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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
96256c6313535fe999db544fc520cc470bfe1edf | [
"if 'scannerSessionDir' in scannerSettings.allSettings:\n self.sessionDir = scannerSettings.allSettings['scannerSessionDir']\nelse:\n print('No scannerSessionDir found in scannerConfig file')\n sys.exit()",
"if self.sessionDir is None:\n self.findSessionDir()\nprint('Session Dir: ')\nprint('{}'.format... | <|body_start_0|>
if 'scannerSessionDir' in scannerSettings.allSettings:
self.sessionDir = scannerSettings.allSettings['scannerSessionDir']
else:
print('No scannerSessionDir found in scannerConfig file')
sys.exit()
<|end_body_0|>
<|body_start_1|>
if self.sessi... | Finding the names and paths of series directories in a Siemens scanning environment. In Siemens environments, using the ideacmdtool, the scanner is set up to export data in real-time to a shared directory that is accessible from a remote workstation (running Pyneal Scanner). For functional data, Siemens scanners store ... | Siemens_DirStructure | [
"MIT",
"LicenseRef-scancode-free-unknown"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Siemens_DirStructure:
"""Finding the names and paths of series directories in a Siemens scanning environment. In Siemens environments, using the ideacmdtool, the scanner is set up to export data in real-time to a shared directory that is accessible from a remote workstation (running Pyneal Scanne... | stack_v2_sparse_classes_75kplus_train_071800 | 30,222 | permissive | [
{
"docstring": "Initialize the class Parameters ---------- scannerSettings : object class attributes represent all of the settings unique to the current scanning environment (many of them read from `scannerConfig.yaml`) See Also -------- general_utils.ScannerSettings",
"name": "__init__",
"signature": "... | 4 | null | Implement the Python class `Siemens_DirStructure` described below.
Class description:
Finding the names and paths of series directories in a Siemens scanning environment. In Siemens environments, using the ideacmdtool, the scanner is set up to export data in real-time to a shared directory that is accessible from a re... | Implement the Python class `Siemens_DirStructure` described below.
Class description:
Finding the names and paths of series directories in a Siemens scanning environment. In Siemens environments, using the ideacmdtool, the scanner is set up to export data in real-time to a shared directory that is accessible from a re... | 750f0ec5a231ccfa77aea960242de9b5019ba493 | <|skeleton|>
class Siemens_DirStructure:
"""Finding the names and paths of series directories in a Siemens scanning environment. In Siemens environments, using the ideacmdtool, the scanner is set up to export data in real-time to a shared directory that is accessible from a remote workstation (running Pyneal Scanne... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Siemens_DirStructure:
"""Finding the names and paths of series directories in a Siemens scanning environment. In Siemens environments, using the ideacmdtool, the scanner is set up to export data in real-time to a shared directory that is accessible from a remote workstation (running Pyneal Scanner). For funct... | the_stack_v2_python_sparse | pyneal_scanner/utils/Siemens_utils.py | jeffmacinnes/pyneal | train | 36 |
0010f8d914ccbf9b6f37a4eefa8f563159bc7b2c | [
"Frame.__init__(self, master)\nself.pack()\nself.createArtistWidgets()",
"Album_Cover_Frame = Frame(self)\nself.labelInputAlbumCover = Label(Album_Cover_Frame, text='Get Album Cover Name')\nself.labelResult = Label(Album_Cover_Frame, text='Album Cover Result')\nself.text_in_Album_Cover = Entry(Album_Cover_Frame)\... | <|body_start_0|>
Frame.__init__(self, master)
self.pack()
self.createArtistWidgets()
<|end_body_0|>
<|body_start_1|>
Album_Cover_Frame = Frame(self)
self.labelInputAlbumCover = Label(Album_Cover_Frame, text='Get Album Cover Name')
self.labelResult = Label(Album_Cover_Fra... | Application main window class. | Application | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Application:
"""Application main window class."""
def __init__(self, master=None):
"""Main frame initialization (mostly delegated)"""
<|body_0|>
def createArtistWidgets(self):
"""Add all the widgets to the main frame."""
<|body_1|>
def handle(self):
... | stack_v2_sparse_classes_75kplus_train_071801 | 1,963 | no_license | [
{
"docstring": "Main frame initialization (mostly delegated)",
"name": "__init__",
"signature": "def __init__(self, master=None)"
},
{
"docstring": "Add all the widgets to the main frame.",
"name": "createArtistWidgets",
"signature": "def createArtistWidgets(self)"
},
{
"docstrin... | 3 | stack_v2_sparse_classes_30k_train_023306 | Implement the Python class `Application` described below.
Class description:
Application main window class.
Method signatures and docstrings:
- def __init__(self, master=None): Main frame initialization (mostly delegated)
- def createArtistWidgets(self): Add all the widgets to the main frame.
- def handle(self): Hand... | Implement the Python class `Application` described below.
Class description:
Application main window class.
Method signatures and docstrings:
- def __init__(self, master=None): Main frame initialization (mostly delegated)
- def createArtistWidgets(self): Add all the widgets to the main frame.
- def handle(self): Hand... | 2dba11861f91e4bdc1ef28279132a6d8dd4ccf54 | <|skeleton|>
class Application:
"""Application main window class."""
def __init__(self, master=None):
"""Main frame initialization (mostly delegated)"""
<|body_0|>
def createArtistWidgets(self):
"""Add all the widgets to the main frame."""
<|body_1|>
def handle(self):
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Application:
"""Application main window class."""
def __init__(self, master=None):
"""Main frame initialization (mostly delegated)"""
Frame.__init__(self, master)
self.pack()
self.createArtistWidgets()
def createArtistWidgets(self):
"""Add all the widgets to t... | the_stack_v2_python_sparse | Mux_Gui/Get_Album_Cover_Gui.py | rduvalwa5/Mux | train | 0 |
a882fa8a40c0ccfb6f84b73582bf3cc90d9e8bee | [
"Graph.__init__(self, n, nodeData)\nself._adjMatrix = []\nrow = [None] * n\nfor i in range(n):\n self._adjMatrix.append(row[:])",
"if node1 < self._numVerts and node2 < self._numVerts:\n self._adjMatrix[node1][node2] = True\n self._adjMatrix[node2][node1] = True\n return True\nelif node1 >= self._numV... | <|body_start_0|>
Graph.__init__(self, n, nodeData)
self._adjMatrix = []
row = [None] * n
for i in range(n):
self._adjMatrix.append(row[:])
<|end_body_0|>
<|body_start_1|>
if node1 < self._numVerts and node2 < self._numVerts:
self._adjMatrix[node1][node2] ... | A graph contains vertices and edges: This implementation uses an adjacency matrix to represent edges. | MatrixGraph | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MatrixGraph:
"""A graph contains vertices and edges: This implementation uses an adjacency matrix to represent edges."""
def __init__(self, n, nodeData=[]):
"""Takes the number of nodes in the graph, and optionally a list of data to associate with each node. The data is assigned to n... | stack_v2_sparse_classes_75kplus_train_071802 | 16,606 | no_license | [
{
"docstring": "Takes the number of nodes in the graph, and optionally a list of data to associate with each node. The data is assigned to nodes in numeric order, starting with node 0. The edge information is represented using an adjacency matrix. This is initialized, but contains no edges; edges must be added ... | 5 | stack_v2_sparse_classes_30k_train_017389 | Implement the Python class `MatrixGraph` described below.
Class description:
A graph contains vertices and edges: This implementation uses an adjacency matrix to represent edges.
Method signatures and docstrings:
- def __init__(self, n, nodeData=[]): Takes the number of nodes in the graph, and optionally a list of da... | Implement the Python class `MatrixGraph` described below.
Class description:
A graph contains vertices and edges: This implementation uses an adjacency matrix to represent edges.
Method signatures and docstrings:
- def __init__(self, n, nodeData=[]): Takes the number of nodes in the graph, and optionally a list of da... | 97bb378a325b1639110de06b88d6e237dffc7330 | <|skeleton|>
class MatrixGraph:
"""A graph contains vertices and edges: This implementation uses an adjacency matrix to represent edges."""
def __init__(self, n, nodeData=[]):
"""Takes the number of nodes in the graph, and optionally a list of data to associate with each node. The data is assigned to n... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MatrixGraph:
"""A graph contains vertices and edges: This implementation uses an adjacency matrix to represent edges."""
def __init__(self, n, nodeData=[]):
"""Takes the number of nodes in the graph, and optionally a list of data to associate with each node. The data is assigned to nodes in numer... | the_stack_v2_python_sparse | backups/speedy_nav-2/scripts/Graphs.py | FoxRobotLab/catkin_ws | train | 6 |
83600cc91e7b63d81b341cee88a7aeb8c2d577f5 | [
"if not root:\n return True\n\ndef recursive(l, r):\n if not l and (not r):\n return True\n elif l and r:\n return l.val == r.val and recursive(l.left, r.right) and recursive(l.right, r.left)\n else:\n return False\nreturn recursive(root.left, root.right)",
"if not root:\n retu... | <|body_start_0|>
if not root:
return True
def recursive(l, r):
if not l and (not r):
return True
elif l and r:
return l.val == r.val and recursive(l.left, r.right) and recursive(l.right, r.left)
else:
return... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def isSymmetric(self, root):
""":type root: TreeNode :rtype: bool"""
<|body_0|>
def isSymmetric(self, root):
""":type root: TreeNode :rtype: bool"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not root:
return True
... | stack_v2_sparse_classes_75kplus_train_071803 | 1,394 | no_license | [
{
"docstring": ":type root: TreeNode :rtype: bool",
"name": "isSymmetric",
"signature": "def isSymmetric(self, root)"
},
{
"docstring": ":type root: TreeNode :rtype: bool",
"name": "isSymmetric",
"signature": "def isSymmetric(self, root)"
}
] | 2 | stack_v2_sparse_classes_30k_train_045258 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isSymmetric(self, root): :type root: TreeNode :rtype: bool
- def isSymmetric(self, root): :type root: TreeNode :rtype: bool | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isSymmetric(self, root): :type root: TreeNode :rtype: bool
- def isSymmetric(self, root): :type root: TreeNode :rtype: bool
<|skeleton|>
class Solution:
def isSymmetric... | 63b7eedc720c1ce14880b80744dcd5ef7107065c | <|skeleton|>
class Solution:
def isSymmetric(self, root):
""":type root: TreeNode :rtype: bool"""
<|body_0|>
def isSymmetric(self, root):
""":type root: TreeNode :rtype: bool"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def isSymmetric(self, root):
""":type root: TreeNode :rtype: bool"""
if not root:
return True
def recursive(l, r):
if not l and (not r):
return True
elif l and r:
return l.val == r.val and recursive(l.left, ... | the_stack_v2_python_sparse | problems/isSymmetric.py | joddiy/leetcode | train | 1 | |
9c92fbd9297794a203831d22c596a06ad3f1623d | [
"Presentation.__init__(self, pere, detail, attribut, False)\nif pere and detail:\n self.construire(detail)",
"detail = self.objet\nsalle = detail.parent\nnouveau_nom = supprimer_accents(arguments)\nif not nouveau_nom:\n self.pere << '|err|Vous devez indiquer un nouveau nom.|ff|'\n return\nif nouveau_nom ... | <|body_start_0|>
Presentation.__init__(self, pere, detail, attribut, False)
if pere and detail:
self.construire(detail)
<|end_body_0|>
<|body_start_1|>
detail = self.objet
salle = detail.parent
nouveau_nom = supprimer_accents(arguments)
if not nouveau_nom:
... | Ce contexte permet d'éditer un detail observable d'une salle. | EdtDetail | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EdtDetail:
"""Ce contexte permet d'éditer un detail observable d'une salle."""
def __init__(self, pere, detail=None, attribut=None):
"""Constructeur de l'éditeur"""
<|body_0|>
def opt_renommer_detail(self, arguments):
"""Renomme le détail courant. Syntaxe : /n <n... | stack_v2_sparse_classes_75kplus_train_071804 | 7,487 | permissive | [
{
"docstring": "Constructeur de l'éditeur",
"name": "__init__",
"signature": "def __init__(self, pere, detail=None, attribut=None)"
},
{
"docstring": "Renomme le détail courant. Syntaxe : /n <nouveau nom>",
"name": "opt_renommer_detail",
"signature": "def opt_renommer_detail(self, argume... | 4 | stack_v2_sparse_classes_30k_train_038086 | Implement the Python class `EdtDetail` described below.
Class description:
Ce contexte permet d'éditer un detail observable d'une salle.
Method signatures and docstrings:
- def __init__(self, pere, detail=None, attribut=None): Constructeur de l'éditeur
- def opt_renommer_detail(self, arguments): Renomme le détail cou... | Implement the Python class `EdtDetail` described below.
Class description:
Ce contexte permet d'éditer un detail observable d'une salle.
Method signatures and docstrings:
- def __init__(self, pere, detail=None, attribut=None): Constructeur de l'éditeur
- def opt_renommer_detail(self, arguments): Renomme le détail cou... | 7e93bff08cdf891352efba587e89c40f3b4a2301 | <|skeleton|>
class EdtDetail:
"""Ce contexte permet d'éditer un detail observable d'une salle."""
def __init__(self, pere, detail=None, attribut=None):
"""Constructeur de l'éditeur"""
<|body_0|>
def opt_renommer_detail(self, arguments):
"""Renomme le détail courant. Syntaxe : /n <n... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class EdtDetail:
"""Ce contexte permet d'éditer un detail observable d'une salle."""
def __init__(self, pere, detail=None, attribut=None):
"""Constructeur de l'éditeur"""
Presentation.__init__(self, pere, detail, attribut, False)
if pere and detail:
self.construire(detail)
... | the_stack_v2_python_sparse | src/primaires/salle/editeurs/redit/edt_detail.py | vincent-lg/tsunami | train | 5 |
c43098e360efe030c96e00170f5b328229875bdf | [
"self.username = username\nself.password = md5(password.encode('utf-8')).hexdigest()\nself.base_params = {'user': self.username, 'pass2': self.password, 'softid': '895210'}\nself.headers = {'Connection': 'Keep-Alive', 'User-Agent': 'Mozilla/4.0 (compatible; MSIE 8.0; Windows NT 5.1; Trident/4.0)'}",
"params = {'c... | <|body_start_0|>
self.username = username
self.password = md5(password.encode('utf-8')).hexdigest()
self.base_params = {'user': self.username, 'pass2': self.password, 'softid': '895210'}
self.headers = {'Connection': 'Keep-Alive', 'User-Agent': 'Mozilla/4.0 (compatible; MSIE 8.0; Windows... | GtClickShot | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GtClickShot:
def __init__(self, username, password):
"""初始化超级鹰 softid已固化到程序 args: username(str):超级鹰普通用户名 password(str):超级鹰密码"""
<|body_0|>
def PostPic(self, im, codetype):
"""发送图片至打码平台 args： im(Byte): 图片字节 codetype(str): 题目类型 参考 http://www.chaojiying.com/price.html r... | stack_v2_sparse_classes_75kplus_train_071805 | 26,194 | no_license | [
{
"docstring": "初始化超级鹰 softid已固化到程序 args: username(str):超级鹰普通用户名 password(str):超级鹰密码",
"name": "__init__",
"signature": "def __init__(self, username, password)"
},
{
"docstring": "发送图片至打码平台 args： im(Byte): 图片字节 codetype(str): 题目类型 参考 http://www.chaojiying.com/price.html return(json):返回打码信息，包含坐标信... | 3 | stack_v2_sparse_classes_30k_train_027487 | Implement the Python class `GtClickShot` described below.
Class description:
Implement the GtClickShot class.
Method signatures and docstrings:
- def __init__(self, username, password): 初始化超级鹰 softid已固化到程序 args: username(str):超级鹰普通用户名 password(str):超级鹰密码
- def PostPic(self, im, codetype): 发送图片至打码平台 args： im(Byte): 图片... | Implement the Python class `GtClickShot` described below.
Class description:
Implement the GtClickShot class.
Method signatures and docstrings:
- def __init__(self, username, password): 初始化超级鹰 softid已固化到程序 args: username(str):超级鹰普通用户名 password(str):超级鹰密码
- def PostPic(self, im, codetype): 发送图片至打码平台 args： im(Byte): 图片... | dc9dbbb5bf5e3d29cd664219826ca334916b953f | <|skeleton|>
class GtClickShot:
def __init__(self, username, password):
"""初始化超级鹰 softid已固化到程序 args: username(str):超级鹰普通用户名 password(str):超级鹰密码"""
<|body_0|>
def PostPic(self, im, codetype):
"""发送图片至打码平台 args： im(Byte): 图片字节 codetype(str): 题目类型 参考 http://www.chaojiying.com/price.html r... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class GtClickShot:
def __init__(self, username, password):
"""初始化超级鹰 softid已固化到程序 args: username(str):超级鹰普通用户名 password(str):超级鹰密码"""
self.username = username
self.password = md5(password.encode('utf-8')).hexdigest()
self.base_params = {'user': self.username, 'pass2': self.password, ... | the_stack_v2_python_sparse | skill/crawler_gov.py | mj3428/python_for_practice | train | 1 | |
36d80e990968519d7bcb23a1410b4e3f6210bf11 | [
"super(LSTMEvolutionSequence, self).__init__(builder, state_size, init_states=init_states, num_inputs=num_inputs, name=name, mode=mode)\nself.init_inode, self.init_hidden_state = (init_states[0], init_states[1])\nbuilder.addDirectedLink(self.init_inode, self, islot=0)\nbuilder.addDirectedLink(self.init_hidden_state... | <|body_start_0|>
super(LSTMEvolutionSequence, self).__init__(builder, state_size, init_states=init_states, num_inputs=num_inputs, name=name, mode=mode)
self.init_inode, self.init_hidden_state = (init_states[0], init_states[1])
builder.addDirectedLink(self.init_inode, self, islot=0)
build... | LSTMEvolutionSequence | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LSTMEvolutionSequence:
def __init__(self, builder, state_size, init_states, num_inputs=3, name=None, mode='forward', **dirs):
"""Initialize the LSTMEvolutionSequence"""
<|body_0|>
def _update_default_directives(self, **dirs):
"""Update the default directives"""
... | stack_v2_sparse_classes_75kplus_train_071806 | 10,836 | no_license | [
{
"docstring": "Initialize the LSTMEvolutionSequence",
"name": "__init__",
"signature": "def __init__(self, builder, state_size, init_states, num_inputs=3, name=None, mode='forward', **dirs)"
},
{
"docstring": "Update the default directives",
"name": "_update_default_directives",
"signat... | 3 | stack_v2_sparse_classes_30k_train_026330 | Implement the Python class `LSTMEvolutionSequence` described below.
Class description:
Implement the LSTMEvolutionSequence class.
Method signatures and docstrings:
- def __init__(self, builder, state_size, init_states, num_inputs=3, name=None, mode='forward', **dirs): Initialize the LSTMEvolutionSequence
- def _updat... | Implement the Python class `LSTMEvolutionSequence` described below.
Class description:
Implement the LSTMEvolutionSequence class.
Method signatures and docstrings:
- def __init__(self, builder, state_size, init_states, num_inputs=3, name=None, mode='forward', **dirs): Initialize the LSTMEvolutionSequence
- def _updat... | 0fe8b6be763ff22e1f301a06d076347e3997224a | <|skeleton|>
class LSTMEvolutionSequence:
def __init__(self, builder, state_size, init_states, num_inputs=3, name=None, mode='forward', **dirs):
"""Initialize the LSTMEvolutionSequence"""
<|body_0|>
def _update_default_directives(self, **dirs):
"""Update the default directives"""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class LSTMEvolutionSequence:
def __init__(self, builder, state_size, init_states, num_inputs=3, name=None, mode='forward', **dirs):
"""Initialize the LSTMEvolutionSequence"""
super(LSTMEvolutionSequence, self).__init__(builder, state_size, init_states=init_states, num_inputs=num_inputs, name=name, m... | the_stack_v2_python_sparse | neurolib/encoder/sequence.py | dhernandd/_neurolib | train | 0 | |
0e9e4c12f04365116929e4b34e34f80e6ff9d198 | [
"self.resource_group = resource_group\nself.storage_account = storage_account\nself.storage_container = storage_container\nself.storage_resource_group = storage_resource_group",
"if dictionary is None:\n return None\nresource_group = cohesity_management_sdk.models.entity_proto.EntityProto.from_dictionary(dicti... | <|body_start_0|>
self.resource_group = resource_group
self.storage_account = storage_account
self.storage_container = storage_container
self.storage_resource_group = storage_resource_group
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
res... | Implementation of the 'ReplicateSnapshotsToAzureParams' model. This is populated for Azure snapshot manager replication. Attributes: resource_group (EntityProto): Resource group to filter regions in UX. storage_account (EntityProto): Name of the storage account that will contain the storage container within which we wi... | ReplicateSnapshotsToAzureParams | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ReplicateSnapshotsToAzureParams:
"""Implementation of the 'ReplicateSnapshotsToAzureParams' model. This is populated for Azure snapshot manager replication. Attributes: resource_group (EntityProto): Resource group to filter regions in UX. storage_account (EntityProto): Name of the storage account... | stack_v2_sparse_classes_75kplus_train_071807 | 3,133 | permissive | [
{
"docstring": "Constructor for the ReplicateSnapshotsToAzureParams class",
"name": "__init__",
"signature": "def __init__(self, resource_group=None, storage_account=None, storage_container=None, storage_resource_group=None)"
},
{
"docstring": "Creates an instance of this model from a dictionary... | 2 | stack_v2_sparse_classes_30k_train_028487 | Implement the Python class `ReplicateSnapshotsToAzureParams` described below.
Class description:
Implementation of the 'ReplicateSnapshotsToAzureParams' model. This is populated for Azure snapshot manager replication. Attributes: resource_group (EntityProto): Resource group to filter regions in UX. storage_account (En... | Implement the Python class `ReplicateSnapshotsToAzureParams` described below.
Class description:
Implementation of the 'ReplicateSnapshotsToAzureParams' model. This is populated for Azure snapshot manager replication. Attributes: resource_group (EntityProto): Resource group to filter regions in UX. storage_account (En... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class ReplicateSnapshotsToAzureParams:
"""Implementation of the 'ReplicateSnapshotsToAzureParams' model. This is populated for Azure snapshot manager replication. Attributes: resource_group (EntityProto): Resource group to filter regions in UX. storage_account (EntityProto): Name of the storage account... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ReplicateSnapshotsToAzureParams:
"""Implementation of the 'ReplicateSnapshotsToAzureParams' model. This is populated for Azure snapshot manager replication. Attributes: resource_group (EntityProto): Resource group to filter regions in UX. storage_account (EntityProto): Name of the storage account that will co... | the_stack_v2_python_sparse | cohesity_management_sdk/models/replicate_snapshots_to_azure_params.py | cohesity/management-sdk-python | train | 24 |
afafaf9b7a3f6c1ee49d2ce0c3913d2c06766e4f | [
"super(Attention, self).__init__()\nself.e = nn.Linear(n_hidden_enc * 2 + n_hidden_dec, n_hidden_dec)\nself.v = nn.Linear(n_hidden_dec, 1, bias=False)",
"hidden = h.unsqueeze(1).repeat(1, o.shape[0], 1)\nencoder_outputs = o.permute(1, 0, 2)\nenergy = torch.tanh(self.e(torch.cat((hidden, encoder_outputs), dim=2)))... | <|body_start_0|>
super(Attention, self).__init__()
self.e = nn.Linear(n_hidden_enc * 2 + n_hidden_dec, n_hidden_dec)
self.v = nn.Linear(n_hidden_dec, 1, bias=False)
<|end_body_0|>
<|body_start_1|>
hidden = h.unsqueeze(1).repeat(1, o.shape[0], 1)
encoder_outputs = o.permute(1, 0,... | An Attention class is used to provide attention-based mechanisms in a neural network layer. References: D. Bahdanau, K. Cho, Y. Bengio. Neural machine translation by jointly learning to align and translate. Preprint arXiv:1409.0473 (2014). | Attention | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Attention:
"""An Attention class is used to provide attention-based mechanisms in a neural network layer. References: D. Bahdanau, K. Cho, Y. Bengio. Neural machine translation by jointly learning to align and translate. Preprint arXiv:1409.0473 (2014)."""
def __init__(self, n_hidden_enc, n_... | stack_v2_sparse_classes_75kplus_train_071808 | 1,748 | permissive | [
{
"docstring": "Initialization method. Args: n_hidden_enc (int): Number of hidden units in the Encoder. n_hidden_dec (int): Number of hidden units in the Decoder.",
"name": "__init__",
"signature": "def __init__(self, n_hidden_enc, n_hidden_dec)"
},
{
"docstring": "Performs a forward pass over t... | 2 | stack_v2_sparse_classes_30k_train_041144 | Implement the Python class `Attention` described below.
Class description:
An Attention class is used to provide attention-based mechanisms in a neural network layer. References: D. Bahdanau, K. Cho, Y. Bengio. Neural machine translation by jointly learning to align and translate. Preprint arXiv:1409.0473 (2014).
Met... | Implement the Python class `Attention` described below.
Class description:
An Attention class is used to provide attention-based mechanisms in a neural network layer. References: D. Bahdanau, K. Cho, Y. Bengio. Neural machine translation by jointly learning to align and translate. Preprint arXiv:1409.0473 (2014).
Met... | cccc670d48995fa0bfbdf9fc8013d13a90ea5e84 | <|skeleton|>
class Attention:
"""An Attention class is used to provide attention-based mechanisms in a neural network layer. References: D. Bahdanau, K. Cho, Y. Bengio. Neural machine translation by jointly learning to align and translate. Preprint arXiv:1409.0473 (2014)."""
def __init__(self, n_hidden_enc, n_... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Attention:
"""An Attention class is used to provide attention-based mechanisms in a neural network layer. References: D. Bahdanau, K. Cho, Y. Bengio. Neural machine translation by jointly learning to align and translate. Preprint arXiv:1409.0473 (2014)."""
def __init__(self, n_hidden_enc, n_hidden_dec):
... | the_stack_v2_python_sparse | textformer/models/layers/attention.py | gugarosa/textformer | train | 3 |
aeca4e325ffb2dba641107fa5ee94232d1d0690a | [
"url = 'http://web.ornl.gov/sci/landscan/' + 'landscan2011/LS11sample_Cyprus.zip'\nzip_dir = os.path.join(self.tmp_dir, 'landscan.zip')\nurlretrieve(url, zip_dir)\nzip_ref = zipfile.ZipFile(zip_dir, 'r')\nlandscan_dir = os.path.join(self.tmp_dir, 'landscan')\nzip_ref.extractall(landscan_dir)\nzip_ref.close()\nretur... | <|body_start_0|>
url = 'http://web.ornl.gov/sci/landscan/' + 'landscan2011/LS11sample_Cyprus.zip'
zip_dir = os.path.join(self.tmp_dir, 'landscan.zip')
urlretrieve(url, zip_dir)
zip_ref = zipfile.ZipFile(zip_dir, 'r')
landscan_dir = os.path.join(self.tmp_dir, 'landscan')
z... | Class for processing sample Landscan data | LandscanProcessor | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LandscanProcessor:
"""Class for processing sample Landscan data"""
def get_landscan(self):
"""Downloads the sample landscan image for Cyprus"""
<|body_0|>
def convert_landscan(self, landscan_dir):
"""Converts arcgrid into a tiff file"""
<|body_1|>
de... | stack_v2_sparse_classes_75kplus_train_071809 | 3,635 | permissive | [
{
"docstring": "Downloads the sample landscan image for Cyprus",
"name": "get_landscan",
"signature": "def get_landscan(self)"
},
{
"docstring": "Converts arcgrid into a tiff file",
"name": "convert_landscan",
"signature": "def convert_landscan(self, landscan_dir)"
},
{
"docstrin... | 4 | null | Implement the Python class `LandscanProcessor` described below.
Class description:
Class for processing sample Landscan data
Method signatures and docstrings:
- def get_landscan(self): Downloads the sample landscan image for Cyprus
- def convert_landscan(self, landscan_dir): Converts arcgrid into a tiff file
- def im... | Implement the Python class `LandscanProcessor` described below.
Class description:
Class for processing sample Landscan data
Method signatures and docstrings:
- def get_landscan(self): Downloads the sample landscan image for Cyprus
- def convert_landscan(self, landscan_dir): Converts arcgrid into a tiff file
- def im... | 9b938f3c2f2b15b75c149f8dd06083f2d888f77d | <|skeleton|>
class LandscanProcessor:
"""Class for processing sample Landscan data"""
def get_landscan(self):
"""Downloads the sample landscan image for Cyprus"""
<|body_0|>
def convert_landscan(self, landscan_dir):
"""Converts arcgrid into a tiff file"""
<|body_1|>
de... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class LandscanProcessor:
"""Class for processing sample Landscan data"""
def get_landscan(self):
"""Downloads the sample landscan image for Cyprus"""
url = 'http://web.ornl.gov/sci/landscan/' + 'landscan2011/LS11sample_Cyprus.zip'
zip_dir = os.path.join(self.tmp_dir, 'landscan.zip')
... | the_stack_v2_python_sparse | dataqs/landscan/landscan.py | dorukozturk/dataqs | train | 1 |
f3c3bcb01f2dbd3316d0cc48eed846e1b6da41bc | [
"while N:\n if self.isMonotone(N):\n return N\n else:\n N -= 1",
"pre_digit = num % 10\nnum = num / 10\nwhile num:\n digit = num % 10\n if digit > pre_digit:\n return False\n num /= 10\n pre_digit = digit\nreturn True"
] | <|body_start_0|>
while N:
if self.isMonotone(N):
return N
else:
N -= 1
<|end_body_0|>
<|body_start_1|>
pre_digit = num % 10
num = num / 10
while num:
digit = num % 10
if digit > pre_digit:
re... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def monotoneIncreasingDigits(self, N):
""":type N: int :rtype: int"""
<|body_0|>
def isMonotone(self, num):
""":type num: int :rtype: bool"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
while N:
if self.isMonotone(N):
... | stack_v2_sparse_classes_75kplus_train_071810 | 733 | no_license | [
{
"docstring": ":type N: int :rtype: int",
"name": "monotoneIncreasingDigits",
"signature": "def monotoneIncreasingDigits(self, N)"
},
{
"docstring": ":type num: int :rtype: bool",
"name": "isMonotone",
"signature": "def isMonotone(self, num)"
}
] | 2 | stack_v2_sparse_classes_30k_train_039179 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def monotoneIncreasingDigits(self, N): :type N: int :rtype: int
- def isMonotone(self, num): :type num: int :rtype: bool | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def monotoneIncreasingDigits(self, N): :type N: int :rtype: int
- def isMonotone(self, num): :type num: int :rtype: bool
<|skeleton|>
class Solution:
def monotoneIncreasing... | f93380721b8383817fe2b0d728deca1321c9ef45 | <|skeleton|>
class Solution:
def monotoneIncreasingDigits(self, N):
""":type N: int :rtype: int"""
<|body_0|>
def isMonotone(self, num):
""":type num: int :rtype: bool"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def monotoneIncreasingDigits(self, N):
""":type N: int :rtype: int"""
while N:
if self.isMonotone(N):
return N
else:
N -= 1
def isMonotone(self, num):
""":type num: int :rtype: bool"""
pre_digit = num % 10
... | the_stack_v2_python_sparse | problems/0738.0_Monotone_Increasing_Digits.py | lixiang2017/leetcode | train | 5 | |
14fd75d115a16cf9c84127e66b755a3686f0939c | [
"if not os.path.isdir(path + 'univariate_timeseries'):\n print('Creating univariate_timeseries Directory')\n os.mkdir(path + 'univariate_timeseries')\nif not os.path.exists(path + 'univariate_timeseries/Univariate2018_arff.zip'):\n td = time.time()\n print('Creating univariate timeseries')\n url = 'h... | <|body_start_0|>
if not os.path.isdir(path + 'univariate_timeseries'):
print('Creating univariate_timeseries Directory')
os.mkdir(path + 'univariate_timeseries')
if not os.path.exists(path + 'univariate_timeseries/Univariate2018_arff.zip'):
td = time.time()
... | univariate_timeseries | univariate_timeseries | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class univariate_timeseries:
"""univariate_timeseries"""
def download(path):
"""Download the univariate_timeseries dataset path Parameters ---------- path: str the path where the downloaded files will be stored. If the directory does not exist, it is created."""
<|body_0|>
def... | stack_v2_sparse_classes_75kplus_train_071811 | 2,541 | permissive | [
{
"docstring": "Download the univariate_timeseries dataset path Parameters ---------- path: str the path where the downloaded files will be stored. If the directory does not exist, it is created.",
"name": "download",
"signature": "def download(path)"
},
{
"docstring": "Parameters ---------- pat... | 2 | null | Implement the Python class `univariate_timeseries` described below.
Class description:
univariate_timeseries
Method signatures and docstrings:
- def download(path): Download the univariate_timeseries dataset path Parameters ---------- path: str the path where the downloaded files will be stored. If the directory does... | Implement the Python class `univariate_timeseries` described below.
Class description:
univariate_timeseries
Method signatures and docstrings:
- def download(path): Download the univariate_timeseries dataset path Parameters ---------- path: str the path where the downloaded files will be stored. If the directory does... | d8778c2eb3254b478cef4f45d934bf921e695619 | <|skeleton|>
class univariate_timeseries:
"""univariate_timeseries"""
def download(path):
"""Download the univariate_timeseries dataset path Parameters ---------- path: str the path where the downloaded files will be stored. If the directory does not exist, it is created."""
