) -> models.QuerySet:
"""Filter queryset by permis... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PermissionQuerySet:
"""Queryset with methods that simlify filtering by permissions."""
def _filter_by_permission(self, user: Optional[User], groups: models.QuerySet, permission: Permission, public: bool=True, with_superuser: bool=True) -> models.QuerySet:
"""Filter queryset by permissions. This i... | the_stack_v2_python_sparse | resolwe/permissions/models.py | genialis/resolwe | train | 35 |
dd8d7728fa8286c059073c039bc8787a14839764 | [
"self._vm = vm\nself.func_code = code\nself.func_name = self.__name__ = name or code.co_name\nself.func_defaults = tuple(defaults)\nself.func_globals = globs\nself.func_locals = self._vm.frame.f_locals\nself.__dict__ = {}\nself.func_closure = closure\nself.__doc__ = code.co_consts[0] if code.co_consts else None\nkw... | <|body_start_0|>
self._vm = vm
self.func_code = code
self.func_name = self.__name__ = name or code.co_name
self.func_defaults = tuple(defaults)
self.func_globals = globs
self.func_locals = self._vm.frame.f_locals
self.__dict__ = {}
self.func_closure = clos... | Create a realistic function object, defining the things the interpreter expects. | Function | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Function:
"""Create a realistic function object, defining the things the interpreter expects."""
def __init__(self, name, code, globs, defaults, closure, vm):
"""You don't need to follow this closely to understand the interpreter."""
<|body_0|>
def __call__(self, *args, ... | stack_v2_sparse_classes_75kplus_train_002538 | 9,627 | permissive | [
{
"docstring": "You don't need to follow this closely to understand the interpreter.",
"name": "__init__",
"signature": "def __init__(self, name, code, globs, defaults, closure, vm)"
},
{
"docstring": "When calling a Function, make a new frame and run it.",
"name": "__call__",
"signature... | 2 | stack_v2_sparse_classes_30k_train_019492 | Implement the Python class `Function` described below.
Class description:
Create a realistic function object, defining the things the interpreter expects.
Method signatures and docstrings:
- def __init__(self, name, code, globs, defaults, closure, vm): You don't need to follow this closely to understand the interpret... | Implement the Python class `Function` described below.
Class description:
Create a realistic function object, defining the things the interpreter expects.
Method signatures and docstrings:
- def __init__(self, name, code, globs, defaults, closure, vm): You don't need to follow this closely to understand the interpret... | 4f5bdab86c71f503ac3ca7fbf5f81a615e323759 | <|skeleton|>
class Function:
"""Create a realistic function object, defining the things the interpreter expects."""
def __init__(self, name, code, globs, defaults, closure, vm):
"""You don't need to follow this closely to understand the interpreter."""
<|body_0|>
def __call__(self, *args, ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Function:
"""Create a realistic function object, defining the things the interpreter expects."""
def __init__(self, name, code, globs, defaults, closure, vm):
"""You don't need to follow this closely to understand the interpreter."""
self._vm = vm
self.func_code = code
sel... | the_stack_v2_python_sparse | python_advance/about_pyhton/simple_interpreter/interpreter_3.py | Dustyposa/goSpider | train | 66 |
bc99bedaceb1954fb9b593b696182d8fe5d3ac82 | [
"super(pnl_mult_mechanism, self).__init__()\nself.n_causes = ncauses\nself.points = points\nself.noise_function = noise_function\nself.noise_coeff = noise_coeff\nself.f1 = lambda x: np.log(np.sum(x, axis=1))\nself.f2 = lambda x: np.exp(x)",
"effect = np.zeros((self.points, 1))\nself.noise = self.noise_coeff * sel... | <|body_start_0|>
super(pnl_mult_mechanism, self).__init__()
self.n_causes = ncauses
self.points = points
self.noise_function = noise_function
self.noise_coeff = noise_coeff
self.f1 = lambda x: np.log(np.sum(x, axis=1))
self.f2 = lambda x: np.exp(x)
<|end_body_0|>
... | Post-Nonlinear model using a exp and log as the non-linearities. This results in a multiplicative model. | pnl_mult_mechanism | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class pnl_mult_mechanism:
"""Post-Nonlinear model using a exp and log as the non-linearities. This results in a multiplicative model."""
def __init__(self, ncauses, points, noise_function, noise_coeff=0.4):
"""Init the mechanism."""
<|body_0|>
def __call__(self, causes):
... | stack_v2_sparse_classes_75kplus_train_002539 | 32,235 | permissive | [
{
"docstring": "Init the mechanism.",
"name": "__init__",
"signature": "def __init__(self, ncauses, points, noise_function, noise_coeff=0.4)"
},
{
"docstring": "Run the mechanism.",
"name": "__call__",
"signature": "def __call__(self, causes)"
}
] | 2 | null | Implement the Python class `pnl_mult_mechanism` described below.
Class description:
Post-Nonlinear model using a exp and log as the non-linearities. This results in a multiplicative model.
Method signatures and docstrings:
- def __init__(self, ncauses, points, noise_function, noise_coeff=0.4): Init the mechanism.
- d... | Implement the Python class `pnl_mult_mechanism` described below.
Class description:
Post-Nonlinear model using a exp and log as the non-linearities. This results in a multiplicative model.
Method signatures and docstrings:
- def __init__(self, ncauses, points, noise_function, noise_coeff=0.4): Init the mechanism.
- d... | c3428c7e919c4332d7421706e641c74ff7f095cd | <|skeleton|>
class pnl_mult_mechanism:
"""Post-Nonlinear model using a exp and log as the non-linearities. This results in a multiplicative model."""
def __init__(self, ncauses, points, noise_function, noise_coeff=0.4):
"""Init the mechanism."""
<|body_0|>
def __call__(self, causes):
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class pnl_mult_mechanism:
"""Post-Nonlinear model using a exp and log as the non-linearities. This results in a multiplicative model."""
def __init__(self, ncauses, points, noise_function, noise_coeff=0.4):
"""Init the mechanism."""
super(pnl_mult_mechanism, self).__init__()
self.n_caus... | the_stack_v2_python_sparse | data/generation/causal_mechanisms.py | jcai-sc/dcdi | train | 0 |
99671453a9064b94bbb2be4df38348e3e447ccf6 | [
"left = 0\nright = len(numbers) - 1\nwhile left < right:\n num_sum = numbers[left] + numbers[right]\n if num_sum == target:\n return [left + 1, right + 1]\n if num_sum < target:\n left += 1\n else:\n right -= 1\nreturn [-1, -1]",
"num_dict = dict()\nfor index, num in enumerate(num... | <|body_start_0|>
left = 0
right = len(numbers) - 1
while left < right:
num_sum = numbers[left] + numbers[right]
if num_sum == target:
return [left + 1, right + 1]
if num_sum < target:
left += 1
else:
... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def twoSum(self, numbers, target):
"""Time complexity: O(n) Space complexity: O(1) This approach will only work for sorted arr :type numbers: List[int] :type target: int :rtype: List[int]"""
<|body_0|>
def twoSum_approach2(self, numbers, target):
"""Time an... | stack_v2_sparse_classes_75kplus_train_002540 | 1,967 | permissive | [
{
"docstring": "Time complexity: O(n) Space complexity: O(1) This approach will only work for sorted arr :type numbers: List[int] :type target: int :rtype: List[int]",
"name": "twoSum",
"signature": "def twoSum(self, numbers, target)"
},
{
"docstring": "Time and space complexity: O(n) This appro... | 2 | stack_v2_sparse_classes_30k_train_027274 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def twoSum(self, numbers, target): Time complexity: O(n) Space complexity: O(1) This approach will only work for sorted arr :type numbers: List[int] :type target: int :rtype: Lis... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def twoSum(self, numbers, target): Time complexity: O(n) Space complexity: O(1) This approach will only work for sorted arr :type numbers: List[int] :type target: int :rtype: Lis... | c7e5b6692ad6772b38de8be029bddf0e273e0bce | <|skeleton|>
class Solution:
def twoSum(self, numbers, target):
"""Time complexity: O(n) Space complexity: O(1) This approach will only work for sorted arr :type numbers: List[int] :type target: int :rtype: List[int]"""
<|body_0|>
def twoSum_approach2(self, numbers, target):
"""Time an... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def twoSum(self, numbers, target):
"""Time complexity: O(n) Space complexity: O(1) This approach will only work for sorted arr :type numbers: List[int] :type target: int :rtype: List[int]"""
left = 0
right = len(numbers) - 1
while left < right:
num_sum = n... | the_stack_v2_python_sparse | arr_str/two_sum_sorted_arr.py | mantoshkumar1/interview_preparation | train | 1 | |
72a42ce091c0aa7848c546124b383abd8b2bed97 | [
"super().__init__()\nself.in_channels = in_channels\nself.out_channels = out_channels\nself.conv1_1 = nn.Sequential(*[nn.Conv2d(in_channels, in_channels, kernel_size=3, padding=1), nn.PReLU()] * 2)\nself.down1 = nn.Conv2d(in_channels, in_channels * 2, kernel_size=3, stride=2, padding=1)\nself.conv2_1 = nn.Sequentia... | <|body_start_0|>
super().__init__()
self.in_channels = in_channels
self.out_channels = out_channels
self.conv1_1 = nn.Sequential(*[nn.Conv2d(in_channels, in_channels, kernel_size=3, padding=1), nn.PReLU()] * 2)
self.down1 = nn.Conv2d(in_channels, in_channels * 2, kernel_size=3, s... | Down-up block (DUB) for :class:`DIDN` model as implemented in [1]_. References ---------- .. [1] Yu, Songhyun, et al. “Deep Iterative Down-Up CNN for Image Denoising.” 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2019, pp. 2095–103. IEEE Xplore, https://doi.org/10.1109/CVPRW.20... | DUB | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DUB:
"""Down-up block (DUB) for :class:`DIDN` model as implemented in [1]_. References ---------- .. [1] Yu, Songhyun, et al. “Deep Iterative Down-Up CNN for Image Denoising.” 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2019, pp. 2095–103. IEEE Xplore, h... | stack_v2_sparse_classes_75kplus_train_002541 | 12,259 | permissive | [
{
"docstring": "Inits :class:`DUB`. Parameters ---------- in_channels: int Number of input channels. out_channels: int Number of output channels.",
"name": "__init__",
"signature": "def __init__(self, in_channels: int, out_channels: int)"
},
{
"docstring": "Pads input to height and width dimensi... | 4 | stack_v2_sparse_classes_30k_train_050985 | Implement the Python class `DUB` described below.
Class description:
Down-up block (DUB) for :class:`DIDN` model as implemented in [1]_. References ---------- .. [1] Yu, Songhyun, et al. “Deep Iterative Down-Up CNN for Image Denoising.” 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVP... | Implement the Python class `DUB` described below.
Class description:
Down-up block (DUB) for :class:`DIDN` model as implemented in [1]_. References ---------- .. [1] Yu, Songhyun, et al. “Deep Iterative Down-Up CNN for Image Denoising.” 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVP... | 2a4c29342bc52a404aae097bc2654fb4323e1ac8 | <|skeleton|>
class DUB:
"""Down-up block (DUB) for :class:`DIDN` model as implemented in [1]_. References ---------- .. [1] Yu, Songhyun, et al. “Deep Iterative Down-Up CNN for Image Denoising.” 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2019, pp. 2095–103. IEEE Xplore, h... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DUB:
"""Down-up block (DUB) for :class:`DIDN` model as implemented in [1]_. References ---------- .. [1] Yu, Songhyun, et al. “Deep Iterative Down-Up CNN for Image Denoising.” 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2019, pp. 2095–103. IEEE Xplore, https://doi.or... | the_stack_v2_python_sparse | direct/nn/didn/didn.py | NKI-AI/direct | train | 151 |
d6e38f29f64dd6bca4ef3fbd1af87e04f30ac82d | [
"self.min_sigma = min_sigma\nself.max_sigma = max_sigma\nself.threshold = threshold",
"img = img_as_float(img_array)\npeaks = blob_dog(img, min_sigma=self.min_sigma, max_sigma=self.max_sigma, threshold=self.threshold)\npeaks = peaks[:, [0, 1]] = peaks[:, [1, 0]]\nreturn peaks"
] | <|body_start_0|>
self.min_sigma = min_sigma
self.max_sigma = max_sigma
self.threshold = threshold
<|end_body_0|>
<|body_start_1|>
img = img_as_float(img_array)
peaks = blob_dog(img, min_sigma=self.min_sigma, max_sigma=self.max_sigma, threshold=self.threshold)
peaks = pea... | A class using difference of gaussian to find peaks. It uses skimage blob_dog internally. ... Attributes ---------- min_sigma (float) max_sigma (int) threshold (float) | PeakFinderDifferenceOfGaussian | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PeakFinderDifferenceOfGaussian:
"""A class using difference of gaussian to find peaks. It uses skimage blob_dog internally. ... Attributes ---------- min_sigma (float) max_sigma (int) threshold (float)"""
def __init__(self, min_sigma=0.75, max_sigma=3, threshold=0.1):
"""For more det... | stack_v2_sparse_classes_75kplus_train_002542 | 4,440 | permissive | [
{
"docstring": "For more detailed information about the parameters in the constructor refer to blob_dog from skimage.feature. Args: min_sigma (float, optional): Defaults to 0.75. max_sigma (int, optional): Defaults to 3. threshold (float, optional): Defaults to 0.1.",
"name": "__init__",
"signature": "d... | 2 | stack_v2_sparse_classes_30k_train_046315 | Implement the Python class `PeakFinderDifferenceOfGaussian` described below.
Class description:
A class using difference of gaussian to find peaks. It uses skimage blob_dog internally. ... Attributes ---------- min_sigma (float) max_sigma (int) threshold (float)
Method signatures and docstrings:
- def __init__(self, ... | Implement the Python class `PeakFinderDifferenceOfGaussian` described below.
Class description:
A class using difference of gaussian to find peaks. It uses skimage blob_dog internally. ... Attributes ---------- min_sigma (float) max_sigma (int) threshold (float)
Method signatures and docstrings:
- def __init__(self, ... | 1358c9817150316be4de6093212ce2f71059d472 | <|skeleton|>
class PeakFinderDifferenceOfGaussian:
"""A class using difference of gaussian to find peaks. It uses skimage blob_dog internally. ... Attributes ---------- min_sigma (float) max_sigma (int) threshold (float)"""
def __init__(self, min_sigma=0.75, max_sigma=3, threshold=0.1):
"""For more det... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PeakFinderDifferenceOfGaussian:
"""A class using difference of gaussian to find peaks. It uses skimage blob_dog internally. ... Attributes ---------- min_sigma (float) max_sigma (int) threshold (float)"""
def __init__(self, min_sigma=0.75, max_sigma=3, threshold=0.1):
"""For more detailed informa... | the_stack_v2_python_sparse | situr/registration/peak_finder.py | 13hannes11/situr | train | 0 |
10b71fa8bdcf6b8cd492f95f819d3ec6154053f0 | [
"target = RegistrationForm({'email': 'test@example.com', 'password1': 'pw1', 'password2': 'invalid'})\nresult = target.is_valid()\nself.assertFalse(result)",
"target = RegistrationForm({'email': 'test@example.com', 'password1': 'passwd', 'password2': 'passwd'})\nresult = target.is_valid()\nself.assertTrue(result)... | <|body_start_0|>
target = RegistrationForm({'email': 'test@example.com', 'password1': 'pw1', 'password2': 'invalid'})
result = target.is_valid()
self.assertFalse(result)
<|end_body_0|>
<|body_start_1|>
target = RegistrationForm({'email': 'test@example.com', 'password1': 'passwd', 'passw... | RegistrationFormTest | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RegistrationFormTest:
def test_form_invalid_if_password2_not_equal_to_password1(self):
"""Form should not validate if password1 != password2."""
<|body_0|>
def test_form_valid_if_password2_equals_password1(self):
"""Form should validate if password1 == password2, no ... | stack_v2_sparse_classes_75kplus_train_002543 | 1,866 | no_license | [
{
"docstring": "Form should not validate if password1 != password2.",
"name": "test_form_invalid_if_password2_not_equal_to_password1",
"signature": "def test_form_invalid_if_password2_not_equal_to_password1(self)"
},
{
"docstring": "Form should validate if password1 == password2, no other errors... | 3 | stack_v2_sparse_classes_30k_train_027201 | Implement the Python class `RegistrationFormTest` described below.
Class description:
Implement the RegistrationFormTest class.
Method signatures and docstrings:
- def test_form_invalid_if_password2_not_equal_to_password1(self): Form should not validate if password1 != password2.
- def test_form_valid_if_password2_eq... | Implement the Python class `RegistrationFormTest` described below.
Class description:
Implement the RegistrationFormTest class.
Method signatures and docstrings:
- def test_form_invalid_if_password2_not_equal_to_password1(self): Form should not validate if password1 != password2.
- def test_form_valid_if_password2_eq... | 41281b6343b457721dc60df88cf6593497f73574 | <|skeleton|>
class RegistrationFormTest:
def test_form_invalid_if_password2_not_equal_to_password1(self):
"""Form should not validate if password1 != password2."""
<|body_0|>
def test_form_valid_if_password2_equals_password1(self):
"""Form should validate if password1 == password2, no ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class RegistrationFormTest:
def test_form_invalid_if_password2_not_equal_to_password1(self):
"""Form should not validate if password1 != password2."""
target = RegistrationForm({'email': 'test@example.com', 'password1': 'pw1', 'password2': 'invalid'})
result = target.is_valid()
self.... | the_stack_v2_python_sparse | src/polishedpagessite/polishedpages/tests.py | platinumazure/polishedpagessite | train | 0 | |
2bcc26ffb1c27bcaf985127d8bdbf6d8b001b5a6 | [
"assert isinstance(radicand, Fixed)\nassert radicand.signed is False\nself.radicand = radicand\nself.root = radicand.with_bits(0)\nself.root_squared = self.root * self.root\nself.remainder = radicand.with_bits(0) - self.root_squared\nself.log2_radix = log2_radix\nself.current_shift = self.root.bit_width",
"if sel... | <|body_start_0|>
assert isinstance(radicand, Fixed)
assert radicand.signed is False
self.radicand = radicand
self.root = radicand.with_bits(0)
self.root_squared = self.root * self.root
self.remainder = radicand.with_bits(0) - self.root_squared
self.log2_radix = lo... | Fixed-point Square-Root/Remainder. :attribute radicand: the radicand :attribute root: the square root :attribute root_squared: the square of ``root`` :attribute remainder: the remainder :attribute log2_radix: the base-2 log of the operation radix. The number of bits of root that are calculated per pipeline stage. :attr... | FixedSqrt | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FixedSqrt:
"""Fixed-point Square-Root/Remainder. :attribute radicand: the radicand :attribute root: the square root :attribute root_squared: the square of ``root`` :attribute remainder: the remainder :attribute log2_radix: the base-2 log of the operation radix. The number of bits of root that are... | stack_v2_sparse_classes_75kplus_train_002544 | 30,970 | no_license | [
{
"docstring": "Create an FixedSqrt. :param radicand: the radicand. :param log2_radix: the base-2 log of the operation radix. The number of bits of root that are calculated per pipeline stage.",
"name": "__init__",
"signature": "def __init__(self, radicand, log2_radix=3)"
},
{
"docstring": "Calc... | 3 | null | Implement the Python class `FixedSqrt` described below.
Class description:
Fixed-point Square-Root/Remainder. :attribute radicand: the radicand :attribute root: the square root :attribute root_squared: the square of ``root`` :attribute remainder: the remainder :attribute log2_radix: the base-2 log of the operation rad... | Implement the Python class `FixedSqrt` described below.
Class description:
Fixed-point Square-Root/Remainder. :attribute radicand: the radicand :attribute root: the square root :attribute root_squared: the square of ``root`` :attribute remainder: the remainder :attribute log2_radix: the base-2 log of the operation rad... | 0cdf4be4df5c0fbae476442c1a91b0e8140e2104 | <|skeleton|>
class FixedSqrt:
"""Fixed-point Square-Root/Remainder. :attribute radicand: the radicand :attribute root: the square root :attribute root_squared: the square of ``root`` :attribute remainder: the remainder :attribute log2_radix: the base-2 log of the operation radix. The number of bits of root that are... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class FixedSqrt:
"""Fixed-point Square-Root/Remainder. :attribute radicand: the radicand :attribute root: the square root :attribute root_squared: the square of ``root`` :attribute remainder: the remainder :attribute log2_radix: the base-2 log of the operation radix. The number of bits of root that are calculated p... | the_stack_v2_python_sparse | src/ieee754/div_rem_sqrt_rsqrt/algorithm.py | ChipFlow/ieee754fpu | train | 0 |
a1f1bd251c00e0d0a305201824497f2a57718bcd | [
"hashmap = {}\nmax_len, dp = (0, 0)\nfor idx, x in enumerate(s):\n last_idx = hashmap.get(x, -1)\n hashmap[x] = idx\n if dp < idx - last_idx:\n dp += 1\n else:\n dp = idx - last_idx\n max_len = max(max_len, dp)\nreturn max_len",
"hashmap = {}\nstart, max_len = (0, 0)\nfor idx, x in en... | <|body_start_0|>
hashmap = {}
max_len, dp = (0, 0)
for idx, x in enumerate(s):
last_idx = hashmap.get(x, -1)
hashmap[x] = idx
if dp < idx - last_idx:
dp += 1
else:
dp = idx - last_idx
max_len = max(max_le... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def lengthOfLongestSubstring(self, s: str) -> int:
"""动态规划"""
<|body_0|>
def lengthOfLongestSubstringSlidingWindows(self, s: str) -> int:
"""滑动窗口"""
<|body_1|>
def lengthOfLongestSubstringSlidingWindows2(self, s: str) -> int:
"""滑动窗口（优化... | stack_v2_sparse_classes_75kplus_train_002545 | 3,304 | no_license | [
{
"docstring": "动态规划",
"name": "lengthOfLongestSubstring",
"signature": "def lengthOfLongestSubstring(self, s: str) -> int"
},
{
"docstring": "滑动窗口",
"name": "lengthOfLongestSubstringSlidingWindows",
"signature": "def lengthOfLongestSubstringSlidingWindows(self, s: str) -> int"
},
{
... | 3 | stack_v2_sparse_classes_30k_train_028847 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def lengthOfLongestSubstring(self, s: str) -> int: 动态规划
- def lengthOfLongestSubstringSlidingWindows(self, s: str) -> int: 滑动窗口
- def lengthOfLongestSubstringSlidingWindows2(self... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def lengthOfLongestSubstring(self, s: str) -> int: 动态规划
- def lengthOfLongestSubstringSlidingWindows(self, s: str) -> int: 滑动窗口
- def lengthOfLongestSubstringSlidingWindows2(self... | 52756b30e9d51794591aca030bc918e707f473f1 | <|skeleton|>
class Solution:
def lengthOfLongestSubstring(self, s: str) -> int:
"""动态规划"""
<|body_0|>
def lengthOfLongestSubstringSlidingWindows(self, s: str) -> int:
"""滑动窗口"""
<|body_1|>
def lengthOfLongestSubstringSlidingWindows2(self, s: str) -> int:
"""滑动窗口（优化... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def lengthOfLongestSubstring(self, s: str) -> int:
"""动态规划"""
hashmap = {}
max_len, dp = (0, 0)
for idx, x in enumerate(s):
last_idx = hashmap.get(x, -1)
hashmap[x] = idx
if dp < idx - last_idx:
dp += 1
e... | the_stack_v2_python_sparse | 3.无重复字符的最长子串/solution.py | QtTao/daily_leetcode | train | 0 | |
f9253e6a9ac773fb0e52eee3ed8bc848ce0e7e0d | [
"self.first_name = first_name\nself.last_name = last_name\nself.middle_name = middle_name\nself.fullname = fullname\nself.address = address\nself.address_2 = address_2\nself.city = city\nself.postal_code = postal_code\nself.gender = gender\nself.raw_json = raw_json\nself.request_id = request_id\nself.additional_pro... | <|body_start_0|>
self.first_name = first_name
self.last_name = last_name
self.middle_name = middle_name
self.fullname = fullname
self.address = address
self.address_2 = address_2
self.city = city
self.postal_code = postal_code
self.gender = gender
... | Implementation of the 'Person.OfficialPersonRegistryResponse' model. TODO: type model description here. Attributes: first_name (string): TODO: type description here. last_name (string): TODO: type description here. middle_name (string): TODO: type description here. fullname (string): TODO: type description here. addres... | PersonOfficialPersonRegistryResponse | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PersonOfficialPersonRegistryResponse:
"""Implementation of the 'Person.OfficialPersonRegistryResponse' model. TODO: type model description here. Attributes: first_name (string): TODO: type description here. last_name (string): TODO: type description here. middle_name (string): TODO: type descript... | stack_v2_sparse_classes_75kplus_train_002546 | 4,269 | permissive | [
{
"docstring": "Constructor for the PersonOfficialPersonRegistryResponse class",
"name": "__init__",
"signature": "def __init__(self, first_name=None, last_name=None, middle_name=None, fullname=None, address=None, address_2=None, city=None, postal_code=None, gender=None, raw_json=None, request_id=None, ... | 2 | stack_v2_sparse_classes_30k_train_028949 | Implement the Python class `PersonOfficialPersonRegistryResponse` described below.
Class description:
Implementation of the 'Person.OfficialPersonRegistryResponse' model. TODO: type model description here. Attributes: first_name (string): TODO: type description here. last_name (string): TODO: type description here. mi... | Implement the Python class `PersonOfficialPersonRegistryResponse` described below.
Class description:
Implementation of the 'Person.OfficialPersonRegistryResponse' model. TODO: type model description here. Attributes: first_name (string): TODO: type description here. last_name (string): TODO: type description here. mi... | fa3918a6c54ea0eedb9146578645b7eb1755b642 | <|skeleton|>
class PersonOfficialPersonRegistryResponse:
"""Implementation of the 'Person.OfficialPersonRegistryResponse' model. TODO: type model description here. Attributes: first_name (string): TODO: type description here. last_name (string): TODO: type description here. middle_name (string): TODO: type descript... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PersonOfficialPersonRegistryResponse:
"""Implementation of the 'Person.OfficialPersonRegistryResponse' model. TODO: type model description here. Attributes: first_name (string): TODO: type description here. last_name (string): TODO: type description here. middle_name (string): TODO: type description here. ful... | the_stack_v2_python_sparse | idfy_rest_client/models/person_official_person_registry_response.py | dealflowteam/Idfy | train | 0 |
f527802f5029eb6b7c7ff35199a6b244b815717b | [
"if not EditDefaultRightPermission.can() and (not EditSpecialRightPermission.can()):\n if current_user.id == profile_id:\n permissions = {action.value: True for action in DEFAULT_ACTIONS}\n permissions.update({p.name: p.is_allowed for p in current_user.permissions_backref.all() if p.is_allowed or A... | <|body_start_0|>
if not EditDefaultRightPermission.can() and (not EditSpecialRightPermission.can()):
if current_user.id == profile_id:
permissions = {action.value: True for action in DEFAULT_ACTIONS}
permissions.update({p.name: p.is_allowed for p in current_user.permi... | ProfilePermissionResource | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProfilePermissionResource:
def get(self, profile_id):
"""Get profile permissions * User can view all **their allowed** permissions * User with permission to **"edit default rights"** can view user permissions from **default list** * User with permission to **"edit special rights"** can v... | stack_v2_sparse_classes_75kplus_train_002547 | 5,086 | permissive | [
{
"docstring": "Get profile permissions * User can view all **their allowed** permissions * User with permission to **\"edit default rights\"** can view user permissions from **default list** * User with permission to **\"edit special rights\"** can view user permissions from **special list**",
"name": "get... | 2 | stack_v2_sparse_classes_30k_train_023232 | Implement the Python class `ProfilePermissionResource` described below.
Class description:
Implement the ProfilePermissionResource class.
Method signatures and docstrings:
- def get(self, profile_id): Get profile permissions * User can view all **their allowed** permissions * User with permission to **"edit default r... | Implement the Python class `ProfilePermissionResource` described below.
Class description:
Implement the ProfilePermissionResource class.
Method signatures and docstrings:
- def get(self, profile_id): Get profile permissions * User can view all **their allowed** permissions * User with permission to **"edit default r... | dce87ffe395ae4bd08b47f28e07594e1889da819 | <|skeleton|>
class ProfilePermissionResource:
def get(self, profile_id):
"""Get profile permissions * User can view all **their allowed** permissions * User with permission to **"edit default rights"** can view user permissions from **default list** * User with permission to **"edit special rights"** can v... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ProfilePermissionResource:
def get(self, profile_id):
"""Get profile permissions * User can view all **their allowed** permissions * User with permission to **"edit default rights"** can view user permissions from **default list** * User with permission to **"edit special rights"** can view user permi... | the_stack_v2_python_sparse | src/backend/app/api/public/profiles/profile/profile_permissions.py | aimanow/sft | train | 0 | |
d2fa83480e237acc950312da0f4d2398ab49f3d1 | [
"self.results['status'] = 1\nself.results['data'] = 'this is a plate!'\nreturn jsonify(self.results)",
"args = self._pop_args(args, arglist=['plateid'])\nplate, results = _getPlate(plateid, nocubes=True, **args)\nself.update_results(results)\nif not isinstance(plate, type(None)):\n platedict = {'plateid': plat... | <|body_start_0|>
self.results['status'] = 1
self.results['data'] = 'this is a plate!'
return jsonify(self.results)
<|end_body_0|>
<|body_start_1|>
args = self._pop_args(args, arglist=['plateid'])
plate, results = _getPlate(plateid, nocubes=True, **args)
self.update_resul... | Class describing API calls related to plates. | PlateView | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PlateView:
"""Class describing API calls related to plates."""
def index(self):
"""Returns general maps info .. :quickref: Plate; Get general plate info :form release: the release of MaNGA data :resjson int status: status of response. 1 if good, -1 if bad. :resjson string error: erro... | stack_v2_sparse_classes_75kplus_train_002548 | 6,678 | permissive | [
{
"docstring": "Returns general maps info .. :quickref: Plate; Get general plate info :form release: the release of MaNGA data :resjson int status: status of response. 1 if good, -1 if bad. :resjson string error: error message, null if None :resjson json inconfig: json of incoming configuration :resjson json ut... | 3 | null | Implement the Python class `PlateView` described below.
Class description:
Class describing API calls related to plates.
Method signatures and docstrings:
- def index(self): Returns general maps info .. :quickref: Plate; Get general plate info :form release: the release of MaNGA data :resjson int status: status of re... | Implement the Python class `PlateView` described below.
Class description:
Class describing API calls related to plates.
Method signatures and docstrings:
- def index(self): Returns general maps info .. :quickref: Plate; Get general plate info :form release: the release of MaNGA data :resjson int status: status of re... | db4c536a65fb2f16fee05a4f34996a7fd35f0527 | <|skeleton|>
class PlateView:
"""Class describing API calls related to plates."""
def index(self):
"""Returns general maps info .. :quickref: Plate; Get general plate info :form release: the release of MaNGA data :resjson int status: status of response. 1 if good, -1 if bad. :resjson string error: erro... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PlateView:
"""Class describing API calls related to plates."""
def index(self):
"""Returns general maps info .. :quickref: Plate; Get general plate info :form release: the release of MaNGA data :resjson int status: status of response. 1 if good, -1 if bad. :resjson string error: error message, nu... | the_stack_v2_python_sparse | python/marvin/api/plate.py | sdss/marvin | train | 56 |
ad112c043252fb4975bd1393214c294bfbb27f78 | [
"self.mount_a.run_shell(['mkdir', 'subdir'])\nself.assertEqual(self.mount_a.getfattr('./subdir', 'ceph.quota.max_files'), None)\nself.assertEqual(self.mount_b.getfattr('./subdir', 'ceph.quota.max_files'), None)\nself.mount_a.setfattr('./subdir', 'ceph.quota.max_files', '10')\nself.assertEqual(self.mount_a.getfattr(... | <|body_start_0|>
self.mount_a.run_shell(['mkdir', 'subdir'])
self.assertEqual(self.mount_a.getfattr('./subdir', 'ceph.quota.max_files'), None)
self.assertEqual(self.mount_b.getfattr('./subdir', 'ceph.quota.max_files'), None)
self.mount_a.setfattr('./subdir', 'ceph.quota.max_files', '10')... | TestQuota | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestQuota:
def test_remote_update_getfattr(self):
"""That quota changes made from one client are visible to another client looking at ceph.quota xattrs"""
<|body_0|>
def test_remote_update_df(self):
"""That when a client modifies the quota on a directory used as anot... | stack_v2_sparse_classes_75kplus_train_002549 | 3,808 | permissive | [
{
"docstring": "That quota changes made from one client are visible to another client looking at ceph.quota xattrs",
"name": "test_remote_update_getfattr",
"signature": "def test_remote_update_getfattr(self)"
},
{
"docstring": "That when a client modifies the quota on a directory used as another... | 3 | stack_v2_sparse_classes_30k_train_011121 | Implement the Python class `TestQuota` described below.
Class description:
Implement the TestQuota class.
Method signatures and docstrings:
- def test_remote_update_getfattr(self): That quota changes made from one client are visible to another client looking at ceph.quota xattrs
- def test_remote_update_df(self): Tha... | Implement the Python class `TestQuota` described below.
Class description:
Implement the TestQuota class.
Method signatures and docstrings:
- def test_remote_update_getfattr(self): That quota changes made from one client are visible to another client looking at ceph.quota xattrs
- def test_remote_update_df(self): Tha... | 6a0747b6b79f5ca814afca6cefeb45f52fb9a509 | <|skeleton|>
class TestQuota:
def test_remote_update_getfattr(self):
"""That quota changes made from one client are visible to another client looking at ceph.quota xattrs"""
<|body_0|>
def test_remote_update_df(self):
"""That when a client modifies the quota on a directory used as anot... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TestQuota:
def test_remote_update_getfattr(self):
"""That quota changes made from one client are visible to another client looking at ceph.quota xattrs"""
self.mount_a.run_shell(['mkdir', 'subdir'])
self.assertEqual(self.mount_a.getfattr('./subdir', 'ceph.quota.max_files'), None)
... | the_stack_v2_python_sparse | qa/tasks/cephfs/test_quota.py | SrinivasaBharath/ceph-1 | train | 0 | |
0edde025936976aa089bd6cf642279cdd08c7033 | [
"super().__init__()\nself.image = None\nself.name = ''\nself.color = ''\nself.screen = chess_game.screen\nself.x, self.y = (0.0, 0.0)",
"self.rect = self.image.get_rect()\nself.rect.topleft = (self.x, self.y)\nself.screen.blit(self.image, self.rect)"
] | <|body_start_0|>
super().__init__()
self.image = None
self.name = ''
self.color = ''
self.screen = chess_game.screen
self.x, self.y = (0.0, 0.0)
<|end_body_0|>
<|body_start_1|>
self.rect = self.image.get_rect()
self.rect.topleft = (self.x, self.y)
... | Represents a chess piece. | Piece | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Piece:
"""Represents a chess piece."""
def __init__(self, chess_game):
"""Initialize attributes to represent a ches piece."""
<|body_0|>
def blitme(self):
"""Draw the piece at its current location."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_75kplus_train_002550 | 2,009 | permissive | [
{
"docstring": "Initialize attributes to represent a ches piece.",
"name": "__init__",
"signature": "def __init__(self, chess_game)"
},
{
"docstring": "Draw the piece at its current location.",
"name": "blitme",
"signature": "def blitme(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_018428 | Implement the Python class `Piece` described below.
Class description:
Represents a chess piece.
Method signatures and docstrings:
- def __init__(self, chess_game): Initialize attributes to represent a ches piece.
- def blitme(self): Draw the piece at its current location. | Implement the Python class `Piece` described below.
Class description:
Represents a chess piece.
Method signatures and docstrings:
- def __init__(self, chess_game): Initialize attributes to represent a ches piece.
- def blitme(self): Draw the piece at its current location.
<|skeleton|>
class Piece:
"""Represents... | 2cb4b45dd14a230aa0e800042e893f8dfb23beda | <|skeleton|>
class Piece:
"""Represents a chess piece."""
def __init__(self, chess_game):
"""Initialize attributes to represent a ches piece."""
<|body_0|>
def blitme(self):
"""Draw the piece at its current location."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Piece:
"""Represents a chess piece."""
def __init__(self, chess_game):
"""Initialize attributes to represent a ches piece."""
super().__init__()
self.image = None
self.name = ''
self.color = ''
self.screen = chess_game.screen
self.x, self.y = (0.0, ... | the_stack_v2_python_sparse | MY_REPOS/Lambda-Resource-Static-Assets/2-resources/BLOG/Python/pcc_2e-master/beyond_pcc/chess_game/chess_set.py | bgoonz/UsefulResourceRepo2.0 | train | 10 |
03196855ad0052f6a2694db96c11224dafa9a81d | [
"if not hasattr(cls, '_instance'):\n with cls._instance_lock:\n if not hasattr(cls, '_instance'):\n cls._instance = object.__new__(cls)\nreturn cls._instance",
"self.common = Common()\ntry:\n log_path = self.common.get_result_path('result.log')\n self.logger = logging.getLogger()\n s... | <|body_start_0|>
if not hasattr(cls, '_instance'):
with cls._instance_lock:
if not hasattr(cls, '_instance'):
cls._instance = object.__new__(cls)
return cls._instance
<|end_body_0|>
<|body_start_1|>
self.common = Common()
try:
... | Log | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Log:
def __new__(cls, *args, **kwargs):
"""单例模式(支持多线程)"""
<|body_0|>
def __init__(self):
"""配置日志数据"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not hasattr(cls, '_instance'):
with cls._instance_lock:
if not hasattr(... | stack_v2_sparse_classes_75kplus_train_002551 | 6,658 | no_license | [
{
"docstring": "单例模式(支持多线程)",
"name": "__new__",
"signature": "def __new__(cls, *args, **kwargs)"
},
{
"docstring": "配置日志数据",
"name": "__init__",
"signature": "def __init__(self)"
}
] | 2 | null | Implement the Python class `Log` described below.
Class description:
Implement the Log class.
Method signatures and docstrings:
- def __new__(cls, *args, **kwargs): 单例模式(支持多线程)
- def __init__(self): 配置日志数据 | Implement the Python class `Log` described below.
Class description:
Implement the Log class.
Method signatures and docstrings:
- def __new__(cls, *args, **kwargs): 单例模式(支持多线程)
- def __init__(self): 配置日志数据
<|skeleton|>
class Log:
def __new__(cls, *args, **kwargs):
"""单例模式(支持多线程)"""
<|body_0|>
... | c6f1f8cef08107b6a791b7be16b008677cac69ba | <|skeleton|>
class Log:
def __new__(cls, *args, **kwargs):
"""单例模式(支持多线程)"""
<|body_0|>
def __init__(self):
"""配置日志数据"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Log:
def __new__(cls, *args, **kwargs):
"""单例模式(支持多线程)"""
if not hasattr(cls, '_instance'):
with cls._instance_lock:
if not hasattr(cls, '_instance'):
cls._instance = object.__new__(cls)
return cls._instance
def __init__(self):
... | the_stack_v2_python_sparse | NT/common/log.py | lm2579250/auto_test_python | train | 0 | |
a380af8b06f859908c3182ff1eaffe3a48b14fff | [
"self.n_sent = 1\nself.data = data\nself.empty = False\nagg_func = lambda s: [(w, p, t) for w, p, t in zip(s['Word'].values.tolist(), s['POS'].values.tolist(), s['Tag'].values.tolist())]\nself.grouped = self.data.groupby('Sentence #').apply(agg_func)\nself.sentences = [s for s in self.grouped]",
"try:\n s = se... | <|body_start_0|>
self.n_sent = 1
self.data = data
self.empty = False
agg_func = lambda s: [(w, p, t) for w, p, t in zip(s['Word'].values.tolist(), s['POS'].values.tolist(), s['Tag'].values.tolist())]
self.grouped = self.data.groupby('Sentence #').apply(agg_func)
self.sent... | SentenceGetter | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SentenceGetter:
def __init__(self, data):
"""Args: data is the pandas.DataFrame which contains the above dataset"""
<|body_0|>
def get_next(self):
"""Return one sentence"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.n_sent = 1
self.da... | stack_v2_sparse_classes_75kplus_train_002552 | 6,255 | no_license | [
{
"docstring": "Args: data is the pandas.DataFrame which contains the above dataset",
"name": "__init__",
"signature": "def __init__(self, data)"
},
{
"docstring": "Return one sentence",
"name": "get_next",
"signature": "def get_next(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_021746 | Implement the Python class `SentenceGetter` described below.
Class description:
Implement the SentenceGetter class.
Method signatures and docstrings:
- def __init__(self, data): Args: data is the pandas.DataFrame which contains the above dataset
- def get_next(self): Return one sentence | Implement the Python class `SentenceGetter` described below.
Class description:
Implement the SentenceGetter class.
Method signatures and docstrings:
- def __init__(self, data): Args: data is the pandas.DataFrame which contains the above dataset
- def get_next(self): Return one sentence
<|skeleton|>
class SentenceGe... | bf09d7700766706ff27b83ef68de6dc5e77f90aa | <|skeleton|>
class SentenceGetter:
def __init__(self, data):
"""Args: data is the pandas.DataFrame which contains the above dataset"""
<|body_0|>
def get_next(self):
"""Return one sentence"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SentenceGetter:
def __init__(self, data):
"""Args: data is the pandas.DataFrame which contains the above dataset"""
self.n_sent = 1
self.data = data
self.empty = False
agg_func = lambda s: [(w, p, t) for w, p, t in zip(s['Word'].values.tolist(), s['POS'].values.tolist()... | the_stack_v2_python_sparse | icd10_model.py | mfshiu/ner_bilstm | train | 0 | |
da94067534fe0d909b4cddfb4a5d47467b9dd595 | [
"global COMPANY_CONN\ncursor = None\ntry:\n cursor = COMPANY_CONN.cursor(buffered=True, dictionary=True)\n sql = 'INSERT INTO lie_goods' + '(cat_id, items_id, goods_sn, goods_name, brand_id,' + 'min_buynum, goods_desc) ' + 'VALUES(%(cat_id)s, %(items_id)s, %(goods_sn)s,%(goods_name)s, %(brand_id)s, %(min_buyn... | <|body_start_0|>
global COMPANY_CONN
cursor = None
try:
cursor = COMPANY_CONN.cursor(buffered=True, dictionary=True)
sql = 'INSERT INTO lie_goods' + '(cat_id, items_id, goods_sn, goods_name, brand_id,' + 'min_buynum, goods_desc) ' + 'VALUES(%(cat_id)s, %(items_id)s, %(goo... | LieGoods | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LieGoods:
def addLieGoods(cls, lieGoods):
"""method: addLieGoods params: lieGoods-type: LieGoods"""
<|body_0|>
def get_goods_id_by_goods_sn(cls, goods_sn_md5):
"""method: get_goods_id_by_goods_sn params: goods_sn_md5-type: str return: goods_id return-type: int"""
... | stack_v2_sparse_classes_75kplus_train_002553 | 13,174 | no_license | [
{
"docstring": "method: addLieGoods params: lieGoods-type: LieGoods",
"name": "addLieGoods",
"signature": "def addLieGoods(cls, lieGoods)"
},
{
"docstring": "method: get_goods_id_by_goods_sn params: goods_sn_md5-type: str return: goods_id return-type: int",
"name": "get_goods_id_by_goods_sn"... | 2 | stack_v2_sparse_classes_30k_train_034354 | Implement the Python class `LieGoods` described below.