<|body_0|>
def... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class univariate_timeseries:
"""univariate_timeseries"""
def download(path):
"""Download the univariate_timeseries dataset path Parameters ---------- path: str the path where the downloaded files will be stored. If the directory does not exist, it is created."""
if not os.path.isdir(path + 'uni... | the_stack_v2_python_sparse | symjax/data/univariate_timeseries.py | SymJAX/SymJAX | train | 52 |
de13dacf90e4b5555d21cd0688e668da22e90a43 | [
"self.max_depth = max_depth\nself.timesToRun = timesToRun\nself.limit = limit_time",
"def evaluator(node):\n return node.path_cost + heuristic.evaluate(node.state)\n\ndef queue_generator():\n return PriorityQueue(evaluator)\nsearch = GraphSearch(queue_generator, self.limit, self.max_depth)\nstart = time.clo... | <|body_start_0|>
self.max_depth = max_depth
self.timesToRun = timesToRun
self.limit = limit_time
<|end_body_0|>
<|body_start_1|>
def evaluator(node):
return node.path_cost + heuristic.evaluate(node.state)
def queue_generator():
return PriorityQueue(evalu... | Implementation of the A* search algorithm for the Problem. It may also take a maximum depth at which to stop, if needed. | AStarAndGreedyHelp | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AStarAndGreedyHelp:
"""Implementation of the A* search algorithm for the Problem. It may also take a maximum depth at which to stop, if needed."""
def __init__(self, timesToRun=infinity, limit_time=infinity, max_depth=infinity):
"""Constructs the A* search. Optionally, a maximum dept... | stack_v2_sparse_classes_75kplus_train_071812 | 5,977 | no_license | [
{
"docstring": "Constructs the A* search. Optionally, a maximum depth may be provided at which to stop looking for the goal state.",
"name": "__init__",
"signature": "def __init__(self, timesToRun=infinity, limit_time=infinity, max_depth=infinity)"
},
{
"docstring": "A* search is best-first grap... | 2 | stack_v2_sparse_classes_30k_train_054099 | Implement the Python class `AStarAndGreedyHelp` described below.
Class description:
Implementation of the A* search algorithm for the Problem. It may also take a maximum depth at which to stop, if needed.
Method signatures and docstrings:
- def __init__(self, timesToRun=infinity, limit_time=infinity, max_depth=infini... | Implement the Python class `AStarAndGreedyHelp` described below.
Class description:
Implementation of the A* search algorithm for the Problem. It may also take a maximum depth at which to stop, if needed.
Method signatures and docstrings:
- def __init__(self, timesToRun=infinity, limit_time=infinity, max_depth=infini... | 656f76259e12c7303600671278a51e7b75a83770 | <|skeleton|>
class AStarAndGreedyHelp:
"""Implementation of the A* search algorithm for the Problem. It may also take a maximum depth at which to stop, if needed."""
def __init__(self, timesToRun=infinity, limit_time=infinity, max_depth=infinity):
"""Constructs the A* search. Optionally, a maximum dept... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AStarAndGreedyHelp:
"""Implementation of the A* search algorithm for the Problem. It may also take a maximum depth at which to stop, if needed."""
def __init__(self, timesToRun=infinity, limit_time=infinity, max_depth=infinity):
"""Constructs the A* search. Optionally, a maximum depth may be prov... | the_stack_v2_python_sparse | Artificial Intelligence/AI Multi Robot/Multi_robot/src/search/astar_and_greedy.py | saedmansour/University-Code | train | 0 |
adf57788e58a7b728876a4017d7cc24de0c2c609 | [
"logger.info('Add new directory to Datary.', path=os.path.join(path, dirname))\nurl = urljoin(self.URL_BASE, 'workdirs/{}/changes'.format(wdir_uuid))\npayload = {'action': 'add', 'filemode': 40000, 'dirname': path, 'basename': dirname}\nresponse = self.request(url, 'POST', **{'data': payload, 'headers': self.header... | <|body_start_0|>
logger.info('Add new directory to Datary.', path=os.path.join(path, dirname))
url = urljoin(self.URL_BASE, 'workdirs/{}/changes'.format(wdir_uuid))
payload = {'action': 'add', 'filemode': 40000, 'dirname': path, 'basename': dirname}
response = self.request(url, 'POST', *... | Datary AddOperation module class | DataryAddOperation | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DataryAddOperation:
"""Datary AddOperation module class"""
def add_dir(self, wdir_uuid, path, dirname):
"""(DEPRECATED) Creates a new directory. ================ ============= ==================================== Parameter Type Description ================ ============= =============... | stack_v2_sparse_classes_75kplus_train_071813 | 3,778 | permissive | [
{
"docstring": "(DEPRECATED) Creates a new directory. ================ ============= ==================================== Parameter Type Description ================ ============= ==================================== wdir_uuid str working directory uuid path str path to the new directory dirname str name of the... | 2 | stack_v2_sparse_classes_30k_train_018111 | Implement the Python class `DataryAddOperation` described below.
Class description:
Datary AddOperation module class
Method signatures and docstrings:
- def add_dir(self, wdir_uuid, path, dirname): (DEPRECATED) Creates a new directory. ================ ============= ==================================== Parameter Type... | Implement the Python class `DataryAddOperation` described below.
Class description:
Datary AddOperation module class
Method signatures and docstrings:
- def add_dir(self, wdir_uuid, path, dirname): (DEPRECATED) Creates a new directory. ================ ============= ==================================== Parameter Type... | 2790a50e1ad262cbe3210665dc34f497625e923d | <|skeleton|>
class DataryAddOperation:
"""Datary AddOperation module class"""
def add_dir(self, wdir_uuid, path, dirname):
"""(DEPRECATED) Creates a new directory. ================ ============= ==================================== Parameter Type Description ================ ============= =============... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DataryAddOperation:
"""Datary AddOperation module class"""
def add_dir(self, wdir_uuid, path, dirname):
"""(DEPRECATED) Creates a new directory. ================ ============= ==================================== Parameter Type Description ================ ============= ==========================... | the_stack_v2_python_sparse | datary/operations/add.py | Datary/python-sdk | train | 0 |
12f1a10b58e738cf333837249ba81bb4dc30f4f0 | [
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')",
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')",
"conte... | <|body_start_0|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!')
<|end_body_0|>
<|body_start_1|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not im... | AuthServicer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AuthServicer:
def CreateDataset(self, request, context):
"""CreateDataset from a given Dataset wrapped in a CreateDatasetRequest"""
<|body_0|>
def SetPermission(self, request, context):
"""SetPermission sets a permission for a dataset using a SetPermissionRequest."""... | stack_v2_sparse_classes_75kplus_train_071814 | 16,615 | permissive | [
{
"docstring": "CreateDataset from a given Dataset wrapped in a CreateDatasetRequest",
"name": "CreateDataset",
"signature": "def CreateDataset(self, request, context)"
},
{
"docstring": "SetPermission sets a permission for a dataset using a SetPermissionRequest.",
"name": "SetPermission",
... | 5 | stack_v2_sparse_classes_30k_train_017481 | Implement the Python class `AuthServicer` described below.
Class description:
Implement the AuthServicer class.
Method signatures and docstrings:
- def CreateDataset(self, request, context): CreateDataset from a given Dataset wrapped in a CreateDatasetRequest
- def SetPermission(self, request, context): SetPermission... | Implement the Python class `AuthServicer` described below.
Class description:
Implement the AuthServicer class.
Method signatures and docstrings:
- def CreateDataset(self, request, context): CreateDataset from a given Dataset wrapped in a CreateDatasetRequest
- def SetPermission(self, request, context): SetPermission... | d93b5f66a00b1e3710257d607d62f9d43736304e | <|skeleton|>
class AuthServicer:
def CreateDataset(self, request, context):
"""CreateDataset from a given Dataset wrapped in a CreateDatasetRequest"""
<|body_0|>
def SetPermission(self, request, context):
"""SetPermission sets a permission for a dataset using a SetPermissionRequest."""... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AuthServicer:
def CreateDataset(self, request, context):
"""CreateDataset from a given Dataset wrapped in a CreateDatasetRequest"""
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!'... | the_stack_v2_python_sparse | CVP_API/Snapshot_Utils/getSnapshots_Resource_API/cloudvision-python/cloudvision/Connector/gen/router_pb2_grpc.py | Hugh-Adams/Example_Scripts | train | 4 | |
3151162f42ae7ddae2bbe036ac009894e81715dc | [
"if s[i] in self.required:\n self.required[s[i]] -= 1\n if self.required[s[i]] >= 0:\n self.requires -= 1",
"if s[i] in self.required:\n self.required[s[i]] += 1\n if self.required[s[i]] > 0:\n self.requires += 1",
"if not s or not t:\n return 0\nself.required.clear()\nself.requires... | <|body_start_0|>
if s[i] in self.required:
self.required[s[i]] -= 1
if self.required[s[i]] >= 0:
self.requires -= 1
<|end_body_0|>
<|body_start_1|>
if s[i] in self.required:
self.required[s[i]] += 1
if self.required[s[i]] > 0:
... | Solution2 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution2:
def add(self, s, i):
"""Add a character into the window"""
<|body_0|>
def remove(self, s, i):
"""Remove a character from the window"""
<|body_1|>
def minWindow(self, s, t):
""":type s: str :type t: str :rtype: str"""
<|body_2|>... | stack_v2_sparse_classes_75kplus_train_071815 | 3,732 | no_license | [
{
"docstring": "Add a character into the window",
"name": "add",
"signature": "def add(self, s, i)"
},
{
"docstring": "Remove a character from the window",
"name": "remove",
"signature": "def remove(self, s, i)"
},
{
"docstring": ":type s: str :type t: str :rtype: str",
"name... | 3 | stack_v2_sparse_classes_30k_test_001549 | Implement the Python class `Solution2` described below.
Class description:
Implement the Solution2 class.
Method signatures and docstrings:
- def add(self, s, i): Add a character into the window
- def remove(self, s, i): Remove a character from the window
- def minWindow(self, s, t): :type s: str :type t: str :rtype:... | Implement the Python class `Solution2` described below.
Class description:
Implement the Solution2 class.
Method signatures and docstrings:
- def add(self, s, i): Add a character into the window
- def remove(self, s, i): Remove a character from the window
- def minWindow(self, s, t): :type s: str :type t: str :rtype:... | 635af6e22aa8eef8e7920a585d43a45a891a8157 | <|skeleton|>
class Solution2:
def add(self, s, i):
"""Add a character into the window"""
<|body_0|>
def remove(self, s, i):
"""Remove a character from the window"""
<|body_1|>
def minWindow(self, s, t):
""":type s: str :type t: str :rtype: str"""
<|body_2|>... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution2:
def add(self, s, i):
"""Add a character into the window"""
if s[i] in self.required:
self.required[s[i]] -= 1
if self.required[s[i]] >= 0:
self.requires -= 1
def remove(self, s, i):
"""Remove a character from the window"""
... | the_stack_v2_python_sparse | code76MinimumWindowSubstring.py | cybelewang/leetcode-python | train | 0 | |
12902aac3f09bed3547f4be6c5aef26623f1117b | [
"self.face_net = cv.dnn.readNet('FaceNet.prototxt', 'FaceNet.caffemodel')\nself.mask_net = load_model('mask_detector.model')\nself.confidence = confidence",
"h, w = frame.shape[:2]\nblob = cv.dnn.blobFromImage(frame, 1.0, (235, 350))\nself.face_net.setInput(blob)\ndetections = self.face_net.forward()\nfaces = []\... | <|body_start_0|>
self.face_net = cv.dnn.readNet('FaceNet.prototxt', 'FaceNet.caffemodel')
self.mask_net = load_model('mask_detector.model')
self.confidence = confidence
<|end_body_0|>
<|body_start_1|>
h, w = frame.shape[:2]
blob = cv.dnn.blobFromImage(frame, 1.0, (235, 350))
... | Class that encapsulates the functionality of the face and mask detector and it's used to get the predictions of the network. | FaceAndMaskDetector | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FaceAndMaskDetector:
"""Class that encapsulates the functionality of the face and mask detector and it's used to get the predictions of the network."""
def __init__(self, confidence: float):
"""Loads the face and mask models and sets the confidence level."""
<|body_0|>
d... | stack_v2_sparse_classes_75kplus_train_071816 | 3,436 | no_license | [
{
"docstring": "Loads the face and mask models and sets the confidence level.",
"name": "__init__",
"signature": "def __init__(self, confidence: float)"
},
{
"docstring": "Gets the current frame and returns the predictions and their corresponding locations.",
"name": "detect_and_predict",
... | 2 | stack_v2_sparse_classes_30k_train_038557 | Implement the Python class `FaceAndMaskDetector` described below.
Class description:
Class that encapsulates the functionality of the face and mask detector and it's used to get the predictions of the network.
Method signatures and docstrings:
- def __init__(self, confidence: float): Loads the face and mask models an... | Implement the Python class `FaceAndMaskDetector` described below.
Class description:
Class that encapsulates the functionality of the face and mask detector and it's used to get the predictions of the network.
Method signatures and docstrings:
- def __init__(self, confidence: float): Loads the face and mask models an... | 8ca1d270d2d382c48c138bb78e0ea7f8e04cffee | <|skeleton|>
class FaceAndMaskDetector:
"""Class that encapsulates the functionality of the face and mask detector and it's used to get the predictions of the network."""
def __init__(self, confidence: float):
"""Loads the face and mask models and sets the confidence level."""
<|body_0|>
d... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class FaceAndMaskDetector:
"""Class that encapsulates the functionality of the face and mask detector and it's used to get the predictions of the network."""
def __init__(self, confidence: float):
"""Loads the face and mask models and sets the confidence level."""
self.face_net = cv.dnn.readNet... | the_stack_v2_python_sparse | utils/face_and_mask_detector.py | rajatrawal/tiago-mask-checker | train | 0 |
c678bf6e311c441d9545e094dd1cb14e85c4091c | [
"self.problem = problem\nself.pp = post.PostProcessor(dict(casedir='Results', clean_casedir=True))\nself.pp.add_field(post.SolutionField('Solution', dict(save=True, save_as=['hdf5', 'xdmf'], plot=True, plot_args=dict(range_min=float(u_min), range_max=float(u_max)))))\nself.pp.add_field(post.SolutionField('Flux', di... | <|body_start_0|>
self.problem = problem
self.pp = post.PostProcessor(dict(casedir='Results', clean_casedir=True))
self.pp.add_field(post.SolutionField('Solution', dict(save=True, save_as=['hdf5', 'xdmf'], plot=True, plot_args=dict(range_min=float(u_min), range_max=float(u_max)))))
self.p... | user_action function for storing the solution and flux. | ProcessSolution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProcessSolution:
"""user_action function for storing the solution and flux."""
def __init__(self, problem, u_min=0, u_max=1):
"""Define fields to be stored/plotted."""
<|body_0|>
def __call__(self, t, u, timestep):
"""Store u and its flux to file."""
<|bo... | stack_v2_sparse_classes_75kplus_train_071817 | 19,607 | no_license | [
{
"docstring": "Define fields to be stored/plotted.",
"name": "__init__",
"signature": "def __init__(self, problem, u_min=0, u_max=1)"
},
{
"docstring": "Store u and its flux to file.",
"name": "__call__",
"signature": "def __call__(self, t, u, timestep)"
}
] | 2 | stack_v2_sparse_classes_30k_train_044939 | Implement the Python class `ProcessSolution` described below.
Class description:
user_action function for storing the solution and flux.
Method signatures and docstrings:
- def __init__(self, problem, u_min=0, u_max=1): Define fields to be stored/plotted.
- def __call__(self, t, u, timestep): Store u and its flux to ... | Implement the Python class `ProcessSolution` described below.
Class description:
user_action function for storing the solution and flux.
Method signatures and docstrings:
- def __init__(self, problem, u_min=0, u_max=1): Define fields to be stored/plotted.
- def __call__(self, t, u, timestep): Store u and its flux to ... | 5e9a0e03aa7ddf5e5ddf89943ccc68d94b539e95 | <|skeleton|>
class ProcessSolution:
"""user_action function for storing the solution and flux."""
def __init__(self, problem, u_min=0, u_max=1):
"""Define fields to be stored/plotted."""
<|body_0|>
def __call__(self, t, u, timestep):
"""Store u and its flux to file."""
<|bo... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ProcessSolution:
"""user_action function for storing the solution and flux."""
def __init__(self, problem, u_min=0, u_max=1):
"""Define fields to be stored/plotted."""
self.problem = problem
self.pp = post.PostProcessor(dict(casedir='Results', clean_casedir=True))
self.pp.... | the_stack_v2_python_sparse | Solving_PDEs_in_Python_Langtangen/src/src/heat_class.py | burakbayramli/books | train | 223 |
a52aab58d71f16daf3a946b0ef0b0fb7583617d7 | [
"self.count, self.result = (0, 0)\ntry:\n self.get_kth_smallest(root, k)\nexcept:\n return self.result",
"if root:\n self.get_kth_smallest(root.left, k)\n self.count += 1\n if self.count == k:\n self.result = root.key\n raise Exception()\n self.get_kth_smallest(root.right, k)"
] | <|body_start_0|>
self.count, self.result = (0, 0)
try:
self.get_kth_smallest(root, k)
except:
return self.result
<|end_body_0|>
<|body_start_1|>
if root:
self.get_kth_smallest(root.left, k)
self.count += 1
if self.count == k:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def kth_smallest(self, root: TreeNode, k: int) -> int:
"""Returns the kth smallest node in a BST. :param root: root of tree :param k: number k :Time: O(H) H = height of tree :Space: O(H) :return: value of kth smallest node"""
<|body_0|>
def get_kth_smallest(self, r... | stack_v2_sparse_classes_75kplus_train_071818 | 2,127 | no_license | [
{
"docstring": "Returns the kth smallest node in a BST. :param root: root of tree :param k: number k :Time: O(H) H = height of tree :Space: O(H) :return: value of kth smallest node",
"name": "kth_smallest",
"signature": "def kth_smallest(self, root: TreeNode, k: int) -> int"
},
{
"docstring": "A... | 2 | stack_v2_sparse_classes_30k_train_052149 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def kth_smallest(self, root: TreeNode, k: int) -> int: Returns the kth smallest node in a BST. :param root: root of tree :param k: number k :Time: O(H) H = height of tree :Space:... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def kth_smallest(self, root: TreeNode, k: int) -> int: Returns the kth smallest node in a BST. :param root: root of tree :param k: number k :Time: O(H) H = height of tree :Space:... | de685690745a5a322e6233e1a3fd10a2d9539076 | <|skeleton|>
class Solution:
def kth_smallest(self, root: TreeNode, k: int) -> int:
"""Returns the kth smallest node in a BST. :param root: root of tree :param k: number k :Time: O(H) H = height of tree :Space: O(H) :return: value of kth smallest node"""
<|body_0|>
def get_kth_smallest(self, r... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def kth_smallest(self, root: TreeNode, k: int) -> int:
"""Returns the kth smallest node in a BST. :param root: root of tree :param k: number k :Time: O(H) H = height of tree :Space: O(H) :return: value of kth smallest node"""
self.count, self.result = (0, 0)
try:
... | the_stack_v2_python_sparse | questions/trees_graphs/BSTKthSmallest.py | aksh0001/algorithms-journal | train | 17 | |
90e3d66ea7b36248c213bcae2c8fd2a12a388b1c | [
"self.config = get_config()\nself.config[STATES_KEYWORD] = {'attrs': self.config[STATES_KEYWORD]['attrs'], 'subset': [0]}\nself.base_path = path_to_base_field\nif randomizer is not None:\n self.randomizer = {}\n for key, def_r in self.default_randomizer.items():\n if key not in randomizer.keys() or ran... | <|body_start_0|>
self.config = get_config()
self.config[STATES_KEYWORD] = {'attrs': self.config[STATES_KEYWORD]['attrs'], 'subset': [0]}
self.base_path = path_to_base_field
if randomizer is not None:
self.randomizer = {}
for key, def_r in self.default_randomizer.i... | Randomization of Fields, based on some base model. | FieldRandomizer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FieldRandomizer:
"""Randomization of Fields, based on some base model."""
def __init__(self, path_to_base_field, randomizer=None):
"""Parameters ---------- path_to_base_field: std Path to the base-field used to randomize around. randomizer: dict Dict with instances of randomizers for... | stack_v2_sparse_classes_75kplus_train_071819 | 13,810 | permissive | [
{
"docstring": "Parameters ---------- path_to_base_field: std Path to the base-field used to randomize around. randomizer: dict Dict with instances of randomizers for states, rock and control (wells) Should have keys the following form: randomizer = { 'states': states_rand, 'rock': rock_rand, 'wells': control_r... | 4 | stack_v2_sparse_classes_30k_train_035860 | Implement the Python class `FieldRandomizer` described below.
Class description:
Randomization of Fields, based on some base model.
Method signatures and docstrings:
- def __init__(self, path_to_base_field, randomizer=None): Parameters ---------- path_to_base_field: std Path to the base-field used to randomize around... | Implement the Python class `FieldRandomizer` described below.
Class description:
Randomization of Fields, based on some base model.
Method signatures and docstrings:
- def __init__(self, path_to_base_field, randomizer=None): Parameters ---------- path_to_base_field: std Path to the base-field used to randomize around... | 3b336ed110ff806316f1f6a99b212f99256a6b56 | <|skeleton|>
class FieldRandomizer:
"""Randomization of Fields, based on some base model."""
def __init__(self, path_to_base_field, randomizer=None):
"""Parameters ---------- path_to_base_field: std Path to the base-field used to randomize around. randomizer: dict Dict with instances of randomizers for... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class FieldRandomizer:
"""Randomization of Fields, based on some base model."""
def __init__(self, path_to_base_field, randomizer=None):
"""Parameters ---------- path_to_base_field: std Path to the base-field used to randomize around. randomizer: dict Dict with instances of randomizers for states, rock... | the_stack_v2_python_sparse | deepfield/datasets/randomize.py | scuervo91/DeepField | train | 0 |
fd8e2a7a758f8308cefd394c7ef1a3d62a97fc29 | [
"regex = InvenTree.helpers.str2bool(request.query_params.get('search_regex', False))\nsearch_fields = super().get_search_fields(view, request)\nfields = []\nif search_fields:\n for field in search_fields:\n if regex:\n field = '$' + field\n fields.append(field)\nreturn fields",
"whole ... | <|body_start_0|>
regex = InvenTree.helpers.str2bool(request.query_params.get('search_regex', False))
search_fields = super().get_search_fields(view, request)
fields = []
if search_fields:
for field in search_fields:
if regex:
field = '$' + ... | Custom search filter which allows adjusting of search terms dynamically | InvenTreeSearchFilter | [
"MIT",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InvenTreeSearchFilter:
"""Custom search filter which allows adjusting of search terms dynamically"""
def get_search_fields(self, view, request):
"""Return a set of search fields for the request, adjusted based on request params. The following query params are available to 'augment' t... | stack_v2_sparse_classes_75kplus_train_071820 | 4,204 | permissive | [
{
"docstring": "Return a set of search fields for the request, adjusted based on request params. The following query params are available to 'augment' the search (in decreasing order of priority) - search_regex: If True, search is performed on 'regex' comparison",
"name": "get_search_fields",
"signature... | 2 | stack_v2_sparse_classes_30k_train_032537 | Implement the Python class `InvenTreeSearchFilter` described below.
Class description:
Custom search filter which allows adjusting of search terms dynamically
Method signatures and docstrings:
- def get_search_fields(self, view, request): Return a set of search fields for the request, adjusted based on request params... | Implement the Python class `InvenTreeSearchFilter` described below.
Class description:
Custom search filter which allows adjusting of search terms dynamically
Method signatures and docstrings:
- def get_search_fields(self, view, request): Return a set of search fields for the request, adjusted based on request params... | e88a8e99a5f0b201c67a95cba097c729f090d5e2 | <|skeleton|>
class InvenTreeSearchFilter:
"""Custom search filter which allows adjusting of search terms dynamically"""
def get_search_fields(self, view, request):
"""Return a set of search fields for the request, adjusted based on request params. The following query params are available to 'augment' t... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class InvenTreeSearchFilter:
"""Custom search filter which allows adjusting of search terms dynamically"""
def get_search_fields(self, view, request):
"""Return a set of search fields for the request, adjusted based on request params. The following query params are available to 'augment' the search (in... | the_stack_v2_python_sparse | InvenTree/InvenTree/filters.py | inventree/InvenTree | train | 3,077 |
c71555d50d8ecacdeb15c3f2ad0a8e83faf454e4 | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn EdiscoveryCase()",
"from ..identity_set import IdentitySet\nfrom .case import Case\nfrom .case_operation import CaseOperation\nfrom .ediscovery_case_settings import EdiscoveryCaseSettings\nfrom .ediscovery_custodian import EdiscoveryCu... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return EdiscoveryCase()
<|end_body_0|>
<|body_start_1|>
from ..identity_set import IdentitySet
from .case import Case
from .case_operation import CaseOperation
from .ediscovery_... | EdiscoveryCase | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EdiscoveryCase:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> EdiscoveryCase:
"""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 Retur... | stack_v2_sparse_classes_75kplus_train_071821 | 6,513 | 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: EdiscoveryCase",
"name": "create_from_discriminator_value",
"signature": "def create_from_discriminator_valu... | 3 | stack_v2_sparse_classes_30k_val_000111 | Implement the Python class `EdiscoveryCase` described below.
Class description:
Implement the EdiscoveryCase class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> EdiscoveryCase: Creates a new instance of the appropriate class based on discriminator va... | Implement the Python class `EdiscoveryCase` described below.
Class description:
Implement the EdiscoveryCase class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> EdiscoveryCase: Creates a new instance of the appropriate class based on discriminator va... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class EdiscoveryCase:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> EdiscoveryCase:
"""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 Retur... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class EdiscoveryCase:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> EdiscoveryCase:
"""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: Ediscovery... | the_stack_v2_python_sparse | msgraph/generated/models/security/ediscovery_case.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
7cbf2015f363bdc69003436862a65a41531440ab | [
"super().__init__()\nself.norm = torch.nn.InstanceNorm1d(in_channels)\nself.aux_conv = torch.nn.Sequential(torch.nn.Conv1d(aux_channels, in_channels, kernel_size, 1, bias=bias, padding=(kernel_size - 1) // 2))\nself.gated_conv = torch.nn.Sequential(torch.nn.Conv1d(in_channels, in_channels * 2, kernel_size, 1, bias=... | <|body_start_0|>
super().__init__()
self.norm = torch.nn.InstanceNorm1d(in_channels)
self.aux_conv = torch.nn.Sequential(torch.nn.Conv1d(aux_channels, in_channels, kernel_size, 1, bias=bias, padding=(kernel_size - 1) // 2))
self.gated_conv = torch.nn.Sequential(torch.nn.Conv1d(in_channel... | TADE Layer module. | TADELayer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TADELayer:
"""TADE Layer module."""
def __init__(self, in_channels: int=64, aux_channels: int=80, kernel_size: int=9, bias: bool=True, upsample_factor: int=2, upsample_mode: str='nearest'):
"""Initilize TADELayer module. Args: in_channels (int): Number of input channles. aux_channels... | stack_v2_sparse_classes_75kplus_train_071822 | 5,864 | permissive | [
{
"docstring": "Initilize TADELayer module. Args: in_channels (int): Number of input channles. aux_channels (int): Number of auxirialy channles. kernel_size (int): Kernel size. bias (bool): Whether to use bias parameter in conv. upsample_factor (int): Upsample factor. upsample_mode (str): Upsample mode.",
"... | 2 | stack_v2_sparse_classes_30k_train_050418 | Implement the Python class `TADELayer` described below.
Class description:
TADE Layer module.
Method signatures and docstrings:
- def __init__(self, in_channels: int=64, aux_channels: int=80, kernel_size: int=9, bias: bool=True, upsample_factor: int=2, upsample_mode: str='nearest'): Initilize TADELayer module. Args: ... | Implement the Python class `TADELayer` described below.
Class description:
TADE Layer module.
Method signatures and docstrings:
- def __init__(self, in_channels: int=64, aux_channels: int=80, kernel_size: int=9, bias: bool=True, upsample_factor: int=2, upsample_mode: str='nearest'): Initilize TADELayer module. Args: ... | bcd20948db7846ee523443ef9fd78c7a1248c95e | <|skeleton|>
class TADELayer:
"""TADE Layer module."""
def __init__(self, in_channels: int=64, aux_channels: int=80, kernel_size: int=9, bias: bool=True, upsample_factor: int=2, upsample_mode: str='nearest'):
"""Initilize TADELayer module. Args: in_channels (int): Number of input channles. aux_channels... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TADELayer:
"""TADE Layer module."""
def __init__(self, in_channels: int=64, aux_channels: int=80, kernel_size: int=9, bias: bool=True, upsample_factor: int=2, upsample_mode: str='nearest'):
"""Initilize TADELayer module. Args: in_channels (int): Number of input channles. aux_channels (int): Numbe... | the_stack_v2_python_sparse | espnet2/gan_tts/style_melgan/tade_res_block.py | espnet/espnet | train | 7,242 |
3fd5af0e201731f08aaf0fdb8aa11e066b959a02 | [
"self.name = name\nself.hw = {}\nself.acron_dofs = []\nself.eid_dofids = []\nself.num_dof = 0\nself.hw_rss = []\nself.read_hwlist()",
"with open(self.name, 'r') as f:\n for line in f:\n if line.__len__() > 20 and line[0] != '$':\n acron = line[0:8].strip()\n if acron not in self.hw... | <|body_start_0|>
self.name = name
self.hw = {}
self.acron_dofs = []
self.eid_dofids = []
self.num_dof = 0
self.hw_rss = []
self.read_hwlist()
<|end_body_0|>
<|body_start_1|>
with open(self.name, 'r') as f:
for line in f:
if lin... | Hardware List Class | HWLIST | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HWLIST:
"""Hardware List Class"""
def __init__(self, name):
"""Initializing the HWLIST class."""
<|body_0|>
def read_hwlist(self):
"""Method to read in the HWLIST attributes. Ex: HWLIST.read_hwlist()"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_75kplus_train_071823 | 2,195 | no_license | [
{
"docstring": "Initializing the HWLIST class.",
"name": "__init__",
"signature": "def __init__(self, name)"
},
{
"docstring": "Method to read in the HWLIST attributes. Ex: HWLIST.read_hwlist()",
"name": "read_hwlist",
"signature": "def read_hwlist(self)"
}
] | 2 | null | Implement the Python class `HWLIST` described below.
Class description:
Hardware List Class
Method signatures and docstrings:
- def __init__(self, name): Initializing the HWLIST class.
- def read_hwlist(self): Method to read in the HWLIST attributes. Ex: HWLIST.read_hwlist() | Implement the Python class `HWLIST` described below.
Class description:
Hardware List Class
Method signatures and docstrings:
- def __init__(self, name): Initializing the HWLIST class.
- def read_hwlist(self): Method to read in the HWLIST attributes. Ex: HWLIST.read_hwlist()
<|skeleton|>
class HWLIST:
"""Hardwar... | 6b37842203ff4318a48dbf0258cbe2b253436e7d | <|skeleton|>
class HWLIST:
"""Hardware List Class"""
def __init__(self, name):
"""Initializing the HWLIST class."""
<|body_0|>
def read_hwlist(self):
"""Method to read in the HWLIST attributes. Ex: HWLIST.read_hwlist()"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class HWLIST:
"""Hardware List Class"""
def __init__(self, name):
"""Initializing the HWLIST class."""
self.name = name
self.hw = {}
self.acron_dofs = []
self.eid_dofids = []
self.num_dof = 0
self.hw_rss = []
self.read_hwlist()
def read_hwlis... | the_stack_v2_python_sparse | loads/hwlist.py | tslowery78/PyLnD | train | 0 |
2fe5e1aa02b31005092dcd43d6f3fb2d697408d6 | [
"self.base_image = pygame.image.load(image)\nself.images = []\nself.duration = duration\nself.last_change = time()\nself.selected_image = 0\nsprite_w = self.base_image.get_width() / w\nsprite_h = self.base_image.get_height() / h\nself.final_size = final_size\nself.invisible_color = invisible_color\nif final_size is... | <|body_start_0|>
self.base_image = pygame.image.load(image)
self.images = []
self.duration = duration
self.last_change = time()
self.selected_image = 0
sprite_w = self.base_image.get_width() / w
sprite_h = self.base_image.get_height() / h
self.final_size =... | SpriteSheet | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SpriteSheet:
def __init__(self, image: str, w: int, h: int, duration: float=None, final_size: tuple=None, invisible_color: tuple=(0, 0, 1)):
"""This class is for creating spritesheets :param image: the path to the image of the sheet :param w: the width of each frame in the sheet :param h... | stack_v2_sparse_classes_75kplus_train_071824 | 2,468 | no_license | [
{
"docstring": "This class is for creating spritesheets :param image: the path to the image of the sheet :param w: the width of each frame in the sheet :param h: the height of each frame in the sheet :param duration: the number of seconds to stay on each frame :param final_size: the final size to scale the imag... | 3 | stack_v2_sparse_classes_30k_train_042184 | Implement the Python class `SpriteSheet` described below.
Class description:
Implement the SpriteSheet class.
Method signatures and docstrings:
- def __init__(self, image: str, w: int, h: int, duration: float=None, final_size: tuple=None, invisible_color: tuple=(0, 0, 1)): This class is for creating spritesheets :par... | Implement the Python class `SpriteSheet` described below.
Class description:
Implement the SpriteSheet class.
Method signatures and docstrings:
- def __init__(self, image: str, w: int, h: int, duration: float=None, final_size: tuple=None, invisible_color: tuple=(0, 0, 1)): This class is for creating spritesheets :par... | e9e68cf3ba4f9f12e66eae81893ca9dcc534835c | <|skeleton|>
class SpriteSheet:
def __init__(self, image: str, w: int, h: int, duration: float=None, final_size: tuple=None, invisible_color: tuple=(0, 0, 1)):
"""This class is for creating spritesheets :param image: the path to the image of the sheet :param w: the width of each frame in the sheet :param h... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SpriteSheet:
def __init__(self, image: str, w: int, h: int, duration: float=None, final_size: tuple=None, invisible_color: tuple=(0, 0, 1)):
"""This class is for creating spritesheets :param image: the path to the image of the sheet :param w: the width of each frame in the sheet :param h: the height o... | the_stack_v2_python_sparse | Objects/SpriteSheet.py | john-palazzolo/PyGE | train | 0 | |
61d0b3819e5ac37ac4b5f5b9c19ababe7fbf21c2 | [
"s, t = (sorted(s), sorted(t))\nn = len(s)\nfor i in range(n):\n if s[i] != t[i]:\n return t[i]\nreturn t[-1]",
"char_count = Counter(s)\nfor char in t:\n if not char_count[char] or char not in char_count:\n return char\n char_count[char] -= 1",
"value = 0\nn = len(s)\nfor i in range(n):\... | <|body_start_0|>
s, t = (sorted(s), sorted(t))
n = len(s)
for i in range(n):
if s[i] != t[i]:
return t[i]
return t[-1]
<|end_body_0|>
<|body_start_1|>
char_count = Counter(s)
for char in t:
if not char_count[char] or char not in ch... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def find_diff_1(self, s, t):
"""Sort the strings and find first different letter. Time complexity: O(n * lg(n)). Space complexity: O(n), n is len(s)."""