Class description:
Implement the LieGoods class.
Method signatures and docstrings:
- def addLieGoods(cls, lieGoods): method: addLieGoods params: lieGoods-type: LieGoods
- def get_goods_id_by_goods_sn(cls, goods_sn_md5): method: get_goods_id_by_goods_sn params: go... | Implement the Python class `LieGoods` described below.
Class description:
Implement the LieGoods class.
Method signatures and docstrings:
- def addLieGoods(cls, lieGoods): method: addLieGoods params: lieGoods-type: LieGoods
- def get_goods_id_by_goods_sn(cls, goods_sn_md5): method: get_goods_id_by_goods_sn params: go... | 1e49a6e13ea4b11427f47999c13a609be9ae3ecf | <|skeleton|>
class LieGoods:
def addLieGoods(cls, lieGoods):
"""method: addLieGoods params: lieGoods-type: LieGoods"""
<|body_0|>
def get_goods_id_by_goods_sn(cls, goods_sn_md5):
"""method: get_goods_id_by_goods_sn params: goods_sn_md5-type: str return: goods_id return-type: int"""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class LieGoods:
def addLieGoods(cls, lieGoods):
"""method: addLieGoods params: lieGoods-type: LieGoods"""
global COMPANY_CONN
cursor = None
try:
cursor = COMPANY_CONN.cursor(buffered=True, dictionary=True)
sql = 'INSERT INTO lie_goods' + '(cat_id, items_id, go... | the_stack_v2_python_sparse | rsonline/server/db/company/mysql_client.py | yunhao-qing/PythonScrapy | train | 0 | |
1a55c6789e5d75c60c38e232bfa5b6b43938252d | [
"if len(s) < 2:\n return s\nss = s + '#' + s[::-1]\nlength, M = (0, len(ss))\ni, lps = (1, [0] * M)\nwhile i < M:\n if ss[i] == ss[length]:\n length += 1\n lps[i] = length\n i += 1\n elif length == 0:\n lps[i] = 0\n i += 1\n else:\n length = lps[length - 1]\nret... | <|body_start_0|>
if len(s) < 2:
return s
ss = s + '#' + s[::-1]
length, M = (0, len(ss))
i, lps = (1, [0] * M)
while i < M:
if ss[i] == ss[length]:
length += 1
lps[i] = length
i += 1
elif length =... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def shortestPalindrome(self, s):
""":type s: str :rtype: str"""
<|body_0|>
def shortestPalindrome2(self, s):
""":type s: str :rtype: str"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if len(s) < 2:
return s
ss = s + '... | stack_v2_sparse_classes_75kplus_train_002554 | 2,505 | no_license | [
{
"docstring": ":type s: str :rtype: str",
"name": "shortestPalindrome",
"signature": "def shortestPalindrome(self, s)"
},
{
"docstring": ":type s: str :rtype: str",
"name": "shortestPalindrome2",
"signature": "def shortestPalindrome2(self, s)"
}
] | 2 | stack_v2_sparse_classes_30k_train_039348 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def shortestPalindrome(self, s): :type s: str :rtype: str
- def shortestPalindrome2(self, s): :type s: str :rtype: str | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def shortestPalindrome(self, s): :type s: str :rtype: str
- def shortestPalindrome2(self, s): :type s: str :rtype: str
<|skeleton|>
class Solution:
def shortestPalindrome(s... | 635af6e22aa8eef8e7920a585d43a45a891a8157 | <|skeleton|>
class Solution:
def shortestPalindrome(self, s):
""":type s: str :rtype: str"""
<|body_0|>
def shortestPalindrome2(self, s):
""":type s: str :rtype: str"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def shortestPalindrome(self, s):
""":type s: str :rtype: str"""
if len(s) < 2:
return s
ss = s + '#' + s[::-1]
length, M = (0, len(ss))
i, lps = (1, [0] * M)
while i < M:
if ss[i] == ss[length]:
length += 1
... | the_stack_v2_python_sparse | code214ShortestPalindrome.py | cybelewang/leetcode-python | train | 0 | |
8163dd216eceb76b5ecaf1e6019d25e96bf65901 | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn KubernetesNamespaceEvidence()",
"from .alert_evidence import AlertEvidence\nfrom .dictionary import Dictionary\nfrom .kubernetes_cluster_evidence import KubernetesClusterEvidence\nfrom .alert_evidence import AlertEvidence\nfrom .dictio... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return KubernetesNamespaceEvidence()
<|end_body_0|>
<|body_start_1|>
from .alert_evidence import AlertEvidence
from .dictionary import Dictionary
from .kubernetes_cluster_evidence impor... | KubernetesNamespaceEvidence | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class KubernetesNamespaceEvidence:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> KubernetesNamespaceEvidence:
"""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 a... | stack_v2_sparse_classes_75kplus_train_002555 | 2,916 | 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: KubernetesNamespaceEvidence",
"name": "create_from_discriminator_value",
"signature": "def create_from_discr... | 3 | null | Implement the Python class `KubernetesNamespaceEvidence` described below.
Class description:
Implement the KubernetesNamespaceEvidence class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> KubernetesNamespaceEvidence: Creates a new instance of the appr... | Implement the Python class `KubernetesNamespaceEvidence` described below.
Class description:
Implement the KubernetesNamespaceEvidence class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> KubernetesNamespaceEvidence: Creates a new instance of the appr... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class KubernetesNamespaceEvidence:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> KubernetesNamespaceEvidence:
"""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 a... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class KubernetesNamespaceEvidence:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> KubernetesNamespaceEvidence:
"""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 ... | the_stack_v2_python_sparse | msgraph/generated/models/security/kubernetes_namespace_evidence.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
48b9789fb5808e7e8fe03e2b8c2c7fa1f47145ce | [
"response = requests.get(cls.search_url, params=query, allow_redirects=False)\n_response_error_handler(response.status_code, response.text)\nreturn response.json()",
"res: [Dict] = []\nfor page_num in range(num_of_pages):\n query['page'] = page_num\n page = cls.execute_query(query)\n for dct in page['dat... | <|body_start_0|>
response = requests.get(cls.search_url, params=query, allow_redirects=False)
_response_error_handler(response.status_code, response.text)
return response.json()
<|end_body_0|>
<|body_start_1|>
res: [Dict] = []
for page_num in range(num_of_pages):
que... | Rapid7 vulnerability database Search API ETL utilities. | Search | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Search:
"""Rapid7 vulnerability database Search API ETL utilities."""
def execute_query(cls, query: Dict) -> Dict:
"""Executes API query by sending a request to API and extracting the result as a python data structure :param query: free form text :return: Data as dictionary"""
... | stack_v2_sparse_classes_75kplus_train_002556 | 5,775 | permissive | [
{
"docstring": "Executes API query by sending a request to API and extracting the result as a python data structure :param query: free form text :return: Data as dictionary",
"name": "execute_query",
"signature": "def execute_query(cls, query: Dict) -> Dict"
},
{
"docstring": "Iterates over avai... | 4 | stack_v2_sparse_classes_30k_train_046119 | Implement the Python class `Search` described below.
Class description:
Rapid7 vulnerability database Search API ETL utilities.
Method signatures and docstrings:
- def execute_query(cls, query: Dict) -> Dict: Executes API query by sending a request to API and extracting the result as a python data structure :param qu... | Implement the Python class `Search` described below.
Class description:
Rapid7 vulnerability database Search API ETL utilities.
Method signatures and docstrings:
- def execute_query(cls, query: Dict) -> Dict: Executes API query by sending a request to API and extracting the result as a python data structure :param qu... | 718d15ca36c57231bb89df0aebc53d0210db400c | <|skeleton|>
class Search:
"""Rapid7 vulnerability database Search API ETL utilities."""
def execute_query(cls, query: Dict) -> Dict:
"""Executes API query by sending a request to API and extracting the result as a python data structure :param query: free form text :return: Data as dictionary"""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Search:
"""Rapid7 vulnerability database Search API ETL utilities."""
def execute_query(cls, query: Dict) -> Dict:
"""Executes API query by sending a request to API and extracting the result as a python data structure :param query: free form text :return: Data as dictionary"""
response = ... | the_stack_v2_python_sparse | plugins/rapid7_vulndb/komand_rapid7_vulndb/util/extract.py | rapid7/insightconnect-plugins | train | 61 |
6b04bb6d719f32a86b1bc83ce357179226385ced | [
"self.kl_weight = 1e-08\nself.num_hypotheses = num_hypotheses\nself.outputs = outputs\nif weights is None:\n self.weights = [1.0] * len(self.outputs)\nelse:\n self.weights = weights\nif stats is not None and len(stats) > 0:\n if len(stats) == 1:\n stats = stats * self.num_hypotheses\n self.st... | <|body_start_0|>
self.kl_weight = 1e-08
self.num_hypotheses = num_hypotheses
self.outputs = outputs
if weights is None:
self.weights = [1.0] * len(self.outputs)
else:
self.weights = weights
if stats is not None and len(stats) > 0:
if le... | This version of the MHP loss assumes that it will receive multiple outputs. | MhpLossWithShape | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MhpLossWithShape:
"""This version of the MHP loss assumes that it will receive multiple outputs."""
def __init__(self, num_hypotheses, outputs, weights=None, loss='mse', avg_weight=0.05, stats=[]):
"""Parameters: ----------- num_hypotheses: number of hypotheses outputs: length of eac... | stack_v2_sparse_classes_75kplus_train_002557 | 7,780 | permissive | [
{
"docstring": "Parameters: ----------- num_hypotheses: number of hypotheses outputs: length of each output weights: None or vector of weights for each target loss: loss function or vector of loss function names to use (keras) avg_weight: amount of weight to give to average loss across all hypotheses stats: mea... | 2 | stack_v2_sparse_classes_30k_train_037468 | Implement the Python class `MhpLossWithShape` described below.
Class description:
This version of the MHP loss assumes that it will receive multiple outputs.
Method signatures and docstrings:
- def __init__(self, num_hypotheses, outputs, weights=None, loss='mse', avg_weight=0.05, stats=[]): Parameters: ----------- nu... | Implement the Python class `MhpLossWithShape` described below.
Class description:
This version of the MHP loss assumes that it will receive multiple outputs.
Method signatures and docstrings:
- def __init__(self, num_hypotheses, outputs, weights=None, loss='mse', avg_weight=0.05, stats=[]): Parameters: ----------- nu... | be5c12f9d0e9d7078e6a5c283d3be059e7f3d040 | <|skeleton|>
class MhpLossWithShape:
"""This version of the MHP loss assumes that it will receive multiple outputs."""
def __init__(self, num_hypotheses, outputs, weights=None, loss='mse', avg_weight=0.05, stats=[]):
"""Parameters: ----------- num_hypotheses: number of hypotheses outputs: length of eac... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MhpLossWithShape:
"""This version of the MHP loss assumes that it will receive multiple outputs."""
def __init__(self, num_hypotheses, outputs, weights=None, loss='mse', avg_weight=0.05, stats=[]):
"""Parameters: ----------- num_hypotheses: number of hypotheses outputs: length of each output weig... | the_stack_v2_python_sparse | costar_models/python/costar_models/mhp_loss.py | lk-greenbird/costar_plan | train | 0 |
2c53abd0954b5f913b94224c855276f3677095e3 | [
"str2int = np.zeros((row, column))\nline = 0\nfor idx, value in enumerate(maze):\n if (idx != 0) & (value == '\\n'):\n line = line + 1\n elif value == '.':\n str2int[line][idx % (column + 1) - 1] = 1\nreturn str2int",
"int2str = ''\nx, y = maze.shape\nfor i in range(0, x):\n for j in range(... | <|body_start_0|>
str2int = np.zeros((row, column))
line = 0
for idx, value in enumerate(maze):
if (idx != 0) & (value == '\n'):
line = line + 1
elif value == '.':
str2int[line][idx % (column + 1) - 1] = 1
return str2int
<|end_body_0... | conversor | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class conversor:
def conv_str2int(row, column, maze):
"""Function to convert string to int. We have big string with * | breakline caracter is very hard to see how to process this format (not impossible) but more difficult to see. Args: row (int): number of line (use number without subtract as ... | stack_v2_sparse_classes_75kplus_train_002558 | 2,464 | no_license | [
{
"docstring": "Function to convert string to int. We have big string with * | breakline caracter is very hard to see how to process this format (not impossible) but more difficult to see. Args: row (int): number of line (use number without subtract as index) column (int): number of column (use number without s... | 2 | stack_v2_sparse_classes_30k_train_021965 | Implement the Python class `conversor` described below.
Class description:
Implement the conversor class.
Method signatures and docstrings:
- def conv_str2int(row, column, maze): Function to convert string to int. We have big string with * | breakline caracter is very hard to see how to process this format (not impos... | Implement the Python class `conversor` described below.
Class description:
Implement the conversor class.
Method signatures and docstrings:
- def conv_str2int(row, column, maze): Function to convert string to int. We have big string with * | breakline caracter is very hard to see how to process this format (not impos... | 71fca6995e19930ecc56aff297c35a3a4228b6ce | <|skeleton|>
class conversor:
def conv_str2int(row, column, maze):
"""Function to convert string to int. We have big string with * | breakline caracter is very hard to see how to process this format (not impossible) but more difficult to see. Args: row (int): number of line (use number without subtract as ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class conversor:
def conv_str2int(row, column, maze):
"""Function to convert string to int. We have big string with * | breakline caracter is very hard to see how to process this format (not impossible) but more difficult to see. Args: row (int): number of line (use number without subtract as index) column ... | the_stack_v2_python_sparse | tools/conversor.py | giovanedemorais/pac_man_intelligence | train | 0 | |
e6fcededbfd5e5af9392bc246fc7de3efdcfaff1 | [
"strategy = Strategy.objects.get(pk=pk)\nstrategy = Strategy.describe_strategies([strategy], verbose=Strategy.MAX_VERBOSE)[0]\nreturn Response({'data': {'strategy': strategy}})",
"strategy = Strategy.objects.get(pk=pk)\nserializer = StrategyCreateUpdateSerializer(strategy, data=request.data, partial=True, context... | <|body_start_0|>
strategy = Strategy.objects.get(pk=pk)
strategy = Strategy.describe_strategies([strategy], verbose=Strategy.MAX_VERBOSE)[0]
return Response({'data': {'strategy': strategy}})
<|end_body_0|>
<|body_start_1|>
strategy = Strategy.objects.get(pk=pk)
serializer = Stra... | SingleStrategyAPIView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SingleStrategyAPIView:
def get(request, pk):
"""获取策略详情"""
<|body_0|>
def put(request, pk):
"""修改策略"""
<|body_1|>
def delete(request, pk):
"""删除策略"""
<|body_2|>
<|end_skeleton|>
<|body_start_0|>
strategy = Strategy.objects.get(pk... | stack_v2_sparse_classes_75kplus_train_002559 | 9,461 | no_license | [
{
"docstring": "获取策略详情",
"name": "get",
"signature": "def get(request, pk)"
},
{
"docstring": "修改策略",
"name": "put",
"signature": "def put(request, pk)"
},
{
"docstring": "删除策略",
"name": "delete",
"signature": "def delete(request, pk)"
}
] | 3 | stack_v2_sparse_classes_30k_train_030812 | Implement the Python class `SingleStrategyAPIView` described below.
Class description:
Implement the SingleStrategyAPIView class.
Method signatures and docstrings:
- def get(request, pk): 获取策略详情
- def put(request, pk): 修改策略
- def delete(request, pk): 删除策略 | Implement the Python class `SingleStrategyAPIView` described below.
Class description:
Implement the SingleStrategyAPIView class.
Method signatures and docstrings:
- def get(request, pk): 获取策略详情
- def put(request, pk): 修改策略
- def delete(request, pk): 删除策略
<|skeleton|>
class SingleStrategyAPIView:
def get(reques... | bb85b52598d68956bde8756c8321ade7b8479ba7 | <|skeleton|>
class SingleStrategyAPIView:
def get(request, pk):
"""获取策略详情"""
<|body_0|>
def put(request, pk):
"""修改策略"""
<|body_1|>
def delete(request, pk):
"""删除策略"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SingleStrategyAPIView:
def get(request, pk):
"""获取策略详情"""
strategy = Strategy.objects.get(pk=pk)
strategy = Strategy.describe_strategies([strategy], verbose=Strategy.MAX_VERBOSE)[0]
return Response({'data': {'strategy': strategy}})
def put(request, pk):
"""修改策略"""
... | the_stack_v2_python_sparse | curd_test/configure/views.py | huiiiuh/huihuiproject | train | 0 | |
1d5ececaad97388d14212fe9610474b2f6773501 | [
"requests_store = RequestJsonStore()\nrequests_store.empty_store()\nkeys_store = KeysJsonStore()\nkeys_store.empty_store()\nmy_manager = AccessManager()\nprint('one')\nmy_manager.request_access_code('05270358T', 'Pedro Martin', 'Resident', 'uc3m@gmail.com', 0)\nprint('two')\nmy_manager.request_access_code('87654123... | <|body_start_0|>
requests_store = RequestJsonStore()
requests_store.empty_store()
keys_store = KeysJsonStore()
keys_store.empty_store()
my_manager = AccessManager()
print('one')
my_manager.request_access_code('05270358T', 'Pedro Martin', 'Resident', 'uc3m@gmail.co... | Test class for testing get_access_key | TestAccessManager | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestAccessManager:
"""Test class for testing get_access_key"""
def setUpClass(cls) -> None:
"""Removing the Stores and creating required AccessRequest for testing"""
<|body_0|>
def test_parametrized_cases_tests(self):
"""Parametrized cases read from testingCases_... | stack_v2_sparse_classes_75kplus_train_002560 | 2,525 | no_license | [
{
"docstring": "Removing the Stores and creating required AccessRequest for testing",
"name": "setUpClass",
"signature": "def setUpClass(cls) -> None"
},
{
"docstring": "Parametrized cases read from testingCases_RF1.csv",
"name": "test_parametrized_cases_tests",
"signature": "def test_pa... | 2 | stack_v2_sparse_classes_30k_train_007660 | Implement the Python class `TestAccessManager` described below.
Class description:
Test class for testing get_access_key
Method signatures and docstrings:
- def setUpClass(cls) -> None: Removing the Stores and creating required AccessRequest for testing
- def test_parametrized_cases_tests(self): Parametrized cases re... | Implement the Python class `TestAccessManager` described below.
Class description:
Test class for testing get_access_key
Method signatures and docstrings:
- def setUpClass(cls) -> None: Removing the Stores and creating required AccessRequest for testing
- def test_parametrized_cases_tests(self): Parametrized cases re... | 113c49682a63736666b95d423d9b26ab3e35d980 | <|skeleton|>
class TestAccessManager:
"""Test class for testing get_access_key"""
def setUpClass(cls) -> None:
"""Removing the Stores and creating required AccessRequest for testing"""
<|body_0|>
def test_parametrized_cases_tests(self):
"""Parametrized cases read from testingCases_... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TestAccessManager:
"""Test class for testing get_access_key"""
def setUpClass(cls) -> None:
"""Removing the Stores and creating required AccessRequest for testing"""
requests_store = RequestJsonStore()
requests_store.empty_store()
keys_store = KeysJsonStore()
keys_... | the_stack_v2_python_sparse | src/unittest/python/test_get_access_key_tests.py | ncoress/G80.T7.FP | train | 0 |
530401e131941f75c3b56d95fe57b246761f270d | [
"super().__init__()\nself.name = 'session-' + secrets.token_hex(16)\nself.port = random.randint(1024, 65535)\nself.api_instance.create_namespaced_pod(body={'apiVersion': 'v1', 'kind': 'Pod', 'metadata': {'name': self.name}, 'spec': {'containers': [{'name': 'executa', 'image': 'stencila/executa', 'args': ['executa',... | <|body_start_0|>
super().__init__()
self.name = 'session-' + secrets.token_hex(16)
self.port = random.randint(1024, 65535)
self.api_instance.create_namespaced_pod(body={'apiVersion': 'v1', 'kind': 'Pod', 'metadata': {'name': self.name}, 'spec': {'containers': [{'name': 'executa', 'image'... | Runs a session as a pod in a Kubernetes cluster. This class in intended for scalably provisioning untrusted sessions. It uses the K8s API to create a new pod inside a cluster, possible the same cluster this process is in. | KubernetesSession | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class KubernetesSession:
"""Runs a session as a pod in a Kubernetes cluster. This class in intended for scalably provisioning untrusted sessions. It uses the K8s API to create a new pod inside a cluster, possible the same cluster this process is in."""
def __init__(self):
"""Create a sessi... | stack_v2_sparse_classes_75kplus_train_002561 | 3,424 | permissive | [
{
"docstring": "Create a session.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Start the session.",
"name": "start",
"signature": "def start(self)"
},
{
"docstring": "Stop the session.",
"name": "stop",
"signature": "def stop(self)"
}
] | 3 | stack_v2_sparse_classes_30k_train_035010 | Implement the Python class `KubernetesSession` described below.
Class description:
Runs a session as a pod in a Kubernetes cluster. This class in intended for scalably provisioning untrusted sessions. It uses the K8s API to create a new pod inside a cluster, possible the same cluster this process is in.
Method signat... | Implement the Python class `KubernetesSession` described below.
Class description:
Runs a session as a pod in a Kubernetes cluster. This class in intended for scalably provisioning untrusted sessions. It uses the K8s API to create a new pod inside a cluster, possible the same cluster this process is in.
Method signat... | 47c6377ccbfe8576b35854053d726537e533e78c | <|skeleton|>
class KubernetesSession:
"""Runs a session as a pod in a Kubernetes cluster. This class in intended for scalably provisioning untrusted sessions. It uses the K8s API to create a new pod inside a cluster, possible the same cluster this process is in."""
def __init__(self):
"""Create a sessi... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class KubernetesSession:
"""Runs a session as a pod in a Kubernetes cluster. This class in intended for scalably provisioning untrusted sessions. It uses the K8s API to create a new pod inside a cluster, possible the same cluster this process is in."""
def __init__(self):
"""Create a session."""
... | the_stack_v2_python_sparse | worker/jobs/session/kubernetes_session.py | gxf1986/hub | train | 0 |
3733e3552366139eaa276f01fcf12ba402b615d2 | [
"self.hass = hass\nself.webhook_id = webhook_id\nself.support_confirm = support_confirm\nself._send_message = send_message\nself.on_teardown = on_teardown\nself.pending_confirms: dict[str, dict] = {}",
"if not self.support_confirm:\n self._send_message(data)\n return\nconfirm_id = random_uuid_hex()\ndata['h... | <|body_start_0|>
self.hass = hass
self.webhook_id = webhook_id
self.support_confirm = support_confirm
self._send_message = send_message
self.on_teardown = on_teardown
self.pending_confirms: dict[str, dict] = {}
<|end_body_0|>
<|body_start_1|>
if not self.support_... | Class that represents a push channel. | PushChannel | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PushChannel:
"""Class that represents a push channel."""
def __init__(self, hass: HomeAssistant, webhook_id: str, support_confirm: bool, send_message: Callable[[dict], None], on_teardown: Callable[[], None]) -> None:
"""Initialize a local push channel."""
<|body_0|>
def ... | stack_v2_sparse_classes_75kplus_train_002562 | 2,897 | permissive | [
{
"docstring": "Initialize a local push channel.",
"name": "__init__",
"signature": "def __init__(self, hass: HomeAssistant, webhook_id: str, support_confirm: bool, send_message: Callable[[dict], None], on_teardown: Callable[[], None]) -> None"
},
{
"docstring": "Send a push notification.",
... | 4 | stack_v2_sparse_classes_30k_train_007522 | Implement the Python class `PushChannel` described below.
Class description:
Class that represents a push channel.
Method signatures and docstrings:
- def __init__(self, hass: HomeAssistant, webhook_id: str, support_confirm: bool, send_message: Callable[[dict], None], on_teardown: Callable[[], None]) -> None: Initial... | Implement the Python class `PushChannel` described below.
Class description:
Class that represents a push channel.
Method signatures and docstrings:
- def __init__(self, hass: HomeAssistant, webhook_id: str, support_confirm: bool, send_message: Callable[[dict], None], on_teardown: Callable[[], None]) -> None: Initial... | 80caeafcb5b6e2f9da192d0ea6dd1a5b8244b743 | <|skeleton|>
class PushChannel:
"""Class that represents a push channel."""
def __init__(self, hass: HomeAssistant, webhook_id: str, support_confirm: bool, send_message: Callable[[dict], None], on_teardown: Callable[[], None]) -> None:
"""Initialize a local push channel."""
<|body_0|>
def ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PushChannel:
"""Class that represents a push channel."""
def __init__(self, hass: HomeAssistant, webhook_id: str, support_confirm: bool, send_message: Callable[[dict], None], on_teardown: Callable[[], None]) -> None:
"""Initialize a local push channel."""
self.hass = hass
self.web... | the_stack_v2_python_sparse | homeassistant/components/mobile_app/push_notification.py | home-assistant/core | train | 35,501 |
b725f242753dfb7e4e8a2df4e17c5f10d28b939a | [
"self.gateway = gateway\nself.status = status\nself.pgid = pgid\nself.created_at = created_at\nself.updated_at = updated_at",
"if dictionary is None:\n return None\ngateway = dictionary.get('gateway')\nstatus = dictionary.get('status')\npgid = dictionary.get('pgid')\ncreated_at = dictionary.get('created_at')\n... | <|body_start_0|>
self.gateway = gateway
self.status = status
self.pgid = pgid
self.created_at = created_at
self.updated_at = updated_at
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
gateway = dictionary.get('gateway')
stat... | Implementation of the 'GetGatewayRecipientResponse' model. Information about the recipient on the gateway Attributes: gateway (string): Gateway name status (string): Status of the recipient on the gateway pgid (string): Recipient id on the gateway created_at (string): Creation date updated_at (string): Last update date | GetGatewayRecipientResponse | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GetGatewayRecipientResponse:
"""Implementation of the 'GetGatewayRecipientResponse' model. Information about the recipient on the gateway Attributes: gateway (string): Gateway name status (string): Status of the recipient on the gateway pgid (string): Recipient id on the gateway created_at (strin... | stack_v2_sparse_classes_75kplus_train_002563 | 2,328 | permissive | [
{
"docstring": "Constructor for the GetGatewayRecipientResponse class",
"name": "__init__",
"signature": "def __init__(self, gateway=None, status=None, pgid=None, created_at=None, updated_at=None)"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: dictionary (dictionar... | 2 | null | Implement the Python class `GetGatewayRecipientResponse` described below.
Class description:
Implementation of the 'GetGatewayRecipientResponse' model. Information about the recipient on the gateway Attributes: gateway (string): Gateway name status (string): Status of the recipient on the gateway pgid (string): Recipi... | Implement the Python class `GetGatewayRecipientResponse` described below.
Class description:
Implementation of the 'GetGatewayRecipientResponse' model. Information about the recipient on the gateway Attributes: gateway (string): Gateway name status (string): Status of the recipient on the gateway pgid (string): Recipi... | 95c80c35dd57bb2a238faeaf30d1e3b4544d2298 | <|skeleton|>
class GetGatewayRecipientResponse:
"""Implementation of the 'GetGatewayRecipientResponse' model. Information about the recipient on the gateway Attributes: gateway (string): Gateway name status (string): Status of the recipient on the gateway pgid (string): Recipient id on the gateway created_at (strin... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class GetGatewayRecipientResponse:
"""Implementation of the 'GetGatewayRecipientResponse' model. Information about the recipient on the gateway Attributes: gateway (string): Gateway name status (string): Status of the recipient on the gateway pgid (string): Recipient id on the gateway created_at (string): Creation ... | the_stack_v2_python_sparse | mundiapi/models/get_gateway_recipient_response.py | mundipagg/MundiAPI-PYTHON | train | 10 |
063d8012ff430f51f55f6ab2552261a2e0f0d1de | [
"payment = order.payments.first() or self.create_pending_payment(order)\nif order_id or authorization:\n payment.data['capture'] = {'order_id': order_id or '', 'authorization': authorization or {}, 'method': self.key}\n payment.save()\nreturn payment",
"payment = self.get_or_create_pending_payment(order, or... | <|body_start_0|>
payment = order.payments.first() or self.create_pending_payment(order)
if order_id or authorization:
payment.data['capture'] = {'order_id': order_id or '', 'authorization': authorization or {}, 'method': self.key}
payment.save()
return payment
<|end_body_... | Single payment processor Processes Paypal's single payment. A single payment means the client has authorized & executed the payment. We receive an authorization code that we check back with Paypal. If the authorization is confirmed by Paypal, the SinglePaymentProcessor updates Plata's payment status to OrderPayment.PRO... | SinglePaymentProcessor | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SinglePaymentProcessor:
"""Single payment processor Processes Paypal's single payment. A single payment means the client has authorized & executed the payment. We receive an authorization code that we check back with Paypal. If the authorization is confirmed by Paypal, the SinglePaymentProcessor ... | stack_v2_sparse_classes_75kplus_train_002564 | 3,820 | permissive | [
{
"docstring": "retrieve order, or create pending Retrieve the first payment known for this order, or create a pending payment. Stores the order_id and authorization data. :param order: Plata order instance :param order_id: Paypal provider order id :param authorization: Paypal provider authorization",
"name... | 2 | stack_v2_sparse_classes_30k_train_007764 | Implement the Python class `SinglePaymentProcessor` described below.
Class description:
Single payment processor Processes Paypal's single payment. A single payment means the client has authorized & executed the payment. We receive an authorization code that we check back with Paypal. If the authorization is confirmed... | Implement the Python class `SinglePaymentProcessor` described below.
Class description:
Single payment processor Processes Paypal's single payment. A single payment means the client has authorized & executed the payment. We receive an authorization code that we check back with Paypal. If the authorization is confirmed... | b6abdd7d26f0d4d4acd2c9bef0c593b874ba5b0c | <|skeleton|>
class SinglePaymentProcessor:
"""Single payment processor Processes Paypal's single payment. A single payment means the client has authorized & executed the payment. We receive an authorization code that we check back with Paypal. If the authorization is confirmed by Paypal, the SinglePaymentProcessor ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SinglePaymentProcessor:
"""Single payment processor Processes Paypal's single payment. A single payment means the client has authorized & executed the payment. We receive an authorization code that we check back with Paypal. If the authorization is confirmed by Paypal, the SinglePaymentProcessor updates Plata... | the_stack_v2_python_sparse | platarestapi/processor/paypal/single.py | miraculixx/plata-restapi | train | 0 |
77c065cc5c558fc27d58151be4e0989edba647b5 | [
"login_page.LoginPage(self.driver).login()\nsleep(2)\nlandlord_nav_page.LandlordNavPage(self.driver).Iamlandlord()\nsleep(2)\nlandlord_nav_page.LandlordNavPage(self.driver).close_weiChat()\nsleep(2)\nlandlord_nav_page.LandlordNavPage(self.driver).roommanager()\npo = landlord_online_editdata.LandlordOnlineEditdata(s... | <|body_start_0|>
login_page.LoginPage(self.driver).login()
sleep(2)
landlord_nav_page.LandlordNavPage(self.driver).Iamlandlord()
sleep(2)
landlord_nav_page.LandlordNavPage(self.driver).close_weiChat()
sleep(2)
landlord_nav_page.LandlordNavPage(self.driver).roomman... | 房源图片 | TestEditdataFypic | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestEditdataFypic:
"""房源图片"""
def test_del_pic(self):
"""修改房源图片——上传图片和删除图片"""
<|body_0|>
def test_setcover(self):
"""设为封面"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
login_page.LoginPage(self.driver).login()
sleep(2)
landlord... | stack_v2_sparse_classes_75kplus_train_002565 | 2,282 | permissive | [
{
"docstring": "修改房源图片——上传图片和删除图片",
"name": "test_del_pic",
"signature": "def test_del_pic(self)"
},
{
"docstring": "设为封面",
"name": "test_setcover",
"signature": "def test_setcover(self)"
}
] | 2 | stack_v2_sparse_classes_30k_test_000597 | Implement the Python class `TestEditdataFypic` described below.
Class description:
房源图片
Method signatures and docstrings:
- def test_del_pic(self): 修改房源图片——上传图片和删除图片
- def test_setcover(self): 设为封面 | Implement the Python class `TestEditdataFypic` described below.
Class description:
房源图片
Method signatures and docstrings:
- def test_del_pic(self): 修改房源图片——上传图片和删除图片
- def test_setcover(self): 设为封面
<|skeleton|>
class TestEditdataFypic:
"""房源图片"""
def test_del_pic(self):
"""修改房源图片——上传图片和删除图片"""
... | 192c70c49a8e9e072b9d0d0136f02c653c589410 | <|skeleton|>
class TestEditdataFypic:
"""房源图片"""
def test_del_pic(self):
"""修改房源图片——上传图片和删除图片"""
<|body_0|>
def test_setcover(self):
"""设为封面"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TestEditdataFypic:
"""房源图片"""
def test_del_pic(self):
"""修改房源图片——上传图片和删除图片"""
login_page.LoginPage(self.driver).login()
sleep(2)
landlord_nav_page.LandlordNavPage(self.driver).Iamlandlord()
sleep(2)
landlord_nav_page.LandlordNavPage(self.driver).close_weiCh... | the_stack_v2_python_sparse | mayi/test_case/test_online_editdata_fypic.py | 18701016443/mayi | train | 0 |
b81479e07e4a219a7544010865d1c7fdb4e5f399 | [
"add_cat('test', 1, 1)\nadd_cat('temp', 1, 1)\nadd_cat('tmp', 1, 1)\nadd_cat('tmp test temp', 1, 1)\nresponse = self.client.get(reverse('index'))\nself.assertEqual(response.status_code, 200)\nself.assertContains(response, 'tmp test temp')\nnum_cats = len(response.context['categories'])\nself.assertEqual(num_cats, 4... | <|body_start_0|>
add_cat('test', 1, 1)
add_cat('temp', 1, 1)
add_cat('tmp', 1, 1)
add_cat('tmp test temp', 1, 1)
response = self.client.get(reverse('index'))
self.assertEqual(response.status_code, 200)
self.assertContains(response, 'tmp test temp')
num_cat... | IndexViewTests | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IndexViewTests:
def test_index_view_with_categories(self):
"""Check that appropriate categories load :return:"""
<|body_0|>
def test_index_view_with_no_categories(self):
"""If no categories exist, an appropriate message should be displayed :return:"""
<|body_... | stack_v2_sparse_classes_75kplus_train_002566 | 2,727 | no_license | [
{
"docstring": "Check that appropriate categories load :return:",
"name": "test_index_view_with_categories",
"signature": "def test_index_view_with_categories(self)"
},
{
"docstring": "If no categories exist, an appropriate message should be displayed :return:",
"name": "test_index_view_with... | 2 | stack_v2_sparse_classes_30k_train_025820 | Implement the Python class `IndexViewTests` described below.
Class description:
Implement the IndexViewTests class.
Method signatures and docstrings:
- def test_index_view_with_categories(self): Check that appropriate categories load :return:
- def test_index_view_with_no_categories(self): If no categories exist, an ... | Implement the Python class `IndexViewTests` described below.
Class description:
Implement the IndexViewTests class.
Method signatures and docstrings:
- def test_index_view_with_categories(self): Check that appropriate categories load :return:
- def test_index_view_with_no_categories(self): If no categories exist, an ... | 205207086c570e6feba887f958d536d029386757 | <|skeleton|>
class IndexViewTests:
def test_index_view_with_categories(self):
"""Check that appropriate categories load :return:"""
<|body_0|>
def test_index_view_with_no_categories(self):
"""If no categories exist, an appropriate message should be displayed :return:"""
<|body_... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class IndexViewTests:
def test_index_view_with_categories(self):
"""Check that appropriate categories load :return:"""
add_cat('test', 1, 1)
add_cat('temp', 1, 1)
add_cat('tmp', 1, 1)
add_cat('tmp test temp', 1, 1)
response = self.client.get(reverse('index'))
... | the_stack_v2_python_sparse | moneykatz/tests.py | flycal6/moneykatz_django | train | 0 | |
1702641cb99fbc8e9025526995d600323caa8558 | [
"if not args:\n args = ('',)\napps = self.catalog_apps(cherrypy.tree.apps, args[0] == 'all')\nif cherrypy.request.wants == 'org':\n checklist = (f'- [ ] {name}' for name, _, _ in apps)\n return '\\n'.join(checklist).encode()\nreturn cherrypy.engine.publish('jinja:render', 'apps/homepage/homepage.jinja.html... | <|body_start_0|>
if not args:
args = ('',)
apps = self.catalog_apps(cherrypy.tree.apps, args[0] == 'all')
if cherrypy.request.wants == 'org':
checklist = (f'- [ ] {name}' for name, _, _ in apps)
return '\n'.join(checklist).encode()
return cherrypy.engi... | Controller | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Controller:
def GET(self, *args: str, **_kwargs: str) -> bytes:
"""List all available applications. Apps can be excluded from this list by setting show_on_homepage to False."""
<|body_0|>
def catalog_apps(apps: Dict[str, cherrypy.Application], show_all: bool=True) -> List[Tu... | stack_v2_sparse_classes_75kplus_train_002567 | 2,402 | no_license | [
{
"docstring": "List all available applications. Apps can be excluded from this list by setting show_on_homepage to False.",
"name": "GET",
"signature": "def GET(self, *args: str, **_kwargs: str) -> bytes"
},
{
"docstring": "Extract app summaries from module docstrings.",
"name": "catalog_ap... | 2 | stack_v2_sparse_classes_30k_test_000509 | Implement the Python class `Controller` described below.
Class description:
Implement the Controller class.
Method signatures and docstrings:
- def GET(self, *args: str, **_kwargs: str) -> bytes: List all available applications. Apps can be excluded from this list by setting show_on_homepage to False.
- def catalog_a... | Implement the Python class `Controller` described below.
Class description:
Implement the Controller class.
Method signatures and docstrings:
- def GET(self, *args: str, **_kwargs: str) -> bytes: List all available applications. Apps can be excluded from this list by setting show_on_homepage to False.
- def catalog_a... | 7129415303b94d5d10b2c29ec432f0c7d41cc651 | <|skeleton|>
class Controller:
def GET(self, *args: str, **_kwargs: str) -> bytes:
"""List all available applications. Apps can be excluded from this list by setting show_on_homepage to False."""
<|body_0|>
def catalog_apps(apps: Dict[str, cherrypy.Application], show_all: bool=True) -> List[Tu... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Controller:
def GET(self, *args: str, **_kwargs: str) -> bytes:
"""List all available applications. Apps can be excluded from this list by setting show_on_homepage to False."""
if not args:
args = ('',)
apps = self.catalog_apps(cherrypy.tree.apps, args[0] == 'all')
... | the_stack_v2_python_sparse | apps/homepage/main.py | lovett/medley | train | 6 | |
b4b000182b765577a6d2c7877a957308a03ab302 | [
"self.init_lr = init_lr\nself.gamma = gamma\nself.iter_steps = iter_steps",
"lr = self.init_lr\nfor iter_step in self.iter_steps:\n if iter >= iter_step:\n lr *= self.gamma\nreturn lr"
] | <|body_start_0|>
self.init_lr = init_lr
self.gamma = gamma
self.iter_steps = iter_steps
<|end_body_0|>
<|body_start_1|>
lr = self.init_lr
for iter_step in self.iter_steps:
if iter >= iter_step:
lr *= self.gamma
return lr
<|end_body_1|>
| StepScheduler Step decay | StepScheduler | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StepScheduler:
"""StepScheduler Step decay"""
def __init__(self, init_lr, gamma, iter_steps):
"""Args: init_lr (float): Initial learning rate. gamma (float): Multiplier. iter_steps (list of int): Iteration at which gamma is multiplied. Example: StepScheduler(0.1, 0.1, [150000, 300000... | stack_v2_sparse_classes_75kplus_train_002568 | 5,375 | permissive | [
{
"docstring": "Args: init_lr (float): Initial learning rate. gamma (float): Multiplier. iter_steps (list of int): Iteration at which gamma is multiplied. Example: StepScheduler(0.1, 0.1, [150000, 300000, 400000])",
"name": "__init__",
"signature": "def __init__(self, init_lr, gamma, iter_steps)"
},
... | 2 | stack_v2_sparse_classes_30k_train_009135 | Implement the Python class `StepScheduler` described below.
Class description:
StepScheduler Step decay
Method signatures and docstrings:
- def __init__(self, init_lr, gamma, iter_steps): Args: init_lr (float): Initial learning rate. gamma (float): Multiplier. iter_steps (list of int): Iteration at which gamma is mul... | Implement the Python class `StepScheduler` described below.