<|body_0|>
def find_diff_2(self, s, t):
"""Use hash map to count the characters in string s, then compar... | stack_v2_sparse_classes_75kplus_train_071825 | 2,403 | no_license | [
{
"docstring": "Sort the strings and find first different letter. Time complexity: O(n * lg(n)). Space complexity: O(n), n is len(s).",
"name": "find_diff_1",
"signature": "def find_diff_1(self, s, t)"
},
{
"docstring": "Use hash map to count the characters in string s, then compare it with char... | 4 | stack_v2_sparse_classes_30k_train_050778 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def find_diff_1(self, s, t): Sort the strings and find first different letter. Time complexity: O(n * lg(n)). Space complexity: O(n), n is len(s).
- def find_diff_2(self, s, t): ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def find_diff_1(self, s, t): Sort the strings and find first different letter. Time complexity: O(n * lg(n)). Space complexity: O(n), n is len(s).
- def find_diff_2(self, s, t): ... | 71b722ddfe8da04572e527b055cf8723d5c87bbf | <|skeleton|>
class Solution:
def find_diff_1(self, s, t):
"""Sort the strings and find first different letter. Time complexity: O(n * lg(n)). Space complexity: O(n), n is len(s)."""
<|body_0|>
def find_diff_2(self, s, t):
"""Use hash map to count the characters in string s, then compar... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def find_diff_1(self, s, t):
"""Sort the strings and find first different letter. Time complexity: O(n * lg(n)). Space complexity: O(n), n is len(s)."""
s, t = (sorted(s), sorted(t))
n = len(s)
for i in range(n):
if s[i] != t[i]:
return t[i... | the_stack_v2_python_sparse | Bit_Manipulation/find_difference.py | vladn90/Algorithms | train | 0 | |
ee48606eaea3b7d522ad62fa25e218c9830d544f | [
"new_article = Article()\nnew_article.title = request.data['title']\nnew_article.synopsis = request.data['synopsis']\nnew_article.link = request.data['link']\nnew_article.reference = request.data['reference']\nnew_article.coder = Coder.objects.get(user=request.auth.user)\nnew_article.save()\nserializer = ArticleSer... | <|body_start_0|>
new_article = Article()
new_article.title = request.data['title']
new_article.synopsis = request.data['synopsis']
new_article.link = request.data['link']
new_article.reference = request.data['reference']
new_article.coder = Coder.objects.get(user=request.... | Articles for codeArchive | Articles | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Articles:
"""Articles for codeArchive"""
def create(self, request):
"""Handle POST operations Returns: Response -- JSON serialized Article instance"""
<|body_0|>
def destroy(self, request, pk=None):
"""Handle DELETE requests for a single article Returns: Response... | stack_v2_sparse_classes_75kplus_train_071826 | 3,493 | no_license | [
{
"docstring": "Handle POST operations Returns: Response -- JSON serialized Article instance",
"name": "create",
"signature": "def create(self, request)"
},
{
"docstring": "Handle DELETE requests for a single article Returns: Response -- 200, 404, or 500 status code",
"name": "destroy",
... | 5 | stack_v2_sparse_classes_30k_train_013573 | Implement the Python class `Articles` described below.
Class description:
Articles for codeArchive
Method signatures and docstrings:
- def create(self, request): Handle POST operations Returns: Response -- JSON serialized Article instance
- def destroy(self, request, pk=None): Handle DELETE requests for a single arti... | Implement the Python class `Articles` described below.
Class description:
Articles for codeArchive
Method signatures and docstrings:
- def create(self, request): Handle POST operations Returns: Response -- JSON serialized Article instance
- def destroy(self, request, pk=None): Handle DELETE requests for a single arti... | 2bd984d13baaa9e12bba63a3bf39c2ff93619e59 | <|skeleton|>
class Articles:
"""Articles for codeArchive"""
def create(self, request):
"""Handle POST operations Returns: Response -- JSON serialized Article instance"""
<|body_0|>
def destroy(self, request, pk=None):
"""Handle DELETE requests for a single article Returns: Response... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Articles:
"""Articles for codeArchive"""
def create(self, request):
"""Handle POST operations Returns: Response -- JSON serialized Article instance"""
new_article = Article()
new_article.title = request.data['title']
new_article.synopsis = request.data['synopsis']
... | the_stack_v2_python_sparse | codearchiveAPIapp/views/article_view.py | shanemiller89/codeArchive_API | train | 0 |
9f2bccb03081cbc1a28beaa34f1547455e602dd9 | [
"threading.Thread.__init__(self)\nself.daemon = True\nself.queue = queue\nself.processedUrls = processedUrls\nself.selectedDomains = selectedDomains\nself.selectedUrls = selectedUrls\nself.baseFileName = baseFileName\nself.parseTimeout = parseTimeout",
"global parseCancelled\nstartTime = time.time()\nlastActionTi... | <|body_start_0|>
threading.Thread.__init__(self)
self.daemon = True
self.queue = queue
self.processedUrls = processedUrls
self.selectedDomains = selectedDomains
self.selectedUrls = selectedUrls
self.baseFileName = baseFileName
self.parseTimeout = parseTime... | SpiderMonitor | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SpiderMonitor:
def __init__(self, queue, processedUrls, selectedDomains, selectedUrls, baseFileName, parseTimeout):
"""Инициализация"""
<|body_0|>
def run(self):
"""Каждые 5 секунд сохраняем базу в файл и выводим текущую информацию. По истечении тайматута завершаем в... | stack_v2_sparse_classes_75kplus_train_071827 | 5,227 | no_license | [
{
"docstring": "Инициализация",
"name": "__init__",
"signature": "def __init__(self, queue, processedUrls, selectedDomains, selectedUrls, baseFileName, parseTimeout)"
},
{
"docstring": "Каждые 5 секунд сохраняем базу в файл и выводим текущую информацию. По истечении тайматута завершаем выполнени... | 2 | stack_v2_sparse_classes_30k_train_016827 | Implement the Python class `SpiderMonitor` described below.
Class description:
Implement the SpiderMonitor class.
Method signatures and docstrings:
- def __init__(self, queue, processedUrls, selectedDomains, selectedUrls, baseFileName, parseTimeout): Инициализация
- def run(self): Каждые 5 секунд сохраняем базу в фай... | Implement the Python class `SpiderMonitor` described below.
Class description:
Implement the SpiderMonitor class.
Method signatures and docstrings:
- def __init__(self, queue, processedUrls, selectedDomains, selectedUrls, baseFileName, parseTimeout): Инициализация
- def run(self): Каждые 5 секунд сохраняем базу в фай... | d2771bf04aa187dda6d468883a5a167237589369 | <|skeleton|>
class SpiderMonitor:
def __init__(self, queue, processedUrls, selectedDomains, selectedUrls, baseFileName, parseTimeout):
"""Инициализация"""
<|body_0|>
def run(self):
"""Каждые 5 секунд сохраняем базу в файл и выводим текущую информацию. По истечении тайматута завершаем в... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SpiderMonitor:
def __init__(self, queue, processedUrls, selectedDomains, selectedUrls, baseFileName, parseTimeout):
"""Инициализация"""
threading.Thread.__init__(self)
self.daemon = True
self.queue = queue
self.processedUrls = processedUrls
self.selectedDomains ... | the_stack_v2_python_sparse | doorsagents/baseparser.py | cash2one/doorscenter | train | 0 | |
2623e01b133e2afcce17d60a49ee127907cea704 | [
"test_treatment = Treatment(treatment='Test Treatment', diet=Diet.objects.get(pk=1), environment=Environment.objects.get(pk=1))\ntest_treatment.save()\ntest_treatment.animals.add(Animal.objects.get(pk=1))\ntest_treatment.researchers.add(Researcher.objects.get(pk=1))\nself.assertEqual(test_treatment.pk, 1)",
"test... | <|body_start_0|>
test_treatment = Treatment(treatment='Test Treatment', diet=Diet.objects.get(pk=1), environment=Environment.objects.get(pk=1))
test_treatment.save()
test_treatment.animals.add(Animal.objects.get(pk=1))
test_treatment.researchers.add(Researcher.objects.get(pk=1))
... | These tests test the functionality of :class:`~mousedb.data.models.Treatment` objects. | TreatmentModelTests | [
"LicenseRef-scancode-unknown-license-reference",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TreatmentModelTests:
"""These tests test the functionality of :class:`~mousedb.data.models.Treatment` objects."""
def test_create_treatment_minimum(self):
"""This test creates a :class:`~mousedb.data.models.Treatment` with the required information only."""
<|body_0|>
def... | stack_v2_sparse_classes_75kplus_train_071828 | 29,846 | permissive | [
{
"docstring": "This test creates a :class:`~mousedb.data.models.Treatment` with the required information only.",
"name": "test_create_treatment_minimum",
"signature": "def test_create_treatment_minimum(self)"
},
{
"docstring": "This test creates a :class:`~mousedb.data.models.Treatment` with al... | 4 | stack_v2_sparse_classes_30k_train_022760 | Implement the Python class `TreatmentModelTests` described below.
Class description:
These tests test the functionality of :class:`~mousedb.data.models.Treatment` objects.
Method signatures and docstrings:
- def test_create_treatment_minimum(self): This test creates a :class:`~mousedb.data.models.Treatment` with the ... | Implement the Python class `TreatmentModelTests` described below.
Class description:
These tests test the functionality of :class:`~mousedb.data.models.Treatment` objects.
Method signatures and docstrings:
- def test_create_treatment_minimum(self): This test creates a :class:`~mousedb.data.models.Treatment` with the ... | 7e423991f72c89468010c99865e3c70c22044df3 | <|skeleton|>
class TreatmentModelTests:
"""These tests test the functionality of :class:`~mousedb.data.models.Treatment` objects."""
def test_create_treatment_minimum(self):
"""This test creates a :class:`~mousedb.data.models.Treatment` with the required information only."""
<|body_0|>
def... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TreatmentModelTests:
"""These tests test the functionality of :class:`~mousedb.data.models.Treatment` objects."""
def test_create_treatment_minimum(self):
"""This test creates a :class:`~mousedb.data.models.Treatment` with the required information only."""
test_treatment = Treatment(treat... | the_stack_v2_python_sparse | mousedb/data/tests.py | BridgesLab/mousedb | train | 0 |
fa0dd20d461e5a73e43759c6ac927d45b3eff850 | [
"self.game = Game()\nself.grid = Grid()\nself.file_manager = FileManager()",
"return_1 = 'Correct!'\nstring_1 = self.game.correct_answer_response()\nself.assertEqual(string_1, return_1)",
"correct_answer = '2014'\nreturn_1 = 'The correct answer is 2014.'\nstring_1 = self.game.incorrect_answer_response(correct_a... | <|body_start_0|>
self.game = Game()
self.grid = Grid()
self.file_manager = FileManager()
<|end_body_0|>
<|body_start_1|>
return_1 = 'Correct!'
string_1 = self.game.correct_answer_response()
self.assertEqual(string_1, return_1)
<|end_body_1|>
<|body_start_2|>
cor... | TestGame | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestGame:
def setUp(self):
"""setUp class"""
<|body_0|>
def test_correct_answer_response(self):
"""test correct_answer_response functionality"""
<|body_1|>
def test_incorrect_answer_response(self):
"""test incorrect_answer_response functionality"... | stack_v2_sparse_classes_75kplus_train_071829 | 1,533 | permissive | [
{
"docstring": "setUp class",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "test correct_answer_response functionality",
"name": "test_correct_answer_response",
"signature": "def test_correct_answer_response(self)"
},
{
"docstring": "test incorrect_answer_res... | 4 | stack_v2_sparse_classes_30k_train_023226 | Implement the Python class `TestGame` described below.
Class description:
Implement the TestGame class.
Method signatures and docstrings:
- def setUp(self): setUp class
- def test_correct_answer_response(self): test correct_answer_response functionality
- def test_incorrect_answer_response(self): test incorrect_answe... | Implement the Python class `TestGame` described below.
Class description:
Implement the TestGame class.
Method signatures and docstrings:
- def setUp(self): setUp class
- def test_correct_answer_response(self): test correct_answer_response functionality
- def test_incorrect_answer_response(self): test incorrect_answe... | 24372001de9281cb37310f12c318a1b5c7f44190 | <|skeleton|>
class TestGame:
def setUp(self):
"""setUp class"""
<|body_0|>
def test_correct_answer_response(self):
"""test correct_answer_response functionality"""
<|body_1|>
def test_incorrect_answer_response(self):
"""test incorrect_answer_response functionality"... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TestGame:
def setUp(self):
"""setUp class"""
self.game = Game()
self.grid = Grid()
self.file_manager = FileManager()
def test_correct_answer_response(self):
"""test correct_answer_response functionality"""
return_1 = 'Correct!'
string_1 = self.game.... | the_stack_v2_python_sparse | test_game.py | xkb1984/Pico-Escape-Room | train | 0 | |
b75e555a1bbc1cdea21510304b331ee3440a0c15 | [
"res = 0\nfor i, c in enumerate(s):\n add = 0\n if c == 'I':\n add = 1\n elif c == 'V':\n add = add + 3 if i > 0 and s[i - 1] == 'I' else add + 5\n elif c == 'X':\n add = add + 8 if i > 0 and s[i - 1] == 'I' else add + 10\n elif c == 'L':\n add = add + 30 if i > 0 and s[i ... | <|body_start_0|>
res = 0
for i, c in enumerate(s):
add = 0
if c == 'I':
add = 1
elif c == 'V':
add = add + 3 if i > 0 and s[i - 1] == 'I' else add + 5
elif c == 'X':
add = add + 8 if i > 0 and s[i - 1] == 'I'... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def romanToInt(self, s: str) -> int:
"""Input: "LVIII" Output: 58 Explanation: L = 50, V= 5, III = 3."""
<|body_0|>
def romanToInt(self, s):
"""Input: "LVIII" Output: 58 Explanation: L = 50, V= 5, III = 3."""
<|body_1|>
<|end_skeleton|>
<|body_sta... | stack_v2_sparse_classes_75kplus_train_071830 | 2,062 | no_license | [
{
"docstring": "Input: \"LVIII\" Output: 58 Explanation: L = 50, V= 5, III = 3.",
"name": "romanToInt",
"signature": "def romanToInt(self, s: str) -> int"
},
{
"docstring": "Input: \"LVIII\" Output: 58 Explanation: L = 50, V= 5, III = 3.",
"name": "romanToInt",
"signature": "def romanToI... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def romanToInt(self, s: str) -> int: Input: "LVIII" Output: 58 Explanation: L = 50, V= 5, III = 3.
- def romanToInt(self, s): Input: "LVIII" Output: 58 Explanation: L = 50, V= 5,... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def romanToInt(self, s: str) -> int: Input: "LVIII" Output: 58 Explanation: L = 50, V= 5, III = 3.
- def romanToInt(self, s): Input: "LVIII" Output: 58 Explanation: L = 50, V= 5,... | 5d3e0b727b0294ecd1099818cbd9c85a0da56de2 | <|skeleton|>
class Solution:
def romanToInt(self, s: str) -> int:
"""Input: "LVIII" Output: 58 Explanation: L = 50, V= 5, III = 3."""
<|body_0|>
def romanToInt(self, s):
"""Input: "LVIII" Output: 58 Explanation: L = 50, V= 5, III = 3."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def romanToInt(self, s: str) -> int:
"""Input: "LVIII" Output: 58 Explanation: L = 50, V= 5, III = 3."""
res = 0
for i, c in enumerate(s):
add = 0
if c == 'I':
add = 1
elif c == 'V':
add = add + 3 if i > 0 an... | the_stack_v2_python_sparse | Python/13_roman_to_integer.py | havefuncoding/Leetcode | train | 0 | |
01db017178fc4890f753e3df1645a759394b93bf | [
"self.goal_map = []\nfor i in range(16):\n self.goal_map.append(i)\nself.goal_lists = goal.tiles\nfor row in range(4):\n for col in range(4):\n self.goal_map[goal.tiles[row][col]] = (row, col)\nself.col_conflicts = []\nfor col in range(4):\n col_list = []\n for row in range(4):\n col_list.... | <|body_start_0|>
self.goal_map = []
for i in range(16):
self.goal_map.append(i)
self.goal_lists = goal.tiles
for row in range(4):
for col in range(4):
self.goal_map[goal.tiles[row][col]] = (row, col)
self.col_conflicts = []
for col ... | Object used to preprocess goal position for heuristic function | HeuristicObj | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HeuristicObj:
"""Object used to preprocess goal position for heuristic function"""
def __init__(self, goal):
"""Preprocess goal position to setup internal data structures that can be used to speed up heuristic."""
<|body_0|>
def heuristic(self, start):
"""Estimat... | stack_v2_sparse_classes_75kplus_train_071831 | 19,259 | permissive | [
{
"docstring": "Preprocess goal position to setup internal data structures that can be used to speed up heuristic.",
"name": "__init__",
"signature": "def __init__(self, goal)"
},
{
"docstring": "Estimates the number of moves from start to goal. The goal was preprocessed in __init__.",
"name... | 2 | null | Implement the Python class `HeuristicObj` described below.
Class description:
Object used to preprocess goal position for heuristic function
Method signatures and docstrings:
- def __init__(self, goal): Preprocess goal position to setup internal data structures that can be used to speed up heuristic.
- def heuristic(... | Implement the Python class `HeuristicObj` described below.
Class description:
Object used to preprocess goal position for heuristic function
Method signatures and docstrings:
- def __init__(self, goal): Preprocess goal position to setup internal data structures that can be used to speed up heuristic.
- def heuristic(... | 85ef834ce1c48bd725893bb29d820236aac98752 | <|skeleton|>
class HeuristicObj:
"""Object used to preprocess goal position for heuristic function"""
def __init__(self, goal):
"""Preprocess goal position to setup internal data structures that can be used to speed up heuristic."""
<|body_0|>
def heuristic(self, start):
"""Estimat... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class HeuristicObj:
"""Object used to preprocess goal position for heuristic function"""
def __init__(self, goal):
"""Preprocess goal position to setup internal data structures that can be used to speed up heuristic."""
self.goal_map = []
for i in range(16):
self.goal_map.ap... | the_stack_v2_python_sparse | old/astar.py | bobbydurrett/my15puzzlesolver | train | 0 |
2dd4b252ddc1859a7d8702f4e77a4cd05bb7df94 | [
"self.PATH = 'data/{}'.format(file)\nself._config = config\nself._load_rawdata()\nself._employee_process()\nself._demand_process()\nself._predict_samples_process()",
"log.info('loading the excel file ......')\ntry:\n self._employees = pd.read_excel(self.PATH, sheet_name='小哥信息')\n self._demands = pd.read_exc... | <|body_start_0|>
self.PATH = 'data/{}'.format(file)
self._config = config
self._load_rawdata()
self._employee_process()
self._demand_process()
self._predict_samples_process()
<|end_body_0|>
<|body_start_1|>
log.info('loading the excel file ......')
try:
... | DataHandler | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DataHandler:
def __init__(self, file, config):
"""file:文件名 :param file: :param config"""
<|body_0|>
def _load_rawdata(self):
"""加载原始文件 :return:"""
<|body_1|>
def _employee_process(self):
"""处理小哥的信息 :return:"""
<|body_2|>
def _demand_... | stack_v2_sparse_classes_75kplus_train_071832 | 5,771 | no_license | [
{
"docstring": "file:文件名 :param file: :param config",
"name": "__init__",
"signature": "def __init__(self, file, config)"
},
{
"docstring": "加载原始文件 :return:",
"name": "_load_rawdata",
"signature": "def _load_rawdata(self)"
},
{
"docstring": "处理小哥的信息 :return:",
"name": "_emplo... | 5 | stack_v2_sparse_classes_30k_val_001965 | Implement the Python class `DataHandler` described below.
Class description:
Implement the DataHandler class.
Method signatures and docstrings:
- def __init__(self, file, config): file:文件名 :param file: :param config
- def _load_rawdata(self): 加载原始文件 :return:
- def _employee_process(self): 处理小哥的信息 :return:
- def _dema... | Implement the Python class `DataHandler` described below.
Class description:
Implement the DataHandler class.
Method signatures and docstrings:
- def __init__(self, file, config): file:文件名 :param file: :param config
- def _load_rawdata(self): 加载原始文件 :return:
- def _employee_process(self): 处理小哥的信息 :return:
- def _dema... | a8933767f4fea431e316b5cf0c9828f703548035 | <|skeleton|>
class DataHandler:
def __init__(self, file, config):
"""file:文件名 :param file: :param config"""
<|body_0|>
def _load_rawdata(self):
"""加载原始文件 :return:"""
<|body_1|>
def _employee_process(self):
"""处理小哥的信息 :return:"""
<|body_2|>
def _demand_... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DataHandler:
def __init__(self, file, config):
"""file:文件名 :param file: :param config"""
self.PATH = 'data/{}'.format(file)
self._config = config
self._load_rawdata()
self._employee_process()
self._demand_process()
self._predict_samples_process()
de... | the_stack_v2_python_sparse | SF_Technology_Algorithm/OR_Own/datahandle.py | perry-xy/SF | train | 0 | |
ffe0e7769c7e2b597fd6fbd3f4c59a209fb5d718 | [
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')",
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')",
"conte... | <|body_start_0|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!')
<|end_body_0|>
<|body_start_1|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not im... | Missing associated documentation comment in .proto file. | BrokerServicer | [
"Unlicense",
"BSD-3-Clause",
"LLVM-exception",
"Apache-2.0",
"BSD-2-Clause",
"MIT",
"CC0-1.0",
"Apache-1.1",
"W3C-19980720",
"MPL-1.1",
"Unicode-TOU",
"W3C",
"LGPL-2.1-or-later",
"CDDL-1.1",
"EPL-1.0",
"GPL-1.0-or-later",
"Classpath-exception-2.0",
"LGPL-2.1-only",
"CC-BY-SA-2.5"... | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BrokerServicer:
"""Missing associated documentation comment in .proto file."""
def GetDatapoints(self, request, context):
"""Request a set of datapoints (values) Returns a list of requested data points. InvalidArgument is returned if the request is malformed."""
<|body_0|>
... | stack_v2_sparse_classes_75kplus_train_071833 | 6,449 | permissive | [
{
"docstring": "Request a set of datapoints (values) Returns a list of requested data points. InvalidArgument is returned if the request is malformed.",
"name": "GetDatapoints",
"signature": "def GetDatapoints(self, request, context)"
},
{
"docstring": "Subscribe to a set of data points or condi... | 3 | stack_v2_sparse_classes_30k_train_006366 | Implement the Python class `BrokerServicer` described below.
Class description:
Missing associated documentation comment in .proto file.
Method signatures and docstrings:
- def GetDatapoints(self, request, context): Request a set of datapoints (values) Returns a list of requested data points. InvalidArgument is retur... | Implement the Python class `BrokerServicer` described below.
Class description:
Missing associated documentation comment in .proto file.
Method signatures and docstrings:
- def GetDatapoints(self, request, context): Request a set of datapoints (values) Returns a list of requested data points. InvalidArgument is retur... | 90b10ec52983a96f7675c9bd8fd9aeac345e882b | <|skeleton|>
class BrokerServicer:
"""Missing associated documentation comment in .proto file."""
def GetDatapoints(self, request, context):
"""Request a set of datapoints (values) Returns a list of requested data points. InvalidArgument is returned if the request is malformed."""
<|body_0|>
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class BrokerServicer:
"""Missing associated documentation comment in .proto file."""
def GetDatapoints(self, request, context):
"""Request a set of datapoints (values) Returns a list of requested data points. InvalidArgument is returned if the request is malformed."""
context.set_code(grpc.Stat... | the_stack_v2_python_sparse | kuksa_databroker/integration_test/gen_proto/sdv/databroker/v1/broker_pb2_grpc.py | eclipse/kuksa.val | train | 74 |
bce9c8b433c7d1742efad2838438560505c55176 | [
"Log.info('Actual value: ' + str(actual))\nLog.info('Expected value: ' + str(expected))\nreturn expected - expected * tolerance <= actual <= expected + expected * tolerance",
"total_time = 0\nfor _ in range(0, retry_count):\n total_time = total_time + operation(*args, **kwargs).duration\nreturn total_time / re... | <|body_start_0|>
Log.info('Actual value: ' + str(actual))
Log.info('Expected value: ' + str(expected))
return expected - expected * tolerance <= actual <= expected + expected * tolerance
<|end_body_0|>
<|body_start_1|>
total_time = 0
for _ in range(0, retry_count):
t... | PerfUtils | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PerfUtils:
def is_value_in_range(actual, expected, tolerance=0.25):
"""Check if value is in range :param actual: Number value. :param expected: Number value. :param tolerance: Tolerance as percent."""
<|body_0|>
def get_average_time(operation, retry_count=3, *args, **kwargs)... | stack_v2_sparse_classes_75kplus_train_071834 | 1,102 | no_license | [
{
"docstring": "Check if value is in range :param actual: Number value. :param expected: Number value. :param tolerance: Tolerance as percent.",
"name": "is_value_in_range",
"signature": "def is_value_in_range(actual, expected, tolerance=0.25)"
},
{
"docstring": "Get average time of Run.command(... | 2 | null | Implement the Python class `PerfUtils` described below.
Class description:
Implement the PerfUtils class.
Method signatures and docstrings:
- def is_value_in_range(actual, expected, tolerance=0.25): Check if value is in range :param actual: Number value. :param expected: Number value. :param tolerance: Tolerance as p... | Implement the Python class `PerfUtils` described below.
Class description:
Implement the PerfUtils class.
Method signatures and docstrings:
- def is_value_in_range(actual, expected, tolerance=0.25): Check if value is in range :param actual: Number value. :param expected: Number value. :param tolerance: Tolerance as p... | 85e9662ab85c68a472b407e890656bcb73a87e70 | <|skeleton|>
class PerfUtils:
def is_value_in_range(actual, expected, tolerance=0.25):
"""Check if value is in range :param actual: Number value. :param expected: Number value. :param tolerance: Tolerance as percent."""
<|body_0|>
def get_average_time(operation, retry_count=3, *args, **kwargs)... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PerfUtils:
def is_value_in_range(actual, expected, tolerance=0.25):
"""Check if value is in range :param actual: Number value. :param expected: Number value. :param tolerance: Tolerance as percent."""
Log.info('Actual value: ' + str(actual))
Log.info('Expected value: ' + str(expected))... | the_stack_v2_python_sparse | core/utils/perf_utils.py | NativeScript/nativescript-tooling-qa | train | 5 | |
4a85a19f015a9cde3d0bd7a1e7009215166250e0 | [
"super(TarProgressFile, self).__init__(path)\nself._steps = set()\nself._total_size = os.path.getsize(path)\nself._logger = logger",
"percent = self.tell() / self._total_size\ntens = int(math.floor(percent * 10)) * 10\nif tens not in self._steps:\n self._steps.add(tens)\n message = 'Overall process: %d of %... | <|body_start_0|>
super(TarProgressFile, self).__init__(path)
self._steps = set()
self._total_size = os.path.getsize(path)
self._logger = logger
<|end_body_0|>
<|body_start_1|>
percent = self.tell() / self._total_size
tens = int(math.floor(percent * 10)) * 10
if t... | An object which is used in TAR callbacks to log extraction progress. This object prints every 10% of the extraction, to avoid being too spammy. | TarProgressFile | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TarProgressFile:
"""An object which is used in TAR callbacks to log extraction progress. This object prints every 10% of the extraction, to avoid being too spammy."""
def __init__(self, path, logger=None):
"""Create the object and store the given logger. Args: path (str): The absolut... | stack_v2_sparse_classes_75kplus_train_071835 | 3,538 | permissive | [
{
"docstring": "Create the object and store the given logger. Args: path (str): The absolute path to the TAR file to extract. logger (`logging.Logger` or NoneType, optional): Some logger to use to print the progress. If no logger is given, the progress messages are printed, instead. Default is None.",
"name... | 2 | stack_v2_sparse_classes_30k_train_000568 | Implement the Python class `TarProgressFile` described below.
Class description:
An object which is used in TAR callbacks to log extraction progress. This object prints every 10% of the extraction, to avoid being too spammy.
Method signatures and docstrings:
- def __init__(self, path, logger=None): Create the object ... | Implement the Python class `TarProgressFile` described below.
Class description:
An object which is used in TAR callbacks to log extraction progress. This object prints every 10% of the extraction, to avoid being too spammy.
Method signatures and docstrings:
- def __init__(self, path, logger=None): Create the object ... | e7efafcd1d7a44ed732e217182388dfa9190f2d0 | <|skeleton|>
class TarProgressFile:
"""An object which is used in TAR callbacks to log extraction progress. This object prints every 10% of the extraction, to avoid being too spammy."""
def __init__(self, path, logger=None):
"""Create the object and store the given logger. Args: path (str): The absolut... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TarProgressFile:
"""An object which is used in TAR callbacks to log extraction progress. This object prints every 10% of the extraction, to avoid being too spammy."""
def __init__(self, path, logger=None):
"""Create the object and store the given logger. Args: path (str): The absolute path to the... | the_stack_v2_python_sparse | utils/progressbar.py | demon7x/rezzurect | train | 0 |
a042af3e690113cc78c03301f42a1775c95ac229 | [
"if mnemonic_type is not None and (not isinstance(mnemonic_type, ElectrumV2MnemonicTypes)):\n raise TypeError('Mnemonic type is not an enumerative of ElectrumV2MnemonicTypes')\nif lang is not None and (not isinstance(lang, ElectrumV2Languages)):\n raise TypeError('Language is not an enumerative of ElectrumV2L... | <|body_start_0|>
if mnemonic_type is not None and (not isinstance(mnemonic_type, ElectrumV2MnemonicTypes)):
raise TypeError('Mnemonic type is not an enumerative of ElectrumV2MnemonicTypes')
if lang is not None and (not isinstance(lang, ElectrumV2Languages)):
raise TypeError('Lang... | Electrum v2 mnemonic decoder class. It decodes a mnemonic phrase to bytes. | ElectrumV2MnemonicDecoder | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ElectrumV2MnemonicDecoder:
"""Electrum v2 mnemonic decoder class. It decodes a mnemonic phrase to bytes."""
def __init__(self, mnemonic_type: Optional[ElectrumV2MnemonicTypes]=None, lang: Optional[ElectrumV2Languages]=None) -> None:
"""Construct class. Args: mnemonic_type (ElectrumV2... | stack_v2_sparse_classes_75kplus_train_071836 | 4,394 | permissive | [
{
"docstring": "Construct class. Args: mnemonic_type (ElectrumV2MnemonicTypes, optional): Mnemonic type, None for all types lang (ElectrumV2Languages, optional) : Language, None for automatic detection Raises: TypeError: If the language is not a ElectrumV2Languages enum ValueError: If loaded words list is not v... | 2 | null | Implement the Python class `ElectrumV2MnemonicDecoder` described below.
Class description:
Electrum v2 mnemonic decoder class. It decodes a mnemonic phrase to bytes.
Method signatures and docstrings:
- def __init__(self, mnemonic_type: Optional[ElectrumV2MnemonicTypes]=None, lang: Optional[ElectrumV2Languages]=None) ... | Implement the Python class `ElectrumV2MnemonicDecoder` described below.
Class description:
Electrum v2 mnemonic decoder class. It decodes a mnemonic phrase to bytes.
Method signatures and docstrings:
- def __init__(self, mnemonic_type: Optional[ElectrumV2MnemonicTypes]=None, lang: Optional[ElectrumV2Languages]=None) ... | d15c75ddd74e4838c396a0d036ef6faf11b06a4b | <|skeleton|>
class ElectrumV2MnemonicDecoder:
"""Electrum v2 mnemonic decoder class. It decodes a mnemonic phrase to bytes."""
def __init__(self, mnemonic_type: Optional[ElectrumV2MnemonicTypes]=None, lang: Optional[ElectrumV2Languages]=None) -> None:
"""Construct class. Args: mnemonic_type (ElectrumV2... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ElectrumV2MnemonicDecoder:
"""Electrum v2 mnemonic decoder class. It decodes a mnemonic phrase to bytes."""
def __init__(self, mnemonic_type: Optional[ElectrumV2MnemonicTypes]=None, lang: Optional[ElectrumV2Languages]=None) -> None:
"""Construct class. Args: mnemonic_type (ElectrumV2MnemonicTypes... | the_stack_v2_python_sparse | bip_utils/electrum/mnemonic_v2/electrum_v2_mnemonic_decoder.py | ebellocchia/bip_utils | train | 244 |
8c11a5fda007282b39b69846cd6acaaec9141609 | [
"self.nmap_services_file = 'nemo/common/utils/nmap-services'\nself.port_service = {}\nself.custom_service_file = 'nemo/common/utils/custom-services.txt'\nself.custom_port_service = {}\nself.__load_services()",
"try:\n with open(self.nmap_services_file) as f:\n for line in f:\n if line.startsw... | <|body_start_0|>
self.nmap_services_file = 'nemo/common/utils/nmap-services'
self.port_service = {}
self.custom_service_file = 'nemo/common/utils/custom-services.txt'
self.custom_port_service = {}
self.__load_services()
<|end_body_0|>
<|body_start_1|>
try:
wi... | 解析端口的Service名称 包括通用定义和自定义 | ParsePortService | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ParsePortService:
"""解析端口的Service名称 包括通用定义和自定义"""
def __init__(self):
"""默认参数"""
<|body_0|>
def __load_services(self):
"""读取映射关系:nmap-services"""
<|body_1|>
def get_service(self, port, port_type='tcp'):
"""根据端口号查找Service名称"""
<|body_2... | stack_v2_sparse_classes_75kplus_train_071837 | 2,419 | no_license | [
{
"docstring": "默认参数",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "读取映射关系:nmap-services",
"name": "__load_services",
"signature": "def __load_services(self)"
},
{
"docstring": "根据端口号查找Service名称",
"name": "get_service",
"signature": "def get_se... | 3 | stack_v2_sparse_classes_30k_train_017647 | Implement the Python class `ParsePortService` described below.
Class description:
解析端口的Service名称 包括通用定义和自定义
Method signatures and docstrings:
- def __init__(self): 默认参数
- def __load_services(self): 读取映射关系:nmap-services
- def get_service(self, port, port_type='tcp'): 根据端口号查找Service名称 | Implement the Python class `ParsePortService` described below.