Class description:
StepScheduler Step decay
Method signatures and docstrings:
- def __init__(self, init_lr, gamma, iter_steps): Args: init_lr (float): Initial learning rate. gamma (float): Multiplier. iter_steps (list of int): Iteration at which gamma is mul... | 93211d0f322d76efc48cfcf27decae7bd818f923 | <|skeleton|>
class StepScheduler:
"""StepScheduler Step decay"""
def __init__(self, init_lr, gamma, iter_steps):
"""Args: init_lr (float): Initial learning rate. gamma (float): Multiplier. iter_steps (list of int): Iteration at which gamma is multiplied. Example: StepScheduler(0.1, 0.1, [150000, 300000... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class StepScheduler:
"""StepScheduler Step decay"""
def __init__(self, init_lr, gamma, iter_steps):
"""Args: init_lr (float): Initial learning rate. gamma (float): Multiplier. iter_steps (list of int): Iteration at which gamma is multiplied. Example: StepScheduler(0.1, 0.1, [150000, 300000, 400000])"""... | the_stack_v2_python_sparse | python/src/nnabla/utils/learning_rate_scheduler.py | Pandinosaurus/nnabla | train | 1 |
3b305228466db9f22342c60928ef3ebe285a69ba | [
"super(NN2, self).__init__()\nself.conv1 = nn.Conv2d(1, 10, kernel_size=3)\nself.conv2 = nn.Conv2d(10, 20, kernel_size=3)\nself.conv2_drop = nn.Dropout2d()\nself.fc1 = nn.Linear(20 * 2 * 2, 50)\nself.fc2 = nn.Linear(50, 10)\nself.fc3 = nn.Linear(100, 30)\nself.fc4 = nn.Linear(30, 20)\nself.fc5 = nn.Linear(20, 10)\n... | <|body_start_0|>
super(NN2, self).__init__()
self.conv1 = nn.Conv2d(1, 10, kernel_size=3)
self.conv2 = nn.Conv2d(10, 20, kernel_size=3)
self.conv2_drop = nn.Dropout2d()
self.fc1 = nn.Linear(20 * 2 * 2, 50)
self.fc2 = nn.Linear(50, 10)
self.fc3 = nn.Linear(100, 30)... | Implementation of Neural Network: with 2 subnetwork architecture to learn the additional information besides the targets 2 convulational and 6 linear layers, ReLU activation function applied Functions: - forward: feeding the specified network with the data x in the forward pass | NN2 | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NN2:
"""Implementation of Neural Network: with 2 subnetwork architecture to learn the additional information besides the targets 2 convulational and 6 linear layers, ReLU activation function applied Functions: - forward: feeding the specified network with the data x in the forward pass"""
de... | stack_v2_sparse_classes_75kplus_train_002569 | 3,129 | permissive | [
{
"docstring": "Defining the functions to be used in building the neural nets' architecture",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "The forward pass iterates through the 2d data and for each applies the network to learn both the digits' classes and targets. Arg... | 2 | stack_v2_sparse_classes_30k_train_028991 | Implement the Python class `NN2` described below.
Class description:
Implementation of Neural Network: with 2 subnetwork architecture to learn the additional information besides the targets 2 convulational and 6 linear layers, ReLU activation function applied Functions: - forward: feeding the specified network with th... | Implement the Python class `NN2` described below.
Class description:
Implementation of Neural Network: with 2 subnetwork architecture to learn the additional information besides the targets 2 convulational and 6 linear layers, ReLU activation function applied Functions: - forward: feeding the specified network with th... | 2ca233821616d38de104caed259118cc48b3fa11 | <|skeleton|>
class NN2:
"""Implementation of Neural Network: with 2 subnetwork architecture to learn the additional information besides the targets 2 convulational and 6 linear layers, ReLU activation function applied Functions: - forward: feeding the specified network with the data x in the forward pass"""
de... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class NN2:
"""Implementation of Neural Network: with 2 subnetwork architecture to learn the additional information besides the targets 2 convulational and 6 linear layers, ReLU activation function applied Functions: - forward: feeding the specified network with the data x in the forward pass"""
def __init__(se... | the_stack_v2_python_sparse | Projects/Project1/nets/NN2.py | Shamanga/deeplearning | train | 0 |
f77064d1595449bce1e7e0d78ddf2b0230403105 | [
"LayoutItem.__init__(self, dom, parent_element, north_arrow_object, mxd, arc_doc)\nself.dom = dom\nself.parent_element = parent_element\nself.north_arrow_object = north_arrow_object\nself.mxd = mxd\nself.arc_doc = arc_doc",
"border = self.north_arrow_object.Border\nbackground = self.north_arrow_object.Background\... | <|body_start_0|>
LayoutItem.__init__(self, dom, parent_element, north_arrow_object, mxd, arc_doc)
self.dom = dom
self.parent_element = parent_element
self.north_arrow_object = north_arrow_object
self.mxd = mxd
self.arc_doc = arc_doc
<|end_body_0|>
<|body_start_1|>
... | NorthArrowElement | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NorthArrowElement:
def __init__(self, dom, parent_element, north_arrow_object, mxd, arc_doc):
"""This function creates a NorthArrow-item :param dom: the Document Object Model :param parent_element: the main layout element, where to put the layout-items :param north_arrow_object: the nort... | stack_v2_sparse_classes_75kplus_train_002570 | 2,222 | permissive | [
{
"docstring": "This function creates a NorthArrow-item :param dom: the Document Object Model :param parent_element: the main layout element, where to put the layout-items :param north_arrow_object: the northArrow as ArcObject :param mxd: the arcpy mxd-document :param arc_doc: the ArcObject IMxDocument",
"n... | 2 | null | Implement the Python class `NorthArrowElement` described below.
Class description:
Implement the NorthArrowElement class.
Method signatures and docstrings:
- def __init__(self, dom, parent_element, north_arrow_object, mxd, arc_doc): This function creates a NorthArrow-item :param dom: the Document Object Model :param ... | Implement the Python class `NorthArrowElement` described below.
Class description:
Implement the NorthArrowElement class.
Method signatures and docstrings:
- def __init__(self, dom, parent_element, north_arrow_object, mxd, arc_doc): This function creates a NorthArrow-item :param dom: the Document Object Model :param ... | cd0aa5f533194c85cf6e098fadc079ea61b63fce | <|skeleton|>
class NorthArrowElement:
def __init__(self, dom, parent_element, north_arrow_object, mxd, arc_doc):
"""This function creates a NorthArrow-item :param dom: the Document Object Model :param parent_element: the main layout element, where to put the layout-items :param north_arrow_object: the nort... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class NorthArrowElement:
def __init__(self, dom, parent_element, north_arrow_object, mxd, arc_doc):
"""This function creates a NorthArrow-item :param dom: the Document Object Model :param parent_element: the main layout element, where to put the layout-items :param north_arrow_object: the northArrow as ArcO... | the_stack_v2_python_sparse | layout/northArrowElement.py | avaldeon/mapqonverter | train | 0 | |
e9b8e24fe6ad82416d65ccf6a39742bf7257fbeb | [
"if base == tgt:\n a = tmp[:]\n lst.append(a)\n return\nfor i in xrange(depth, len(ref)):\n if base + ref[i] <= tgt:\n tmp.append(ref[i])\n self.CS(base + ref[i], tgt, lst, ref, tmp, i)\n tmp.pop()",
"candidates.sort()\nres, tmp = ([], [])\nself.CS(0, target, res, candidates, tmp,... | <|body_start_0|>
if base == tgt:
a = tmp[:]
lst.append(a)
return
for i in xrange(depth, len(ref)):
if base + ref[i] <= tgt:
tmp.append(ref[i])
self.CS(base + ref[i], tgt, lst, ref, tmp, i)
tmp.pop()
<|end_bod... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def CS(self, base, tgt, lst, ref, tmp, depth):
"""base: value already calculated tgt: target number lst: result List ref: candidates List tmp: one answer depth: 到了第几个数"""
<|body_0|>
def combinationSum(self, candidates, target):
""":type candidates: List[int... | stack_v2_sparse_classes_75kplus_train_002571 | 3,337 | no_license | [
{
"docstring": "base: value already calculated tgt: target number lst: result List ref: candidates List tmp: one answer depth: 到了第几个数",
"name": "CS",
"signature": "def CS(self, base, tgt, lst, ref, tmp, depth)"
},
{
"docstring": ":type candidates: List[int] :type target: int :rtype: List[List[in... | 2 | stack_v2_sparse_classes_30k_train_017749 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def CS(self, base, tgt, lst, ref, tmp, depth): base: value already calculated tgt: target number lst: result List ref: candidates List tmp: one answer depth: 到了第几个数
- def combina... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def CS(self, base, tgt, lst, ref, tmp, depth): base: value already calculated tgt: target number lst: result List ref: candidates List tmp: one answer depth: 到了第几个数
- def combina... | 507ed2efeff7818ca9cf53a8ee7fb80d3c530d67 | <|skeleton|>
class Solution:
def CS(self, base, tgt, lst, ref, tmp, depth):
"""base: value already calculated tgt: target number lst: result List ref: candidates List tmp: one answer depth: 到了第几个数"""
<|body_0|>
def combinationSum(self, candidates, target):
""":type candidates: List[int... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def CS(self, base, tgt, lst, ref, tmp, depth):
"""base: value already calculated tgt: target number lst: result List ref: candidates List tmp: one answer depth: 到了第几个数"""
if base == tgt:
a = tmp[:]
lst.append(a)
return
for i in xrange(depth... | the_stack_v2_python_sparse | Leetcode/Backtracking/#39-Combination Sum/main.py | qizongjun/Algorithms-1 | train | 0 | |
58c903cd2492d29938bb5ec575c8b8bfae6a729f | [
"self.__logger = log(self.__class__.__name__)\nself.symbols = []\ns = self.symbolFactory(geoType, graduation.symbol(), layerTransparency)\nself.symbols.append(s)\nself.field = field\nself.label = str(graduation.label())\nself.value = str(graduation.lowerValue()) + ' - ' + str(graduation.upperValue())\nself.lowValue... | <|body_start_0|>
self.__logger = log(self.__class__.__name__)
self.symbols = []
s = self.symbolFactory(geoType, graduation.symbol(), layerTransparency)
self.symbols.append(s)
self.field = field
self.label = str(graduation.label())
self.value = str(graduation.lower... | Graduated renderer class | graduated | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class graduated:
"""Graduated renderer class"""
def __init__(self, geoType, field, graduation, layerTransparency):
"""Initialise the symbol range :param geoType: Layer.geometryType() GeometryType of the layer. :type geoType: GeometryType e.g. QGis.WKBPolygon :param field: Name of the attri... | stack_v2_sparse_classes_75kplus_train_002572 | 36,198 | permissive | [
{
"docstring": "Initialise the symbol range :param geoType: Layer.geometryType() GeometryType of the layer. :type geoType: GeometryType e.g. QGis.WKBPolygon :param field: Name of the attribute field used in the symbology :type field: str :param graduation: The graduation range object. :type graduation: QgsRende... | 3 | stack_v2_sparse_classes_30k_train_051139 | Implement the Python class `graduated` described below.
Class description:
Graduated renderer class
Method signatures and docstrings:
- def __init__(self, geoType, field, graduation, layerTransparency): Initialise the symbol range :param geoType: Layer.geometryType() GeometryType of the layer. :type geoType: Geometry... | Implement the Python class `graduated` described below.
Class description:
Graduated renderer class
Method signatures and docstrings:
- def __init__(self, geoType, field, graduation, layerTransparency): Initialise the symbol range :param geoType: Layer.geometryType() GeometryType of the layer. :type geoType: Geometry... | aa3733f2cc0e52ca70b93bc55d5f8f7059b73e31 | <|skeleton|>
class graduated:
"""Graduated renderer class"""
def __init__(self, geoType, field, graduation, layerTransparency):
"""Initialise the symbol range :param geoType: Layer.geometryType() GeometryType of the layer. :type geoType: GeometryType e.g. QGis.WKBPolygon :param field: Name of the attri... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class graduated:
"""Graduated renderer class"""
def __init__(self, geoType, field, graduation, layerTransparency):
"""Initialise the symbol range :param geoType: Layer.geometryType() GeometryType of the layer. :type geoType: GeometryType e.g. QGis.WKBPolygon :param field: Name of the attribute field us... | the_stack_v2_python_sparse | symbology.py | Real-Currents/d3MapRenderer | train | 0 |
868a99cf61cbf050fcf871009d097b549a06d0af | [
"self.logger = log.get_logger(__name__, os.path.join(log_directory, 'parseAndPopulate.log'))\nself.file_name = file_name\nself.yang_modules: dict[str, Module] = {}",
"key = f'{yang.name}@{yang.revision}/{yang.organization}'\nself.logger.debug(f'Module {key} parsed')\nif key in self.yang_modules:\n self.yang_mo... | <|body_start_0|>
self.logger = log.get_logger(__name__, os.path.join(log_directory, 'parseAndPopulate.log'))
self.file_name = file_name
self.yang_modules: dict[str, Module] = {}
<|end_body_0|>
<|body_start_1|>
key = f'{yang.name}@{yang.revision}/{yang.organization}'
self.logger.... | A dumper for yang module metadata. | Dumper | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Dumper:
"""A dumper for yang module metadata."""
def __init__(self, log_directory: str, file_name: str):
"""Arguments: :param log_directory: (str) directory where the log file is saved :param file_name: (str) name of the file to which the modules are dumped"""
<|body_0|>
... | stack_v2_sparse_classes_75kplus_train_002573 | 12,099 | permissive | [
{
"docstring": "Arguments: :param log_directory: (str) directory where the log file is saved :param file_name: (str) name of the file to which the modules are dumped",
"name": "__init__",
"signature": "def __init__(self, log_directory: str, file_name: str)"
},
{
"docstring": "Add a module's data... | 4 | null | Implement the Python class `Dumper` described below.
Class description:
A dumper for yang module metadata.
Method signatures and docstrings:
- def __init__(self, log_directory: str, file_name: str): Arguments: :param log_directory: (str) directory where the log file is saved :param file_name: (str) name of the file t... | Implement the Python class `Dumper` described below.
Class description:
A dumper for yang module metadata.
Method signatures and docstrings:
- def __init__(self, log_directory: str, file_name: str): Arguments: :param log_directory: (str) directory where the log file is saved :param file_name: (str) name of the file t... | fa393721824e4d30704405132b08f4c01cbde6c1 | <|skeleton|>
class Dumper:
"""A dumper for yang module metadata."""
def __init__(self, log_directory: str, file_name: str):
"""Arguments: :param log_directory: (str) directory where the log file is saved :param file_name: (str) name of the file to which the modules are dumped"""
<|body_0|>
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Dumper:
"""A dumper for yang module metadata."""
def __init__(self, log_directory: str, file_name: str):
"""Arguments: :param log_directory: (str) directory where the log file is saved :param file_name: (str) name of the file to which the modules are dumped"""
self.logger = log.get_logger... | the_stack_v2_python_sparse | parseAndPopulate/dumper.py | YangCatalog/backend | train | 3 |
e7262655819394e3f313bdf5f6601c2d8632a94f | [
"super().__init__()\nif filename is not None:\n self.readFile(filename)",
"types = {'flashPortionHistoryID': np.int64, 'flashPortionID': str, 'flashID': str, 'nullTime': str, 'time': str, 'lat': np.float, 'lon': np.float, 'alt': np.float, 'type': str, 'amp': np.float}\npdArgs = {'skiprows': 1, 'chunksize': 100... | <|body_start_0|>
super().__init__()
if filename is not None:
self.readFile(filename)
<|end_body_0|>
<|body_start_1|>
types = {'flashPortionHistoryID': np.int64, 'flashPortionID': str, 'flashID': str, 'nullTime': str, 'time': str, 'lat': np.float, 'lon': np.float, 'alt': np.float, 't... | Class to handle Earth Networks Total Lightning Network data. Many of the following are not attributes of the class, but are columns in the underlying Dataframe. But, you can access them as you would an attribute.... Attributes ----------- _data : Dataframe The underlying data. A "real" attribute of the class. flashID :... | ENTLN | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ENTLN:
"""Class to handle Earth Networks Total Lightning Network data. Many of the following are not attributes of the class, but are columns in the underlying Dataframe. But, you can access them as you would an attribute.... Attributes ----------- _data : Dataframe The underlying data. A "real" ... | stack_v2_sparse_classes_75kplus_train_002574 | 7,079 | no_license | [
{
"docstring": "If you don't provide a file name, you'll have to call :meth:`readFile` yourself to actually do anything useful. Parameters ---------- filename : str The file name to be read in.",
"name": "__init__",
"signature": "def __init__(self, filename=None)"
},
{
"docstring": "Given a file... | 2 | stack_v2_sparse_classes_30k_train_019883 | Implement the Python class `ENTLN` described below.
Class description:
Class to handle Earth Networks Total Lightning Network data. Many of the following are not attributes of the class, but are columns in the underlying Dataframe. But, you can access them as you would an attribute.... Attributes ----------- _data : D... | Implement the Python class `ENTLN` described below.
Class description:
Class to handle Earth Networks Total Lightning Network data. Many of the following are not attributes of the class, but are columns in the underlying Dataframe. But, you can access them as you would an attribute.... Attributes ----------- _data : D... | 67f98b5d96ad26407efe98d4303a7d0b084bf06b | <|skeleton|>
class ENTLN:
"""Class to handle Earth Networks Total Lightning Network data. Many of the following are not attributes of the class, but are columns in the underlying Dataframe. But, you can access them as you would an attribute.... Attributes ----------- _data : Dataframe The underlying data. A "real" ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ENTLN:
"""Class to handle Earth Networks Total Lightning Network data. Many of the following are not attributes of the class, but are columns in the underlying Dataframe. But, you can access them as you would an attribute.... Attributes ----------- _data : Dataframe The underlying data. A "real" attribute of ... | the_stack_v2_python_sparse | pyltg/core/entln.py | safelysparky/pyltg | train | 0 |
bac662a2ecfdd80a4b669b79de86cc2363323e0c | [
"server, validation_resources = self._create_server()\nif CONF.validation.run_validation:\n linux_client = remote_client.RemoteClient(self.get_server_ip(server, validation_resources), self.image_ssh_user, self.image_ssh_password, validation_resources['keypair']['private_key'], server=server, servers_client=self.... | <|body_start_0|>
server, validation_resources = self._create_server()
if CONF.validation.run_validation:
linux_client = remote_client.RemoteClient(self.get_server_ip(server, validation_resources), self.image_ssh_user, self.image_ssh_password, validation_resources['keypair']['private_key'], s... | Test attaching volume to server | AttachVolumeTestJSON | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AttachVolumeTestJSON:
"""Test attaching volume to server"""
def test_attach_detach_volume(self):
"""Test attaching and detaching volume from server Stop and Start a server with an attached volume, ensuring that the volume remains attached."""
<|body_0|>
def test_list_get... | stack_v2_sparse_classes_75kplus_train_002575 | 23,311 | permissive | [
{
"docstring": "Test attaching and detaching volume from server Stop and Start a server with an attached volume, ensuring that the volume remains attached.",
"name": "test_attach_detach_volume",
"signature": "def test_attach_detach_volume(self)"
},
{
"docstring": "Test listing and getting volume... | 2 | stack_v2_sparse_classes_30k_train_032263 | Implement the Python class `AttachVolumeTestJSON` described below.
Class description:
Test attaching volume to server
Method signatures and docstrings:
- def test_attach_detach_volume(self): Test attaching and detaching volume from server Stop and Start a server with an attached volume, ensuring that the volume remai... | Implement the Python class `AttachVolumeTestJSON` described below.
Class description:
Test attaching volume to server
Method signatures and docstrings:
- def test_attach_detach_volume(self): Test attaching and detaching volume from server Stop and Start a server with an attached volume, ensuring that the volume remai... | 3932a799e620a20d7abf7b89e21b520683a1809b | <|skeleton|>
class AttachVolumeTestJSON:
"""Test attaching volume to server"""
def test_attach_detach_volume(self):
"""Test attaching and detaching volume from server Stop and Start a server with an attached volume, ensuring that the volume remains attached."""
<|body_0|>
def test_list_get... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AttachVolumeTestJSON:
"""Test attaching volume to server"""
def test_attach_detach_volume(self):
"""Test attaching and detaching volume from server Stop and Start a server with an attached volume, ensuring that the volume remains attached."""
server, validation_resources = self._create_se... | the_stack_v2_python_sparse | tempest/api/compute/volumes/test_attach_volume.py | openstack/tempest | train | 270 |
8ed236b3786393e0614b3e3b51ebed760f928cfb | [
"self._model = dict()\nself._ngram = 1\nself._epsilon = sppasPerplexity.DEFAULT_EPSILON\nself.set_model(model)\nself.set_ngram(ngram)",
"eps = float(eps)\nif eps < 0.0 or eps > 0.1:\n raise InsideIntervalError(eps, 0.0, 0.1)\nif self._model is not None:\n p_min = round(min((proba for proba in self._model.va... | <|body_start_0|>
self._model = dict()
self._ngram = 1
self._epsilon = sppasPerplexity.DEFAULT_EPSILON
self.set_model(model)
self.set_ngram(ngram)
<|end_body_0|>
<|body_start_1|>
eps = float(eps)
if eps < 0.0 or eps > 0.1:
raise InsideIntervalError(eps... | Perplexity estimator. :author: Brigitte Bigi :organization: Laboratoire Parole et Langage, Aix-en-Provence, France :contact: develop@sppas.org :license: GPL, v3 :copyright: Copyright (C) 2011-2018 Brigitte Bigi Perplexity is a measurement of how well a probability distribution or probability model predicts a sample. Th... | sppasPerplexity | [
"MIT",
"GFDL-1.1-or-later",
"GPL-3.0-only",
"GPL-3.0-or-later"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class sppasPerplexity:
"""Perplexity estimator. :author: Brigitte Bigi :organization: Laboratoire Parole et Langage, Aix-en-Provence, France :contact: develop@sppas.org :license: GPL, v3 :copyright: Copyright (C) 2011-2018 Brigitte Bigi Perplexity is a measurement of how well a probability distribution... | stack_v2_sparse_classes_75kplus_train_002576 | 6,620 | permissive | [
{
"docstring": "Create a Perplexity instance with a list of symbols. :param model: (dict) a dictionary with key=item, value=probability :param ngram: (int) the n value, in the range 1..8",
"name": "__init__",
"signature": "def __init__(self, model, ngram=1)"
},
{
"docstring": "Set a value for ep... | 5 | stack_v2_sparse_classes_30k_val_000207 | Implement the Python class `sppasPerplexity` described below.