Class description:
解析端口的Service名称 包括通用定义和自定义
Method signatures and docstrings:
- def __init__(self): 默认参数
- def __load_services(self): 读取映射关系:nmap-services
- def get_service(self, port, port_type='tcp'): 根据端口号查找Service名称
<|skeleton|>
class ParsePortServi... | ac9b63c60a64677d4d070afe069af04be591dfcc | <|skeleton|>
class ParsePortService:
"""解析端口的Service名称 包括通用定义和自定义"""
def __init__(self):
"""默认参数"""
<|body_0|>
def __load_services(self):
"""读取映射关系:nmap-services"""
<|body_1|>
def get_service(self, port, port_type='tcp'):
"""根据端口号查找Service名称"""
<|body_2... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ParsePortService:
"""解析端口的Service名称 包括通用定义和自定义"""
def __init__(self):
"""默认参数"""
self.nmap_services_file = 'nemo/common/utils/nmap-services'
self.port_service = {}
self.custom_service_file = 'nemo/common/utils/custom-services.txt'
self.custom_port_service = {}
... | the_stack_v2_python_sparse | nemo/common/utils/parseservice.py | xiaolushuo/nemo | train | 0 |
190da7317440f3bf7f063bddfff4be87af038d97 | [
"if not node:\n return None\nnode_map = dict()\nqueue = [node]\nin_queue = set([node.val])\nclone_head = None\nwhile queue:\n curr = queue.pop(0)\n val = curr.val\n if val not in node_map:\n node_map[val] = curr_clone = Node(val)\n if clone_head is None:\n clone_head = curr_clon... | <|body_start_0|>
if not node:
return None
node_map = dict()
queue = [node]
in_queue = set([node.val])
clone_head = None
while queue:
curr = queue.pop(0)
val = curr.val
if val not in node_map:
node_map[val] = ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def cloneGraph_v1(self, node: Node) -> Node:
"""Use a queue."""
<|body_0|>
def cloneGraph_v2(self, node: Node) -> Node:
"""Use recurssion."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not node:
return None
node_ma... | stack_v2_sparse_classes_75kplus_train_071838 | 4,045 | no_license | [
{
"docstring": "Use a queue.",
"name": "cloneGraph_v1",
"signature": "def cloneGraph_v1(self, node: Node) -> Node"
},
{
"docstring": "Use recurssion.",
"name": "cloneGraph_v2",
"signature": "def cloneGraph_v2(self, node: Node) -> Node"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def cloneGraph_v1(self, node: Node) -> Node: Use a queue.
- def cloneGraph_v2(self, node: Node) -> Node: Use recurssion. | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def cloneGraph_v1(self, node: Node) -> Node: Use a queue.
- def cloneGraph_v2(self, node: Node) -> Node: Use recurssion.
<|skeleton|>
class Solution:
def cloneGraph_v1(self... | 97a2386f5e3adbd7138fd123810c3232bdf7f622 | <|skeleton|>
class Solution:
def cloneGraph_v1(self, node: Node) -> Node:
"""Use a queue."""
<|body_0|>
def cloneGraph_v2(self, node: Node) -> Node:
"""Use recurssion."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def cloneGraph_v1(self, node: Node) -> Node:
"""Use a queue."""
if not node:
return None
node_map = dict()
queue = [node]
in_queue = set([node.val])
clone_head = None
while queue:
curr = queue.pop(0)
val = cu... | the_stack_v2_python_sparse | python3/trees_and_graphs/clone_undirected_graph.py | victorchu/algorithms | train | 0 | |
8dd83da0fd67b0a131220d441fbafda02da776d7 | [
"super(Encoder, self).__init__()\nself.N = N\nself.dm = dm\nself.embedding = tf.keras.layers.Embedding(input_vocab, dm)\nself.positional_encoding = positional_encoding(max_seq_len, self.dm)\nself.blocks = [EncoderBlock(dm, h, hidden, drop_rate) for _ in range(N)]\nself.dropout = tf.keras.layers.Dropout(drop_rate)",... | <|body_start_0|>
super(Encoder, self).__init__()
self.N = N
self.dm = dm
self.embedding = tf.keras.layers.Embedding(input_vocab, dm)
self.positional_encoding = positional_encoding(max_seq_len, self.dm)
self.blocks = [EncoderBlock(dm, h, hidden, drop_rate) for _ in range(N... | Encoder class for machine translation | Encoder | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Encoder:
"""Encoder class for machine translation"""
def __init__(self, N, dm, h, hidden, input_vocab, max_seq_len, drop_rate=0.1):
"""Class constructor :param N: number of blocks in the encoder :param dm: dimensionality of the model :param h: number of heads :param hidden: number of... | stack_v2_sparse_classes_75kplus_train_071839 | 16,008 | no_license | [
{
"docstring": "Class constructor :param N: number of blocks in the encoder :param dm: dimensionality of the model :param h: number of heads :param hidden: number of hidden units in the fully connected layer :param input_vocab: size of the input vocabulary :param max_seq_len: maximum sequence length possible :p... | 2 | stack_v2_sparse_classes_30k_test_002144 | Implement the Python class `Encoder` described below.
Class description:
Encoder class for machine translation
Method signatures and docstrings:
- def __init__(self, N, dm, h, hidden, input_vocab, max_seq_len, drop_rate=0.1): Class constructor :param N: number of blocks in the encoder :param dm: dimensionality of the... | Implement the Python class `Encoder` described below.
Class description:
Encoder class for machine translation
Method signatures and docstrings:
- def __init__(self, N, dm, h, hidden, input_vocab, max_seq_len, drop_rate=0.1): Class constructor :param N: number of blocks in the encoder :param dm: dimensionality of the... | f83a60babb1d2a510a4a0e0f58aa3880fd9f93a7 | <|skeleton|>
class Encoder:
"""Encoder class for machine translation"""
def __init__(self, N, dm, h, hidden, input_vocab, max_seq_len, drop_rate=0.1):
"""Class constructor :param N: number of blocks in the encoder :param dm: dimensionality of the model :param h: number of heads :param hidden: number of... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Encoder:
"""Encoder class for machine translation"""
def __init__(self, N, dm, h, hidden, input_vocab, max_seq_len, drop_rate=0.1):
"""Class constructor :param N: number of blocks in the encoder :param dm: dimensionality of the model :param h: number of heads :param hidden: number of hidden units... | the_stack_v2_python_sparse | supervised_learning/0x12-transformer_apps/5-transformer.py | jalondono/holbertonschool-machine_learning | train | 2 |
aa0cc171ae3fe4d89fde92d096dd4a5ac3a3be91 | [
"kwargs.setdefault('is_staff', True)\nkwargs.setdefault('is_superuser', True)\nkwargs.setdefault('is_active', True)\nif kwargs.get('is_staff') is not True:\n raise ValueError('Superuser must be assigned to is_staff=True')\nif kwargs.get('is_superuser') is not True:\n raise ValueError('Superuser must be assign... | <|body_start_0|>
kwargs.setdefault('is_staff', True)
kwargs.setdefault('is_superuser', True)
kwargs.setdefault('is_active', True)
if kwargs.get('is_staff') is not True:
raise ValueError('Superuser must be assigned to is_staff=True')
if kwargs.get('is_superuser') is no... | AccountManager | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AccountManager:
def create_superuser(self, email, username, password, **kwargs):
"""Create superuser Creates a new superuser. Will default `is_staff`, `is_superuser` and `is_active` Args: email (str): The email of the new user username (str): The username of the new user password (str): ... | stack_v2_sparse_classes_75kplus_train_071840 | 2,438 | no_license | [
{
"docstring": "Create superuser Creates a new superuser. Will default `is_staff`, `is_superuser` and `is_active` Args: email (str): The email of the new user username (str): The username of the new user password (str): The password of the new user Optional Args: is_staff (bool): Flag to indicate if the unew us... | 2 | null | Implement the Python class `AccountManager` described below.
Class description:
Implement the AccountManager class.
Method signatures and docstrings:
- def create_superuser(self, email, username, password, **kwargs): Create superuser Creates a new superuser. Will default `is_staff`, `is_superuser` and `is_active` Arg... | Implement the Python class `AccountManager` described below.
Class description:
Implement the AccountManager class.
Method signatures and docstrings:
- def create_superuser(self, email, username, password, **kwargs): Create superuser Creates a new superuser. Will default `is_staff`, `is_superuser` and `is_active` Arg... | 3fa600d67c82559694612a0634590a205b1790eb | <|skeleton|>
class AccountManager:
def create_superuser(self, email, username, password, **kwargs):
"""Create superuser Creates a new superuser. Will default `is_staff`, `is_superuser` and `is_active` Args: email (str): The email of the new user username (str): The username of the new user password (str): ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AccountManager:
def create_superuser(self, email, username, password, **kwargs):
"""Create superuser Creates a new superuser. Will default `is_staff`, `is_superuser` and `is_active` Args: email (str): The email of the new user username (str): The username of the new user password (str): The password o... | the_stack_v2_python_sparse | backend/accounts/manager.py | aaronsnig501/drams | train | 0 | |
5baba72b0b871f1940e2a59e77a40b993d2eaa55 | [
"super(Pendulum, self).__init__()\nself._mass = mass\nself._length = length\nself._friction = friction\nself._g = gravity",
"x1 = state[..., 0:1]\nx2 = state[..., 1:2]\nif p is None:\n mass = self._mass\n length = self._length\n friction = self._friction\nelse:\n assert len(p) == 3\n mass = p[0]\n ... | <|body_start_0|>
super(Pendulum, self).__init__()
self._mass = mass
self._length = length
self._friction = friction
self._g = gravity
<|end_body_0|>
<|body_start_1|>
x1 = state[..., 0:1]
x2 = state[..., 1:2]
if p is None:
mass = self._mass
... | Ground dynamics for a pendulum with friction. The state is two dimensional and represents angular position and velocity. | Pendulum | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Pendulum:
"""Ground dynamics for a pendulum with friction. The state is two dimensional and represents angular position and velocity."""
def __init__(self, mass: float=1.0, length: float=1.0, friction: float=0.1, gravity: float=9.80665) -> None:
"""Initialize a pendulum system. Param... | stack_v2_sparse_classes_75kplus_train_071841 | 9,729 | permissive | [
{
"docstring": "Initialize a pendulum system. Parameters ---------- mass : float, default=1.0 The mass of the pendulum. length : float, default=1.0 The length of the pendulum. friction : float, default=0.1 The friction coefficient. gravity : float, default=9.80665 Gravity.",
"name": "__init__",
"signatu... | 3 | stack_v2_sparse_classes_30k_train_016150 | Implement the Python class `Pendulum` described below.
Class description:
Ground dynamics for a pendulum with friction. The state is two dimensional and represents angular position and velocity.
Method signatures and docstrings:
- def __init__(self, mass: float=1.0, length: float=1.0, friction: float=0.1, gravity: fl... | Implement the Python class `Pendulum` described below.
Class description:
Ground dynamics for a pendulum with friction. The state is two dimensional and represents angular position and velocity.
Method signatures and docstrings:
- def __init__(self, mass: float=1.0, length: float=1.0, friction: float=0.1, gravity: fl... | 184b1537c22ebc2f614677be8fe171de785bda42 | <|skeleton|>
class Pendulum:
"""Ground dynamics for a pendulum with friction. The state is two dimensional and represents angular position and velocity."""
def __init__(self, mass: float=1.0, length: float=1.0, friction: float=0.1, gravity: float=9.80665) -> None:
"""Initialize a pendulum system. Param... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Pendulum:
"""Ground dynamics for a pendulum with friction. The state is two dimensional and represents angular position and velocity."""
def __init__(self, mass: float=1.0, length: float=1.0, friction: float=0.1, gravity: float=9.80665) -> None:
"""Initialize a pendulum system. Parameters -------... | the_stack_v2_python_sparse | dynamics_learning/networks/dynamics.py | cristovaoiglesias/replay-overshooting | train | 0 |
ed846e615602f0e5c4f9087e6f59dae5e34e1d30 | [
"self.file_name = file_name\nself.file_handler = None\nreturn",
"print('enter:', self.file_name)\nself.file_handler = open(self.file_name, 'r')\nreturn self.file_handler",
"print('exit:', exc_type, exc_val, exc_tb)\nif self.file_handler:\n self.file_handler.close()\nreturn False"
] | <|body_start_0|>
self.file_name = file_name
self.file_handler = None
return
<|end_body_0|>
<|body_start_1|>
print('enter:', self.file_name)
self.file_handler = open(self.file_name, 'r')
return self.file_handler
<|end_body_1|>
<|body_start_2|>
print('exit:', exc_... | MyOpen | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MyOpen:
def __init__(self, file_name):
"""初始化方法"""
<|body_0|>
def __enter__(self):
"""enter方法，返回file_handler"""
<|body_1|>
def __exit__(self, exc_type, exc_val, exc_tb):
"""exit方法，关闭文件并返回True"""
<|body_2|>
<|end_skeleton|>
<|body_start_... | stack_v2_sparse_classes_75kplus_train_071842 | 910 | no_license | [
{
"docstring": "初始化方法",
"name": "__init__",
"signature": "def __init__(self, file_name)"
},
{
"docstring": "enter方法，返回file_handler",
"name": "__enter__",
"signature": "def __enter__(self)"
},
{
"docstring": "exit方法，关闭文件并返回True",
"name": "__exit__",
"signature": "def __exi... | 3 | stack_v2_sparse_classes_30k_train_006094 | Implement the Python class `MyOpen` described below.
Class description:
Implement the MyOpen class.
Method signatures and docstrings:
- def __init__(self, file_name): 初始化方法
- def __enter__(self): enter方法，返回file_handler
- def __exit__(self, exc_type, exc_val, exc_tb): exit方法，关闭文件并返回True | Implement the Python class `MyOpen` described below.
Class description:
Implement the MyOpen class.
Method signatures and docstrings:
- def __init__(self, file_name): 初始化方法
- def __enter__(self): enter方法，返回file_handler
- def __exit__(self, exc_type, exc_val, exc_tb): exit方法，关闭文件并返回True
<|skeleton|>
class MyOpen:
... | a0202c81372758922128dc6e4c8911849f2663ad | <|skeleton|>
class MyOpen:
def __init__(self, file_name):
"""初始化方法"""
<|body_0|>
def __enter__(self):
"""enter方法，返回file_handler"""
<|body_1|>
def __exit__(self, exc_type, exc_val, exc_tb):
"""exit方法，关闭文件并返回True"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MyOpen:
def __init__(self, file_name):
"""初始化方法"""
self.file_name = file_name
self.file_handler = None
return
def __enter__(self):
"""enter方法，返回file_handler"""
print('enter:', self.file_name)
self.file_handler = open(self.file_name, 'r')
ret... | the_stack_v2_python_sparse | 核心编程_2/chapter_10_error/10.4_context_management/10.4.2_context_management_protocol/My_with.py | MonsterDragon/play_python | train | 1 | |
f0364dc0b2b690913cdd4e02c100e26e3b54cb4f | [
"super().__init__(env)\nself.num_envs = getattr(env, 'num_envs', 1)\nself.t0 = time.perf_counter()\nself.episode_count = 0\nself.episode_returns: Optional[np.ndarray] = None\nself.episode_lengths: Optional[np.ndarray] = None\nself.return_queue = deque(maxlen=deque_size)\nself.length_queue = deque(maxlen=deque_size)... | <|body_start_0|>
super().__init__(env)
self.num_envs = getattr(env, 'num_envs', 1)
self.t0 = time.perf_counter()
self.episode_count = 0
self.episode_returns: Optional[np.ndarray] = None
self.episode_lengths: Optional[np.ndarray] = None
self.return_queue = deque(ma... | This wrapper will keep track of cumulative rewards and episode lengths. At the end of an episode, the statistics of the episode will be added to ``info`` using the key ``episode``. If using a vectorized environment also the key ``_episode`` is used which indicates whether the env at the respective index has the episode... | RecordEpisodeStatistics | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RecordEpisodeStatistics:
"""This wrapper will keep track of cumulative rewards and episode lengths. At the end of an episode, the statistics of the episode will be added to ``info`` using the key ``episode``. If using a vectorized environment also the key ``_episode`` is used which indicates whet... | stack_v2_sparse_classes_75kplus_train_071843 | 5,650 | permissive | [
{
"docstring": "This wrapper will keep track of cumulative rewards and episode lengths. Args: env (Env): The environment to apply the wrapper deque_size: The size of the buffers :attr:`return_queue` and :attr:`length_queue`",
"name": "__init__",
"signature": "def __init__(self, env: gym.Env, deque_size:... | 3 | stack_v2_sparse_classes_30k_train_054325 | Implement the Python class `RecordEpisodeStatistics` described below.
Class description:
This wrapper will keep track of cumulative rewards and episode lengths. At the end of an episode, the statistics of the episode will be added to ``info`` using the key ``episode``. If using a vectorized environment also the key ``... | Implement the Python class `RecordEpisodeStatistics` described below.
Class description:
This wrapper will keep track of cumulative rewards and episode lengths. At the end of an episode, the statistics of the episode will be added to ``info`` using the key ``episode``. If using a vectorized environment also the key ``... | 53d784eafed28d31ec41c36ebd9eee14b0dc6d41 | <|skeleton|>
class RecordEpisodeStatistics:
"""This wrapper will keep track of cumulative rewards and episode lengths. At the end of an episode, the statistics of the episode will be added to ``info`` using the key ``episode``. If using a vectorized environment also the key ``_episode`` is used which indicates whet... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class RecordEpisodeStatistics:
"""This wrapper will keep track of cumulative rewards and episode lengths. At the end of an episode, the statistics of the episode will be added to ``info`` using the key ``episode``. If using a vectorized environment also the key ``_episode`` is used which indicates whether the env a... | the_stack_v2_python_sparse | gym/wrappers/record_episode_statistics.py | thomascherickal/gym | train | 2 |
4ab317c298f1eea37897b20be341e5d8a27b3110 | [
"if data is None:\n n = int(n)\n p = float(p)\n if n <= 0:\n raise ValueError('n must be a positive value')\n if p <= 0 or p >= 1:\n raise ValueError('p must be greater than 0 and less than 1')\n self.p = p\n self.n = n\nelse:\n if type(data) is not list:\n raise TypeError(... | <|body_start_0|>
if data is None:
n = int(n)
p = float(p)
if n <= 0:
raise ValueError('n must be a positive value')
if p <= 0 or p >= 1:
raise ValueError('p must be greater than 0 and less than 1')
self.p = p
... | class Binomial | Binomial | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Binomial:
"""class Binomial"""
def __init__(self, data=None, n=1, p=0.5):
"""constructor"""
<|body_0|>
def pmf(self, k):
"""Probability Mass Function PMF"""
<|body_1|>
def cdf(self, k):
"""Cumulative Distribution Function CDF"""
<|bod... | stack_v2_sparse_classes_75kplus_train_071844 | 1,891 | no_license | [
{
"docstring": "constructor",
"name": "__init__",
"signature": "def __init__(self, data=None, n=1, p=0.5)"
},
{
"docstring": "Probability Mass Function PMF",
"name": "pmf",
"signature": "def pmf(self, k)"
},
{
"docstring": "Cumulative Distribution Function CDF",
"name": "cdf"... | 3 | stack_v2_sparse_classes_30k_train_014125 | Implement the Python class `Binomial` described below.
Class description:
class Binomial
Method signatures and docstrings:
- def __init__(self, data=None, n=1, p=0.5): constructor
- def pmf(self, k): Probability Mass Function PMF
- def cdf(self, k): Cumulative Distribution Function CDF | Implement the Python class `Binomial` described below.
Class description:
class Binomial
Method signatures and docstrings:
- def __init__(self, data=None, n=1, p=0.5): constructor
- def pmf(self, k): Probability Mass Function PMF
- def cdf(self, k): Cumulative Distribution Function CDF
<|skeleton|>
class Binomial:
... | 8ad4c2594ff78b345dbd92e9d54d2a143ac4071a | <|skeleton|>
class Binomial:
"""class Binomial"""
def __init__(self, data=None, n=1, p=0.5):
"""constructor"""
<|body_0|>
def pmf(self, k):
"""Probability Mass Function PMF"""
<|body_1|>
def cdf(self, k):
"""Cumulative Distribution Function CDF"""
<|bod... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Binomial:
"""class Binomial"""
def __init__(self, data=None, n=1, p=0.5):
"""constructor"""
if data is None:
n = int(n)
p = float(p)
if n <= 0:
raise ValueError('n must be a positive value')
if p <= 0 or p >= 1:
... | the_stack_v2_python_sparse | math/0x03-probability/graphs/binomial.py | jorgezafra94/holbertonschool-machine_learning | train | 1 |
98f16f954ead872ae1f5f0ddad6fc6eba9818c7e | [
"def inorder(r: TreeNode) -> List[int]:\n return inorder(r.left) + [r.val] + inorder(r.right) if r else []\nreturn inorder(root)[k - 1]",
"stack = []\nwhile True:\n while root:\n stack.append(root)\n root = root.left\n root = stack.pop()\n k -= 1\n if not k:\n return root.val\n... | <|body_start_0|>
def inorder(r: TreeNode) -> List[int]:
return inorder(r.left) + [r.val] + inorder(r.right) if r else []
return inorder(root)[k - 1]
<|end_body_0|>
<|body_start_1|>
stack = []
while True:
while root:
stack.append(root)
... | OfficialSolution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OfficialSolution:
def ktn_smallest(self, root: TreeNode, k: int) -> int:
"""递归（中序遍历）。"""
<|body_0|>
def ktn_smallest_2(self, root: TreeNode, k: int) -> int:
"""root 是二叉搜索树， 使用迭代来中序遍历树，不用像递归那样遍历整棵树，可以在找到答案后停止。"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_75kplus_train_071845 | 4,935 | no_license | [
{
"docstring": "递归（中序遍历）。",
"name": "ktn_smallest",
"signature": "def ktn_smallest(self, root: TreeNode, k: int) -> int"
},
{
"docstring": "root 是二叉搜索树， 使用迭代来中序遍历树，不用像递归那样遍历整棵树，可以在找到答案后停止。",
"name": "ktn_smallest_2",
"signature": "def ktn_smallest_2(self, root: TreeNode, k: int) -> int"
... | 2 | stack_v2_sparse_classes_30k_train_044293 | Implement the Python class `OfficialSolution` described below.
Class description:
Implement the OfficialSolution class.
Method signatures and docstrings:
- def ktn_smallest(self, root: TreeNode, k: int) -> int: 递归（中序遍历）。
- def ktn_smallest_2(self, root: TreeNode, k: int) -> int: root 是二叉搜索树， 使用迭代来中序遍历树，不用像递归那样遍历整棵树，可... | Implement the Python class `OfficialSolution` described below.
Class description:
Implement the OfficialSolution class.
Method signatures and docstrings:
- def ktn_smallest(self, root: TreeNode, k: int) -> int: 递归（中序遍历）。
- def ktn_smallest_2(self, root: TreeNode, k: int) -> int: root 是二叉搜索树， 使用迭代来中序遍历树，不用像递归那样遍历整棵树，可... | 6932d69353b94ec824dd0ddc86a92453f6673232 | <|skeleton|>
class OfficialSolution:
def ktn_smallest(self, root: TreeNode, k: int) -> int:
"""递归（中序遍历）。"""
<|body_0|>
def ktn_smallest_2(self, root: TreeNode, k: int) -> int:
"""root 是二叉搜索树， 使用迭代来中序遍历树，不用像递归那样遍历整棵树，可以在找到答案后停止。"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class OfficialSolution:
def ktn_smallest(self, root: TreeNode, k: int) -> int:
"""递归（中序遍历）。"""
def inorder(r: TreeNode) -> List[int]:
return inorder(r.left) + [r.val] + inorder(r.right) if r else []
return inorder(root)[k - 1]
def ktn_smallest_2(self, root: TreeNode, k: int)... | the_stack_v2_python_sparse | 0230_kth-smallest-element-in-a-bst.py | Nigirimeshi/leetcode | train | 0 | |
de15db075e6f7a57a3b944d75654fd4d9c333642 | [
"self.metrics = format_metrics(metrics)\nself.do_score = do_score\nself.__in_fold = in_fold if in_fold else []\nself.__oof = oof if oof else []\nself.__holdout = holdout if holdout else []\nself._validate_metrics_list_parameters()\nself.last_evaluation_results = dict(in_fold=None, oof=None, holdout=None)",
"for _... | <|body_start_0|>
self.metrics = format_metrics(metrics)
self.do_score = do_score
self.__in_fold = in_fold if in_fold else []
self.__oof = oof if oof else []
self.__holdout = holdout if holdout else []
self._validate_metrics_list_parameters()
self.last_evaluation_r... | ScoringMixIn | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ScoringMixIn:
def __init__(self, metrics, in_fold='all', oof='all', holdout='all', do_score=True):
"""MixIn class to manage metrics to record for each dataset type, and perform evaluations Parameters ---------- metrics: Dict, List Specifies all metrics to be used by their id keys, along ... | stack_v2_sparse_classes_75kplus_train_071846 | 23,341 | permissive | [
{
"docstring": "MixIn class to manage metrics to record for each dataset type, and perform evaluations Parameters ---------- metrics: Dict, List Specifies all metrics to be used by their id keys, along with a means to compute the metric. If list, all values must be strings that are attributes in :mod:`sklearn.m... | 3 | null | Implement the Python class `ScoringMixIn` described below.
Class description:
Implement the ScoringMixIn class.
Method signatures and docstrings:
- def __init__(self, metrics, in_fold='all', oof='all', holdout='all', do_score=True): MixIn class to manage metrics to record for each dataset type, and perform evaluation... | Implement the Python class `ScoringMixIn` described below.
Class description:
Implement the ScoringMixIn class.
Method signatures and docstrings:
- def __init__(self, metrics, in_fold='all', oof='all', holdout='all', do_score=True): MixIn class to manage metrics to record for each dataset type, and perform evaluation... | bfbd1faf63272a62e6f971d7e9a0487d71aea8f6 | <|skeleton|>
class ScoringMixIn:
def __init__(self, metrics, in_fold='all', oof='all', holdout='all', do_score=True):
"""MixIn class to manage metrics to record for each dataset type, and perform evaluations Parameters ---------- metrics: Dict, List Specifies all metrics to be used by their id keys, along ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ScoringMixIn:
def __init__(self, metrics, in_fold='all', oof='all', holdout='all', do_score=True):
"""MixIn class to manage metrics to record for each dataset type, and perform evaluations Parameters ---------- metrics: Dict, List Specifies all metrics to be used by their id keys, along with a means t... | the_stack_v2_python_sparse | hyperparameter_hunter/metrics.py | mdjabc/hyperparameter_hunter | train | 1 | |
778fb8755ea8a1899219b17128acb489e8095a1d | [
"self.expdf = assign_rxn_types(selected_df.copy())\nself.expdf = add_interpreted_columns(self.expdf)\nif alldf is not None:\n self.alldf = assign_rxn_types(alldf.copy())\n self.alldf = add_interpreted_columns(self.alldf)\nif expname is not None:\n self.expname = expname\nelse:\n self.expname = str(self.... | <|body_start_0|>
self.expdf = assign_rxn_types(selected_df.copy())
self.expdf = add_interpreted_columns(self.expdf)
if alldf is not None:
self.alldf = assign_rxn_types(alldf.copy())
self.alldf = add_interpreted_columns(self.alldf)
if expname is not None:
... | CAZyExperiment2 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CAZyExperiment2:
def __init__(self, selected_df, alldf=None, expname=None):
"""Takes a tecan dataframe, makes a copy and adds fields needed for activity calculations (inc baseline subtractions) Arguments: selected_df: the dataframe Kewyord arguments: alldf: the dataframe with all activit... | stack_v2_sparse_classes_75kplus_train_071847 | 17,357 | no_license | [
{
"docstring": "Takes a tecan dataframe, makes a copy and adds fields needed for activity calculations (inc baseline subtractions) Arguments: selected_df: the dataframe Kewyord arguments: alldf: the dataframe with all activities (default None) expname: name for this experiment (otherwise use date)- default None... | 2 | stack_v2_sparse_classes_30k_test_002099 | Implement the Python class `CAZyExperiment2` described below.
Class description:
Implement the CAZyExperiment2 class.
Method signatures and docstrings:
- def __init__(self, selected_df, alldf=None, expname=None): Takes a tecan dataframe, makes a copy and adds fields needed for activity calculations (inc baseline subt... | Implement the Python class `CAZyExperiment2` described below.
Class description:
Implement the CAZyExperiment2 class.
Method signatures and docstrings:
- def __init__(self, selected_df, alldf=None, expname=None): Takes a tecan dataframe, makes a copy and adds fields needed for activity calculations (inc baseline subt... | 458822d7f5221e04387bd53d6539d290b7e1630a | <|skeleton|>
class CAZyExperiment2:
def __init__(self, selected_df, alldf=None, expname=None):
"""Takes a tecan dataframe, makes a copy and adds fields needed for activity calculations (inc baseline subtractions) Arguments: selected_df: the dataframe Kewyord arguments: alldf: the dataframe with all activit... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CAZyExperiment2:
def __init__(self, selected_df, alldf=None, expname=None):
"""Takes a tecan dataframe, makes a copy and adds fields needed for activity calculations (inc baseline subtractions) Arguments: selected_df: the dataframe Kewyord arguments: alldf: the dataframe with all activities (default N... | the_stack_v2_python_sparse | tecanpack/tecandata.py | KirkVM/kdatapack | train | 0 | |
eedf072f38a5bd0cf24c5bde2febdee1785981fa | [
"self._disable_patching = True\nself._validate_base(self)\nself._disable_patching = False",
"self._validate()\nresult = method(*args, **kwargs)\nself._validate()\nreturn result",
"attr = super().__getattribute__(name)\nif name in ('_patched_method', '_validate', '_validate_base', '_disable_patching'):\n retu... | <|body_start_0|>
self._disable_patching = True
self._validate_base(self)
self._disable_patching = False
<|end_body_0|>
<|body_start_1|>
self._validate()
result = method(*args, **kwargs)
self._validate()
return result
<|end_body_1|>
<|body_start_2|>
attr ... | InvariantedClass | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InvariantedClass:
def _validate(self) -> None:
"""Step 5 (1st flow) or Step 4 (2nd flow). Process contract for object."""
<|body_0|>
def _patched_method(self, method: Callable, *args, **kwargs):
"""Step 4 (1st flow). Call method"""
<|body_1|>
def __getat... | stack_v2_sparse_classes_75kplus_train_071848 | 3,490 | permissive | [
{
"docstring": "Step 5 (1st flow) or Step 4 (2nd flow). Process contract for object.",
"name": "_validate",
"signature": "def _validate(self) -> None"
},
{
"docstring": "Step 4 (1st flow). Call method",
"name": "_patched_method",
"signature": "def _patched_method(self, method: Callable, ... | 4 | stack_v2_sparse_classes_30k_train_028257 | Implement the Python class `InvariantedClass` described below.
Class description:
Implement the InvariantedClass class.
Method signatures and docstrings:
- def _validate(self) -> None: Step 5 (1st flow) or Step 4 (2nd flow). Process contract for object.
- def _patched_method(self, method: Callable, *args, **kwargs): ... | Implement the Python class `InvariantedClass` described below.
Class description:
Implement the InvariantedClass class.
Method signatures and docstrings:
- def _validate(self) -> None: Step 5 (1st flow) or Step 4 (2nd flow). Process contract for object.
- def _patched_method(self, method: Callable, *args, **kwargs): ... | 9dff86e1dc5c8607f02ded34b6d64e770f1959fa | <|skeleton|>
class InvariantedClass:
def _validate(self) -> None:
"""Step 5 (1st flow) or Step 4 (2nd flow). Process contract for object."""
<|body_0|>
def _patched_method(self, method: Callable, *args, **kwargs):
"""Step 4 (1st flow). Call method"""
<|body_1|>
def __getat... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class InvariantedClass:
def _validate(self) -> None:
"""Step 5 (1st flow) or Step 4 (2nd flow). Process contract for object."""
self._disable_patching = True
self._validate_base(self)
self._disable_patching = False
def _patched_method(self, method: Callable, *args, **kwargs):
... | the_stack_v2_python_sparse | deal/_decorators/inv.py | toonarmycaptain/deal | train | 0 | |
dd6fb69a0c1d23d068dec2e74c66a484ccbfbd8f | [
"super(FilterSpinAgent, self).__init__(parent, datatree)\nself.addRequest('spinfield')\nself.requestUpdatedSignal.connect(self.buildSpin)\nself.spin_values = list()\nself.spin_field = ''\nself.spin_selected = -1",
"if len(indexList) > 1:\n indexList = list(indexList[0])\nself.requestAddIndices('spinfield', ind... | <|body_start_0|>
super(FilterSpinAgent, self).__init__(parent, datatree)
self.addRequest('spinfield')
self.requestUpdatedSignal.connect(self.buildSpin)
self.spin_values = list()
self.spin_field = ''
self.spin_selected = -1
<|end_body_0|>
<|body_start_1|>
if len(i... | Agent for all FilterSpin modules, associates filters with modules. The Filter Spin takes a single numeric field and adds a filter setting all data under it to whatever a specific value in that field is. The idea is that using a spin control, the user can move through all the values of the field separately. For example,... | FilterSpinAgent | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FilterSpinAgent:
"""Agent for all FilterSpin modules, associates filters with modules. The Filter Spin takes a single numeric field and adds a filter setting all data under it to whatever a specific value in that field is. The idea is that using a spin control, the user can move through all the v... | stack_v2_sparse_classes_75kplus_train_071849 | 6,795 | no_license | [
{
"docstring": "Constructor for FilterSpinAgent.",
"name": "__init__",
"signature": "def __init__(self, parent, datatree)"
},
{
"docstring": "This function handles an added list of DataTree indices by associated them with the agent's Request. We only accept a single index in the Filter Spin so w... | 4 | stack_v2_sparse_classes_30k_train_051497 | Implement the Python class `FilterSpinAgent` described below.
Class description:
Agent for all FilterSpin modules, associates filters with modules. The Filter Spin takes a single numeric field and adds a filter setting all data under it to whatever a specific value in that field is. The idea is that using a spin contr... | Implement the Python class `FilterSpinAgent` described below.
Class description:
Agent for all FilterSpin modules, associates filters with modules. The Filter Spin takes a single numeric field and adds a filter setting all data under it to whatever a specific value in that field is. The idea is that using a spin contr... | afa9c9547716909d806a0bd8165bfe896617ca7e | <|skeleton|>
class FilterSpinAgent:
"""Agent for all FilterSpin modules, associates filters with modules. The Filter Spin takes a single numeric field and adds a filter setting all data under it to whatever a specific value in that field is. The idea is that using a spin control, the user can move through all the v... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class FilterSpinAgent:
"""Agent for all FilterSpin modules, associates filters with modules. The Filter Spin takes a single numeric field and adds a filter setting all data under it to whatever a specific value in that field is. The idea is that using a spin control, the user can move through all the values of the ... | the_stack_v2_python_sparse | boxfish/FilterSpin.py | LLNL/boxfish | train | 4 |
4d3951c9086673f5c536c16ea668685ce67ed6b1 | [
"try:\n _file = os.path.join(TRANSFORMED_DATA_DIR, file_name)\n if mode == 'a':\n if not os.path.isfile(_file):\n data.to_csv(_file, mode='a', index=False)\n else:\n data.to_csv(_file, mode='a', header=False, index=False)\n elif mode == 'w':\n data.to_csv(_file, m... | <|body_start_0|>
try:
_file = os.path.join(TRANSFORMED_DATA_DIR, file_name)
if mode == 'a':
if not os.path.isfile(_file):
data.to_csv(_file, mode='a', index=False)
else:
data.to_csv(_file, mode='a', header=False, ind... | This class contains methods to Extract data from pre-decided sources and Transform them according to the project needs. Then writes the data sources to a predefined location as stated in TRANSFORMED_DATA_DIR. | ExtractTransform | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ExtractTransform:
"""This class contains methods to Extract data from pre-decided sources and Transform them according to the project needs. Then writes the data sources to a predefined location as stated in TRANSFORMED_DATA_DIR."""
def _perform_write(self, data, file_name, mode='w'):
... | stack_v2_sparse_classes_75kplus_train_071850 | 2,911 | permissive | [
{
"docstring": "Writes the data to disk",
"name": "_perform_write",
"signature": "def _perform_write(self, data, file_name, mode='w')"
},
{
"docstring": "Fetches data from each of the sources serially.",
"name": "pipeline",
"signature": "def pipeline(self, mode='w')"
}
] | 2 | stack_v2_sparse_classes_30k_train_015826 | Implement the Python class `ExtractTransform` described below.
Class description:
This class contains methods to Extract data from pre-decided sources and Transform them according to the project needs. Then writes the data sources to a predefined location as stated in TRANSFORMED_DATA_DIR.
Method signatures and docst... | Implement the Python class `ExtractTransform` described below.
Class description:
This class contains methods to Extract data from pre-decided sources and Transform them according to the project needs. Then writes the data sources to a predefined location as stated in TRANSFORMED_DATA_DIR.
Method signatures and docst... | 8f33a8b0194eb77e3018f16c153291bd451fb072 | <|skeleton|>
class ExtractTransform:
"""This class contains methods to Extract data from pre-decided sources and Transform them according to the project needs. Then writes the data sources to a predefined location as stated in TRANSFORMED_DATA_DIR."""
def _perform_write(self, data, file_name, mode='w'):
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ExtractTransform:
"""This class contains methods to Extract data from pre-decided sources and Transform them according to the project needs. Then writes the data sources to a predefined location as stated in TRANSFORMED_DATA_DIR."""
def _perform_write(self, data, file_name, mode='w'):
"""Writes t... | the_stack_v2_python_sparse | src/etl/extract_transform.py | gunnerVivek/Abusive-language-detection-in-Online-content | train | 0 |
706ef83f8504f257c5a7d287bf342f597038bd88 | [
"cpacs_path = mif.get_toolinput_file_path('SMUse')\ntixi = cpsf.open_tixi(cpacs_path)\nself.Model = smu.load_surrogate(tixi)\ncpsf.close_tixi(tixi, cpacs_path)\ndf = self.Model.df\ndf.set_index('Name', inplace=True)\nfor name in df.index:\n if df.loc[name, 'type'] == 'obj':\n self.add_output(name)\n el... | <|body_start_0|>
cpacs_path = mif.get_toolinput_file_path('SMUse')
tixi = cpsf.open_tixi(cpacs_path)
self.Model = smu.load_surrogate(tixi)
cpsf.close_tixi(tixi, cpacs_path)
df = self.Model.df
df.set_index('Name', inplace=True)
for name in df.index:
if ... | Uses a surrogate model to make a prediction | SmComp | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SmComp:
"""Uses a surrogate model to make a prediction"""
def setup(self):
"""Setup inputs and outputs"""
<|body_0|>
def compute(self, inputs, outputs):
"""Make a prediction"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
cpacs_path = mif.get_to... | stack_v2_sparse_classes_75kplus_train_071851 | 21,151 | permissive | [
{
"docstring": "Setup inputs and outputs",
"name": "setup",
"signature": "def setup(self)"
},
{
"docstring": "Make a prediction",
"name": "compute",
"signature": "def compute(self, inputs, outputs)"
}
] | 2 | stack_v2_sparse_classes_30k_train_024581 | Implement the Python class `SmComp` described below.
Class description:
Uses a surrogate model to make a prediction
Method signatures and docstrings:
- def setup(self): Setup inputs and outputs
- def compute(self, inputs, outputs): Make a prediction | Implement the Python class `SmComp` described below.
Class description:
Uses a surrogate model to make a prediction
Method signatures and docstrings:
- def setup(self): Setup inputs and outputs
- def compute(self, inputs, outputs): Make a prediction
<|skeleton|>
class SmComp:
"""Uses a surrogate model to make a ... | 3cc211507caab176a76213e442238abfa43afa42 | <|skeleton|>
class SmComp:
"""Uses a surrogate model to make a prediction"""
def setup(self):
"""Setup inputs and outputs"""
<|body_0|>
def compute(self, inputs, outputs):
"""Make a prediction"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SmComp:
"""Uses a surrogate model to make a prediction"""
def setup(self):
"""Setup inputs and outputs"""
cpacs_path = mif.get_toolinput_file_path('SMUse')
tixi = cpsf.open_tixi(cpacs_path)
self.Model = smu.load_surrogate(tixi)
cpsf.close_tixi(tixi, cpacs_path)
... | the_stack_v2_python_sparse | ceasiompy/Optimisation/optimisation.py | schneo/CEASIOMpy | train | 0 |
3edee89c120048c8326d2ad98a278301d369d2e9 | [
"assert isinstance(node, Node)\nmethod = 'visit_' + node.__class__.__name__\nvisitor = getattr(self, method, self.generic_visit)\nreturn visitor(node)",
"assert isinstance(node, Node)\nfor child in node.children():\n self.visit(child)"
] | <|body_start_0|>
assert isinstance(node, Node)
method = 'visit_' + node.__class__.__name__
visitor = getattr(self, method, self.generic_visit)
return visitor(node)
<|end_body_0|>
<|body_start_1|>
assert isinstance(node, Node)
for child in node.children():
sel... | A node visitor base class that walks the abstract syntax tree and calls a visitor function for every node found. This function may return a value which is forwarded by the `visit` method. This class is meant to be subclassed, with the subclass adding visitor methods. Per default the visitor functions for the nodes are ... | NodeVisitor | [
"BSD-2-Clause-Views"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NodeVisitor:
"""A node visitor base class that walks the abstract syntax tree and calls a visitor function for every node found. This function may return a value which is forwarded by the `visit` method. This class is meant to be subclassed, with the subclass adding visitor methods. Per default t... | stack_v2_sparse_classes_75kplus_train_071852 | 1,431 | permissive | [
{
"docstring": "Visit a node.",
"name": "visit",
"signature": "def visit(self, node)"
},
{
"docstring": "Called if no explicit visitor function exists for a node. Implements preorder visiting of the node.",
"name": "generic_visit",
"signature": "def generic_visit(self, node)"
}
] | 2 | stack_v2_sparse_classes_30k_train_025679 | Implement the Python class `NodeVisitor` described below.
Class description:
A node visitor base class that walks the abstract syntax tree and calls a visitor function for every node found. This function may return a value which is forwarded by the `visit` method. This class is meant to be subclassed, with the subclas... | Implement the Python class `NodeVisitor` described below.
Class description:
A node visitor base class that walks the abstract syntax tree and calls a visitor function for every node found. This function may return a value which is forwarded by the `visit` method. This class is meant to be subclassed, with the subclas... | 230fc9df874d20739bb98273dc45e45519f0402c | <|skeleton|>
class NodeVisitor:
"""A node visitor base class that walks the abstract syntax tree and calls a visitor function for every node found. This function may return a value which is forwarded by the `visit` method. This class is meant to be subclassed, with the subclass adding visitor methods. Per default t... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class NodeVisitor:
"""A node visitor base class that walks the abstract syntax tree and calls a visitor function for every node found. This function may return a value which is forwarded by the `visit` method. This class is meant to be subclassed, with the subclass adding visitor methods. Per default the visitor fu... | the_stack_v2_python_sparse | cvx4py/ast/node_visitor.py | ssarkar2/cvx4py_2 | train | 0 |
9aac3f9e15d04d21001cfcf25b61b9058b719cee | [
"super().__init__()\nself.WRD_EMB_DIM = WRD_EMB_DIM\nself.ENC_DIM = ENC_DIM\nself.bilstm = torch.nn.LSTM(input_size=self.WRD_EMB_DIM, hidden_size=self.ENC_DIM // 2, num_layers=1, batch_first=True, bidirectional=True)\nd = self.ENC_DIM // 2\nfan_avg = (d * 4 + (d + self.WRD_EMB_DIM)) / 2.0\nbound = np.sqrt(3.0 / fan... | <|body_start_0|>
super().__init__()
self.WRD_EMB_DIM = WRD_EMB_DIM
self.ENC_DIM = ENC_DIM
self.bilstm = torch.nn.LSTM(input_size=self.WRD_EMB_DIM, hidden_size=self.ENC_DIM // 2, num_layers=1, batch_first=True, bidirectional=True)
d = self.ENC_DIM // 2
fan_avg = (d * 4 + (... | BiLSTM | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BiLSTM:
def __init__(self, WRD_EMB_DIM: int, ENC_DIM: int, forget_gate_bias: float=1.0) -> None:
"""Initialization of BiLSTM. Args: WRD_EMB_DIM: the word embedding dimension ENC_DIM: the dimension of the encoder for BiLSTM, which is twice of the hidden state dimension forget_gate_bias:(o... | stack_v2_sparse_classes_75kplus_train_071853 | 5,915 | permissive | [
{
"docstring": "Initialization of BiLSTM. Args: WRD_EMB_DIM: the word embedding dimension ENC_DIM: the dimension of the encoder for BiLSTM, which is twice of the hidden state dimension forget_gate_bias:(optional):the initialization of the forget-gate bias",
"name": "__init__",
"signature": "def __init__... | 2 | stack_v2_sparse_classes_30k_train_033330 | Implement the Python class `BiLSTM` described below.
Class description:
Implement the BiLSTM class.
Method signatures and docstrings:
- def __init__(self, WRD_EMB_DIM: int, ENC_DIM: int, forget_gate_bias: float=1.0) -> None: Initialization of BiLSTM. Args: WRD_EMB_DIM: the word embedding dimension ENC_DIM: the dimens... | Implement the Python class `BiLSTM` described below.
Class description:
Implement the BiLSTM class.
Method signatures and docstrings:
- def __init__(self, WRD_EMB_DIM: int, ENC_DIM: int, forget_gate_bias: float=1.0) -> None: Initialization of BiLSTM. Args: WRD_EMB_DIM: the word embedding dimension ENC_DIM: the dimens... | af87a17275f02c94932bb2e29f132a84db812002 | <|skeleton|>
class BiLSTM:
def __init__(self, WRD_EMB_DIM: int, ENC_DIM: int, forget_gate_bias: float=1.0) -> None:
"""Initialization of BiLSTM. Args: WRD_EMB_DIM: the word embedding dimension ENC_DIM: the dimension of the encoder for BiLSTM, which is twice of the hidden state dimension forget_gate_bias:(o... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class BiLSTM:
def __init__(self, WRD_EMB_DIM: int, ENC_DIM: int, forget_gate_bias: float=1.0) -> None:
"""Initialization of BiLSTM. Args: WRD_EMB_DIM: the word embedding dimension ENC_DIM: the dimension of the encoder for BiLSTM, which is twice of the hidden state dimension forget_gate_bias:(optional):the i... | the_stack_v2_python_sparse | imix/models/encoder/lcgnencoder.py | linxi1158/iMIX | train | 0 | |
bd5a1d63333b2f3b11af9f73a0f5c2b9751ed557 | [
"word = self.sentence[i]\nnew_indexes = self.indexes + (i,)\nfor subtree in self.ngram_tree.iter_subtrees_matching_word(word):\n yield NgramPartialMatch(subtree, self.sentence, self.n_available_gaps, new_indexes)\nif self.n_available_gaps > 0 and self.indexes:\n yield NgramPartialMatch(self.ngram_tree, self.s... | <|body_start_0|>
word = self.sentence[i]
new_indexes = self.indexes + (i,)
for subtree in self.ngram_tree.iter_subtrees_matching_word(word):
yield NgramPartialMatch(subtree, self.sentence, self.n_available_gaps, new_indexes)
if self.n_available_gaps > 0 and self.indexes:
... | Instances of NgramPartialMatch represent a partial match of a sentence fragment as a path in an NgramTree. You need to use this class when: * You want to find matches with gaps; or * You want to have multiple matches with many different starting indexes in a sentence; or * You want a list of all matched indexes. Argume... | NgramPartialMatch | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NgramPartialMatch:
"""Instances of NgramPartialMatch represent a partial match of a sentence fragment as a path in an NgramTree. You need to use this class when: * You want to find matches with gaps; or * You want to have multiple matches with many different starting indexes in a sentence; or * Y... | stack_v2_sparse_classes_75kplus_train_071854 | 6,098 | no_license | [
{
"docstring": "For a given sentence index `i`, walk the tree and yield new NgramPartialMatch instances.",
"name": "matching_at",
"signature": "def matching_at(self, i)"
},
{
"docstring": "For a given sentence index `i`, check if the current tree position is associated with Ngram instances and y... | 2 | stack_v2_sparse_classes_30k_train_014019 | Implement the Python class `NgramPartialMatch` described below.
Class description:
Instances of NgramPartialMatch represent a partial match of a sentence fragment as a path in an NgramTree. You need to use this class when: * You want to find matches with gaps; or * You want to have multiple matches with many different... | Implement the Python class `NgramPartialMatch` described below.
Class description:
Instances of NgramPartialMatch represent a partial match of a sentence fragment as a path in an NgramTree. You need to use this class when: * You want to find matches with gaps; or * You want to have multiple matches with many different... | e53ed9ff78640a2e579a23aca8bf94543cb58545 | <|skeleton|>
class NgramPartialMatch:
"""Instances of NgramPartialMatch represent a partial match of a sentence fragment as a path in an NgramTree. You need to use this class when: * You want to find matches with gaps; or * You want to have multiple matches with many different starting indexes in a sentence; or * Y... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class NgramPartialMatch:
"""Instances of NgramPartialMatch represent a partial match of a sentence fragment as a path in an NgramTree. You need to use this class when: * You want to find matches with gaps; or * You want to have multiple matches with many different starting indexes in a sentence; or * You want a lis... | the_stack_v2_python_sparse | TP01-corpus/bin/libs/base/ngramtree.py | LicenceInformatique3/Licence3LangageNaturelTD-TP | train | 0 |
09840e39a2c9da557345d141cc92efcedf96aae5 | [
"super(MLPSubNet, self).__init__()\nself.norm = nn.BatchNorm1d(in_size)\nself.drop = nn.Dropout(p=dropout)\nself.linear_1 = nn.Linear(in_size, hidden_size)\nself.linear_2 = nn.Linear(hidden_size, hidden_size)\nself.linear_3 = nn.Linear(hidden_size, hidden_size)",
"x = torch.mean(x, dim=1, keepdim=False)\nnormed =... | <|body_start_0|>
super(MLPSubNet, self).__init__()
self.norm = nn.BatchNorm1d(in_size)
self.drop = nn.Dropout(p=dropout)
self.linear_1 = nn.Linear(in_size, hidden_size)
self.linear_2 = nn.Linear(hidden_size, hidden_size)
self.linear_3 = nn.Linear(hidden_size, hidden_size)... | The subnetwork that is used in TFN for video and audio in the pre-fusion stage | MLPSubNet | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MLPSubNet:
"""The subnetwork that is used in TFN for video and audio in the pre-fusion stage"""
def __init__(self, in_size, hidden_size, dropout):
"""Args: in_size: input dimension hidden_size: hidden layer dimension dropout: dropout probability Output: (return value in forward) a te... | stack_v2_sparse_classes_75kplus_train_071855 | 4,871 | no_license | [
{
"docstring": "Args: in_size: input dimension hidden_size: hidden layer dimension dropout: dropout probability Output: (return value in forward) a tensor of shape (batch_size, hidden_size)",
"name": "__init__",
"signature": "def __init__(self, in_size, hidden_size, dropout)"
},
{
"docstring": "... | 2 | stack_v2_sparse_classes_30k_train_053636 | Implement the Python class `MLPSubNet` described below.
Class description:
The subnetwork that is used in TFN for video and audio in the pre-fusion stage
Method signatures and docstrings:
- def __init__(self, in_size, hidden_size, dropout): Args: in_size: input dimension hidden_size: hidden layer dimension dropout: d... | Implement the Python class `MLPSubNet` described below.
Class description:
The subnetwork that is used in TFN for video and audio in the pre-fusion stage
Method signatures and docstrings:
- def __init__(self, in_size, hidden_size, dropout): Args: in_size: input dimension hidden_size: hidden layer dimension dropout: d... | 1291ba64cd2e6e723abf290e6feef1392da7ee82 | <|skeleton|>
class MLPSubNet:
"""The subnetwork that is used in TFN for video and audio in the pre-fusion stage"""
def __init__(self, in_size, hidden_size, dropout):
"""Args: in_size: input dimension hidden_size: hidden layer dimension dropout: dropout probability Output: (return value in forward) a te... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MLPSubNet:
"""The subnetwork that is used in TFN for video and audio in the pre-fusion stage"""
def __init__(self, in_size, hidden_size, dropout):
"""Args: in_size: input dimension hidden_size: hidden layer dimension dropout: dropout probability Output: (return value in forward) a tensor of shape... | the_stack_v2_python_sparse | models/.ipynb_checkpoints/TFN-checkpoint.py | littlehacker26/diasenti | train | 0 |
8490fd537ed5d3c28cd597e45f54b5668d6934b4 | [
"super().__init__()\nassert method in ('max', 'avg', 'sum')\nself._method = method",
"assert x.dim() == 3, 'Requires x shape (batch_size x seq_len x feature_dim)'\nb, t = (x.shape[0], x.shape[1])\nif mask is None:\n mask = torch.ones((b, t), dtype=torch.bool)\nif self._method == 'max':\n x[~mask, :] = float... | <|body_start_0|>
super().__init__()
assert method in ('max', 'avg', 'sum')
self._method = method
<|end_body_0|>
<|body_start_1|>
assert x.dim() == 3, 'Requires x shape (batch_size x seq_len x feature_dim)'
b, t = (x.shape[0], x.shape[1])
if mask is None:
mask... | Applies temporal pooling operations on masked inputs. For each pooling operation all masked values are ignored. | MaskedTemporalPooling | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MaskedTemporalPooling:
"""Applies temporal pooling operations on masked inputs. For each pooling operation all masked values are ignored."""
def __init__(self, method: str):
"""method (str): the method of pooling to use. Options: 'max': reduces temporal dimension to each valid max va... | stack_v2_sparse_classes_75kplus_train_071856 | 13,032 | permissive | [
{
"docstring": "method (str): the method of pooling to use. Options: 'max': reduces temporal dimension to each valid max value. 'avg': averages valid values in the temporal dimension. 'sum': sums valid values in the temporal dimension. Note if all batch row elements are invalid, the temporal dimension is pooled... | 2 | stack_v2_sparse_classes_30k_train_018408 | Implement the Python class `MaskedTemporalPooling` described below.
Class description:
Applies temporal pooling operations on masked inputs. For each pooling operation all masked values are ignored.
Method signatures and docstrings:
- def __init__(self, method: str): method (str): the method of pooling to use. Option... | Implement the Python class `MaskedTemporalPooling` described below.
Class description:
Applies temporal pooling operations on masked inputs. For each pooling operation all masked values are ignored.
Method signatures and docstrings:
- def __init__(self, method: str): method (str): the method of pooling to use. Option... | 16f2abf2f8aa174915316007622bbb260215dee8 | <|skeleton|>
class MaskedTemporalPooling:
"""Applies temporal pooling operations on masked inputs. For each pooling operation all masked values are ignored."""
def __init__(self, method: str):
"""method (str): the method of pooling to use. Options: 'max': reduces temporal dimension to each valid max va... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MaskedTemporalPooling:
"""Applies temporal pooling operations on masked inputs. For each pooling operation all masked values are ignored."""
def __init__(self, method: str):
"""method (str): the method of pooling to use. Options: 'max': reduces temporal dimension to each valid max value. 'avg': a... | the_stack_v2_python_sparse | pytorchvideo/models/masked_multistream.py | xchani/pytorchvideo | train | 0 |
51e9825fcc6c272dee0a5941a4b6b82e6335c8b2 | [
"ref = set('01689')\n\ndef transform(num):\n trans = ''\n for each in num[::-1]:\n if each == '0':\n trans += '0'\n elif each == '6':\n trans += '9'\n elif each == '9':\n trans += '6'\n elif each == '8':\n trans += '8'\n elif each ... | <|body_start_0|>
ref = set('01689')
def transform(num):
trans = ''
for each in num[::-1]:
if each == '0':
trans += '0'
elif each == '6':
trans += '9'
elif each == '9':
tra... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def isStrobogrammatic(self, num):
""":type num: str :rtype: bool"""
<|body_0|>
def isStrobogrammatic(self, num):
""":type num: str :rtype: bool"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
ref = set('01689')
def transform(num):... | stack_v2_sparse_classes_75kplus_train_071857 | 1,533 | no_license | [
{
"docstring": ":type num: str :rtype: bool",
"name": "isStrobogrammatic",
"signature": "def isStrobogrammatic(self, num)"
},
{
"docstring": ":type num: str :rtype: bool",
"name": "isStrobogrammatic",
"signature": "def isStrobogrammatic(self, num)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isStrobogrammatic(self, num): :type num: str :rtype: bool
- def isStrobogrammatic(self, num): :type num: str :rtype: bool | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isStrobogrammatic(self, num): :type num: str :rtype: bool
- def isStrobogrammatic(self, num): :type num: str :rtype: bool
<|skeleton|>
class Solution:
def isStrobogramm... | 8bb17099be02d997d554519be360ef4aa1c028e3 | <|skeleton|>
class Solution:
def isStrobogrammatic(self, num):
""":type num: str :rtype: bool"""
<|body_0|>
def isStrobogrammatic(self, num):
""":type num: str :rtype: bool"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def isStrobogrammatic(self, num):
""":type num: str :rtype: bool"""
ref = set('01689')
def transform(num):
trans = ''
for each in num[::-1]:
if each == '0':
trans += '0'
elif each == '6':
... | the_stack_v2_python_sparse | Google/1. easy/246. Strobogrammatic Number.py | yemao616/summer18 | train | 0 | |
d61e244dc98461ad386353ac916b535d7681454e | [
"IO_files = {}\nfile_names = set()\nfor fl in in_dir.files:\n if self.name not in fl.users:\n if utils.splitext(fl.name)[-1] in self.input_types:\n IO_files['-!i'] = os.path.join(in_dir.path, fl.name)\n command_ids = [utils.infer_path_id(IO_files['-!i'])]\n in_dir.use_file... | <|body_start_0|>
IO_files = {}
file_names = set()
for fl in in_dir.files:
if self.name not in fl.users:
if utils.splitext(fl.name)[-1] in self.input_types:
IO_files['-!i'] = os.path.join(in_dir.path, fl.name)
command_ids = [util... | Class for using psmc2history. Parameters: in_cmd: String containing a command line in_dir: Directory object containing input files out_dir: Directory object containing output files NOTICE! Keep the directory objects up to date about file edits! Attributes: name: Name of the function. input_type: Input types accepted by... | psmc2history | [
"BSD-3-Clause",
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class psmc2history:
"""Class for using psmc2history. Parameters: in_cmd: String containing a command line in_dir: Directory object containing input files out_dir: Directory object containing output files NOTICE! Keep the directory objects up to date about file edits! Attributes: name: Name of the funct... | stack_v2_sparse_classes_75kplus_train_071858 | 19,984 | permissive | [
{
"docstring": "Infers the input and output file paths. This method must keep the directory objects up to date of the file edits! Parameters: in_cmd: A dict containing the command line. in_dir: Input directory (instance of filetypes.Directory). out_dir: Output directory (instance of filetypes.Directory). Return... | 2 | stack_v2_sparse_classes_30k_train_021516 | Implement the Python class `psmc2history` described below.
Class description:
Class for using psmc2history. Parameters: in_cmd: String containing a command line in_dir: Directory object containing input files out_dir: Directory object containing output files NOTICE! Keep the directory objects up to date about file edi... | Implement the Python class `psmc2history` described below.
Class description:
Class for using psmc2history. Parameters: in_cmd: String containing a command line in_dir: Directory object containing input files out_dir: Directory object containing output files NOTICE! Keep the directory objects up to date about file edi... | fd83eee4be0bb78c67a111fd1c1c1dff4c16aefe | <|skeleton|>
class psmc2history:
"""Class for using psmc2history. Parameters: in_cmd: String containing a command line in_dir: Directory object containing input files out_dir: Directory object containing output files NOTICE! Keep the directory objects up to date about file edits! Attributes: name: Name of the funct... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class psmc2history:
"""Class for using psmc2history. Parameters: in_cmd: String containing a command line in_dir: Directory object containing input files out_dir: Directory object containing output files NOTICE! Keep the directory objects up to date about file edits! Attributes: name: Name of the function. input_ty... | the_stack_v2_python_sparse | modules/psmc.py | tyrmi/STAPLER | train | 4 |
e7d8f8aee7912478c24376017d6fa0e23ce9e49a | [
"if not email:\n raise ValueError('Users must have an email address')\nuser = self.model(email=self.normalize_email(email), **extra_fields)\nuser.set_password(password)\nuser.save(using=self._db)\nreturn user",
"user = self.create_user(email=email, password=password, **extra_fields)\nuser.is_admin = True\nuser... | <|body_start_0|>
if not email:
raise ValueError('Users must have an email address')
user = self.model(email=self.normalize_email(email), **extra_fields)
user.set_password(password)
user.save(using=self._db)
return user
<|end_body_0|>
<|body_start_1|>
user = s... | A custom user manager for sef. | CustomUserManager | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CustomUserManager:
"""A custom user manager for sef."""
def create_user(self, email=None, password=None, **extra_fields):
"""Create and save a User with the given email, password."""
<|body_0|>
def create_superuser(self, email=None, password=None, **extra_fields):
... | stack_v2_sparse_classes_75kplus_train_071859 | 2,020 | no_license | [
{
"docstring": "Create and save a User with the given email, password.",
"name": "create_user",
"signature": "def create_user(self, email=None, password=None, **extra_fields)"
},
{
"docstring": "Create and save a User.",
"name": "create_superuser",
"signature": "def create_superuser(self... | 2 | stack_v2_sparse_classes_30k_train_006000 | Implement the Python class `CustomUserManager` described below.
Class description:
A custom user manager for sef.
Method signatures and docstrings:
- def create_user(self, email=None, password=None, **extra_fields): Create and save a User with the given email, password.
- def create_superuser(self, email=None, passwo... | Implement the Python class `CustomUserManager` described below.
Class description:
A custom user manager for sef.
Method signatures and docstrings:
- def create_user(self, email=None, password=None, **extra_fields): Create and save a User with the given email, password.
- def create_superuser(self, email=None, passwo... | 345e6f4964c6223c5765793e1d04ba73a499d935 | <|skeleton|>
class CustomUserManager:
"""A custom user manager for sef."""
def create_user(self, email=None, password=None, **extra_fields):
"""Create and save a User with the given email, password."""
<|body_0|>
def create_superuser(self, email=None, password=None, **extra_fields):
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CustomUserManager:
"""A custom user manager for sef."""
def create_user(self, email=None, password=None, **extra_fields):
"""Create and save a User with the given email, password."""
if not email:
raise ValueError('Users must have an email address')
user = self.model(e... | the_stack_v2_python_sparse | sef/user/models/models.py | dmbuguah/sef-api | train | 0 |
73039ce8069918e0f2192da82ae9276e38581553 | [
"if dtype not in NUMERIC_TYPES:\n raise ValueError(\"invalid numeric type '{}'\".format(dtype))\nsuper(Numeric, self).__init__(dtype=dtype, name=name, index=index, label=label, help=help, default=default, required=required, group=group)\nself.constraint = constraint",
"if value in ['-inf', 'inf']:\n value =... | <|body_start_0|>
if dtype not in NUMERIC_TYPES:
raise ValueError("invalid numeric type '{}'".format(dtype))
super(Numeric, self).__init__(dtype=dtype, name=name, index=index, label=label, help=help, default=default, required=required, group=group)
self.constraint = constraint
<|end_b... | Base class for numeric parameter types. Extends the base class with an optional range constraint. | Numeric | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Numeric:
"""Base class for numeric parameter types. Extends the base class with an optional range constraint."""
def __init__(self, dtype: str, name: str, index: Optional[int]=0, label: Optional[str]=None, help: Optional[str]=None, default: Optional[Union[int, float]]=None, required: Optiona... | stack_v2_sparse_classes_75kplus_train_071860 | 16,105 | permissive | [
{
"docstring": "Initialize the base properties for a numeric parameter declaration. Parameters ---------- dtype: string Parameter type identifier. name: string Unique parameter identifier index: int Index position of the parameter (for display purposes). label: string Human-readable parameter name. help: string... | 4 | stack_v2_sparse_classes_30k_train_013935 | Implement the Python class `Numeric` described below.
Class description:
Base class for numeric parameter types. Extends the base class with an optional range constraint.
Method signatures and docstrings:
- def __init__(self, dtype: str, name: str, index: Optional[int]=0, label: Optional[str]=None, help: Optional[str... | Implement the Python class `Numeric` described below.
Class description:
Base class for numeric parameter types. Extends the base class with an optional range constraint.
Method signatures and docstrings:
- def __init__(self, dtype: str, name: str, index: Optional[int]=0, label: Optional[str]=None, help: Optional[str... | 7116b7060aa68ab36bf08e6393be166dc5db955f | <|skeleton|>
class Numeric:
"""Base class for numeric parameter types. Extends the base class with an optional range constraint."""
def __init__(self, dtype: str, name: str, index: Optional[int]=0, label: Optional[str]=None, help: Optional[str]=None, default: Optional[Union[int, float]]=None, required: Optiona... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Numeric:
"""Base class for numeric parameter types. Extends the base class with an optional range constraint."""
def __init__(self, dtype: str, name: str, index: Optional[int]=0, label: Optional[str]=None, help: Optional[str]=None, default: Optional[Union[int, float]]=None, required: Optional[bool]=False... | the_stack_v2_python_sparse | flowserv/model/parameter/numeric.py | anrunw/flowserv-core-1 | train | 0 |
e93e366ca062494ce59a1196eb02a3ae4e63152c | [
"super(ReactorEnumerate, self).__init__(achem, mols)\nself.maxmols = len(mols)\nself.mols = []\nself.tested = []\nself.untested = []\nfor mol in mols:\n self.add_mol(mol)",
"if mol not in self.mols:\n self.mols.append(mol)\n noreactants = self.achem.noreactants\n try:\n noreactants = set(noreac... | <|body_start_0|>
super(ReactorEnumerate, self).__init__(achem, mols)
self.maxmols = len(mols)
self.mols = []
self.tested = []
self.untested = []
for mol in mols:
self.add_mol(mol)
<|end_body_0|>
<|body_start_1|>
if mol not in self.mols:
se... | Reactor object designed to exaustively enumerate all possible reactant collections, adding new reactant collections as novel products appear. | ReactorEnumerate | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ReactorEnumerate:
"""Reactor object designed to exaustively enumerate all possible reactant collections, adding new reactant collections as novel products appear."""
def __init__(self, achem, mols):
""":param achem: :py:class:`achemkit.achem.AChem` object or equivalent. :param mols: ... | stack_v2_sparse_classes_75kplus_train_071861 | 7,950 | permissive | [
{
"docstring": ":param achem: :py:class:`achemkit.achem.AChem` object or equivalent. :param mols: Initial molecular species.",
"name": "__init__",
"signature": "def __init__(self, achem, mols)"
},
{
"docstring": "Internal utility function used to ensure molecular species have the relevant reacti... | 3 | stack_v2_sparse_classes_30k_train_049006 | Implement the Python class `ReactorEnumerate` described below.
Class description:
Reactor object designed to exaustively enumerate all possible reactant collections, adding new reactant collections as novel products appear.
Method signatures and docstrings:
- def __init__(self, achem, mols): :param achem: :py:class:`... | Implement the Python class `ReactorEnumerate` described below.
Class description:
Reactor object designed to exaustively enumerate all possible reactant collections, adding new reactant collections as novel products appear.
Method signatures and docstrings:
- def __init__(self, achem, mols): :param achem: :py:class:`... | 4800044693fdf8a228430eae5ee8b0283fde9920 | <|skeleton|>
class ReactorEnumerate:
"""Reactor object designed to exaustively enumerate all possible reactant collections, adding new reactant collections as novel products appear."""
def __init__(self, achem, mols):
""":param achem: :py:class:`achemkit.achem.AChem` object or equivalent. :param mols: ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ReactorEnumerate:
"""Reactor object designed to exaustively enumerate all possible reactant collections, adding new reactant collections as novel products appear."""
def __init__(self, achem, mols):
""":param achem: :py:class:`achemkit.achem.AChem` object or equivalent. :param mols: Initial molec... | the_stack_v2_python_sparse | achemkit/sim/simple.py | afaulconbridge/PyAChemKit | train | 2 |
41a3ca75c0fd3236909dcfa66b645d06b1a80273 | [
"if len(key) not in key_size:\n raise ValueError('Incorrect key length for Salsa20 (%d bytes)' % len(key))\nif len(nonce) != 8:\n raise ValueError('Incorrect nonce length for Salsa20 (%d bytes)' % len(nonce))\nself.nonce = nonce\nexpect_byte_string(key)\nexpect_byte_string(nonce)\nself._state = VoidPointer()\... | <|body_start_0|>
if len(key) not in key_size:
raise ValueError('Incorrect key length for Salsa20 (%d bytes)' % len(key))
if len(nonce) != 8:
raise ValueError('Incorrect nonce length for Salsa20 (%d bytes)' % len(nonce))
self.nonce = nonce
expect_byte_string(key)
... | Salsa20 cipher object | Salsa20Cipher | [
"LicenseRef-scancode-python-cwi",
"GPL-1.0-or-later",
"LicenseRef-scancode-other-copyleft",
"LicenseRef-scancode-free-unknown",
"Python-2.0",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Salsa20Cipher:
"""Salsa20 cipher object"""
def __init__(self, key, nonce):
"""Initialize a Salsa20 cipher object See also `new()` at the module level."""