Class description:
Perplexity estimator. :author: Brigitte Bigi :organization: Laboratoire Parole et Langage, Aix-en-Provence, France :contact: develop@sppas.org :license: GPL, v3 :copyright: Copyright (C) 2011-2018 Brigitte Bigi Perplexity is a measurement... | Implement the Python class `sppasPerplexity` described below.
Class description:
Perplexity estimator. :author: Brigitte Bigi :organization: Laboratoire Parole et Langage, Aix-en-Provence, France :contact: develop@sppas.org :license: GPL, v3 :copyright: Copyright (C) 2011-2018 Brigitte Bigi Perplexity is a measurement... | 3167b65f576abcc27a8767d24c274a04712bd948 | <|skeleton|>
class sppasPerplexity:
"""Perplexity estimator. :author: Brigitte Bigi :organization: Laboratoire Parole et Langage, Aix-en-Provence, France :contact: develop@sppas.org :license: GPL, v3 :copyright: Copyright (C) 2011-2018 Brigitte Bigi Perplexity is a measurement of how well a probability distribution... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class sppasPerplexity:
"""Perplexity estimator. :author: Brigitte Bigi :organization: Laboratoire Parole et Langage, Aix-en-Provence, France :contact: develop@sppas.org :license: GPL, v3 :copyright: Copyright (C) 2011-2018 Brigitte Bigi Perplexity is a measurement of how well a probability distribution or probabili... | the_stack_v2_python_sparse | sppas/sppas/src/calculus/infotheory/perplexity.py | mirfan899/MTTS | train | 0 |
9bea97f082fa6abee64e2d9cc400ac36880a3655 | [
"list_c = []\nfor index, item in enumerate(S):\n if C == item:\n list_c.append(index)\nlist_return = []\nfor index, item in enumerate(S):\n list_dif = []\n for dif in list_c:\n list_dif.append(abs(index - dif))\n list_return.append(min(list_dif))\nreturn list_return",
"list_c = []\nfor i... | <|body_start_0|>
list_c = []
for index, item in enumerate(S):
if C == item:
list_c.append(index)
list_return = []
for index, item in enumerate(S):
list_dif = []
for dif in list_c:
list_dif.append(abs(index - dif))
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def shortestToChar(self, S, C):
""":type S: str :type C: str :rtype: List[int]"""
<|body_0|>
def shortestToChar2(self, S, C):
""":type S: str :type C: str :rtype: List[int]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
list_c = []
... | stack_v2_sparse_classes_75kplus_train_002577 | 1,081 | no_license | [
{
"docstring": ":type S: str :type C: str :rtype: List[int]",
"name": "shortestToChar",
"signature": "def shortestToChar(self, S, C)"
},
{
"docstring": ":type S: str :type C: str :rtype: List[int]",
"name": "shortestToChar2",
"signature": "def shortestToChar2(self, S, C)"
}
] | 2 | stack_v2_sparse_classes_30k_train_023938 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def shortestToChar(self, S, C): :type S: str :type C: str :rtype: List[int]
- def shortestToChar2(self, S, C): :type S: str :type C: str :rtype: List[int] | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def shortestToChar(self, S, C): :type S: str :type C: str :rtype: List[int]
- def shortestToChar2(self, S, C): :type S: str :type C: str :rtype: List[int]
<|skeleton|>
class Sol... | f777f0224f188a787457c418fa3331c1e92d13e5 | <|skeleton|>
class Solution:
def shortestToChar(self, S, C):
""":type S: str :type C: str :rtype: List[int]"""
<|body_0|>
def shortestToChar2(self, S, C):
""":type S: str :type C: str :rtype: List[int]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def shortestToChar(self, S, C):
""":type S: str :type C: str :rtype: List[int]"""
list_c = []
for index, item in enumerate(S):
if C == item:
list_c.append(index)
list_return = []
for index, item in enumerate(S):
list_dif... | the_stack_v2_python_sparse | let821.py | fredfeng0326/LeetCode | train | 3 | |
99450ced7e4c106cabf7ef9ec30fd8835b4f84a2 | [
"super(AdamWeightDecayOptimizer, self).__init__(False, name)\nself.learning_rate = learning_rate\nself.weight_decay_rate = weight_decay_rate\nself.beta_1 = beta_1\nself.beta_2 = beta_2\nself.epsilon = epsilon\nself.exclude_from_weight_decay = exclude_from_weight_decay",
"assignments = []\nfor grad, param in grads... | <|body_start_0|>
super(AdamWeightDecayOptimizer, self).__init__(False, name)
self.learning_rate = learning_rate
self.weight_decay_rate = weight_decay_rate
self.beta_1 = beta_1
self.beta_2 = beta_2
self.epsilon = epsilon
self.exclude_from_weight_decay = exclude_fro... | A basic Adam optimizer that includes "correct" L2 weight decay. | AdamWeightDecayOptimizer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AdamWeightDecayOptimizer:
"""A basic Adam optimizer that includes "correct" L2 weight decay."""
def __init__(self, learning_rate, weight_decay_rate=0.0, beta_1=0.9, beta_2=0.999, epsilon=1e-06, exclude_from_weight_decay=None, name='AdamWeightDecayOptimizer'):
"""Constructs a AdamWeig... | stack_v2_sparse_classes_75kplus_train_002578 | 16,787 | no_license | [
{
"docstring": "Constructs a AdamWeightDecayOptimizer.",
"name": "__init__",
"signature": "def __init__(self, learning_rate, weight_decay_rate=0.0, beta_1=0.9, beta_2=0.999, epsilon=1e-06, exclude_from_weight_decay=None, name='AdamWeightDecayOptimizer')"
},
{
"docstring": "See base class.",
... | 4 | stack_v2_sparse_classes_30k_test_002081 | Implement the Python class `AdamWeightDecayOptimizer` described below.
Class description:
A basic Adam optimizer that includes "correct" L2 weight decay.
Method signatures and docstrings:
- def __init__(self, learning_rate, weight_decay_rate=0.0, beta_1=0.9, beta_2=0.999, epsilon=1e-06, exclude_from_weight_decay=None... | Implement the Python class `AdamWeightDecayOptimizer` described below.
Class description:
A basic Adam optimizer that includes "correct" L2 weight decay.
Method signatures and docstrings:
- def __init__(self, learning_rate, weight_decay_rate=0.0, beta_1=0.9, beta_2=0.999, epsilon=1e-06, exclude_from_weight_decay=None... | 7be89d283b4f0572b47ba0150647080976e5928f | <|skeleton|>
class AdamWeightDecayOptimizer:
"""A basic Adam optimizer that includes "correct" L2 weight decay."""
def __init__(self, learning_rate, weight_decay_rate=0.0, beta_1=0.9, beta_2=0.999, epsilon=1e-06, exclude_from_weight_decay=None, name='AdamWeightDecayOptimizer'):
"""Constructs a AdamWeig... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AdamWeightDecayOptimizer:
"""A basic Adam optimizer that includes "correct" L2 weight decay."""
def __init__(self, learning_rate, weight_decay_rate=0.0, beta_1=0.9, beta_2=0.999, epsilon=1e-06, exclude_from_weight_decay=None, name='AdamWeightDecayOptimizer'):
"""Constructs a AdamWeightDecayOptimi... | the_stack_v2_python_sparse | model/utils.py | SangMyeongWoh/mass_raw_tf1 | train | 0 |
9b90606d3456f8603f6db3ae0aea5585b0173077 | [
"picking_obj = self.pool.get('stock.picking')\nseq_obj_name = self._name\nvals['name'] = self.pool.get('ir.sequence').get(cr, user, seq_obj_name)\nnew_id = picking_obj.create(cr, user, vals, context)\nreturn new_id",
"picking_obj = self.pool.get('stock.picking')\nwrite_boolean = picking_obj.write(cr, uid, ids, va... | <|body_start_0|>
picking_obj = self.pool.get('stock.picking')
seq_obj_name = self._name
vals['name'] = self.pool.get('ir.sequence').get(cr, user, seq_obj_name)
new_id = picking_obj.create(cr, user, vals, context)
return new_id
<|end_body_0|>
<|body_start_1|>
picking_obj ... | stock_picking_out | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class stock_picking_out:
def create(self, cr, user, vals, context=None):
"""Override create to call create of stock.picking"""
<|body_0|>
def write(self, cr, uid, ids, vals, context=None):
"""Override write to call write of stock.picking"""
<|body_1|>
<|end_skelet... | stack_v2_sparse_classes_75kplus_train_002579 | 17,898 | no_license | [
{
"docstring": "Override create to call create of stock.picking",
"name": "create",
"signature": "def create(self, cr, user, vals, context=None)"
},
{
"docstring": "Override write to call write of stock.picking",
"name": "write",
"signature": "def write(self, cr, uid, ids, vals, context=... | 2 | stack_v2_sparse_classes_30k_train_047224 | Implement the Python class `stock_picking_out` described below.
Class description:
Implement the stock_picking_out class.
Method signatures and docstrings:
- def create(self, cr, user, vals, context=None): Override create to call create of stock.picking
- def write(self, cr, uid, ids, vals, context=None): Override wr... | Implement the Python class `stock_picking_out` described below.
Class description:
Implement the stock_picking_out class.
Method signatures and docstrings:
- def create(self, cr, user, vals, context=None): Override create to call create of stock.picking
- def write(self, cr, uid, ids, vals, context=None): Override wr... | 0b997095c260d58b026440967fea3a202bef7efb | <|skeleton|>
class stock_picking_out:
def create(self, cr, user, vals, context=None):
"""Override create to call create of stock.picking"""
<|body_0|>
def write(self, cr, uid, ids, vals, context=None):
"""Override write to call write of stock.picking"""
<|body_1|>
<|end_skelet... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class stock_picking_out:
def create(self, cr, user, vals, context=None):
"""Override create to call create of stock.picking"""
picking_obj = self.pool.get('stock.picking')
seq_obj_name = self._name
vals['name'] = self.pool.get('ir.sequence').get(cr, user, seq_obj_name)
new_id... | the_stack_v2_python_sparse | v_7/NISS/shamil_v3/stock_oc/model/stock.py | musabahmed/baba | train | 0 | |
9e2d322cb9719fde8286510f62034d0149e75876 | [
"ret = []\nstk = collections.deque()\nwhile root is not None or len(stk) > 0:\n if root is not None:\n ret.append(str(root.val))\n stk.append(root)\n root = root.left\n else:\n root = stk.pop()\n root = root.right\nreturn ' '.join(ret)",
"def insert(root, val):\n pre = ... | <|body_start_0|>
ret = []
stk = collections.deque()
while root is not None or len(stk) > 0:
if root is not None:
ret.append(str(root.val))
stk.append(root)
root = root.left
else:
root = stk.pop()
... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|>
<|body_... | stack_v2_sparse_classes_75kplus_train_002580 | 2,336 | 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_val_001056 | 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:... | 9190d3d178f1733aa226973757ee7e045b7bab00 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
ret = []
stk = collections.deque()
while root is not None or len(stk) > 0:
if root is not None:
ret.append(str(root.val))
stk.... | the_stack_v2_python_sparse | SerializeAndDeserializeBST.py | ellinx/LC-python | train | 1 | |
b22daa7f7a70b6536b155a86a2f36f8e9cdb12e0 | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn Acl()",
"from .access_type import AccessType\nfrom .acl_type import AclType\nfrom .access_type import AccessType\nfrom .acl_type import AclType\nfields: Dict[str, Callable[[Any], None]] = {'accessType': lambda n: setattr(self, 'access_... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return Acl()
<|end_body_0|>
<|body_start_1|>
from .access_type import AccessType
from .acl_type import AclType
from .access_type import AccessType
from .acl_type import AclType
... | Acl | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Acl:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Acl:
"""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: Acl"""
<|b... | stack_v2_sparse_classes_75kplus_train_002581 | 3,338 | 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: Acl",
"name": "create_from_discriminator_value",
"signature": "def create_from_discriminator_value(parse_nod... | 3 | stack_v2_sparse_classes_30k_train_028210 | Implement the Python class `Acl` described below.
Class description:
Implement the Acl class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Acl: Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse n... | Implement the Python class `Acl` described below.
Class description:
Implement the Acl class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Acl: Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse n... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class Acl:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Acl:
"""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: Acl"""
<|b... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Acl:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Acl:
"""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: Acl"""
if not parse_node... | the_stack_v2_python_sparse | msgraph/generated/models/external_connectors/acl.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
d01ee51a5c177eb4089f6f2f03824c2bc03a329c | [
"trial_questionpaper = self.get(quiz_id=original_quiz_id)\nfixed_ques = trial_questionpaper.get_ordered_questions()\ntrial_questions = {'fixed_questions': fixed_ques, 'random_questions': trial_questionpaper.random_questions.all()}\ntrial_questionpaper.pk = None\ntrial_questionpaper.save()\nreturn (trial_questionpap... | <|body_start_0|>
trial_questionpaper = self.get(quiz_id=original_quiz_id)
fixed_ques = trial_questionpaper.get_ordered_questions()
trial_questions = {'fixed_questions': fixed_ques, 'random_questions': trial_questionpaper.random_questions.all()}
trial_questionpaper.pk = None
trial... | QuestionPaperManager | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class QuestionPaperManager:
def _create_trial_from_questionpaper(self, original_quiz_id):
"""Creates a copy of the original questionpaper"""
<|body_0|>
def create_trial_paper_to_test_questions(self, trial_quiz, questions_list):
"""Creates a trial question paper to test sel... | stack_v2_sparse_classes_75kplus_train_002582 | 39,625 | no_license | [
{
"docstring": "Creates a copy of the original questionpaper",
"name": "_create_trial_from_questionpaper",
"signature": "def _create_trial_from_questionpaper(self, original_quiz_id)"
},
{
"docstring": "Creates a trial question paper to test selected questions",
"name": "create_trial_paper_to... | 3 | null | Implement the Python class `QuestionPaperManager` described below.
Class description:
Implement the QuestionPaperManager class.
Method signatures and docstrings:
- def _create_trial_from_questionpaper(self, original_quiz_id): Creates a copy of the original questionpaper
- def create_trial_paper_to_test_questions(self... | Implement the Python class `QuestionPaperManager` described below.
Class description:
Implement the QuestionPaperManager class.
Method signatures and docstrings:
- def _create_trial_from_questionpaper(self, original_quiz_id): Creates a copy of the original questionpaper
- def create_trial_paper_to_test_questions(self... | 16c742d20fcfc220e0e8c7fe3ebade54c516dcf4 | <|skeleton|>
class QuestionPaperManager:
def _create_trial_from_questionpaper(self, original_quiz_id):
"""Creates a copy of the original questionpaper"""
<|body_0|>
def create_trial_paper_to_test_questions(self, trial_quiz, questions_list):
"""Creates a trial question paper to test sel... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class QuestionPaperManager:
def _create_trial_from_questionpaper(self, original_quiz_id):
"""Creates a copy of the original questionpaper"""
trial_questionpaper = self.get(quiz_id=original_quiz_id)
fixed_ques = trial_questionpaper.get_ordered_questions()
trial_questions = {'fixed_que... | the_stack_v2_python_sparse | preassesment/models.py | ajayradiantinfonet/lms | train | 0 | |
e7328d03f5696e1e2f9556deafc134bada5772aa | [
"if not await get_data_from_req(self.request).samples.has_right(sample_id, self.request['client'], SampleRight.read):\n raise InsufficientRights\ntry:\n sample = await get_data_from_req(self.request).samples.get(sample_id)\nexcept ResourceNotFoundError:\n raise NotFound\nreturn json_response(sample)",
"i... | <|body_start_0|>
if not await get_data_from_req(self.request).samples.has_right(sample_id, self.request['client'], SampleRight.read):
raise InsufficientRights
try:
sample = await get_data_from_req(self.request).samples.get(sample_id)
except ResourceNotFoundError:
... | SampleView | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SampleView:
async def get(self, sample_id: str, /) -> Union[r200[GetSampleResponse], r403, r404]:
"""Get a sample. Fetches the details for a sample. Status Codes: 200: Successful operation 400: Invalid query"""
<|body_0|>
async def patch(self, sample_id: str, /, data: Update... | stack_v2_sparse_classes_75kplus_train_002583 | 29,048 | permissive | [
{
"docstring": "Get a sample. Fetches the details for a sample. Status Codes: 200: Successful operation 400: Invalid query",
"name": "get",
"signature": "async def get(self, sample_id: str, /) -> Union[r200[GetSampleResponse], r403, r404]"
},
{
"docstring": "Update a sample. Updates a sample usi... | 3 | stack_v2_sparse_classes_30k_train_008744 | Implement the Python class `SampleView` described below.
Class description:
Implement the SampleView class.
Method signatures and docstrings:
- async def get(self, sample_id: str, /) -> Union[r200[GetSampleResponse], r403, r404]: Get a sample. Fetches the details for a sample. Status Codes: 200: Successful operation ... | Implement the Python class `SampleView` described below.
Class description:
Implement the SampleView class.
Method signatures and docstrings:
- async def get(self, sample_id: str, /) -> Union[r200[GetSampleResponse], r403, r404]: Get a sample. Fetches the details for a sample. Status Codes: 200: Successful operation ... | 1d17d2ba570cf5487e7514bec29250a5b368bb0a | <|skeleton|>
class SampleView:
async def get(self, sample_id: str, /) -> Union[r200[GetSampleResponse], r403, r404]:
"""Get a sample. Fetches the details for a sample. Status Codes: 200: Successful operation 400: Invalid query"""
<|body_0|>
async def patch(self, sample_id: str, /, data: Update... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SampleView:
async def get(self, sample_id: str, /) -> Union[r200[GetSampleResponse], r403, r404]:
"""Get a sample. Fetches the details for a sample. Status Codes: 200: Successful operation 400: Invalid query"""
if not await get_data_from_req(self.request).samples.has_right(sample_id, self.requ... | the_stack_v2_python_sparse | virtool/samples/api.py | virtool/virtool | train | 45 | |
e04541ffaf3fd42fb9eafd1b284fd6c1cdff0f20 | [
"super(Pan, self).__init__(image=Pan.image, x=games.mouse.x, bottom=games.screen.height)\nself.score = games.Text(value=0, size=25, color=color.black, top=5, right=games.screen.width - 10)\ngames.screen.add(self.score)",
"self.x = games.mouse.x\nif self.left < 0:\n self.left = 0\nif self.right > games.screen.w... | <|body_start_0|>
super(Pan, self).__init__(image=Pan.image, x=games.mouse.x, bottom=games.screen.height)
self.score = games.Text(value=0, size=25, color=color.black, top=5, right=games.screen.width - 10)
games.screen.add(self.score)
<|end_body_0|>
<|body_start_1|>
self.x = games.mouse.x... | Сковорода, в которую игрок может ловить падающий бургер. | Pan | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Pan:
"""Сковорода, в которую игрок может ловить падающий бургер."""
def __init__(self):
"""Инициализирует объект Рап и создает объект Text для отображения счета"""
<|body_0|>
def update(self):
"""Передвигает объект по горизонтали"""
<|body_1|>
def ch... | stack_v2_sparse_classes_75kplus_train_002584 | 5,097 | no_license | [
{
"docstring": "Инициализирует объект Рап и создает объект Text для отображения счета",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Передвигает объект по горизонтали",
"name": "update",
"signature": "def update(self)"
},
{
"docstring": "Проверяет, пой... | 3 | stack_v2_sparse_classes_30k_train_009342 | Implement the Python class `Pan` described below.
Class description:
Сковорода, в которую игрок может ловить падающий бургер.
Method signatures and docstrings:
- def __init__(self): Инициализирует объект Рап и создает объект Text для отображения счета
- def update(self): Передвигает объект по горизонтали
- def check_... | Implement the Python class `Pan` described below.
Class description:
Сковорода, в которую игрок может ловить падающий бургер.
Method signatures and docstrings:
- def __init__(self): Инициализирует объект Рап и создает объект Text для отображения счета
- def update(self): Передвигает объект по горизонтали
- def check_... | 19244b259eec779381c5deb348d2ddf5f439a364 | <|skeleton|>
class Pan:
"""Сковорода, в которую игрок может ловить падающий бургер."""
def __init__(self):
"""Инициализирует объект Рап и создает объект Text для отображения счета"""
<|body_0|>
def update(self):
"""Передвигает объект по горизонтали"""
<|body_1|>
def ch... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Pan:
"""Сковорода, в которую игрок может ловить падающий бургер."""
def __init__(self):
"""Инициализирует объект Рап и создает объект Text для отображения счета"""
super(Pan, self).__init__(image=Pan.image, x=games.mouse.x, bottom=games.screen.height)
self.score = games.Text(value... | the_stack_v2_python_sparse | Graphics/burger_panic.py | kononenkoie/CS50_examples_PYTHON | train | 0 |
b04296dcd2aee21189dbd8245f8be756ea711409 | [
"self.type = 'Optim'\nself.date = ''\nself.modules = []\nself.minmax = 'min'\nself.objective = ['cl']\nself.driver = 'COBYLA'\nself.save_iter = 1\nself.max_iter = 200\nself.tol = 0.001\nself.doedriver = 'uniform'\nself.samplesnb = 3\nself.doe_file = ''\nself.user_config = '../Optimisation/Default_config.csv'\nself.... | <|body_start_0|>
self.type = 'Optim'
self.date = ''
self.modules = []
self.minmax = 'min'
self.objective = ['cl']
self.driver = 'COBYLA'
self.save_iter = 1
self.max_iter = 200
self.tol = 0.001
self.doedriver = 'uniform'
self.samples... | Setup the routine to launch in Openmdao. | Routine | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Routine:
"""Setup the routine to launch in Openmdao."""
def __init__(self):
"""Define default main parameters."""