<|body_0|>
def encrypt(self, plaintext):
"""Encrypt a piece of data. :Parameters: plaintext : byte string The... | stack_v2_sparse_classes_75kplus_train_071862 | 5,685 | permissive | [
{
"docstring": "Initialize a Salsa20 cipher object See also `new()` at the module level.",
"name": "__init__",
"signature": "def __init__(self, key, nonce)"
},
{
"docstring": "Encrypt a piece of data. :Parameters: plaintext : byte string The piece of data to encrypt. It can be of any size. :Retu... | 3 | null | Implement the Python class `Salsa20Cipher` described below.
Class description:
Salsa20 cipher object
Method signatures and docstrings:
- def __init__(self, key, nonce): Initialize a Salsa20 cipher object See also `new()` at the module level.
- def encrypt(self, plaintext): Encrypt a piece of data. :Parameters: plaint... | Implement the Python class `Salsa20Cipher` described below.
Class description:
Salsa20 cipher object
Method signatures and docstrings:
- def __init__(self, key, nonce): Initialize a Salsa20 cipher object See also `new()` at the module level.
- def encrypt(self, plaintext): Encrypt a piece of data. :Parameters: plaint... | d9741aafd54126f05ba43e6f4ad6517755797c76 | <|skeleton|>
class Salsa20Cipher:
"""Salsa20 cipher object"""
def __init__(self, key, nonce):
"""Initialize a Salsa20 cipher object See also `new()` at the module level."""
<|body_0|>
def encrypt(self, plaintext):
"""Encrypt a piece of data. :Parameters: plaintext : byte string The... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Salsa20Cipher:
"""Salsa20 cipher object"""
def __init__(self, key, nonce):
"""Initialize a Salsa20 cipher object See also `new()` at the module level."""
if len(key) not in key_size:
raise ValueError('Incorrect key length for Salsa20 (%d bytes)' % len(key))
if len(nonc... | the_stack_v2_python_sparse | venv/lib/python3.7/site-packages/Crypto/Cipher/Salsa20.py | basemanbase/Animal-Health | train | 0 |
f650c8c5f1375cca1005c5beaf6ff3341f6ecbcf | [
"values = super(CustomerPortal, self)._prepare_home_portal_values()\nvalues['student_count'] = request.env['student.student'].search_count([])\nvalues['application_count'] = request.env['job.application'].search_count([])\nreturn values",
"values = self._prepare_portal_layout_values()\nStudentStudent = request.en... | <|body_start_0|>
values = super(CustomerPortal, self)._prepare_home_portal_values()
values['student_count'] = request.env['student.student'].search_count([])
values['application_count'] = request.env['job.application'].search_count([])
return values
<|end_body_0|>
<|body_start_1|>
... | CustomerPortal | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CustomerPortal:
def _prepare_home_portal_values(self):
"""Returns the count of the student and job applications"""
<|body_0|>
def portal_my_students(self, page=1, sortby=None, **kw):
"""Sortby values and pager functionality"""
<|body_1|>
def portal_my_ap... | stack_v2_sparse_classes_75kplus_train_071863 | 3,836 | no_license | [
{
"docstring": "Returns the count of the student and job applications",
"name": "_prepare_home_portal_values",
"signature": "def _prepare_home_portal_values(self)"
},
{
"docstring": "Sortby values and pager functionality",
"name": "portal_my_students",
"signature": "def portal_my_student... | 3 | null | Implement the Python class `CustomerPortal` described below.
Class description:
Implement the CustomerPortal class.
Method signatures and docstrings:
- def _prepare_home_portal_values(self): Returns the count of the student and job applications
- def portal_my_students(self, page=1, sortby=None, **kw): Sortby values ... | Implement the Python class `CustomerPortal` described below.
Class description:
Implement the CustomerPortal class.
Method signatures and docstrings:
- def _prepare_home_portal_values(self): Returns the count of the student and job applications
- def portal_my_students(self, page=1, sortby=None, **kw): Sortby values ... | 36239c223224ae57fb58942a74d09d643c288a14 | <|skeleton|>
class CustomerPortal:
def _prepare_home_portal_values(self):
"""Returns the count of the student and job applications"""
<|body_0|>
def portal_my_students(self, page=1, sortby=None, **kw):
"""Sortby values and pager functionality"""
<|body_1|>
def portal_my_ap... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CustomerPortal:
def _prepare_home_portal_values(self):
"""Returns the count of the student and job applications"""
values = super(CustomerPortal, self)._prepare_home_portal_values()
values['student_count'] = request.env['student.student'].search_count([])
values['application_co... | the_stack_v2_python_sparse | controllers/portal.py | dhruv-suthar-aktiv/school-module | train | 0 | |
874ac81b7f3c374c4c879a8cf346bd15b116d482 | [
"services_interval = kwargs.pop('services_interval', DEFAULT_SERVICES_INTERVAL)\nsuper().__init__(tick_interval=services_interval, **kwargs)\nself._registered_service_description = None\nself.is_items_created = False\nself.is_items_minted = False\nself.token_ids = []",
"strategy = cast(Strategy, self.context.stra... | <|body_start_0|>
services_interval = kwargs.pop('services_interval', DEFAULT_SERVICES_INTERVAL)
super().__init__(tick_interval=services_interval, **kwargs)
self._registered_service_description = None
self.is_items_created = False
self.is_items_minted = False
self.token_id... | This class implements a behaviour. | ServiceRegistrationBehaviour | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ServiceRegistrationBehaviour:
"""This class implements a behaviour."""
def __init__(self, **kwargs):
"""Initialise the behaviour."""
<|body_0|>
def setup(self) -> None:
"""Implement the setup. :return: None"""
<|body_1|>
def act(self) -> None:
... | stack_v2_sparse_classes_75kplus_train_071864 | 8,205 | permissive | [
{
"docstring": "Initialise the behaviour.",
"name": "__init__",
"signature": "def __init__(self, **kwargs)"
},
{
"docstring": "Implement the setup. :return: None",
"name": "setup",
"signature": "def setup(self) -> None"
},
{
"docstring": "Implement the act. :return: None",
"n... | 6 | stack_v2_sparse_classes_30k_train_038270 | Implement the Python class `ServiceRegistrationBehaviour` described below.
Class description:
This class implements a behaviour.
Method signatures and docstrings:
- def __init__(self, **kwargs): Initialise the behaviour.
- def setup(self) -> None: Implement the setup. :return: None
- def act(self) -> None: Implement ... | Implement the Python class `ServiceRegistrationBehaviour` described below.
Class description:
This class implements a behaviour.
Method signatures and docstrings:
- def __init__(self, **kwargs): Initialise the behaviour.
- def setup(self) -> None: Implement the setup. :return: None
- def act(self) -> None: Implement ... | 6636decff2b1c4a4b62152912d631afe6d287b5c | <|skeleton|>
class ServiceRegistrationBehaviour:
"""This class implements a behaviour."""
def __init__(self, **kwargs):
"""Initialise the behaviour."""
<|body_0|>
def setup(self) -> None:
"""Implement the setup. :return: None"""
<|body_1|>
def act(self) -> None:
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ServiceRegistrationBehaviour:
"""This class implements a behaviour."""
def __init__(self, **kwargs):
"""Initialise the behaviour."""
services_interval = kwargs.pop('services_interval', DEFAULT_SERVICES_INTERVAL)
super().__init__(tick_interval=services_interval, **kwargs)
s... | the_stack_v2_python_sparse | packages/fetchai/skills/erc1155_deploy/behaviours.py | yangjue-han/agents-aea | train | 0 |
a0298bbe517ebf59679dc7adb45fa3094f95502d | [
"self.driver.get(url)\nself.driver.max_window()\nself.driver.find_element(locator.HeaderLocator.qgg).click()\nself.driver.pause(3)\nself.driver.switch_to_window()\ntag_is_dispayed = self.driver.is_display(locator.HeaderLocator.qgg_tag)\nself.driver.pause(3)\ntt_check.assertTrue(tag_is_dispayed, '列表页全国购签是否显示：%s' % t... | <|body_start_0|>
self.driver.get(url)
self.driver.max_window()
self.driver.find_element(locator.HeaderLocator.qgg).click()
self.driver.pause(3)
self.driver.switch_to_window()
tag_is_dispayed = self.driver.is_display(locator.HeaderLocator.qgg_tag)
self.driver.pause... | qgg_floor | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class qgg_floor:
def test_qgg(self):
"""测试首页全国购楼层跳转,@author:xulanzhong"""
<|body_0|>
def test_qgg(self):
"""测试首页全国购楼层-查看全部跳转,@author:xulanzhong"""
<|body_1|>
def test_qgg_img(self):
"""测试首页全国购楼层-车图-跳转,@author:xulanzhong"""
<|body_2|>
def t... | stack_v2_sparse_classes_75kplus_train_071865 | 2,392 | no_license | [
{
"docstring": "测试首页全国购楼层跳转,@author:xulanzhong",
"name": "test_qgg",
"signature": "def test_qgg(self)"
},
{
"docstring": "测试首页全国购楼层-查看全部跳转,@author:xulanzhong",
"name": "test_qgg",
"signature": "def test_qgg(self)"
},
{
"docstring": "测试首页全国购楼层-车图-跳转,@author:xulanzhong",
"name"... | 4 | stack_v2_sparse_classes_30k_train_046548 | Implement the Python class `qgg_floor` described below.
Class description:
Implement the qgg_floor class.
Method signatures and docstrings:
- def test_qgg(self): 测试首页全国购楼层跳转,@author:xulanzhong
- def test_qgg(self): 测试首页全国购楼层-查看全部跳转,@author:xulanzhong
- def test_qgg_img(self): 测试首页全国购楼层-车图-跳转,@author:xulanzhong
- def ... | Implement the Python class `qgg_floor` described below.
Class description:
Implement the qgg_floor class.
Method signatures and docstrings:
- def test_qgg(self): 测试首页全国购楼层跳转,@author:xulanzhong
- def test_qgg(self): 测试首页全国购楼层-查看全部跳转,@author:xulanzhong
- def test_qgg_img(self): 测试首页全国购楼层-车图-跳转,@author:xulanzhong
- def ... | 204856bd33c06d25f2970eba13799db75d4fd4fe | <|skeleton|>
class qgg_floor:
def test_qgg(self):
"""测试首页全国购楼层跳转,@author:xulanzhong"""
<|body_0|>
def test_qgg(self):
"""测试首页全国购楼层-查看全部跳转,@author:xulanzhong"""
<|body_1|>
def test_qgg_img(self):
"""测试首页全国购楼层-车图-跳转,@author:xulanzhong"""
<|body_2|>
def t... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class qgg_floor:
def test_qgg(self):
"""测试首页全国购楼层跳转,@author:xulanzhong"""
self.driver.get(url)
self.driver.max_window()
self.driver.find_element(locator.HeaderLocator.qgg).click()
self.driver.pause(3)
self.driver.switch_to_window()
tag_is_dispayed = self.drive... | the_stack_v2_python_sparse | mc/taochePC/test_crawler/test_homepage/test_qgg.py | boeai/mc | train | 0 | |
539c85f03c6c4eb2cbe2d6760142ecf37b91434f | [
"left, right = (1, n)\nnum = int(math.log(n, 2))\nsum = 0\nwhile num:\n mid = (left + right) / 2 + 1\n sum += mid\n left = mid + 1\n num -= 1\nreturn sum",
"dp = [[0 for _ in range(n + 1)] for _ in range(n + 1)]\nfor start in range(1, n + 1):\n for j in range(start, n + 1):\n i = j - start\n... | <|body_start_0|>
left, right = (1, n)
num = int(math.log(n, 2))
sum = 0
while num:
mid = (left + right) / 2 + 1
sum += mid
left = mid + 1
num -= 1
return sum
<|end_body_0|>
<|body_start_1|>
dp = [[0 for _ in range(n + 1)] f... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def getMoneyAmount(self, n):
""":type n: int :rtype: int"""
<|body_0|>
def getMoneyAmount2(self, n):
""":type n: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
left, right = (1, n)
num = int(math.log(n, 2))
... | stack_v2_sparse_classes_75kplus_train_071866 | 1,610 | no_license | [
{
"docstring": ":type n: int :rtype: int",
"name": "getMoneyAmount",
"signature": "def getMoneyAmount(self, n)"
},
{
"docstring": ":type n: int :rtype: int",
"name": "getMoneyAmount2",
"signature": "def getMoneyAmount2(self, n)"
}
] | 2 | stack_v2_sparse_classes_30k_train_044742 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def getMoneyAmount(self, n): :type n: int :rtype: int
- def getMoneyAmount2(self, n): :type n: int :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def getMoneyAmount(self, n): :type n: int :rtype: int
- def getMoneyAmount2(self, n): :type n: int :rtype: int
<|skeleton|>
class Solution:
def getMoneyAmount(self, n):
... | 0fc4c7af59246e3064db41989a45d9db413a624b | <|skeleton|>
class Solution:
def getMoneyAmount(self, n):
""":type n: int :rtype: int"""
<|body_0|>
def getMoneyAmount2(self, n):
""":type n: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def getMoneyAmount(self, n):
""":type n: int :rtype: int"""
left, right = (1, n)
num = int(math.log(n, 2))
sum = 0
while num:
mid = (left + right) / 2 + 1
sum += mid
left = mid + 1
num -= 1
return sum
... | the_stack_v2_python_sparse | 375. Guess Number Higher or Lower II/guess2.py | Macielyoung/LeetCode | train | 1 | |
75cb25c365b813ffbfc8189c1425049cbaaf5847 | [
"i2c = I2C(scl=scl_pin, sda=sda_pin)\nself.roll = 0\nself.pitch = 0\nself.xyz_calib_factor = {'AcX': 1, 'AcY': 1, 'AcZ': 1}\nself.xyz_calib_offset = {'AcX': 0.0, 'AcY': 0.4, 'AcZ': 0.0}\nself.gyro_calib_offset = {'AcX': -14, 'AcY': 2.6, 'AcZ': 1.4}\nself.accelerometer = accel(i2c)\nself.time = 0\nself.crash_detecti... | <|body_start_0|>
i2c = I2C(scl=scl_pin, sda=sda_pin)
self.roll = 0
self.pitch = 0
self.xyz_calib_factor = {'AcX': 1, 'AcY': 1, 'AcZ': 1}
self.xyz_calib_offset = {'AcX': 0.0, 'AcY': 0.4, 'AcZ': 0.0}
self.gyro_calib_offset = {'AcX': -14, 'AcY': 2.6, 'AcZ': 1.4}
self... | MpuSensor | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MpuSensor:
def __init__(self, scl_pin, sda_pin):
"""Initialise the MPU6050 sensor to read accelerometer and gyroscope data. :param scl_pin: A Pin object connected to SCL on the sensor. :param sda_pin: A Pin object connected to SDA on the sensor. :param samples: An integer representing nu... | stack_v2_sparse_classes_75kplus_train_071867 | 5,290 | no_license | [
{
"docstring": "Initialise the MPU6050 sensor to read accelerometer and gyroscope data. :param scl_pin: A Pin object connected to SCL on the sensor. :param sda_pin: A Pin object connected to SDA on the sensor. :param samples: An integer representing number of readings to take the average of.",
"name": "__in... | 4 | stack_v2_sparse_classes_30k_train_000287 | Implement the Python class `MpuSensor` described below.
Class description:
Implement the MpuSensor class.
Method signatures and docstrings:
- def __init__(self, scl_pin, sda_pin): Initialise the MPU6050 sensor to read accelerometer and gyroscope data. :param scl_pin: A Pin object connected to SCL on the sensor. :para... | Implement the Python class `MpuSensor` described below.
Class description:
Implement the MpuSensor class.
Method signatures and docstrings:
- def __init__(self, scl_pin, sda_pin): Initialise the MPU6050 sensor to read accelerometer and gyroscope data. :param scl_pin: A Pin object connected to SCL on the sensor. :para... | 1029f1eb50c0f3a220a12b467bb9f6a0dbcb02bd | <|skeleton|>
class MpuSensor:
def __init__(self, scl_pin, sda_pin):
"""Initialise the MPU6050 sensor to read accelerometer and gyroscope data. :param scl_pin: A Pin object connected to SCL on the sensor. :param sda_pin: A Pin object connected to SDA on the sensor. :param samples: An integer representing nu... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MpuSensor:
def __init__(self, scl_pin, sda_pin):
"""Initialise the MPU6050 sensor to read accelerometer and gyroscope data. :param scl_pin: A Pin object connected to SCL on the sensor. :param sda_pin: A Pin object connected to SDA on the sensor. :param samples: An integer representing number of readin... | the_stack_v2_python_sparse | wireless_modules/sensors/mpu_sensor.py | monash-human-power/data-acquisition-system | train | 2 | |
4695784a3f157e9a6d3e17212f1f079d42b282fc | [
"assert isinstance(response, scrapy.http.response.html.HtmlResponse)\nBOARDS = ['Shore Fishing']\nURLS = ['http://www.nesa.co.uk/forums/shore-fishing/']\nPAGES = [501]\nassert len(BOARDS) == len(URLS) == len(PAGES), 'Setup list lengths DO NOT match'\nfor i, root_url in enumerate(URLS):\n curboard = BOARDS[i]\n ... | <|body_start_0|>
assert isinstance(response, scrapy.http.response.html.HtmlResponse)
BOARDS = ['Shore Fishing']
URLS = ['http://www.nesa.co.uk/forums/shore-fishing/']
PAGES = [501]
assert len(BOARDS) == len(URLS) == len(PAGES), 'Setup list lengths DO NOT match'
for i, roo... | scrape reports from angling addicts forum | NESASpider | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NESASpider:
"""scrape reports from angling addicts forum"""
def parse(self, response):
"""generate links to pages in a board"""
<|body_0|>
def crawl_board_threads(self, response):
"""crawl"""
<|body_1|>
def parse_thread(self, response):
"""op... | stack_v2_sparse_classes_75kplus_train_071868 | 13,051 | no_license | [
{
"docstring": "generate links to pages in a board",
"name": "parse",
"signature": "def parse(self, response)"
},
{
"docstring": "crawl",
"name": "crawl_board_threads",
"signature": "def crawl_board_threads(self, response)"
},
{
"docstring": "open a report thread and parse first ... | 3 | stack_v2_sparse_classes_30k_train_029064 | Implement the Python class `NESASpider` described below.
Class description:
scrape reports from angling addicts forum
Method signatures and docstrings:
- def parse(self, response): generate links to pages in a board
- def crawl_board_threads(self, response): crawl
- def parse_thread(self, response): open a report thr... | Implement the Python class `NESASpider` described below.
Class description:
scrape reports from angling addicts forum
Method signatures and docstrings:
- def parse(self, response): generate links to pages in a board
- def crawl_board_threads(self, response): crawl
- def parse_thread(self, response): open a report thr... | 9123aa6baf538b662143b9098d963d55165e8409 | <|skeleton|>
class NESASpider:
"""scrape reports from angling addicts forum"""
def parse(self, response):
"""generate links to pages in a board"""
<|body_0|>
def crawl_board_threads(self, response):
"""crawl"""
<|body_1|>
def parse_thread(self, response):
"""op... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class NESASpider:
"""scrape reports from angling addicts forum"""
def parse(self, response):
"""generate links to pages in a board"""
assert isinstance(response, scrapy.http.response.html.HtmlResponse)
BOARDS = ['Shore Fishing']
URLS = ['http://www.nesa.co.uk/forums/shore-fishin... | the_stack_v2_python_sparse | imgscrape/spiders/nesa.py | gmonkman/python | train | 0 |
c55368d7f7f25a9f08c079abd77c5f4db0d74b50 | [
"array = [head]\nwhile array[-1].next:\n array.append(array[-1].next)\nreturn array[len(array) // 2]",
"n, cur = (0, head)\nwhile cur:\n n += 1\n cur = cur.next\nk, cur = (0, head)\nwhile k < n // 2:\n k += 1\n cur = cur.next\nreturn cur",
"fast = slow = head\nwhile fast and fast.next:\n slow ... | <|body_start_0|>
array = [head]
while array[-1].next:
array.append(array[-1].next)
return array[len(array) // 2]
<|end_body_0|>
<|body_start_1|>
n, cur = (0, head)
while cur:
n += 1
cur = cur.next
k, cur = (0, head)
while k < n... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def middle_node(cls, head: ListNode) -> ListNode:
"""数组"""
<|body_0|>
def middle_node_v2(cls, head: ListNode) -> ListNode:
"""单指针"""
<|body_1|>
def middle_node_v3(cls, head: ListNode) -> ListNode:
"""快慢指针"""
<|body_2|>
<|end_sk... | stack_v2_sparse_classes_75kplus_train_071869 | 1,920 | no_license | [
{
"docstring": "数组",
"name": "middle_node",
"signature": "def middle_node(cls, head: ListNode) -> ListNode"
},
{
"docstring": "单指针",
"name": "middle_node_v2",
"signature": "def middle_node_v2(cls, head: ListNode) -> ListNode"
},
{
"docstring": "快慢指针",
"name": "middle_node_v3"... | 3 | stack_v2_sparse_classes_30k_train_012771 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def middle_node(cls, head: ListNode) -> ListNode: 数组
- def middle_node_v2(cls, head: ListNode) -> ListNode: 单指针
- def middle_node_v3(cls, head: ListNode) -> ListNode: 快慢指针 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def middle_node(cls, head: ListNode) -> ListNode: 数组
- def middle_node_v2(cls, head: ListNode) -> ListNode: 单指针
- def middle_node_v3(cls, head: ListNode) -> ListNode: 快慢指针
<|ske... | 1d1876620a55ff88af7bc390cf1a4fd4350d8d16 | <|skeleton|>
class Solution:
def middle_node(cls, head: ListNode) -> ListNode:
"""数组"""
<|body_0|>
def middle_node_v2(cls, head: ListNode) -> ListNode:
"""单指针"""
<|body_1|>
def middle_node_v3(cls, head: ListNode) -> ListNode:
"""快慢指针"""
<|body_2|>
<|end_sk... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def middle_node(cls, head: ListNode) -> ListNode:
"""数组"""
array = [head]
while array[-1].next:
array.append(array[-1].next)
return array[len(array) // 2]
def middle_node_v2(cls, head: ListNode) -> ListNode:
"""单指针"""
n, cur = (0, head... | the_stack_v2_python_sparse | 01-数据结构/链表/876.链表的中间结点.py | jh-lau/leetcode_in_python | train | 0 | |
b61b07855853756ae65f18936035b9d828f6706e | [
"super(StandardBlock, self).__init__()\nself.main_mapping = nn.Sequential(convolution(in_channels=in_channels, out_channels=in_channels, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=True), normalization(num_features=in_channels, affine=True, track_running_stats=True), activation(), convolution(in_channel... | <|body_start_0|>
super(StandardBlock, self).__init__()
self.main_mapping = nn.Sequential(convolution(in_channels=in_channels, out_channels=in_channels, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=True), normalization(num_features=in_channels, affine=True, track_running_stats=True), activatio... | This class implements a standard convolution block including two convolutions, each followed by a normalization and an activation function. | StandardBlock | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StandardBlock:
"""This class implements a standard convolution block including two convolutions, each followed by a normalization and an activation function."""
def __init__(self, in_channels: int, out_channels: int, convolution: Type=nn.Conv2d, normalization: Type=nn.InstanceNorm2d, activat... | stack_v2_sparse_classes_75kplus_train_071870 | 10,361 | permissive | [
{
"docstring": "Constructor method :param in_channels: (int) Number of input channels :param out_channels: (int) Number of output channels :param convolution: (Type) Type of convolution to be utilized :param normalization: (Type) Type of normalization to be utilized :param activation: (Type) Type of activation ... | 2 | null | Implement the Python class `StandardBlock` described below.
Class description:
This class implements a standard convolution block including two convolutions, each followed by a normalization and an activation function.
Method signatures and docstrings:
- def __init__(self, in_channels: int, out_channels: int, convolu... | Implement the Python class `StandardBlock` described below.
Class description:
This class implements a standard convolution block including two convolutions, each followed by a normalization and an activation function.
Method signatures and docstrings:
- def __init__(self, in_channels: int, out_channels: int, convolu... | 7b43b3e021ffad0a516571d7af92c718dd82fb2a | <|skeleton|>
class StandardBlock:
"""This class implements a standard convolution block including two convolutions, each followed by a normalization and an activation function."""
def __init__(self, in_channels: int, out_channels: int, convolution: Type=nn.Conv2d, normalization: Type=nn.InstanceNorm2d, activat... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class StandardBlock:
"""This class implements a standard convolution block including two convolutions, each followed by a normalization and an activation function."""
def __init__(self, in_channels: int, out_channels: int, convolution: Type=nn.Conv2d, normalization: Type=nn.InstanceNorm2d, activation: Type=nn.... | the_stack_v2_python_sparse | backbone.py | ChristophReich1996/Cell-DETR | train | 89 |
6a6c77da9c880f4f5751ccd10b67a89561471698 | [
"self.cfg_index = cfg_index\nself.conditions = conditions\nself.pars_dir = pars_dir\nself.step_title = step_title\nself.use_defaults = use_defaults\nself.input_cfg_json_data = input_cfg_json_data\nif not self.input_cfg_json_data:\n self._get_params()",
"self.outpars = {}\nfor cfg_key in self.pars_multidict.key... | <|body_start_0|>
self.cfg_index = cfg_index
self.conditions = conditions
self.pars_dir = pars_dir
self.step_title = step_title
self.use_defaults = use_defaults
self.input_cfg_json_data = input_cfg_json_data
if not self.input_cfg_json_data:
self._get_pa... | Par | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Par:
def __init__(self, cfg_index, conditions, pars_dir, step_title, use_defaults, input_cfg_json_data):
"""Parent class for alignment_pars, astrodrizzle_pars, catalog_generation_pars, and quality_control_pars Parameters ---------- cfg_index : dictionary portion of the index config file ... | stack_v2_sparse_classes_75kplus_train_071871 | 24,456 | permissive | [
{
"docstring": "Parent class for alignment_pars, astrodrizzle_pars, catalog_generation_pars, and quality_control_pars Parameters ---------- cfg_index : dictionary portion of the index config file returned for a specific step conditions : list list of observing conditions that will be used to build the final com... | 6 | stack_v2_sparse_classes_30k_test_001508 | Implement the Python class `Par` described below.
Class description:
Implement the Par class.
Method signatures and docstrings:
- def __init__(self, cfg_index, conditions, pars_dir, step_title, use_defaults, input_cfg_json_data): Parent class for alignment_pars, astrodrizzle_pars, catalog_generation_pars, and quality... | Implement the Python class `Par` described below.
Class description:
Implement the Par class.
Method signatures and docstrings:
- def __init__(self, cfg_index, conditions, pars_dir, step_title, use_defaults, input_cfg_json_data): Parent class for alignment_pars, astrodrizzle_pars, catalog_generation_pars, and quality... | 490574e16571cd60d5cb3f9910ec08042dcaec09 | <|skeleton|>
class Par:
def __init__(self, cfg_index, conditions, pars_dir, step_title, use_defaults, input_cfg_json_data):
"""Parent class for alignment_pars, astrodrizzle_pars, catalog_generation_pars, and quality_control_pars Parameters ---------- cfg_index : dictionary portion of the index config file ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Par:
def __init__(self, cfg_index, conditions, pars_dir, step_title, use_defaults, input_cfg_json_data):
"""Parent class for alignment_pars, astrodrizzle_pars, catalog_generation_pars, and quality_control_pars Parameters ---------- cfg_index : dictionary portion of the index config file returned for a... | the_stack_v2_python_sparse | drizzlepac/hlautils/config_utils.py | eslavich/drizzlepac | train | 0 | |
30f5da1e8c105f688997e87cb4a598a63ef4cf17 | [
"self.countTable = ChainingHashMap(1000)\nself.totalTable = ChainingHashMap(1000)\nself.totalWords = 0",
"textList = text.split()\nfor i in range(len(textList) - 1):\n self.totalWords += 1\n if self.totalTable[textList[i]] == None:\n self.totalTable[textList[i]] = 1\n else:\n self.totalTabl... | <|body_start_0|>
self.countTable = ChainingHashMap(1000)
self.totalTable = ChainingHashMap(1000)
self.totalWords = 0
<|end_body_0|>
<|body_start_1|>
textList = text.split()
for i in range(len(textList) - 1):
self.totalWords += 1
if self.totalTable[textLis... | A class that allows one to generate random text in the style of some provided source text | TextGenerator | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TextGenerator:
"""A class that allows one to generate random text in the style of some provided source text"""
def __init__(self):
"""Initializes the text generator"""
<|body_0|>
def train(self, text):
"""Takes a body of text (as a string) and increases the appro... | stack_v2_sparse_classes_75kplus_train_071872 | 6,228 | no_license | [
{
"docstring": "Initializes the text generator",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Takes a body of text (as a string) and increases the appropriate frequency counts",
"name": "train",
"signature": "def train(self, text)"
},
{
"docstring": "C... | 4 | stack_v2_sparse_classes_30k_train_047617 | Implement the Python class `TextGenerator` described below.
Class description:
A class that allows one to generate random text in the style of some provided source text
Method signatures and docstrings:
- def __init__(self): Initializes the text generator
- def train(self, text): Takes a body of text (as a string) an... | Implement the Python class `TextGenerator` described below.
Class description:
A class that allows one to generate random text in the style of some provided source text
Method signatures and docstrings:
- def __init__(self): Initializes the text generator
- def train(self, text): Takes a body of text (as a string) an... | 0290deb3e1f008305fb2da353eda86210a7ba1e6 | <|skeleton|>
class TextGenerator:
"""A class that allows one to generate random text in the style of some provided source text"""
def __init__(self):
"""Initializes the text generator"""
<|body_0|>
def train(self, text):
"""Takes a body of text (as a string) and increases the appro... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TextGenerator:
"""A class that allows one to generate random text in the style of some provided source text"""
def __init__(self):
"""Initializes the text generator"""
self.countTable = ChainingHashMap(1000)
self.totalTable = ChainingHashMap(1000)
self.totalWords = 0
... | the_stack_v2_python_sparse | Random Text Generation/textgenerator.py | mbastola/Algorithms-Data-Structures-in-Python | train | 0 |
a1dd273127380c8f645f0ec31338f73ba141b04e | [
"Uniligne.__init__(self, pere, objet, attribut)\nself.ajouter_option('u', self.opt_bouger_up)\nself.ajouter_option('d', self.opt_bouger_down)",
"sujet = self.objet\ncle_fils = arguments\nsujet_fils = importeur.information.sujets.get(cle_fils)\nif not sujet_fils or not sujet.est_fils(sujet_fils):\n self.pere <<... | <|body_start_0|>
Uniligne.__init__(self, pere, objet, attribut)
self.ajouter_option('u', self.opt_bouger_up)
self.ajouter_option('d', self.opt_bouger_down)
<|end_body_0|>
<|body_start_1|>
sujet = self.objet
cle_fils = arguments
sujet_fils = importeur.information.sujets.g... | Classe définissant le contexte-éditeur 'fils'. Ce contexte permet de hiérarchiser les sujets d'aide. | EdtFils | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EdtFils:
"""Classe définissant le contexte-éditeur 'fils'. Ce contexte permet de hiérarchiser les sujets d'aide."""
def __init__(self, pere, objet=None, attribut=None):
"""Constructeur de l'éditeur."""
<|body_0|>
def opt_bouger_up(self, arguments):
"""Option perm... | stack_v2_sparse_classes_75kplus_train_071873 | 4,546 | permissive | [
{
"docstring": "Constructeur de l'éditeur.",
"name": "__init__",
"signature": "def __init__(self, pere, objet=None, attribut=None)"
},
{
"docstring": "Option permettant de bouger un sujet vers le haut de la liste. Syntaxe : /u <sujet>",
"name": "opt_bouger_up",
"signature": "def opt_boug... | 4 | null | Implement the Python class `EdtFils` described below.
Class description:
Classe définissant le contexte-éditeur 'fils'. Ce contexte permet de hiérarchiser les sujets d'aide.
Method signatures and docstrings:
- def __init__(self, pere, objet=None, attribut=None): Constructeur de l'éditeur.
- def opt_bouger_up(self, ar... | Implement the Python class `EdtFils` described below.
Class description:
Classe définissant le contexte-éditeur 'fils'. Ce contexte permet de hiérarchiser les sujets d'aide.
Method signatures and docstrings:
- def __init__(self, pere, objet=None, attribut=None): Constructeur de l'éditeur.
- def opt_bouger_up(self, ar... | 7e93bff08cdf891352efba587e89c40f3b4a2301 | <|skeleton|>
class EdtFils:
"""Classe définissant le contexte-éditeur 'fils'. Ce contexte permet de hiérarchiser les sujets d'aide."""
def __init__(self, pere, objet=None, attribut=None):
"""Constructeur de l'éditeur."""
<|body_0|>
def opt_bouger_up(self, arguments):
"""Option perm... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class EdtFils:
"""Classe définissant le contexte-éditeur 'fils'. Ce contexte permet de hiérarchiser les sujets d'aide."""
def __init__(self, pere, objet=None, attribut=None):
"""Constructeur de l'éditeur."""