<|body_0|>
def get_user_inputs(self, tixi):
"""Take user inputs from the GUI."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.... | stack_v2_sparse_classes_75kplus_train_002585 | 19,812 | permissive | [
{
"docstring": "Define default main parameters.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Take user inputs from the GUI.",
"name": "get_user_inputs",
"signature": "def get_user_inputs(self, tixi)"
}
] | 2 | stack_v2_sparse_classes_30k_train_044759 | Implement the Python class `Routine` described below.
Class description:
Setup the routine to launch in Openmdao.
Method signatures and docstrings:
- def __init__(self): Define default main parameters.
- def get_user_inputs(self, tixi): Take user inputs from the GUI. | Implement the Python class `Routine` described below.
Class description:
Setup the routine to launch in Openmdao.
Method signatures and docstrings:
- def __init__(self): Define default main parameters.
- def get_user_inputs(self, tixi): Take user inputs from the GUI.
<|skeleton|>
class Routine:
"""Setup the rout... | 3cc211507caab176a76213e442238abfa43afa42 | <|skeleton|>
class Routine:
"""Setup the routine to launch in Openmdao."""
def __init__(self):
"""Define default main parameters."""
<|body_0|>
def get_user_inputs(self, tixi):
"""Take user inputs from the GUI."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Routine:
"""Setup the routine to launch in Openmdao."""
def __init__(self):
"""Define default main parameters."""
self.type = 'Optim'
self.date = ''
self.modules = []
self.minmax = 'min'
self.objective = ['cl']
self.driver = 'COBYLA'
self.sa... | the_stack_v2_python_sparse | ceasiompy/Optimisation/func/optimfunctions.py | schneo/CEASIOMpy | train | 0 |
628a9332b03ada0a770325ba6fe7bda689c4a831 | [
"assert isinstance(node, NodeDefinition)\nself._node = node\nself.rules = list()",
"if not closure is None:\n assert Tool.isCallable(closure)\n self.rules.append(closure)\n return self\nself.rules.append(ExprBuilder(self._node))\nreturn self.rules[-1]"
] | <|body_start_0|>
assert isinstance(node, NodeDefinition)
self._node = node
self.rules = list()
<|end_body_0|>
<|body_start_1|>
if not closure is None:
assert Tool.isCallable(closure)
self.rules.append(closure)
return self
self.rules.append(Exp... | This class builds validation conditions. @author Christophe Coevoet <stof@notk.org> | ValidationBuilder | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ValidationBuilder:
"""This class builds validation conditions. @author Christophe Coevoet <stof@notk.org>"""
def __init__(self, node):
"""Constructor @param node: NodeDefinition The related node"""
<|body_0|>
def rule(self, closure=None):
"""Registers a closure t... | stack_v2_sparse_classes_75kplus_train_002586 | 40,265 | permissive | [
{
"docstring": "Constructor @param node: NodeDefinition The related node",
"name": "__init__",
"signature": "def __init__(self, node)"
},
{
"docstring": "Registers a closure to run as normalization or an expression builder to build it if null is provided. @param closure: callable @return: ExprBu... | 2 | null | Implement the Python class `ValidationBuilder` described below.
Class description:
This class builds validation conditions. @author Christophe Coevoet <stof@notk.org>
Method signatures and docstrings:
- def __init__(self, node): Constructor @param node: NodeDefinition The related node
- def rule(self, closure=None): ... | Implement the Python class `ValidationBuilder` described below.
Class description:
This class builds validation conditions. @author Christophe Coevoet <stof@notk.org>
Method signatures and docstrings:
- def __init__(self, node): Constructor @param node: NodeDefinition The related node
- def rule(self, closure=None): ... | 4b40f042f8096eb59d2c85524981a4a5262364cb | <|skeleton|>
class ValidationBuilder:
"""This class builds validation conditions. @author Christophe Coevoet <stof@notk.org>"""
def __init__(self, node):
"""Constructor @param node: NodeDefinition The related node"""
<|body_0|>
def rule(self, closure=None):
"""Registers a closure t... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ValidationBuilder:
"""This class builds validation conditions. @author Christophe Coevoet <stof@notk.org>"""
def __init__(self, node):
"""Constructor @param node: NodeDefinition The related node"""
assert isinstance(node, NodeDefinition)
self._node = node
self.rules = list... | the_stack_v2_python_sparse | src/pymfony/component/config/definition/builder.py | pymfony/pymfony | train | 1 |
8fa95c869dfbd447b514faa456200ee97fc9ce5c | [
"if serialized != None:\n self.root = simplejson.loads(serialized)\nelse:\n self.root = {}\nself._cache = {}",
"if node is None:\n node = self.root\nreturn simplejson.dumps(node, ensure_ascii=False)",
"if type(path) != tuple:\n raise AttributeError('Path of type tuple required (path was %s)' % (path... | <|body_start_0|>
if serialized != None:
self.root = simplejson.loads(serialized)
else:
self.root = {}
self._cache = {}
<|end_body_0|>
<|body_start_1|>
if node is None:
node = self.root
return simplejson.dumps(node, ensure_ascii=False)
<|end_bo... | AttrTree | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AttrTree:
def __init__(self, serialized=None):
"""Initialize a tree object. if serialized is set, the tree is initialized based on a tree object it expects in JSON format."""
<|body_0|>
def serialize(self, node=None):
"""Returns a JSON-dump-formatted representation o... | stack_v2_sparse_classes_75kplus_train_002587 | 2,078 | no_license | [
{
"docstring": "Initialize a tree object. if serialized is set, the tree is initialized based on a tree object it expects in JSON format.",
"name": "__init__",
"signature": "def __init__(self, serialized=None)"
},
{
"docstring": "Returns a JSON-dump-formatted representation of the tree.",
"n... | 4 | stack_v2_sparse_classes_30k_train_012600 | Implement the Python class `AttrTree` described below.
Class description:
Implement the AttrTree class.
Method signatures and docstrings:
- def __init__(self, serialized=None): Initialize a tree object. if serialized is set, the tree is initialized based on a tree object it expects in JSON format.
- def serialize(sel... | Implement the Python class `AttrTree` described below.
Class description:
Implement the AttrTree class.
Method signatures and docstrings:
- def __init__(self, serialized=None): Initialize a tree object. if serialized is set, the tree is initialized based on a tree object it expects in JSON format.
- def serialize(sel... | d49d48923a1e88cc94254f2fb66a4f1dc74d3480 | <|skeleton|>
class AttrTree:
def __init__(self, serialized=None):
"""Initialize a tree object. if serialized is set, the tree is initialized based on a tree object it expects in JSON format."""
<|body_0|>
def serialize(self, node=None):
"""Returns a JSON-dump-formatted representation o... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AttrTree:
def __init__(self, serialized=None):
"""Initialize a tree object. if serialized is set, the tree is initialized based on a tree object it expects in JSON format."""
if serialized != None:
self.root = simplejson.loads(serialized)
else:
self.root = {}
... | the_stack_v2_python_sparse | attr_tree.py | mixerlabs/util | train | 2 | |
4a0521e733d7580ef3eba6519f3e26a369b68637 | [
"super().__init__()\nself.unpooling = unpooling\nself.kernel_size = kernel_size\nself.dec_l1 = SphericalChebBNPoolConcat(512, 512, laps[1], self.unpooling, self.kernel_size)\nself.dec_l2 = SphericalChebBNPoolConcat(512, 256, laps[2], self.unpooling, self.kernel_size)\nself.dec_l3 = SphericalChebBNPoolConcat(256, 12... | <|body_start_0|>
super().__init__()
self.unpooling = unpooling
self.kernel_size = kernel_size
self.dec_l1 = SphericalChebBNPoolConcat(512, 512, laps[1], self.unpooling, self.kernel_size)
self.dec_l2 = SphericalChebBNPoolConcat(512, 256, laps[2], self.unpooling, self.kernel_size)
... | The decoder of the Spherical UNet. | Decoder | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Decoder:
"""The decoder of the Spherical UNet."""
def __init__(self, unpooling, laps, kernel_size):
"""Initialization. Args: unpooling (:obj:`torch.nn.Module`): The unpooling object. laps (list): List of laplacians."""
<|body_0|>
def forward(self, x_enc0, x_enc1, x_enc2,... | stack_v2_sparse_classes_75kplus_train_002588 | 41,403 | no_license | [
{
"docstring": "Initialization. Args: unpooling (:obj:`torch.nn.Module`): The unpooling object. laps (list): List of laplacians.",
"name": "__init__",
"signature": "def __init__(self, unpooling, laps, kernel_size)"
},
{
"docstring": "Forward Pass. Args: x_enc* (:obj:`torch.Tensor`): input tensor... | 2 | stack_v2_sparse_classes_30k_train_021104 | Implement the Python class `Decoder` described below.
Class description:
The decoder of the Spherical UNet.
Method signatures and docstrings:
- def __init__(self, unpooling, laps, kernel_size): Initialization. Args: unpooling (:obj:`torch.nn.Module`): The unpooling object. laps (list): List of laplacians.
- def forwa... | Implement the Python class `Decoder` described below.
Class description:
The decoder of the Spherical UNet.
Method signatures and docstrings:
- def __init__(self, unpooling, laps, kernel_size): Initialization. Args: unpooling (:obj:`torch.nn.Module`): The unpooling object. laps (list): List of laplacians.
- def forwa... | 7e55a422588c1d1e00f35a3d3a3ff896cce59e18 | <|skeleton|>
class Decoder:
"""The decoder of the Spherical UNet."""
def __init__(self, unpooling, laps, kernel_size):
"""Initialization. Args: unpooling (:obj:`torch.nn.Module`): The unpooling object. laps (list): List of laplacians."""
<|body_0|>
def forward(self, x_enc0, x_enc1, x_enc2,... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Decoder:
"""The decoder of the Spherical UNet."""
def __init__(self, unpooling, laps, kernel_size):
"""Initialization. Args: unpooling (:obj:`torch.nn.Module`): The unpooling object. laps (list): List of laplacians."""
super().__init__()
self.unpooling = unpooling
self.ker... | the_stack_v2_python_sparse | generated/test_deepsphere_deepsphere_pytorch.py | jansel/pytorch-jit-paritybench | train | 35 |
9459da75311c991c93dbf96ffebf399ec11f5916 | [
"super().__init__(game, neural_net, args, MCTS, DefaultAlphaZeroPlayer)\nif run_name is None:\n run_name = datetime.now().strftime('%Y%m%d-%H%M%S')\nself.log_dir = f'out/logs/AlphaZero/{self.neural_net.architecture}/' + run_name\nself.file_writer = tf.summary.create_file_writer(self.log_dir + '/metrics')\nself.f... | <|body_start_0|>
super().__init__(game, neural_net, args, MCTS, DefaultAlphaZeroPlayer)
if run_name is None:
run_name = datetime.now().strftime('%Y%m%d-%H%M%S')
self.log_dir = f'out/logs/AlphaZero/{self.neural_net.architecture}/' + run_name
self.file_writer = tf.summary.creat... | Implement base Coach class to define proper data-batch sampling procedures and logging objects. | AlphaZeroCoach | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AlphaZeroCoach:
"""Implement base Coach class to define proper data-batch sampling procedures and logging objects."""
def __init__(self, game, neural_net, args: DotDict, run_name: typing.Optional[str]=None) -> None:
"""Initialize the class for self-play. This inherited method initial... | stack_v2_sparse_classes_75kplus_train_002589 | 3,434 | permissive | [
{
"docstring": "Initialize the class for self-play. This inherited method initializes tensorboard logging. The super class is initialized with the proper search engine and agent-interface. (MCTS, AlphaZeroPlayer) :param game: Game Implementation of Game class for environment logic. :param neural_net: AlphaNeura... | 2 | stack_v2_sparse_classes_30k_test_002713 | Implement the Python class `AlphaZeroCoach` described below.
Class description:
Implement base Coach class to define proper data-batch sampling procedures and logging objects.
Method signatures and docstrings:
- def __init__(self, game, neural_net, args: DotDict, run_name: typing.Optional[str]=None) -> None: Initiali... | Implement the Python class `AlphaZeroCoach` described below.
Class description:
Implement base Coach class to define proper data-batch sampling procedures and logging objects.
Method signatures and docstrings:
- def __init__(self, game, neural_net, args: DotDict, run_name: typing.Optional[str]=None) -> None: Initiali... | 78478c6a8a0f0e0e740159236d6cbb30a9396f5a | <|skeleton|>
class AlphaZeroCoach:
"""Implement base Coach class to define proper data-batch sampling procedures and logging objects."""
def __init__(self, game, neural_net, args: DotDict, run_name: typing.Optional[str]=None) -> None:
"""Initialize the class for self-play. This inherited method initial... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AlphaZeroCoach:
"""Implement base Coach class to define proper data-batch sampling procedures and logging objects."""
def __init__(self, game, neural_net, args: DotDict, run_name: typing.Optional[str]=None) -> None:
"""Initialize the class for self-play. This inherited method initializes tensorbo... | the_stack_v2_python_sparse | AlphaZero/AlphaCoach.py | frankbryce/muzero | train | 1 |
c047775f02c6f9a4b46bf701e8baea7b6b79f7c4 | [
"sum_square = sum([pow(x[i] - y[i], 2) for i in xrange(len(x))])\nscore = 1 / (1 + sqrt(sum_square))\nreturn score",
"n = len(x)\nvals = range(n)\nsum_x = sum([float(x[i]) for i in vals])\nsum_y = sum([float(y[i]) for i in vals])\nsum_x_square = sum([x[i] ** 2.0 for i in vals])\nsum_y_square = sum([y[i] ** 2.0 fo... | <|body_start_0|>
sum_square = sum([pow(x[i] - y[i], 2) for i in xrange(len(x))])
score = 1 / (1 + sqrt(sum_square))
return score
<|end_body_0|>
<|body_start_1|>
n = len(x)
vals = range(n)
sum_x = sum([float(x[i]) for i in vals])
sum_y = sum([float(y[i]) for i in ... | Various algorithms to calculate similarity score | Similarity | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Similarity:
"""Various algorithms to calculate similarity score"""
def euclidean(self, x, y):
"""Calculates euclidean score between two lists of same length"""
<|body_0|>
def pearson(self, x, y):
"""Calculates pearson correlation coefficient between two lists of ... | stack_v2_sparse_classes_75kplus_train_002590 | 951 | permissive | [
{
"docstring": "Calculates euclidean score between two lists of same length",
"name": "euclidean",
"signature": "def euclidean(self, x, y)"
},
{
"docstring": "Calculates pearson correlation coefficient between two lists of same length",
"name": "pearson",
"signature": "def pearson(self, ... | 2 | stack_v2_sparse_classes_30k_train_025205 | Implement the Python class `Similarity` described below.
Class description:
Various algorithms to calculate similarity score
Method signatures and docstrings:
- def euclidean(self, x, y): Calculates euclidean score between two lists of same length
- def pearson(self, x, y): Calculates pearson correlation coefficient ... | Implement the Python class `Similarity` described below.
Class description:
Various algorithms to calculate similarity score
Method signatures and docstrings:
- def euclidean(self, x, y): Calculates euclidean score between two lists of same length
- def pearson(self, x, y): Calculates pearson correlation coefficient ... | 58000e48b4196ee0a07233eb3038d31732ca4040 | <|skeleton|>
class Similarity:
"""Various algorithms to calculate similarity score"""
def euclidean(self, x, y):
"""Calculates euclidean score between two lists of same length"""
<|body_0|>
def pearson(self, x, y):
"""Calculates pearson correlation coefficient between two lists of ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Similarity:
"""Various algorithms to calculate similarity score"""
def euclidean(self, x, y):
"""Calculates euclidean score between two lists of same length"""
sum_square = sum([pow(x[i] - y[i], 2) for i in xrange(len(x))])
score = 1 / (1 + sqrt(sum_square))
return score
... | the_stack_v2_python_sparse | Recommendation-System/classes/similarity.py | kinshuk4/kaggle-solutions | train | 1 |
5f88fc41f2c324b042f3e5cb856b695f0d0c8fa0 | [
"tf.logging.info('Creating MultiHeadDQNAgent with following parameters:')\ntf.logging.info('\\t num_heads: %d', num_heads)\ntf.logging.info('\\t transform_strategy: %s', transform_strategy)\ntf.logging.info('\\t num_convex_combinations: %d', num_convex_combinations)\ntf.logging.info('\\t init_checkpoint_dir: %s', i... | <|body_start_0|>
tf.logging.info('Creating MultiHeadDQNAgent with following parameters:')
tf.logging.info('\t num_heads: %d', num_heads)
tf.logging.info('\t transform_strategy: %s', transform_strategy)
tf.logging.info('\t num_convex_combinations: %d', num_convex_combinations)
tf.... | DQN agent with multiple heads. | MultiHeadDQNAgent | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MultiHeadDQNAgent:
"""DQN agent with multiple heads."""
def __init__(self, sess, num_actions, num_heads=1, transform_strategy='IDENTITY', num_convex_combinations=1, network=atari_helpers.MultiHeadQNetwork, init_checkpoint_dir=None, **kwargs):
"""Initializes the agent and constructs t... | stack_v2_sparse_classes_75kplus_train_002591 | 5,707 | permissive | [
{
"docstring": "Initializes the agent and constructs the components of its graph. Args: sess: tf.Session, for executing ops. num_actions: int, number of actions the agent can take at any state. num_heads: int, Number of heads per action output of the Q function. transform_strategy: str, Possible options include... | 4 | stack_v2_sparse_classes_30k_train_004474 | Implement the Python class `MultiHeadDQNAgent` described below.
Class description:
DQN agent with multiple heads.
Method signatures and docstrings:
- def __init__(self, sess, num_actions, num_heads=1, transform_strategy='IDENTITY', num_convex_combinations=1, network=atari_helpers.MultiHeadQNetwork, init_checkpoint_di... | Implement the Python class `MultiHeadDQNAgent` described below.
Class description:
DQN agent with multiple heads.
Method signatures and docstrings:
- def __init__(self, sess, num_actions, num_heads=1, transform_strategy='IDENTITY', num_convex_combinations=1, network=atari_helpers.MultiHeadQNetwork, init_checkpoint_di... | 6f7f4d55af077b7f27648d8b970cf1558c3e791d | <|skeleton|>
class MultiHeadDQNAgent:
"""DQN agent with multiple heads."""
def __init__(self, sess, num_actions, num_heads=1, transform_strategy='IDENTITY', num_convex_combinations=1, network=atari_helpers.MultiHeadQNetwork, init_checkpoint_dir=None, **kwargs):
"""Initializes the agent and constructs t... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MultiHeadDQNAgent:
"""DQN agent with multiple heads."""
def __init__(self, sess, num_actions, num_heads=1, transform_strategy='IDENTITY', num_convex_combinations=1, network=atari_helpers.MultiHeadQNetwork, init_checkpoint_dir=None, **kwargs):
"""Initializes the agent and constructs the components... | the_stack_v2_python_sparse | batch_rl/multi_head/multi_head_dqn_agent.py | google-research/batch_rl | train | 484 |
e0764768d0223253f5b731c708b8922ab74d8968 | [
"self.logger = logging.getLogger('SMBO')\nself.incumbent = None\nself.scenario = scenario\nself.config_space = scenario.cs\nself.stats = stats\nself.initial_design = initial_design\nself.runhistory = runhistory\nself.rh2EPM = runhistory2epm\nself.intensifier = intensifier\nself.aggregate_func = aggregate_func\nself... | <|body_start_0|>
self.logger = logging.getLogger('SMBO')
self.incumbent = None
self.scenario = scenario
self.config_space = scenario.cs
self.stats = stats
self.initial_design = initial_design
self.runhistory = runhistory
self.rh2EPM = runhistory2epm
... | PCSMBOSigmoidRandomSearch | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PCSMBOSigmoidRandomSearch:
def __init__(self, scenario: Scenario, stats: Stats, initial_design: InitialDesign, runhistory: RunHistory, runhistory2epm: AbstractRunHistory2EPM, intensifier: Intensifier, aggregate_func: callable, num_run: int, model: RandomForestWithInstances, rng: np.random.Random... | stack_v2_sparse_classes_75kplus_train_002592 | 13,167 | no_license | [
{
"docstring": "Interface that contains the main Bayesian optimization loop Parameters ---------- scenario: smac.scenario.scenario.Scenario Scenario object stats: Stats statistics object with configuration budgets initial_design: InitialDesign initial sampling design runhistory: RunHistory runhistory with all r... | 2 | stack_v2_sparse_classes_30k_train_002226 | Implement the Python class `PCSMBOSigmoidRandomSearch` described below.
Class description:
Implement the PCSMBOSigmoidRandomSearch class.
Method signatures and docstrings:
- def __init__(self, scenario: Scenario, stats: Stats, initial_design: InitialDesign, runhistory: RunHistory, runhistory2epm: AbstractRunHistory2E... | Implement the Python class `PCSMBOSigmoidRandomSearch` described below.
Class description:
Implement the PCSMBOSigmoidRandomSearch class.