Uniligne.__init__(self, pere, objet, attribut)
self.ajouter_option('u', self.op... | the_stack_v2_python_sparse | src/primaires/information/editeurs/hedit/edt_fils.py | vincent-lg/tsunami | train | 5 |
56ce47752cabfbc1604a1d051a305a6a741bfae4 | [
"res = 0\nn = len(nums)\nevs = [nums[x] for x in range(n) if x % 2 == 0]\nods = [nums[x] for x in range(n) if x % 2 != 0]\nreturn sum((min(evs[x], ods[x]) for x in range(n / 2)))",
"nums.sort()\nneg = []\nres = 0\nres += self.get_sum(nums)\nreturn res"
] | <|body_start_0|>
res = 0
n = len(nums)
evs = [nums[x] for x in range(n) if x % 2 == 0]
ods = [nums[x] for x in range(n) if x % 2 != 0]
return sum((min(evs[x], ods[x]) for x in range(n / 2)))
<|end_body_0|>
<|body_start_1|>
nums.sort()
neg = []
res = 0
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def get_sum(self, nums):
"""Doc"""
<|body_0|>
def arrayPairSum(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
res = 0
n = len(nums)
evs = [nums[x] for x in range(n) if x % ... | stack_v2_sparse_classes_75kplus_train_071874 | 517 | no_license | [
{
"docstring": "Doc",
"name": "get_sum",
"signature": "def get_sum(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "arrayPairSum",
"signature": "def arrayPairSum(self, nums)"
}
] | 2 | stack_v2_sparse_classes_30k_train_043512 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def get_sum(self, nums): Doc
- def arrayPairSum(self, nums): :type nums: List[int] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def get_sum(self, nums): Doc
- def arrayPairSum(self, nums): :type nums: List[int] :rtype: int
<|skeleton|>
class Solution:
def get_sum(self, nums):
"""Doc"""
... | b00f649598a6e57af30b517baa304f3094345f6d | <|skeleton|>
class Solution:
def get_sum(self, nums):
"""Doc"""
<|body_0|>
def arrayPairSum(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def get_sum(self, nums):
"""Doc"""
res = 0
n = len(nums)
evs = [nums[x] for x in range(n) if x % 2 == 0]
ods = [nums[x] for x in range(n) if x % 2 != 0]
return sum((min(evs[x], ods[x]) for x in range(n / 2)))
def arrayPairSum(self, nums):
... | the_stack_v2_python_sparse | array_pair_sum.py | grewy/practice_py | train | 0 | |
8141b39e473bac486091d05e3fdfc659d8f6e57f | [
"sortedBuilding = sorted([(L, -H, R) for L, R, H in buildings] + list({(R, 0, None) for _, R, _ in buildings}))\nres, hp = ([[0, 0]], [(0, float('inf'))])\nfor x, negH, R in sortedBuilding:\n while x >= hp[0][1]:\n heapq.heappop(hp)\n if negH:\n heapq.heappush(hp, (negH, R))\n if res[-1][1] +... | <|body_start_0|>
sortedBuilding = sorted([(L, -H, R) for L, R, H in buildings] + list({(R, 0, None) for _, R, _ in buildings}))
res, hp = ([[0, 0]], [(0, float('inf'))])
for x, negH, R in sortedBuilding:
while x >= hp[0][1]:
heapq.heappop(hp)
if negH:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def getSkyline(self, buildings):
""":type buildings: List[List[int]] :rtype: List[List[int]]"""
<|body_0|>
def getSkylineSlow(self, buildings):
""":type buildings: List[List[int]] :rtype: List[List[int]]"""
<|body_1|>
<|end_skeleton|>
<|body_start... | stack_v2_sparse_classes_75kplus_train_071875 | 1,831 | no_license | [
{
"docstring": ":type buildings: List[List[int]] :rtype: List[List[int]]",
"name": "getSkyline",
"signature": "def getSkyline(self, buildings)"
},
{
"docstring": ":type buildings: List[List[int]] :rtype: List[List[int]]",
"name": "getSkylineSlow",
"signature": "def getSkylineSlow(self, b... | 2 | stack_v2_sparse_classes_30k_test_001760 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def getSkyline(self, buildings): :type buildings: List[List[int]] :rtype: List[List[int]]
- def getSkylineSlow(self, buildings): :type buildings: List[List[int]] :rtype: List[Lis... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def getSkyline(self, buildings): :type buildings: List[List[int]] :rtype: List[List[int]]
- def getSkylineSlow(self, buildings): :type buildings: List[List[int]] :rtype: List[Lis... | 75aef2f6c42aeb51261b9450a24099957a084d51 | <|skeleton|>
class Solution:
def getSkyline(self, buildings):
""":type buildings: List[List[int]] :rtype: List[List[int]]"""
<|body_0|>
def getSkylineSlow(self, buildings):
""":type buildings: List[List[int]] :rtype: List[List[int]]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def getSkyline(self, buildings):
""":type buildings: List[List[int]] :rtype: List[List[int]]"""
sortedBuilding = sorted([(L, -H, R) for L, R, H in buildings] + list({(R, 0, None) for _, R, _ in buildings}))
res, hp = ([[0, 0]], [(0, float('inf'))])
for x, negH, R in s... | the_stack_v2_python_sparse | Python/0218_TheSkylineProblem/getSkyline.py | mtmmy/Leetcode | train | 3 | |
80e130debf343b1ea7769e77323115739ddc4391 | [
"if not graph.is_directed():\n raise ValueError('the graph is not directed')\nself.graph = graph\nself.T = dict()\nfor source in self.graph.iternodes():\n self.T[source] = dict()\n for target in self.graph.iternodes():\n self.T[source][target] = False\n self.T[source][source] = True",
"for sour... | <|body_start_0|>
if not graph.is_directed():
raise ValueError('the graph is not directed')
self.graph = graph
self.T = dict()
for source in self.graph.iternodes():
self.T[source] = dict()
for target in self.graph.iternodes():
self.T[sou... | Based on the BFS, O(V*(V+E)) time. | TransitiveClosureBFS | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TransitiveClosureBFS:
"""Based on the BFS, O(V*(V+E)) time."""
def __init__(self, graph):
"""The algorithm initialization, O(V**2) time."""
<|body_0|>
def run(self):
"""Executable pseudocode."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if no... | stack_v2_sparse_classes_75kplus_train_071876 | 3,816 | permissive | [
{
"docstring": "The algorithm initialization, O(V**2) time.",
"name": "__init__",
"signature": "def __init__(self, graph)"
},
{
"docstring": "Executable pseudocode.",
"name": "run",
"signature": "def run(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_029218 | Implement the Python class `TransitiveClosureBFS` described below.
Class description:
Based on the BFS, O(V*(V+E)) time.
Method signatures and docstrings:
- def __init__(self, graph): The algorithm initialization, O(V**2) time.
- def run(self): Executable pseudocode. | Implement the Python class `TransitiveClosureBFS` described below.
Class description:
Based on the BFS, O(V*(V+E)) time.
Method signatures and docstrings:
- def __init__(self, graph): The algorithm initialization, O(V**2) time.
- def run(self): Executable pseudocode.
<|skeleton|>
class TransitiveClosureBFS:
"""B... | 0ff4ae303e8824e6bb8474d23b29a7b3e5ed8e60 | <|skeleton|>
class TransitiveClosureBFS:
"""Based on the BFS, O(V*(V+E)) time."""
def __init__(self, graph):
"""The algorithm initialization, O(V**2) time."""
<|body_0|>
def run(self):
"""Executable pseudocode."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TransitiveClosureBFS:
"""Based on the BFS, O(V*(V+E)) time."""
def __init__(self, graph):
"""The algorithm initialization, O(V**2) time."""
if not graph.is_directed():
raise ValueError('the graph is not directed')
self.graph = graph
self.T = dict()
for ... | the_stack_v2_python_sparse | graphtheory/algorithms/closure.py | kgashok/graphs-dict | train | 0 |
462ecb3196a7c99896ebfdb0eb28f4dcad84f6ad | [
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')",
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')"
] | <|body_start_0|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!')
<|end_body_0|>
<|body_start_1|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not im... | Missing associated documentation comment in .proto file. | BasicServiceServicer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BasicServiceServicer:
"""Missing associated documentation comment in .proto file."""
def InferenceItem(self, request, context):
"""Missing associated documentation comment in .proto file."""
<|body_0|>
def ChangeThreads(self, request, context):
"""Missing associa... | stack_v2_sparse_classes_75kplus_train_071877 | 3,873 | permissive | [
{
"docstring": "Missing associated documentation comment in .proto file.",
"name": "InferenceItem",
"signature": "def InferenceItem(self, request, context)"
},
{
"docstring": "Missing associated documentation comment in .proto file.",
"name": "ChangeThreads",
"signature": "def ChangeThre... | 2 | stack_v2_sparse_classes_30k_train_007113 | Implement the Python class `BasicServiceServicer` described below.
Class description:
Missing associated documentation comment in .proto file.
Method signatures and docstrings:
- def InferenceItem(self, request, context): Missing associated documentation comment in .proto file.
- def ChangeThreads(self, request, cont... | Implement the Python class `BasicServiceServicer` described below.
Class description:
Missing associated documentation comment in .proto file.
Method signatures and docstrings:
- def InferenceItem(self, request, context): Missing associated documentation comment in .proto file.
- def ChangeThreads(self, request, cont... | ac090279109f4975f253e3c3f37772b6bb20aad3 | <|skeleton|>
class BasicServiceServicer:
"""Missing associated documentation comment in .proto file."""
def InferenceItem(self, request, context):
"""Missing associated documentation comment in .proto file."""
<|body_0|>
def ChangeThreads(self, request, context):
"""Missing associa... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class BasicServiceServicer:
"""Missing associated documentation comment in .proto file."""
def InferenceItem(self, request, context):
"""Missing associated documentation comment in .proto file."""
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemente... | the_stack_v2_python_sparse | vision/classification_and_detection/python/basic_pb2_grpc.py | omarnaman/inference | train | 0 |
78d14cf55078c93108950c6e5aef9377914cdd2b | [
"if root:\n head, tail = self.helper(root)\n return head\nreturn None",
"head, tail = (root, root)\nif root.left:\n lh, lt = self.helper(root.left)\n lt.right = root\n root.left = lt\n head = lh\nif root.right:\n rh, rt = self.helper(root.right)\n rh.left = root\n root.right = rh\n t... | <|body_start_0|>
if root:
head, tail = self.helper(root)
return head
return None
<|end_body_0|>
<|body_start_1|>
head, tail = (root, root)
if root.left:
lh, lt = self.helper(root.left)
lt.right = root
root.left = lt
... | Solution3 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution3:
def treeToDoublyList(self, root):
""":type root: Node :rtype: Node"""
<|body_0|>
def helper(self, root):
"""Idea: Construct a DLL for each subtree, then return the head and tail"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if root:
... | stack_v2_sparse_classes_75kplus_train_071878 | 3,060 | no_license | [
{
"docstring": ":type root: Node :rtype: Node",
"name": "treeToDoublyList",
"signature": "def treeToDoublyList(self, root)"
},
{
"docstring": "Idea: Construct a DLL for each subtree, then return the head and tail",
"name": "helper",
"signature": "def helper(self, root)"
}
] | 2 | stack_v2_sparse_classes_30k_train_047624 | Implement the Python class `Solution3` described below.
Class description:
Implement the Solution3 class.
Method signatures and docstrings:
- def treeToDoublyList(self, root): :type root: Node :rtype: Node
- def helper(self, root): Idea: Construct a DLL for each subtree, then return the head and tail | Implement the Python class `Solution3` described below.
Class description:
Implement the Solution3 class.
Method signatures and docstrings:
- def treeToDoublyList(self, root): :type root: Node :rtype: Node
- def helper(self, root): Idea: Construct a DLL for each subtree, then return the head and tail
<|skeleton|>
cl... | 11d6bf2ba7b50c07e048df37c4e05c8f46b92241 | <|skeleton|>
class Solution3:
def treeToDoublyList(self, root):
""":type root: Node :rtype: Node"""
<|body_0|>
def helper(self, root):
"""Idea: Construct a DLL for each subtree, then return the head and tail"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution3:
def treeToDoublyList(self, root):
""":type root: Node :rtype: Node"""
if root:
head, tail = self.helper(root)
return head
return None
def helper(self, root):
"""Idea: Construct a DLL for each subtree, then return the head and tail"""
... | the_stack_v2_python_sparse | LeetCodes/facebook/Convert Binary SearchTreetoSortedDoublyLinkedList.py | chutianwen/LeetCodes | train | 0 | |
30494a7b1a538396380a9897b4209b08a10edfaa | [
"try:\n ScfUser.objects.get(username=data)\n raise ValidationError('User {} name already exist'.format(data))\nexcept ScfUser.DoesNotExist:\n return data",
"try:\n ScfUser.objects.get(email=data)\n raise ValidationError('User {} email already exist'.format(data))\nexcept ScfUser.DoesNotExist:\n ... | <|body_start_0|>
try:
ScfUser.objects.get(username=data)
raise ValidationError('User {} name already exist'.format(data))
except ScfUser.DoesNotExist:
return data
<|end_body_0|>
<|body_start_1|>
try:
ScfUser.objects.get(email=data)
rai... | Signup with mandatory fields | SignupSerializer | [
"Apache-2.0",
"GPL-3.0-only",
"BSD-3-Clause",
"AGPL-3.0-only",
"GPL-1.0-or-later",
"Python-2.0",
"BSD-2-Clause",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SignupSerializer:
"""Signup with mandatory fields"""
def validate_username(self, data):
"""check user name is exist or not"""
<|body_0|>
def validate_email(self, data):
"""check email is exist or not"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_75kplus_train_071879 | 4,134 | permissive | [
{
"docstring": "check user name is exist or not",
"name": "validate_username",
"signature": "def validate_username(self, data)"
},
{
"docstring": "check email is exist or not",
"name": "validate_email",
"signature": "def validate_email(self, data)"
}
] | 2 | stack_v2_sparse_classes_30k_train_044676 | Implement the Python class `SignupSerializer` described below.
Class description:
Signup with mandatory fields
Method signatures and docstrings:
- def validate_username(self, data): check user name is exist or not
- def validate_email(self, data): check email is exist or not | Implement the Python class `SignupSerializer` described below.
Class description:
Signup with mandatory fields
Method signatures and docstrings:
- def validate_username(self, data): check user name is exist or not
- def validate_email(self, data): check email is exist or not
<|skeleton|>
class SignupSerializer:
... | 4df3f46e35eb8fcab796be27fc1cc7fa7ed561f3 | <|skeleton|>
class SignupSerializer:
"""Signup with mandatory fields"""
def validate_username(self, data):
"""check user name is exist or not"""
<|body_0|>
def validate_email(self, data):
"""check email is exist or not"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SignupSerializer:
"""Signup with mandatory fields"""
def validate_username(self, data):
"""check user name is exist or not"""
try:
ScfUser.objects.get(username=data)
raise ValidationError('User {} name already exist'.format(data))
except ScfUser.DoesNotExis... | the_stack_v2_python_sparse | SCRM/ums/serializers.py | aricent/secure-cloud-native-fabric | train | 2 |
7b2b1c18377a9cb3b9cf0ce37624c37013f4c92c | [
"items = self.node(parent)\nif items and kwargs:\n for item in items:\n for key, value in kwargs.iteritems():\n setattr(item, key, value)\nreturn items",
"try:\n return self.node.scope[name]\nexcept KeyError:\n msg = \"'%s' object has no attribute '%s'\"\n raise AttributeError(msg % ... | <|body_start_0|>
items = self.node(parent)
if items and kwargs:
for item in items:
for key, value in kwargs.iteritems():
setattr(item, key, value)
return items
<|end_body_0|>
<|body_start_1|>
try:
return self.node.scope[name]
... | A class representing a template instantiation. Instances of this class are created by instances of Template. They should not be created directly by user code. | TemplateInstance | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TemplateInstance:
"""A class representing a template instantiation. Instances of this class are created by instances of Template. They should not be created directly by user code."""
def __call__(self, parent=None, **kwargs):
"""Instantiate the list of items for the template. Paramet... | stack_v2_sparse_classes_75kplus_train_071880 | 8,361 | permissive | [
{
"docstring": "Instantiate the list of items for the template. Parameters ---------- parent : Object, optional The parent object for the generated objects. **kwargs Additional keyword arguments to apply to the returned items. Returns ------- result : list The list of objects generated by the template.",
"n... | 2 | stack_v2_sparse_classes_30k_test_001990 | Implement the Python class `TemplateInstance` described below.
Class description:
A class representing a template instantiation. Instances of this class are created by instances of Template. They should not be created directly by user code.
Method signatures and docstrings:
- def __call__(self, parent=None, **kwargs)... | Implement the Python class `TemplateInstance` described below.
Class description:
A class representing a template instantiation. Instances of this class are created by instances of Template. They should not be created directly by user code.
Method signatures and docstrings:
- def __call__(self, parent=None, **kwargs)... | 1544e7fb371b8f941cfa2fde682795e479380284 | <|skeleton|>
class TemplateInstance:
"""A class representing a template instantiation. Instances of this class are created by instances of Template. They should not be created directly by user code."""
def __call__(self, parent=None, **kwargs):
"""Instantiate the list of items for the template. Paramet... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TemplateInstance:
"""A class representing a template instantiation. Instances of this class are created by instances of Template. They should not be created directly by user code."""
def __call__(self, parent=None, **kwargs):
"""Instantiate the list of items for the template. Parameters ---------... | the_stack_v2_python_sparse | enaml/core/template.py | MatthieuDartiailh/enaml | train | 26 |
1f5e3faf3330b45c3fec6323424104ff061d18fc | [
"starttime = int(time.time())\ncount = 0\nwhile True:\n elements = self.find_elements(by=by, value=value)\n if not elements:\n time.sleep(0.1)\n nowtime = int(time.time())\n if nowtime - starttime > outtime:\n raise TypeError('此xpath未找到元素：{}'.format(value))\n continue\n ... | <|body_start_0|>
starttime = int(time.time())
count = 0
while True:
elements = self.find_elements(by=by, value=value)
if not elements:
time.sleep(0.1)
nowtime = int(time.time())
if nowtime - starttime > outtime:
... | Driver | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Driver:
def getelement(self, value=None, by=By.XPATH, outtime=10):
"""返回xpath指向的元素，如果指向多个可见的，只返回第一个，能自动过滤网页中的隐藏元素，并且带超时等待 :param value: xpath，或者是用其他方式查找元素依赖的参数 :param by: 默认用xpath的方法去找，也可以根据自己的需求定义 :param outtime: 一个作用是等待元素出现，第二是配置了超时时间,不能低于2s，有可能会导致元素获取不到 :return: webelemnet元素"""
... | stack_v2_sparse_classes_75kplus_train_071881 | 6,948 | no_license | [
{
"docstring": "返回xpath指向的元素，如果指向多个可见的，只返回第一个，能自动过滤网页中的隐藏元素，并且带超时等待 :param value: xpath，或者是用其他方式查找元素依赖的参数 :param by: 默认用xpath的方法去找，也可以根据自己的需求定义 :param outtime: 一个作用是等待元素出现，第二是配置了超时时间,不能低于2s，有可能会导致元素获取不到 :return: webelemnet元素",
"name": "getelement",
"signature": "def getelement(self, value=None, by=By.XP... | 4 | stack_v2_sparse_classes_30k_train_027112 | Implement the Python class `Driver` described below.
Class description:
Implement the Driver class.
Method signatures and docstrings:
- def getelement(self, value=None, by=By.XPATH, outtime=10): 返回xpath指向的元素，如果指向多个可见的，只返回第一个，能自动过滤网页中的隐藏元素，并且带超时等待 :param value: xpath，或者是用其他方式查找元素依赖的参数 :param by: 默认用xpath的方法去找，也可以根据自己的... | Implement the Python class `Driver` described below.
Class description:
Implement the Driver class.
Method signatures and docstrings:
- def getelement(self, value=None, by=By.XPATH, outtime=10): 返回xpath指向的元素，如果指向多个可见的，只返回第一个，能自动过滤网页中的隐藏元素，并且带超时等待 :param value: xpath，或者是用其他方式查找元素依赖的参数 :param by: 默认用xpath的方法去找，也可以根据自己的... | 504a454503895371a7c5d679684560d4239b81bf | <|skeleton|>
class Driver:
def getelement(self, value=None, by=By.XPATH, outtime=10):
"""返回xpath指向的元素，如果指向多个可见的，只返回第一个，能自动过滤网页中的隐藏元素，并且带超时等待 :param value: xpath，或者是用其他方式查找元素依赖的参数 :param by: 默认用xpath的方法去找，也可以根据自己的需求定义 :param outtime: 一个作用是等待元素出现，第二是配置了超时时间,不能低于2s，有可能会导致元素获取不到 :return: webelemnet元素"""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Driver:
def getelement(self, value=None, by=By.XPATH, outtime=10):
"""返回xpath指向的元素，如果指向多个可见的，只返回第一个，能自动过滤网页中的隐藏元素，并且带超时等待 :param value: xpath，或者是用其他方式查找元素依赖的参数 :param by: 默认用xpath的方法去找，也可以根据自己的需求定义 :param outtime: 一个作用是等待元素出现，第二是配置了超时时间,不能低于2s，有可能会导致元素获取不到 :return: webelemnet元素"""
starttime = ... | the_stack_v2_python_sparse | autotest.py | xiaoshihu/learn | train | 2 | |
cf586e2b98dd52477c0779f45bc3eb91dbe87816 | [
"super(HybridAlluviumModel, self).__init__(input_file=input_file, params=params)\nself.flow_router = FlowRouter(self.grid, **self.params)\nself.lake_filler = DepressionFinderAndRouter(self.grid, **self.params)\nif self.params['discharge_method'] is not None:\n if self.params['discharge_method'] == 'area_field':\... | <|body_start_0|>
super(HybridAlluviumModel, self).__init__(input_file=input_file, params=params)
self.flow_router = FlowRouter(self.grid, **self.params)
self.lake_filler = DepressionFinderAndRouter(self.grid, **self.params)
if self.params['discharge_method'] is not None:
if s... | A HybridAlluviumModel computes erosion of sediment and bedrock using dual mass conservation on the bed and in the water column. It applies exponential entrainment rules to account for bed cover. | HybridAlluviumModel | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HybridAlluviumModel:
"""A HybridAlluviumModel computes erosion of sediment and bedrock using dual mass conservation on the bed and in the water column. It applies exponential entrainment rules to account for bed cover."""
def __init__(self, input_file=None, params=None):
"""Initializ... | stack_v2_sparse_classes_75kplus_train_071882 | 3,512 | no_license | [
{
"docstring": "Initialize the HybridAlluviumModel.",
"name": "__init__",
"signature": "def __init__(self, input_file=None, params=None)"
},
{
"docstring": "Advance model for one time-step of duration dt.",
"name": "run_one_step",
"signature": "def run_one_step(self, dt)"
}
] | 2 | null | Implement the Python class `HybridAlluviumModel` described below.
Class description:
A HybridAlluviumModel computes erosion of sediment and bedrock using dual mass conservation on the bed and in the water column. It applies exponential entrainment rules to account for bed cover.
Method signatures and docstrings:
- de... | Implement the Python class `HybridAlluviumModel` described below.
Class description:
A HybridAlluviumModel computes erosion of sediment and bedrock using dual mass conservation on the bed and in the water column. It applies exponential entrainment rules to account for bed cover.
Method signatures and docstrings:
- de... | 3506ec741a7c8a170ea654d40c6119fefe1b93ba | <|skeleton|>
class HybridAlluviumModel:
"""A HybridAlluviumModel computes erosion of sediment and bedrock using dual mass conservation on the bed and in the water column. It applies exponential entrainment rules to account for bed cover."""
def __init__(self, input_file=None, params=None):
"""Initializ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class HybridAlluviumModel:
"""A HybridAlluviumModel computes erosion of sediment and bedrock using dual mass conservation on the bed and in the water column. It applies exponential entrainment rules to account for bed cover."""
def __init__(self, input_file=None, params=None):
"""Initialize the HybridA... | the_stack_v2_python_sparse | erosion_modeling_suite/erosion_model/single_component/hybrid_alluvium/hybrid_alluvium_model.py | kbarnhart/inverting_topography_postglacial | train | 4 |
22e3916e150a9d46ab71c346c824bd3d63c807ef | [
"self.found = found\nself.displaying = displaying\nself.more_available = more_available\nself.created_date = created_date\nself.institutions = institutions\nself.additional_properties = additional_properties",
"if dictionary is None:\n return None\nfound = dictionary.get('found')\ndisplaying = dictionary.get('... | <|body_start_0|>
self.found = found
self.displaying = displaying
self.more_available = more_available
self.created_date = created_date
self.institutions = institutions
self.additional_properties = additional_properties
<|end_body_0|>
<|body_start_1|>
if dictionar... | Implementation of the 'Get Certified Institutions Response' model. TODO: type model description here. Attributes: found (int): Total number of results found displaying (int): Displaying count more_available (bool): Indicates if there are more institutions to display that match the parameters created_date (int): Date th... | GetCertifiedInstitutionsResponse | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GetCertifiedInstitutionsResponse:
"""Implementation of the 'Get Certified Institutions Response' model. TODO: type model description here. Attributes: found (int): Total number of results found displaying (int): Displaying count more_available (bool): Indicates if there are more institutions to d... | stack_v2_sparse_classes_75kplus_train_071883 | 3,106 | permissive | [
{
"docstring": "Constructor for the GetCertifiedInstitutionsResponse class",
"name": "__init__",
"signature": "def __init__(self, found=None, displaying=None, more_available=None, created_date=None, institutions=None, additional_properties={})"
},
{
"docstring": "Creates an instance of this mode... | 2 | stack_v2_sparse_classes_30k_train_039924 | Implement the Python class `GetCertifiedInstitutionsResponse` described below.
Class description:
Implementation of the 'Get Certified Institutions Response' model. TODO: type model description here. Attributes: found (int): Total number of results found displaying (int): Displaying count more_available (bool): Indica... | Implement the Python class `GetCertifiedInstitutionsResponse` described below.
Class description:
Implementation of the 'Get Certified Institutions Response' model. TODO: type model description here. Attributes: found (int): Total number of results found displaying (int): Displaying count more_available (bool): Indica... | b2ab1ded435db75c78d42261f5e4acd2a3061487 | <|skeleton|>
class GetCertifiedInstitutionsResponse:
"""Implementation of the 'Get Certified Institutions Response' model. TODO: type model description here. Attributes: found (int): Total number of results found displaying (int): Displaying count more_available (bool): Indicates if there are more institutions to d... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class GetCertifiedInstitutionsResponse:
"""Implementation of the 'Get Certified Institutions Response' model. TODO: type model description here. Attributes: found (int): Total number of results found displaying (int): Displaying count more_available (bool): Indicates if there are more institutions to display that m... | the_stack_v2_python_sparse | finicityapi/models/get_certified_institutions_response.py | monarchmoney/finicity-python | train | 0 |
3fd636b94e876d923862d5c30b36c30fcef28fdf | [
"li.append(root.val)\nif not root.left and (not root.right):\n if root.val == sum:\n self.li.append(li)\n return\n else:\n return\nsum -= root.val\n'\\n There is a more clear way:\\n \\n '\ntmp_left = li[:]\ntmp_right = li[:]\nif root.left:\n self.DFS(root.left, tm... | <|body_start_0|>
li.append(root.val)
if not root.left and (not root.right):
if root.val == sum:
self.li.append(li)
return
else:
return
sum -= root.val
'\n There is a more clear way:\n \n '
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def DFS(self, root, li, sum):
"""More clear way if not root.left and not root.right: if root.val==sum: self.li.append(li+[root.val]) sum-=root.val if root.left:self.DFS(root.left, [root.val]+li,sum) if root.right:self.DFS(root.right, [root.val]+li,sum)"""
<|body_0|>
... | stack_v2_sparse_classes_75kplus_train_071884 | 1,469 | no_license | [
{
"docstring": "More clear way if not root.left and not root.right: if root.val==sum: self.li.append(li+[root.val]) sum-=root.val if root.left:self.DFS(root.left, [root.val]+li,sum) if root.right:self.DFS(root.right, [root.val]+li,sum)",
"name": "DFS",
"signature": "def DFS(self, root, li, sum)"
},
... | 2 | stack_v2_sparse_classes_30k_train_011913 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def DFS(self, root, li, sum): More clear way if not root.left and not root.right: if root.val==sum: self.li.append(li+[root.val]) sum-=root.val if root.left:self.DFS(root.left, [... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def DFS(self, root, li, sum): More clear way if not root.left and not root.right: if root.val==sum: self.li.append(li+[root.val]) sum-=root.val if root.left:self.DFS(root.left, [... | 1c427934dc4ee4dce76fefbe1c1d7caeefe09946 | <|skeleton|>
class Solution:
def DFS(self, root, li, sum):
"""More clear way if not root.left and not root.right: if root.val==sum: self.li.append(li+[root.val]) sum-=root.val if root.left:self.DFS(root.left, [root.val]+li,sum) if root.right:self.DFS(root.right, [root.val]+li,sum)"""
<|body_0|>
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def DFS(self, root, li, sum):
"""More clear way if not root.left and not root.right: if root.val==sum: self.li.append(li+[root.val]) sum-=root.val if root.left:self.DFS(root.left, [root.val]+li,sum) if root.right:self.DFS(root.right, [root.val]+li,sum)"""
li.append(root.val)
... | the_stack_v2_python_sparse | 113_path_sum_2.py | tek-life/algorithm-practice | train | 0 | |
b4bfaa705ed7e4580a6799aa47c50f45c3df0ebf | [
"queryset = super().get_queryset()\nif self.request.GET.get('empresa'):\n queryset = queryset.filter(name__icontains=self.request.GET['empresa'])\n return queryset",
"context = super().get_context_data(**kwargs)\ncompanies = context['companies'] or []\ncompany_user_profiles = [company.users.all() for compan... | <|body_start_0|>
queryset = super().get_queryset()
if self.request.GET.get('empresa'):
queryset = queryset.filter(name__icontains=self.request.GET['empresa'])
return queryset
<|end_body_0|>
<|body_start_1|>
context = super().get_context_data(**kwargs)
companies =... | CompanyAssociationListView | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CompanyAssociationListView:
def get_queryset(self):
"""Filter companies if 'empresa' is passed as query param with the search value"""
<|body_0|>
def get_context_data(self, **kwargs):
"""Add 'busqueda' to context if 'empresa' is passed as query param, in order to set... | stack_v2_sparse_classes_75kplus_train_071885 | 10,214 | permissive | [
{
"docstring": "Filter companies if 'empresa' is passed as query param with the search value",
"name": "get_queryset",
"signature": "def get_queryset(self)"
},
{
"docstring": "Add 'busqueda' to context if 'empresa' is passed as query param, in order to set the search input previous value.",
... | 2 | stack_v2_sparse_classes_30k_train_000022 | Implement the Python class `CompanyAssociationListView` described below.
Class description:
Implement the CompanyAssociationListView class.
Method signatures and docstrings:
- def get_queryset(self): Filter companies if 'empresa' is passed as query param with the search value
- def get_context_data(self, **kwargs): A... | Implement the Python class `CompanyAssociationListView` described below.
Class description:
Implement the CompanyAssociationListView class.
Method signatures and docstrings:
- def get_queryset(self): Filter companies if 'empresa' is passed as query param with the search value
- def get_context_data(self, **kwargs): A... | 5f88d1ea0cea9bd67547b70dc2c8bbaa3b8b9d03 | <|skeleton|>
class CompanyAssociationListView:
def get_queryset(self):
"""Filter companies if 'empresa' is passed as query param with the search value"""
<|body_0|>
def get_context_data(self, **kwargs):
"""Add 'busqueda' to context if 'empresa' is passed as query param, in order to set... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CompanyAssociationListView:
def get_queryset(self):
"""Filter companies if 'empresa' is passed as query param with the search value"""
queryset = super().get_queryset()
if self.request.GET.get('empresa'):
queryset = queryset.filter(name__icontains=self.request.GET['empresa'... | the_stack_v2_python_sparse | pycompanies/views.py | PyAr/pyarweb | train | 64 | |
95f8d5cdb04db131eec782075bf3a3abf601f4e7 | [
"self.momentum = momentum\nvelocitys = dict()\nfor k, v in model.params.items():\n velocitys[k] = np.zeros_like(v)\nself.velocitys = velocitys",
"momentum = self.momentum\nvelocitys = self.velocitys\nparams = model.params\ngrads = model.grads\nfor k in grads:\n velocitys[k] = momentum * velocitys[k] + learn... | <|body_start_0|>
self.momentum = momentum
velocitys = dict()
for k, v in model.params.items():
velocitys[k] = np.zeros_like(v)
self.velocitys = velocitys
<|end_body_0|>
<|body_start_1|>
momentum = self.momentum
velocitys = self.velocitys
params = mode... | SGDmomentumOptim | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SGDmomentumOptim:
def __init__(self, model, momentum=0.5):
"""Inputs: :param model: a neural netowrk class object :param momentum: (float)"""
<|body_0|>
def step(self, model, learning_rate):
"""Implement a one-step SGD+momentum update on network's parameters Inputs: ... | stack_v2_sparse_classes_75kplus_train_071886 | 9,004 | no_license | [
{
"docstring": "Inputs: :param model: a neural netowrk class object :param momentum: (float)",
"name": "__init__",
"signature": "def __init__(self, model, momentum=0.5)"
},
{
"docstring": "Implement a one-step SGD+momentum update on network's parameters Inputs: :param model: a neural network cla... | 2 | stack_v2_sparse_classes_30k_train_004696 | Implement the Python class `SGDmomentumOptim` described below.
Class description:
Implement the SGDmomentumOptim class.
Method signatures and docstrings:
- def __init__(self, model, momentum=0.5): Inputs: :param model: a neural netowrk class object :param momentum: (float)
- def step(self, model, learning_rate): Impl... | Implement the Python class `SGDmomentumOptim` described below.
Class description:
Implement the SGDmomentumOptim class.
Method signatures and docstrings:
- def __init__(self, model, momentum=0.5): Inputs: :param model: a neural netowrk class object :param momentum: (float)
- def step(self, model, learning_rate): Impl... | a401d09c28432109e9ced10e5011bff97dda05b9 | <|skeleton|>
class SGDmomentumOptim:
def __init__(self, model, momentum=0.5):
"""Inputs: :param model: a neural netowrk class object :param momentum: (float)"""
<|body_0|>
def step(self, model, learning_rate):
"""Implement a one-step SGD+momentum update on network's parameters Inputs: ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SGDmomentumOptim:
def __init__(self, model, momentum=0.5):
"""Inputs: :param model: a neural netowrk class object :param momentum: (float)"""
self.momentum = momentum
velocitys = dict()
for k, v in model.params.items():
velocitys[k] = np.zeros_like(v)
self.v... | the_stack_v2_python_sparse | assignment2/E4040.2017.Assign2.xw2501/E4040.2017.Assign2.xw2501/ecbm4040/optimizers.py | xw2501/Deep_Learning_study | train | 7 | |
814e5fcc0d1f13731b57488fba287ebc4e3d681a | [
"self._stage_pool = collections.deque()\nif timeout is None:\n self._cvar = threading.Condition()\nelse:\n from . import shared_queue\n self._cvar = shared_queue.HeartbeatCondition(timeout)\nself._timeout = timeout\nfor _ in range(N_stages):\n self._stage_pool.append(StagePool.StagePoolWrapper(dataset.c... | <|body_start_0|>
self._stage_pool = collections.deque()
if timeout is None:
self._cvar = threading.Condition()
else:
from . import shared_queue
self._cvar = shared_queue.HeartbeatCondition(timeout)
self._timeout = timeout
for _ in range(N_stage... | Manages a pool from which stages can be acquired and returned. | StagePool | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StagePool:
"""Manages a pool from which stages can be acquired and returned."""
def __init__(self, dataset, stage_size, N_stages, timeout=None):
"""Create a stage pool based on a given dataset. :param dataset: Parent dataset that is used to calculate the size of the member stage elem... | stack_v2_sparse_classes_75kplus_train_071887 | 4,636 | permissive | [
{
"docstring": "Create a stage pool based on a given dataset. :param dataset: Parent dataset that is used to calculate the size of the member stage elements. :stage_size: Size of each stage in the pool, this is passed to the constructor for the stage. :N_stages: The number of stages to be allocated in the pool.... | 3 | stack_v2_sparse_classes_30k_train_054046 | Implement the Python class `StagePool` described below.