Method signatures and docstrings:
- def __init__(self, scenario: Scenario, stats: Stats, initial_design: InitialDesign, runhistory: RunHistory, runhistory2epm: AbstractRunHistory2E... | 0a6e8719438a3f510e0aaeda19c14dd8005d8c65 | <|skeleton|>
class PCSMBOSigmoidRandomSearch:
def __init__(self, scenario: Scenario, stats: Stats, initial_design: InitialDesign, runhistory: RunHistory, runhistory2epm: AbstractRunHistory2EPM, intensifier: Intensifier, aggregate_func: callable, num_run: int, model: RandomForestWithInstances, rng: np.random.Random... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PCSMBOSigmoidRandomSearch:
def __init__(self, scenario: Scenario, stats: Stats, initial_design: InitialDesign, runhistory: RunHistory, runhistory2epm: AbstractRunHistory2EPM, intensifier: Intensifier, aggregate_func: callable, num_run: int, model: RandomForestWithInstances, rng: np.random.RandomState, select_... | the_stack_v2_python_sparse | pc_smac/pc_smbo/pc_smbo.py | jtuyls/pc_smac | train | 0 | |
fe41227834695fdd301389de35bdcae17b541183 | [
"def _dot(x, y):\n if isinstance(x, SS.SparseVariable):\n return SS.structured_dot(x, y)\n else:\n return TT.dot(x, y)\n\ndef weight(n):\n return 'w' if len(self.inputs) == 1 else 'w_{}'.format(n)\nxws = ((inputs[n], self.find(weight(n))) for n in self.inputs)\npre = sum((_dot(x, w) for x, w ... | <|body_start_0|>
def _dot(x, y):
if isinstance(x, SS.SparseVariable):
return SS.structured_dot(x, y)
else:
return TT.dot(x, y)
def weight(n):
return 'w' if len(self.inputs) == 1 else 'w_{}'.format(n)
xws = ((inputs[n], self.fin... | A feedforward neural network layer performs a transform of its input. More precisely, feedforward layers as implemented here perform an affine transformation of their input, followed by a potentially nonlinear "activation" function performed elementwise on the transformed input. Feedforward layers are the fundamental b... | Feedforward | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Feedforward:
"""A feedforward neural network layer performs a transform of its input. More precisely, feedforward layers as implemented here perform an affine transformation of their input, followed by a potentially nonlinear "activation" function performed elementwise on the transformed input. F... | stack_v2_sparse_classes_75kplus_train_002593 | 8,072 | permissive | [
{
"docstring": "Transform the inputs for this layer into an output for the layer. Parameters ---------- inputs : dict of Theano expressions Symbolic inputs to this layer, given as a dictionary mapping string names to Theano expressions. See :func:`Layer.connect`. Returns ------- outputs : dict of Theano express... | 2 | stack_v2_sparse_classes_30k_train_010980 | Implement the Python class `Feedforward` described below.
Class description:
A feedforward neural network layer performs a transform of its input. More precisely, feedforward layers as implemented here perform an affine transformation of their input, followed by a potentially nonlinear "activation" function performed ... | Implement the Python class `Feedforward` described below.
Class description:
A feedforward neural network layer performs a transform of its input. More precisely, feedforward layers as implemented here perform an affine transformation of their input, followed by a potentially nonlinear "activation" function performed ... | 06b5b6f5de05220702f34c943f309d8188010b57 | <|skeleton|>
class Feedforward:
"""A feedforward neural network layer performs a transform of its input. More precisely, feedforward layers as implemented here perform an affine transformation of their input, followed by a potentially nonlinear "activation" function performed elementwise on the transformed input. F... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Feedforward:
"""A feedforward neural network layer performs a transform of its input. More precisely, feedforward layers as implemented here perform an affine transformation of their input, followed by a potentially nonlinear "activation" function performed elementwise on the transformed input. Feedforward la... | the_stack_v2_python_sparse | code/seq2seq_graph/src/theanets-0.6.1/theanets/layers/feedforward.py | scylla/masters_thesis | train | 2 |
11ef01f03025f4049d8a9c4b631680f48a632216 | [
"self.operands: List[Operand] = list(operands)\nfor i in range(len(self.operands)):\n self.operands[i] = Operand.validate_operand(self.operands[i])\nsuper().__init__()",
"incomplete_expression = False\nfor operand in self.operands:\n if not issubclass(type(operand), Operand):\n raise RuntimeError(f'O... | <|body_start_0|>
self.operands: List[Operand] = list(operands)
for i in range(len(self.operands)):
self.operands[i] = Operand.validate_operand(self.operands[i])
super().__init__()
<|end_body_0|>
<|body_start_1|>
incomplete_expression = False
for operand in self.opera... | Or operator class for filtering JumpStart content. | Or | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Or:
"""Or operator class for filtering JumpStart content."""
def __init__(self, *operands: Union[Operand, str]) -> None:
"""Instantiates Or object. Args: operands (Operand): Operand for Or-ing. Raises: RuntimeError: If the operands cannot be validated."""
<|body_0|>
def ... | stack_v2_sparse_classes_75kplus_train_002594 | 16,623 | permissive | [
{
"docstring": "Instantiates Or object. Args: operands (Operand): Operand for Or-ing. Raises: RuntimeError: If the operands cannot be validated.",
"name": "__init__",
"signature": "def __init__(self, *operands: Union[Operand, str]) -> None"
},
{
"docstring": "Evaluates operator. Raises: RuntimeE... | 3 | stack_v2_sparse_classes_30k_train_012923 | Implement the Python class `Or` described below.
Class description:
Or operator class for filtering JumpStart content.
Method signatures and docstrings:
- def __init__(self, *operands: Union[Operand, str]) -> None: Instantiates Or object. Args: operands (Operand): Operand for Or-ing. Raises: RuntimeError: If the oper... | Implement the Python class `Or` described below.
Class description:
Or operator class for filtering JumpStart content.
Method signatures and docstrings:
- def __init__(self, *operands: Union[Operand, str]) -> None: Instantiates Or object. Args: operands (Operand): Operand for Or-ing. Raises: RuntimeError: If the oper... | 8d5d7fd8ae1a917ed3e2b988d5e533bce244fd85 | <|skeleton|>
class Or:
"""Or operator class for filtering JumpStart content."""
def __init__(self, *operands: Union[Operand, str]) -> None:
"""Instantiates Or object. Args: operands (Operand): Operand for Or-ing. Raises: RuntimeError: If the operands cannot be validated."""
<|body_0|>
def ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Or:
"""Or operator class for filtering JumpStart content."""
def __init__(self, *operands: Union[Operand, str]) -> None:
"""Instantiates Or object. Args: operands (Operand): Operand for Or-ing. Raises: RuntimeError: If the operands cannot be validated."""
self.operands: List[Operand] = li... | the_stack_v2_python_sparse | src/sagemaker/jumpstart/filters.py | aws/sagemaker-python-sdk | train | 2,050 |
bc0209c31b5ff4c086589c6d9b173bc56ec20580 | [
"super().__init__()\nself.in_channels = channels\nself.filter_channels = filter_channels\nself.kernel_size = kernel_size\nself.dropout_rate = dropout_rate\nself.drop = torch.nn.Dropout(dropout_rate)\nself.conv_1 = torch.nn.Conv1d(channels, filter_channels, kernel_size, padding=kernel_size // 2)\nself.norm_1 = Layer... | <|body_start_0|>
super().__init__()
self.in_channels = channels
self.filter_channels = filter_channels
self.kernel_size = kernel_size
self.dropout_rate = dropout_rate
self.drop = torch.nn.Dropout(dropout_rate)
self.conv_1 = torch.nn.Conv1d(channels, filter_channel... | DurationPredictor | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DurationPredictor:
def __init__(self, channels, filter_channels, kernel_size, dropout_rate, global_channels=0):
"""Initialize duration predictor module. Args: channels (int): Number of input channels. filter_channels (int): Number of filter channels. kernel_size (int): Size of the convol... | stack_v2_sparse_classes_75kplus_train_002595 | 2,729 | permissive | [
{
"docstring": "Initialize duration predictor module. Args: channels (int): Number of input channels. filter_channels (int): Number of filter channels. kernel_size (int): Size of the convolutional kernel. dropout_rate (float): Dropout rate. global_channels (int, optional): Number of global conditioning channels... | 2 | null | Implement the Python class `DurationPredictor` described below.
Class description:
Implement the DurationPredictor class.
Method signatures and docstrings:
- def __init__(self, channels, filter_channels, kernel_size, dropout_rate, global_channels=0): Initialize duration predictor module. Args: channels (int): Number ... | Implement the Python class `DurationPredictor` described below.
Class description:
Implement the DurationPredictor class.
Method signatures and docstrings:
- def __init__(self, channels, filter_channels, kernel_size, dropout_rate, global_channels=0): Initialize duration predictor module. Args: channels (int): Number ... | bcd20948db7846ee523443ef9fd78c7a1248c95e | <|skeleton|>
class DurationPredictor:
def __init__(self, channels, filter_channels, kernel_size, dropout_rate, global_channels=0):
"""Initialize duration predictor module. Args: channels (int): Number of input channels. filter_channels (int): Number of filter channels. kernel_size (int): Size of the convol... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DurationPredictor:
def __init__(self, channels, filter_channels, kernel_size, dropout_rate, global_channels=0):
"""Initialize duration predictor module. Args: channels (int): Number of input channels. filter_channels (int): Number of filter channels. kernel_size (int): Size of the convolutional kernel... | the_stack_v2_python_sparse | espnet2/gan_svs/vits/duration_predictor.py | espnet/espnet | train | 7,242 | |
1a789202b316c5f420bdb0b95847af9fded6dbd0 | [
"dp = np.zeros(len(nums))\nlength = 0\nfor num in nums:\n i = self.binary_search(nums, 0, length, num)\n if i < 0:\n i = -(i + 1)\n dp[i] = num\n if i + 1 > length:\n length = i + 1\nreturn length",
"if r >= l:\n mid = int(l + (r - l) / 2)\n if nums[mid] == x:\n return mid\n... | <|body_start_0|>
dp = np.zeros(len(nums))
length = 0
for num in nums:
i = self.binary_search(nums, 0, length, num)
if i < 0:
i = -(i + 1)
dp[i] = num
if i + 1 > length:
length = i + 1
return length
<|end_body... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def length_of_LIS(self, nums: List[int]) -> int:
"""最长增数组 Args: nums:数组 Returns: 数组长度"""
<|body_0|>
def binary_search(self, nums: List[int], l: int, r: int, x: int):
"""二分查找 Args: nums: 输入数组 l: 开始下标 r: 结束下标 x: 要查找的数 Returns: 要查找数的下标"""
<|body_1|>
... | stack_v2_sparse_classes_75kplus_train_002596 | 2,886 | permissive | [
{
"docstring": "最长增数组 Args: nums:数组 Returns: 数组长度",
"name": "length_of_LIS",
"signature": "def length_of_LIS(self, nums: List[int]) -> int"
},
{
"docstring": "二分查找 Args: nums: 输入数组 l: 开始下标 r: 结束下标 x: 要查找的数 Returns: 要查找数的下标",
"name": "binary_search",
"signature": "def binary_search(self, ... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def length_of_LIS(self, nums: List[int]) -> int: 最长增数组 Args: nums:数组 Returns: 数组长度
- def binary_search(self, nums: List[int], l: int, r: int, x: int): 二分查找 Args: nums: 输入数组 l: 开始... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def length_of_LIS(self, nums: List[int]) -> int: 最长增数组 Args: nums:数组 Returns: 数组长度
- def binary_search(self, nums: List[int], l: int, r: int, x: int): 二分查找 Args: nums: 输入数组 l: 开始... | 50f35eef6a0ad63173efed10df3c835b1dceaa3f | <|skeleton|>
class Solution:
def length_of_LIS(self, nums: List[int]) -> int:
"""最长增数组 Args: nums:数组 Returns: 数组长度"""
<|body_0|>
def binary_search(self, nums: List[int], l: int, r: int, x: int):
"""二分查找 Args: nums: 输入数组 l: 开始下标 r: 结束下标 x: 要查找的数 Returns: 要查找数的下标"""
<|body_1|>
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def length_of_LIS(self, nums: List[int]) -> int:
"""最长增数组 Args: nums:数组 Returns: 数组长度"""
dp = np.zeros(len(nums))
length = 0
for num in nums:
i = self.binary_search(nums, 0, length, num)
if i < 0:
i = -(i + 1)
dp[i] ... | the_stack_v2_python_sparse | src/leetcodepython/array/longest_increasing_subsequence_300.py | zhangyu345293721/leetcode | train | 101 | |
c9b26b95d1890e17806162f3c42619bfc8f4636c | [
"header('Access-Control-Allow-Origin', ctx.env.get('HTTP_ORIGIN'))\nheader('Access-Control-Allow-Headers', ctx.env.get('HTTP_ACCESS_CONTROL_REQUEST_HEADERS'))\nheader('Access-Control-Allow-Methods', '*')\nheader('Access-Control-Allow-Credentials', 'true')\nheader('Access-Control-Expose-Headers', 'X-Rucio-Auth-Token... | <|body_start_0|>
header('Access-Control-Allow-Origin', ctx.env.get('HTTP_ORIGIN'))
header('Access-Control-Allow-Headers', ctx.env.get('HTTP_ACCESS_CONTROL_REQUEST_HEADERS'))
header('Access-Control-Allow-Methods', '*')
header('Access-Control-Allow-Credentials', 'true')
header('Acc... | Request a challenge token for SSH authentication | SSHChallengeToken | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SSHChallengeToken:
"""Request a challenge token for SSH authentication"""
def OPTIONS(self):
"""HTTP Success: 200 OK Allow cross-site scripting. Explicit for Authentication."""
<|body_0|>
def GET(self):
"""HTTP Success: 200 OK HTTP Error: 401 Unauthorized :param ... | stack_v2_sparse_classes_75kplus_train_002597 | 18,732 | permissive | [
{
"docstring": "HTTP Success: 200 OK Allow cross-site scripting. Explicit for Authentication.",
"name": "OPTIONS",
"signature": "def OPTIONS(self)"
},
{
"docstring": "HTTP Success: 200 OK HTTP Error: 401 Unauthorized :param Rucio-Account: Account identifier as a string. :param Rucio-AppID: Appli... | 2 | stack_v2_sparse_classes_30k_train_021106 | Implement the Python class `SSHChallengeToken` described below.
Class description:
Request a challenge token for SSH authentication
Method signatures and docstrings:
- def OPTIONS(self): HTTP Success: 200 OK Allow cross-site scripting. Explicit for Authentication.
- def GET(self): HTTP Success: 200 OK HTTP Error: 401... | Implement the Python class `SSHChallengeToken` described below.
Class description:
Request a challenge token for SSH authentication
Method signatures and docstrings:
- def OPTIONS(self): HTTP Success: 200 OK Allow cross-site scripting. Explicit for Authentication.
- def GET(self): HTTP Success: 200 OK HTTP Error: 401... | 355a997a5ea213c427a5d841ab151ceb01073eb4 | <|skeleton|>
class SSHChallengeToken:
"""Request a challenge token for SSH authentication"""
def OPTIONS(self):
"""HTTP Success: 200 OK Allow cross-site scripting. Explicit for Authentication."""
<|body_0|>
def GET(self):
"""HTTP Success: 200 OK HTTP Error: 401 Unauthorized :param ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SSHChallengeToken:
"""Request a challenge token for SSH authentication"""
def OPTIONS(self):
"""HTTP Success: 200 OK Allow cross-site scripting. Explicit for Authentication."""
header('Access-Control-Allow-Origin', ctx.env.get('HTTP_ORIGIN'))
header('Access-Control-Allow-Headers',... | the_stack_v2_python_sparse | lib/rucio/web/rest/webpy/v1/authentication.py | pujanm/rucio | train | 1 |
ceba0d60df7913255f7a2af9a0c5a667f4df4183 | [
"this_dir, this_filename = os.path.split(__file__)\ncylinderpath = Filename.fromOsSpecific(os.path.join(this_dir, 'geomprim', 'cylinder.egg'))\nconepath = Filename.fromOsSpecific(os.path.join(this_dir, 'geomprim', 'sphere.egg'))\nboxpath = Filename.fromOsSpecific(os.path.join(this_dir, 'geomprim', 'box.egg'))\nself... | <|body_start_0|>
this_dir, this_filename = os.path.split(__file__)
cylinderpath = Filename.fromOsSpecific(os.path.join(this_dir, 'geomprim', 'cylinder.egg'))
conepath = Filename.fromOsSpecific(os.path.join(this_dir, 'geomprim', 'sphere.egg'))
boxpath = Filename.fromOsSpecific(os.path.joi... | use class to preload files and generate various models | PandaGeomGen | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PandaGeomGen:
"""use class to preload files and generate various models"""
def __init__(self):
"""prepload the files the models will be instanceTo nodepaths to avoid frequent disk access"""
<|body_0|>
def gendumbbell(self, spos=None, epos=None, length=None, thickness=1.5... | stack_v2_sparse_classes_75kplus_train_002598 | 31,568 | no_license | [
{
"docstring": "prepload the files the models will be instanceTo nodepaths to avoid frequent disk access",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "generate a dumbbell to plot the stick model of a robot the function is essentially a copy of pandaplotutils/pandageo... | 3 | stack_v2_sparse_classes_30k_train_034115 | Implement the Python class `PandaGeomGen` described below.
Class description:
use class to preload files and generate various models
Method signatures and docstrings:
- def __init__(self): prepload the files the models will be instanceTo nodepaths to avoid frequent disk access
- def gendumbbell(self, spos=None, epos=... | Implement the Python class `PandaGeomGen` described below.
Class description:
use class to preload files and generate various models
Method signatures and docstrings:
- def __init__(self): prepload the files the models will be instanceTo nodepaths to avoid frequent disk access
- def gendumbbell(self, spos=None, epos=... | 60e24c28a6b39621a235187483d9a13cbbffe987 | <|skeleton|>
class PandaGeomGen:
"""use class to preload files and generate various models"""
def __init__(self):
"""prepload the files the models will be instanceTo nodepaths to avoid frequent disk access"""
<|body_0|>
def gendumbbell(self, spos=None, epos=None, length=None, thickness=1.5... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PandaGeomGen:
"""use class to preload files and generate various models"""
def __init__(self):
"""prepload the files the models will be instanceTo nodepaths to avoid frequent disk access"""
this_dir, this_filename = os.path.split(__file__)
cylinderpath = Filename.fromOsSpecific(os... | the_stack_v2_python_sparse | pandaplotutils/pandageom.py | wanweiwei07/pyhiro | train | 7 |
a8ccf4183d5e013b468afff2b5b6e33994844f31 | [
"super().__init__(process_manager, msg_queue)\nself.srf02 = srf02\nself.distance_threshold = distance_threshold\nself.near_obstacle_threshold = near_obstacle_threshold\nself.interval = interval\nself.addr_list = addr_list\nself.smoothing_coeff = 0.75\nself.max_distance = 50\nfor addr in self.addr_list:\n self.st... | <|body_start_0|>
super().__init__(process_manager, msg_queue)
self.srf02 = srf02
self.distance_threshold = distance_threshold
self.near_obstacle_threshold = near_obstacle_threshold
self.interval = interval
self.addr_list = addr_list
self.smoothing_coeff = 0.75
... | 超音波センサ(Srf02)を操作するクラス | Srf02Node | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Srf02Node:
"""超音波センサ(Srf02)を操作するクラス"""
def __init__(self, process_manager, msg_queue, srf02, distance_threshold=15, near_obstacle_threshold=5, interval=0.5, addr_list=[112]):
"""コンストラクタ"""
<|body_0|>
def update(self):
"""入力を処理して状態を更新"""
<|body_1|>
<|end_... | stack_v2_sparse_classes_75kplus_train_002599 | 3,473 | no_license | [
{
"docstring": "コンストラクタ",
"name": "__init__",
"signature": "def __init__(self, process_manager, msg_queue, srf02, distance_threshold=15, near_obstacle_threshold=5, interval=0.5, addr_list=[112])"
},
{
"docstring": "入力を処理して状態を更新",
"name": "update",
"signature": "def update(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_023952 | Implement the Python class `Srf02Node` described below.
Class description:
超音波センサ(Srf02)を操作するクラス
Method signatures and docstrings:
- def __init__(self, process_manager, msg_queue, srf02, distance_threshold=15, near_obstacle_threshold=5, interval=0.5, addr_list=[112]): コンストラクタ
- def update(self): 入力を処理して状態を更新 | Implement the Python class `Srf02Node` described below.
Class description:
超音波センサ(Srf02)を操作するクラス
Method signatures and docstrings:
- def __init__(self, process_manager, msg_queue, srf02, distance_threshold=15, near_obstacle_threshold=5, interval=0.5, addr_list=[112]): コンストラクタ
- def update(self): 入力を処理して状態を更新
<|skele... | a4659621011c87c9d9a97d63223aab51cbdd6e67 | <|skeleton|>
class Srf02Node:
"""超音波センサ(Srf02)を操作するクラス"""
def __init__(self, process_manager, msg_queue, srf02, distance_threshold=15, near_obstacle_threshold=5, interval=0.5, addr_list=[112]):
"""コンストラクタ"""
<|body_0|>
def update(self):
"""入力を処理して状態を更新"""
<|body_1|>
<|end_... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Srf02Node:
"""超音波センサ(Srf02)を操作するクラス"""
def __init__(self, process_manager, msg_queue, srf02, distance_threshold=15, near_obstacle_threshold=5, interval=0.5, addr_list=[112]):
"""コンストラクタ"""
super().__init__(process_manager, msg_queue)
self.srf02 = srf02
self.distance_thresh... | the_stack_v2_python_sparse | robot_lib/srf02_node.py | sterngerlach/raspi-robot | train | 1 |
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