Class description:
Manages a pool from which stages can be acquired and returned.
Method signatures and docstrings:
- def __init__(self, dataset, stage_size, N_stages, timeout=None): Create a stage pool based on a given dataset. :param dataset: Parent dataset th... | Implement the Python class `StagePool` described below.
Class description:
Manages a pool from which stages can be acquired and returned.
Method signatures and docstrings:
- def __init__(self, dataset, stage_size, N_stages, timeout=None): Create a stage pool based on a given dataset. :param dataset: Parent dataset th... | 43a48122c70917761c04e178d11132ccadbc28b6 | <|skeleton|>
class StagePool:
"""Manages a pool from which stages can be acquired and returned."""
def __init__(self, dataset, stage_size, N_stages, timeout=None):
"""Create a stage pool based on a given dataset. :param dataset: Parent dataset that is used to calculate the size of the member stage elem... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class StagePool:
"""Manages a pool from which stages can be acquired and returned."""
def __init__(self, dataset, stage_size, N_stages, timeout=None):
"""Create a stage pool based on a given dataset. :param dataset: Parent dataset that is used to calculate the size of the member stage elements. :stage_... | the_stack_v2_python_sparse | multitables/stage.py | ghcollin/multitables | train | 15 |
47c1372c924a27b39091b5582b11ed75eb85d0cb | [
"key_string = 'sqlite_version'\nerror_strings = ['fts3tokenize', 'unknown tokenizer', 'file error', 'unable to delete/modify user-function due to active statements', 'DISTINCT is not supported for window functions', 'ORDER BY clause', 'abbreviated query algorithm search']\nkey_error_strings = [error_strings[0], err... | <|body_start_0|>
key_string = 'sqlite_version'
error_strings = ['fts3tokenize', 'unknown tokenizer', 'file error', 'unable to delete/modify user-function due to active statements', 'DISTINCT is not supported for window functions', 'ORDER BY clause', 'abbreviated query algorithm search']
key_erro... | Seeker (Identifier) for the zlib open source library. | SqliteSeeker | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SqliteSeeker:
"""Seeker (Identifier) for the zlib open source library."""
def searchLib(self, logger):
"""Check if the open source library is located somewhere in the binary. Args: logger (logger): elementals logger instance Return Value: number of library instances that were found i... | stack_v2_sparse_classes_75kplus_train_071888 | 3,269 | permissive | [
{
"docstring": "Check if the open source library is located somewhere in the binary. Args: logger (logger): elementals logger instance Return Value: number of library instances that were found in the binary",
"name": "searchLib",
"signature": "def searchLib(self, logger)"
},
{
"docstring": "Iden... | 2 | stack_v2_sparse_classes_30k_train_052879 | Implement the Python class `SqliteSeeker` described below.
Class description:
Seeker (Identifier) for the zlib open source library.
Method signatures and docstrings:
- def searchLib(self, logger): Check if the open source library is located somewhere in the binary. Args: logger (logger): elementals logger instance Re... | Implement the Python class `SqliteSeeker` described below.
Class description:
Seeker (Identifier) for the zlib open source library.
Method signatures and docstrings:
- def searchLib(self, logger): Check if the open source library is located somewhere in the binary. Args: logger (logger): elementals logger instance Re... | 03adda0775bfa338bfc61bfac14fe457b283a85c | <|skeleton|>
class SqliteSeeker:
"""Seeker (Identifier) for the zlib open source library."""
def searchLib(self, logger):
"""Check if the open source library is located somewhere in the binary. Args: logger (logger): elementals logger instance Return Value: number of library instances that were found i... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SqliteSeeker:
"""Seeker (Identifier) for the zlib open source library."""
def searchLib(self, logger):
"""Check if the open source library is located somewhere in the binary. Args: logger (logger): elementals logger instance Return Value: number of library instances that were found in the binary"... | the_stack_v2_python_sparse | src/libs/sqlite.py | MITRE-Reversing-Internship/Karta-Modified | train | 1 |
1b6299249952c91c17556548319bdf85b8e5809f | [
"system = Atoms(cell=[[3.3, 0.0, 0.0], [0.0, 1.0, 0.0], [-1.0, 0.0, 3.0]], scaled_positions=[[0.5, 0.5, 0.0], [0.5, 0.0, 0.5], [0.0, 0.0, 0.0], [0.0, 0.5, 0.5]], symbols=['C', 'H', 'C', 'H'], pbc=True)\ncorrect_state = ['d', 'a', 'd', 'a']\nanalyzer = SymmetryAnalyzer(system)\norig_wyckoffs = analyzer.get_wyckoff_l... | <|body_start_0|>
system = Atoms(cell=[[3.3, 0.0, 0.0], [0.0, 1.0, 0.0], [-1.0, 0.0, 3.0]], scaled_positions=[[0.5, 0.5, 0.0], [0.5, 0.0, 0.5], [0.0, 0.0, 0.0], [0.0, 0.5, 0.5]], symbols=['C', 'H', 'C', 'H'], pbc=True)
correct_state = ['d', 'a', 'd', 'a']
analyzer = SymmetryAnalyzer(system)
... | Tests that the correct normalizer is applied to reach minimal configuration score that defines the Wyckoff positions. | GroundStateTests | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GroundStateTests:
"""Tests that the correct normalizer is applied to reach minimal configuration score that defines the Wyckoff positions."""
def test_translation(self):
"""Test a transform that translates atoms."""
<|body_0|>
def test_transformation_affine(self):
... | stack_v2_sparse_classes_75kplus_train_071889 | 41,331 | permissive | [
{
"docstring": "Test a transform that translates atoms.",
"name": "test_translation",
"signature": "def test_translation(self)"
},
{
"docstring": "Test a transform where the transformation is a proper rigid transformation in the scaled cell basis, but will be non-rigid in the cartesian basis. Th... | 3 | stack_v2_sparse_classes_30k_train_013453 | Implement the Python class `GroundStateTests` described below.
Class description:
Tests that the correct normalizer is applied to reach minimal configuration score that defines the Wyckoff positions.
Method signatures and docstrings:
- def test_translation(self): Test a transform that translates atoms.
- def test_tra... | Implement the Python class `GroundStateTests` described below.
Class description:
Tests that the correct normalizer is applied to reach minimal configuration score that defines the Wyckoff positions.
Method signatures and docstrings:
- def test_translation(self): Test a transform that translates atoms.
- def test_tra... | ae7c5ee1912b58a32fc7ea6edbf2fa2dc9155146 | <|skeleton|>
class GroundStateTests:
"""Tests that the correct normalizer is applied to reach minimal configuration score that defines the Wyckoff positions."""
def test_translation(self):
"""Test a transform that translates atoms."""
<|body_0|>
def test_transformation_affine(self):
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class GroundStateTests:
"""Tests that the correct normalizer is applied to reach minimal configuration score that defines the Wyckoff positions."""
def test_translation(self):
"""Test a transform that translates atoms."""
system = Atoms(cell=[[3.3, 0.0, 0.0], [0.0, 1.0, 0.0], [-1.0, 0.0, 3.0]],... | the_stack_v2_python_sparse | regtests/symmetrytests.py | SINGROUP/matid | train | 25 |
1807ab34f2edb6d249c1c488a59fb9fa964fdeec | [
"self.resume_command = a.get_command_message(resume_args)\nself.command = get_log_reversed(command_log, stack_level)\nself.output_dir = get_log_reversed(dirs_log, stack_level)\nself.defaults_file = os.path.join(self.output_dir, DEFAULTS_FILE)\nself.args = [arg.decode(u.BIGML_SYS_ENCODING) for arg in shlex.split(sel... | <|body_start_0|>
self.resume_command = a.get_command_message(resume_args)
self.command = get_log_reversed(command_log, stack_level)
self.output_dir = get_log_reversed(dirs_log, stack_level)
self.defaults_file = os.path.join(self.output_dir, DEFAULTS_FILE)
self.args = [arg.decode(... | Objects derived from a stored bigmler command | StoredCommand | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StoredCommand:
"""Objects derived from a stored bigmler command"""
def __init__(self, resume_args, command_log, dirs_log, stack_level=0):
"""Constructor that extracts the command from the file ``command_log``: file for stored commands ``dirs_log``: file for associated work directorie... | stack_v2_sparse_classes_75kplus_train_071890 | 13,144 | permissive | [
{
"docstring": "Constructor that extracts the command from the file ``command_log``: file for stored commands ``dirs_log``: file for associated work directories ``stack_level``: index in the stack for the command to be retrieved",
"name": "__init__",
"signature": "def __init__(self, resume_args, command... | 2 | stack_v2_sparse_classes_30k_train_002329 | Implement the Python class `StoredCommand` described below.
Class description:
Objects derived from a stored bigmler command
Method signatures and docstrings:
- def __init__(self, resume_args, command_log, dirs_log, stack_level=0): Constructor that extracts the command from the file ``command_log``: file for stored c... | Implement the Python class `StoredCommand` described below.
Class description:
Objects derived from a stored bigmler command
Method signatures and docstrings:
- def __init__(self, resume_args, command_log, dirs_log, stack_level=0): Constructor that extracts the command from the file ``command_log``: file for stored c... | bbf221e41ef04e8d37a511a35a63216b64689449 | <|skeleton|>
class StoredCommand:
"""Objects derived from a stored bigmler command"""
def __init__(self, resume_args, command_log, dirs_log, stack_level=0):
"""Constructor that extracts the command from the file ``command_log``: file for stored commands ``dirs_log``: file for associated work directorie... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class StoredCommand:
"""Objects derived from a stored bigmler command"""
def __init__(self, resume_args, command_log, dirs_log, stack_level=0):
"""Constructor that extracts the command from the file ``command_log``: file for stored commands ``dirs_log``: file for associated work directories ``stack_lev... | the_stack_v2_python_sparse | bigmler/command.py | jaor/bigmler | train | 0 |
b81ccd7caa88effd27e064c47ab46646502c6348 | [
"self = super(DataPlane.PollSuccess, cls).__new__(cls, device, port, packet, time)\nself.expected_packet = expected_packet\nreturn self",
"try:\n stdout_save = sys.stdout\n sys.stdout = StringIO()\n print('========== RECEIVED ==========')\n if isinstance(self.expected_packet, packet.Packet):\n ... | <|body_start_0|>
self = super(DataPlane.PollSuccess, cls).__new__(cls, device, port, packet, time)
self.expected_packet = expected_packet
return self
<|end_body_0|>
<|body_start_1|>
try:
stdout_save = sys.stdout
sys.stdout = StringIO()
print('========... | Returned by poll() when it successfully finds a matching packet. | PollSuccess | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PollSuccess:
"""Returned by poll() when it successfully finds a matching packet."""
def __new__(cls, device, port, packet, expected_packet, time):
"""Initialize. (We're an immutable tuple, so we can't use __init__.)"""
<|body_0|>
def format(self):
"""Returns a st... | stack_v2_sparse_classes_75kplus_train_071891 | 35,906 | permissive | [
{
"docstring": "Initialize. (We're an immutable tuple, so we can't use __init__.)",
"name": "__new__",
"signature": "def __new__(cls, device, port, packet, expected_packet, time)"
},
{
"docstring": "Returns a string containing a nice (but verbose) representation of this packet. If the expected p... | 2 | null | Implement the Python class `PollSuccess` described below.
Class description:
Returned by poll() when it successfully finds a matching packet.
Method signatures and docstrings:
- def __new__(cls, device, port, packet, expected_packet, time): Initialize. (We're an immutable tuple, so we can't use __init__.)
- def forma... | Implement the Python class `PollSuccess` described below.
Class description:
Returned by poll() when it successfully finds a matching packet.
Method signatures and docstrings:
- def __new__(cls, device, port, packet, expected_packet, time): Initialize. (We're an immutable tuple, so we can't use __init__.)
- def forma... | d2e2d8ad005a451ad11f9d21af50079a0552921a | <|skeleton|>
class PollSuccess:
"""Returned by poll() when it successfully finds a matching packet."""
def __new__(cls, device, port, packet, expected_packet, time):
"""Initialize. (We're an immutable tuple, so we can't use __init__.)"""
<|body_0|>
def format(self):
"""Returns a st... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PollSuccess:
"""Returned by poll() when it successfully finds a matching packet."""
def __new__(cls, device, port, packet, expected_packet, time):
"""Initialize. (We're an immutable tuple, so we can't use __init__.)"""
self = super(DataPlane.PollSuccess, cls).__new__(cls, device, port, pa... | the_stack_v2_python_sparse | src/ptf/dataplane.py | p4lang/ptf | train | 131 |
790b4ef362190da006623b1aa1a5ce396ecd9608 | [
"self._build_info_path = control.get('build_info_path')\nself._build_label_pattern = control.get('build_label_pattern')\nself._build_version_pattern = control.get('build_version_pattern')\nself._capture_groups = control.get('capture_groups')\nself._fallback_build_label = control.get('fallback_build_label') or None\... | <|body_start_0|>
self._build_info_path = control.get('build_info_path')
self._build_label_pattern = control.get('build_label_pattern')
self._build_version_pattern = control.get('build_version_pattern')
self._capture_groups = control.get('capture_groups')
self._fallback_build_labe... | Implements the core functionality of the versioning tool. | VersionTool | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VersionTool:
"""Implements the core functionality of the versioning tool."""
def __init__(self, control):
"""Initializes VersionTool with the given control options. Args: control: The dictionary of options used to control the tool. Please see the moduledoc for a description of the fo... | stack_v2_sparse_classes_75kplus_train_071892 | 9,887 | permissive | [
{
"docstring": "Initializes VersionTool with the given control options. Args: control: The dictionary of options used to control the tool. Please see the moduledoc for a description of the format of this dictionary.",
"name": "__init__",
"signature": "def __init__(self, control)"
},
{
"docstring... | 4 | stack_v2_sparse_classes_30k_train_015559 | Implement the Python class `VersionTool` described below.
Class description:
Implements the core functionality of the versioning tool.
Method signatures and docstrings:
- def __init__(self, control): Initializes VersionTool with the given control options. Args: control: The dictionary of options used to control the t... | Implement the Python class `VersionTool` described below.
Class description:
Implements the core functionality of the versioning tool.
Method signatures and docstrings:
- def __init__(self, control): Initializes VersionTool with the given control options. Args: control: The dictionary of options used to control the t... | 55cf5c2bec04b05b9ab435e24174834c5681be12 | <|skeleton|>
class VersionTool:
"""Implements the core functionality of the versioning tool."""
def __init__(self, control):
"""Initializes VersionTool with the given control options. Args: control: The dictionary of options used to control the tool. Please see the moduledoc for a description of the fo... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class VersionTool:
"""Implements the core functionality of the versioning tool."""
def __init__(self, control):
"""Initializes VersionTool with the given control options. Args: control: The dictionary of options used to control the tool. Please see the moduledoc for a description of the format of this ... | the_stack_v2_python_sparse | tools/versiontool/versiontool.py | bazelbuild/rules_apple | train | 449 |
c1e0980c580a973589e2c9b9dc4500cf2002ec27 | [
"if not features.has('organizations:incidents', project.organization, actor=request.user):\n raise ResourceDoesNotExist\nreturn self.paginate(request, queryset=AlertRule.objects.fetch_for_project(project), order_by='-date_added', paginator_cls=OffsetPaginator, on_results=lambda x: serialize(x, request.user), def... | <|body_start_0|>
if not features.has('organizations:incidents', project.organization, actor=request.user):
raise ResourceDoesNotExist
return self.paginate(request, queryset=AlertRule.objects.fetch_for_project(project), order_by='-date_added', paginator_cls=OffsetPaginator, on_results=lambda ... | ProjectAlertRuleIndexEndpoint | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProjectAlertRuleIndexEndpoint:
def get(self, request, project):
"""Fetches alert rules for a project"""
<|body_0|>
def post(self, request, project):
"""Create an alert rule"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not features.has('organiz... | stack_v2_sparse_classes_75kplus_train_071893 | 1,640 | permissive | [
{
"docstring": "Fetches alert rules for a project",
"name": "get",
"signature": "def get(self, request, project)"
},
{
"docstring": "Create an alert rule",
"name": "post",
"signature": "def post(self, request, project)"
}
] | 2 | stack_v2_sparse_classes_30k_train_041426 | Implement the Python class `ProjectAlertRuleIndexEndpoint` described below.
Class description:
Implement the ProjectAlertRuleIndexEndpoint class.
Method signatures and docstrings:
- def get(self, request, project): Fetches alert rules for a project
- def post(self, request, project): Create an alert rule | Implement the Python class `ProjectAlertRuleIndexEndpoint` described below.
Class description:
Implement the ProjectAlertRuleIndexEndpoint class.
Method signatures and docstrings:
- def get(self, request, project): Fetches alert rules for a project
- def post(self, request, project): Create an alert rule
<|skeleton|... | c0d9ea9be63887654f9bf3bcc386969f2fb0b8a4 | <|skeleton|>
class ProjectAlertRuleIndexEndpoint:
def get(self, request, project):
"""Fetches alert rules for a project"""
<|body_0|>
def post(self, request, project):
"""Create an alert rule"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ProjectAlertRuleIndexEndpoint:
def get(self, request, project):
"""Fetches alert rules for a project"""
if not features.has('organizations:incidents', project.organization, actor=request.user):
raise ResourceDoesNotExist
return self.paginate(request, queryset=AlertRule.obje... | the_stack_v2_python_sparse | src/sentry/incidents/endpoints/project_alert_rule_index.py | kiranps/sentry | train | 1 | |
50fc99b90c935089ead7d3ea45ba25f2c45fe583 | [
"data = etree.Element('data')\nfor key, value in result.items():\n room = etree.SubElement(data, 'room', id=str(key))\n room.text = value['name']\n for stud in value['students']:\n student = etree.SubElement(room, 'student')\n student.text = stud\ndata = etree.ElementTree(data)\nreturn data",... | <|body_start_0|>
data = etree.Element('data')
for key, value in result.items():
room = etree.SubElement(data, 'room', id=str(key))
room.text = value['name']
for stud in value['students']:
student = etree.SubElement(room, 'student')
stud... | XMLSerializer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class XMLSerializer:
def create_xml_data(self, result: dict):
"""Creating structure XML file"""
<|body_0|>
def output_xml(result: dict, name_file: str):
"""Output data to a XML file"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
data = etree.Element('dat... | stack_v2_sparse_classes_75kplus_train_071894 | 1,321 | no_license | [
{
"docstring": "Creating structure XML file",
"name": "create_xml_data",
"signature": "def create_xml_data(self, result: dict)"
},
{
"docstring": "Output data to a XML file",
"name": "output_xml",
"signature": "def output_xml(result: dict, name_file: str)"
}
] | 2 | stack_v2_sparse_classes_30k_test_000792 | Implement the Python class `XMLSerializer` described below.
Class description:
Implement the XMLSerializer class.
Method signatures and docstrings:
- def create_xml_data(self, result: dict): Creating structure XML file
- def output_xml(result: dict, name_file: str): Output data to a XML file | Implement the Python class `XMLSerializer` described below.
Class description:
Implement the XMLSerializer class.
Method signatures and docstrings:
- def create_xml_data(self, result: dict): Creating structure XML file
- def output_xml(result: dict, name_file: str): Output data to a XML file
<|skeleton|>
class XMLSe... | 949161970d842e35b364c590b6d8e22bd8f0a1b6 | <|skeleton|>
class XMLSerializer:
def create_xml_data(self, result: dict):
"""Creating structure XML file"""
<|body_0|>
def output_xml(result: dict, name_file: str):
"""Output data to a XML file"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class XMLSerializer:
def create_xml_data(self, result: dict):
"""Creating structure XML file"""
data = etree.Element('data')
for key, value in result.items():
room = etree.SubElement(data, 'room', id=str(key))
room.text = value['name']
for stud in value['s... | the_stack_v2_python_sparse | task1/serializer.py | INVICTA1/LeverX | train | 0 | |
4649897dee9754b1070f95959e1a17b932f164df | [
"area, left, right = (0, 0, len(height) - 1)\nwhile left < right:\n new_area = (right - left) * min(height[left], height[right])\n area = max(area, new_area)\n if height[left] <= height[right]:\n left += 1\n else:\n right -= 1\nreturn area",
"max_index = height.index(max(height))\nprint(... | <|body_start_0|>
area, left, right = (0, 0, len(height) - 1)
while left < right:
new_area = (right - left) * min(height[left], height[right])
area = max(area, new_area)
if height[left] <= height[right]:
left += 1
else:
right... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxArea(self, height):
""":type height: List[int] :rtype: int"""
<|body_0|>
def maxArea_v2(self, height):
"""NOTE: This doesnt work for all cases: For example: [1, 2, 1] :type height: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body... | stack_v2_sparse_classes_75kplus_train_071895 | 1,697 | permissive | [
{
"docstring": ":type height: List[int] :rtype: int",
"name": "maxArea",
"signature": "def maxArea(self, height)"
},
{
"docstring": "NOTE: This doesnt work for all cases: For example: [1, 2, 1] :type height: List[int] :rtype: int",
"name": "maxArea_v2",
"signature": "def maxArea_v2(self,... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxArea(self, height): :type height: List[int] :rtype: int
- def maxArea_v2(self, height): NOTE: This doesnt work for all cases: For example: [1, 2, 1] :type height: List[int... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxArea(self, height): :type height: List[int] :rtype: int
- def maxArea_v2(self, height): NOTE: This doesnt work for all cases: For example: [1, 2, 1] :type height: List[int... | 547c200b627c774535bc22880b16d5390183aeba | <|skeleton|>
class Solution:
def maxArea(self, height):
""":type height: List[int] :rtype: int"""
<|body_0|>
def maxArea_v2(self, height):
"""NOTE: This doesnt work for all cases: For example: [1, 2, 1] :type height: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def maxArea(self, height):
""":type height: List[int] :rtype: int"""
area, left, right = (0, 0, len(height) - 1)
while left < right:
new_area = (right - left) * min(height[left], height[right])
area = max(area, new_area)
if height[left] <= ... | the_stack_v2_python_sparse | medium/11_container_with_most_waters.py | Sukhrobjon/leetcode | train | 0 | |
18f3c4e9f1ec2dd0cde3e8094f3c21404dfb3a85 | [
"super().__init__()\nself._id = request_id\nself._project_name = project_name\nself._model_path = model_path\nself._input_precision = input_precision\nself._model_output_path = model_output_path\nself._output_precision = output_precision\nself._mode = mode\nself._workload_path = workload_path\nself._status = status... | <|body_start_0|>
super().__init__()
self._id = request_id
self._project_name = project_name
self._model_path = model_path
self._input_precision = input_precision
self._model_output_path = model_output_path
self._output_precision = output_precision
self._mo... | Create template for workload_list entity. | WorkloadInfo | [
"MIT",
"Intel",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WorkloadInfo:
"""Create template for workload_list entity."""
def __init__(self, request_id: str, project_name: Optional[str], workload_path: Optional[str], model_path: Optional[str], input_precision: Optional[str], model_output_path: Optional[str], output_precision: Optional[str], mode: Opt... | stack_v2_sparse_classes_75kplus_train_071896 | 12,851 | permissive | [
{
"docstring": "Initialize configuration WorkloadInfo class.",
"name": "__init__",
"signature": "def __init__(self, request_id: str, project_name: Optional[str], workload_path: Optional[str], model_path: Optional[str], input_precision: Optional[str], model_output_path: Optional[str], output_precision: O... | 3 | stack_v2_sparse_classes_30k_train_011536 | Implement the Python class `WorkloadInfo` described below.
Class description:
Create template for workload_list entity.
Method signatures and docstrings:
- def __init__(self, request_id: str, project_name: Optional[str], workload_path: Optional[str], model_path: Optional[str], input_precision: Optional[str], model_ou... | Implement the Python class `WorkloadInfo` described below.
Class description:
Create template for workload_list entity.
Method signatures and docstrings:
- def __init__(self, request_id: str, project_name: Optional[str], workload_path: Optional[str], model_path: Optional[str], input_precision: Optional[str], model_ou... | 3976edc4215398e69ce0213f87ec295f5dc96e0e | <|skeleton|>
class WorkloadInfo:
"""Create template for workload_list entity."""
def __init__(self, request_id: str, project_name: Optional[str], workload_path: Optional[str], model_path: Optional[str], input_precision: Optional[str], model_output_path: Optional[str], output_precision: Optional[str], mode: Opt... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class WorkloadInfo:
"""Create template for workload_list entity."""
def __init__(self, request_id: str, project_name: Optional[str], workload_path: Optional[str], model_path: Optional[str], input_precision: Optional[str], model_output_path: Optional[str], output_precision: Optional[str], mode: Optional[str], m... | the_stack_v2_python_sparse | neural_compressor/ux/utils/workload/workloads_list.py | Skp80/neural-compressor | train | 0 |
c183d223ccbbf9f2619c866a42cb99e4bd9ef6dc | [
"assert isinstance(output_size, (int, tuple))\nif isinstance(output_size, int):\n self.output_size = (output_size,)\n for _ in range(out_dim - 1):\n self.output_size += (output_size,)\nelse:\n assert len(output_size) == out_dim\n self.output_size = output_size\nself.out_dim = out_dim",
"mask = ... | <|body_start_0|>
assert isinstance(output_size, (int, tuple))
if isinstance(output_size, int):
self.output_size = (output_size,)
for _ in range(out_dim - 1):
self.output_size += (output_size,)
else:
assert len(output_size) == out_dim
... | base class for crop transform | CropBase | [
"CC-BY-3.0",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CropBase:
"""base class for crop transform"""
def __init__(self, out_dim: int, output_size: Union[tuple, int]):
"""provide the common functionality for RandomCrop2D and RandomCrop3D"""
<|body_0|>
def _get_sample_idxs(self, img: np.ndarray) -> Tuple[int, int, int]:
... | stack_v2_sparse_classes_75kplus_train_071897 | 17,484 | permissive | [
{
"docstring": "provide the common functionality for RandomCrop2D and RandomCrop3D",
"name": "__init__",
"signature": "def __init__(self, out_dim: int, output_size: Union[tuple, int])"
},
{
"docstring": "get the set of indices from which to sample (foreground)",
"name": "_get_sample_idxs",
... | 2 | stack_v2_sparse_classes_30k_test_000927 | Implement the Python class `CropBase` described below.
Class description:
base class for crop transform
Method signatures and docstrings:
- def __init__(self, out_dim: int, output_size: Union[tuple, int]): provide the common functionality for RandomCrop2D and RandomCrop3D
- def _get_sample_idxs(self, img: np.ndarray)... | Implement the Python class `CropBase` described below.
Class description:
base class for crop transform
Method signatures and docstrings:
- def __init__(self, out_dim: int, output_size: Union[tuple, int]): provide the common functionality for RandomCrop2D and RandomCrop3D
- def _get_sample_idxs(self, img: np.ndarray)... | b17509aa1cc8029b7de702971a7ad3a9dcd3c7f4 | <|skeleton|>
class CropBase:
"""base class for crop transform"""
def __init__(self, out_dim: int, output_size: Union[tuple, int]):
"""provide the common functionality for RandomCrop2D and RandomCrop3D"""
<|body_0|>
def _get_sample_idxs(self, img: np.ndarray) -> Tuple[int, int, int]:
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CropBase:
"""base class for crop transform"""
def __init__(self, out_dim: int, output_size: Union[tuple, int]):
"""provide the common functionality for RandomCrop2D and RandomCrop3D"""
assert isinstance(output_size, (int, tuple))
if isinstance(output_size, int):
self.o... | the_stack_v2_python_sparse | DeepNormalize/io/transforms.py | pldelisle/deepNormalize | train | 0 |
4cb57cab5178e80faf3156cd7422bc0a309559fe | [
"self.K = K\nself.X, self.T = ([], [])\nself.flagKLinReg = flagKLinReg",
"self.X, self.T = (np.array(X), np.array(T))\nself.N, self.D = self.X.shape\nself.kdtree = scipy.spatial.KDTree(self.X)",
"if K == None:\n K = self.K\nif flagKLinReg == None:\n flagKLinReg = self.flagKLinReg\nnn = self.kdtree.query(x... | <|body_start_0|>
self.K = K
self.X, self.T = ([], [])
self.flagKLinReg = flagKLinReg
<|end_body_0|>
<|body_start_1|>
self.X, self.T = (np.array(X), np.array(T))
self.N, self.D = self.X.shape
self.kdtree = scipy.spatial.KDTree(self.X)
<|end_body_1|>
<|body_start_2|>
... | Class for fast K-Nearest-Neighbor-Regression using KD-trees | KNNRegressifier | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class KNNRegressifier:
"""Class for fast K-Nearest-Neighbor-Regression using KD-trees"""
def __init__(self, K, flagKLinReg=0):
"""Constructor of class KNNRegressifier :param K: number of nearest neighbors that are used to compute prediction :flagKLinReg: if >0 then the do a linear (least s... | stack_v2_sparse_classes_75kplus_train_071898 | 21,971 | no_license | [
{
"docstring": "Constructor of class KNNRegressifier :param K: number of nearest neighbors that are used to compute prediction :flagKLinReg: if >0 then the do a linear (least squares) regression on the the K nearest neighbors and their target values otherwise just take the mean of the K nearest neighbors target... | 3 | stack_v2_sparse_classes_30k_test_000414 | Implement the Python class `KNNRegressifier` described below.
Class description:
Class for fast K-Nearest-Neighbor-Regression using KD-trees
Method signatures and docstrings:
- def __init__(self, K, flagKLinReg=0): Constructor of class KNNRegressifier :param K: number of nearest neighbors that are used to compute pre... | Implement the Python class `KNNRegressifier` described below.
Class description:
Class for fast K-Nearest-Neighbor-Regression using KD-trees
Method signatures and docstrings:
- def __init__(self, K, flagKLinReg=0): Constructor of class KNNRegressifier :param K: number of nearest neighbors that are used to compute pre... | de2ba4e2afdad7e2e1ba0c145edbd341f8555802 | <|skeleton|>
class KNNRegressifier:
"""Class for fast K-Nearest-Neighbor-Regression using KD-trees"""
def __init__(self, K, flagKLinReg=0):
"""Constructor of class KNNRegressifier :param K: number of nearest neighbors that are used to compute prediction :flagKLinReg: if >0 then the do a linear (least s... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class KNNRegressifier:
"""Class for fast K-Nearest-Neighbor-Regression using KD-trees"""
def __init__(self, K, flagKLinReg=0):
"""Constructor of class KNNRegressifier :param K: number of nearest neighbors that are used to compute prediction :flagKLinReg: if >0 then the do a linear (least squares) regre... | the_stack_v2_python_sparse | versuch2/src/V2A2_Regression.py | xsjad0/ias-neuronale-netze | train | 1 |
5b4777008ee54e4f6e24402e464a6fc765465c62 | [
"if hasattr(cls, name):\n return getattr(cls, name)\nelse:\n return default",
"out = {}\nfor att_name in dir(cls):\n if att_name.isupper():\n out[att_name] = getattr(cls, att_name)\nreturn out",
"base_path = os.path.dirname(__file__)\nfull_path = os.path.join(base_path, 'default_policy.json')\nf... | <|body_start_0|>
if hasattr(cls, name):
return getattr(cls, name)
else:
return default
<|end_body_0|>
<|body_start_1|>
out = {}
for att_name in dir(cls):
if att_name.isupper():
out[att_name] = getattr(cls, att_name)
return out
... | BaseConfig | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BaseConfig:
def get(cls, name, default=None):
"""Emulate get method from dict"""
<|body_0|>
def to_dict(cls):
"""Return dict of all uppercase attributes"""
<|body_1|>
def setup_policies(cls):
"""Read default policy file"""
<|body_2|>
<|e... | stack_v2_sparse_classes_75kplus_train_071899 | 2,610 | permissive | [
{
"docstring": "Emulate get method from dict",
"name": "get",
"signature": "def get(cls, name, default=None)"
},
{
"docstring": "Return dict of all uppercase attributes",
"name": "to_dict",
"signature": "def to_dict(cls)"
},
{
"docstring": "Read default policy file",
"name": ... | 3 | stack_v2_sparse_classes_30k_test_002368 | Implement the Python class `BaseConfig` described below.
Class description:
Implement the BaseConfig class.
Method signatures and docstrings:
- def get(cls, name, default=None): Emulate get method from dict
- def to_dict(cls): Return dict of all uppercase attributes
- def setup_policies(cls): Read default policy file | Implement the Python class `BaseConfig` described below.
Class description:
Implement the BaseConfig class.
Method signatures and docstrings:
- def get(cls, name, default=None): Emulate get method from dict
- def to_dict(cls): Return dict of all uppercase attributes
- def setup_policies(cls): Read default policy file... | 8841c069bb5a53ae18affc0222356956220bbd47 | <|skeleton|>
class BaseConfig:
def get(cls, name, default=None):
"""Emulate get method from dict"""
<|body_0|>
def to_dict(cls):
"""Return dict of all uppercase attributes"""
<|body_1|>
def setup_policies(cls):
"""Read default policy file"""
<|body_2|>
<|e... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class BaseConfig:
def get(cls, name, default=None):
"""Emulate get method from dict"""
if hasattr(cls, name):
return getattr(cls, name)
else:
return default
def to_dict(cls):
"""Return dict of all uppercase attributes"""
out = {}
for att_n... | the_stack_v2_python_sparse | kqueen/config/base.py | Mirantis/kqueen | train | 146 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.