blob_id stringlengths 40 40 | bodies listlengths 2 6 | bodies_text stringlengths 196 6.73k | class_docstring stringlengths 0 700 | class_name stringlengths 1 86 | detected_licenses listlengths 0 45 | format_version stringclasses 1
value | full_text stringlengths 438 7.52k | id stringlengths 40 40 | length_bytes int64 506 50k | license_type stringclasses 2
values | methods listlengths 2 6 | n_methods int64 2 6 | original_id stringlengths 38 40 ⌀ | prompt stringlengths 153 4.25k | prompted_full_text stringlengths 645 10.7k | revision_id stringlengths 40 40 | skeleton stringlengths 162 4.34k | snapshot_name stringclasses 1
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value | solution stringlengths 302 7.33k | source stringclasses 1
value | source_path stringlengths 4 177 | source_repo stringlengths 6 110 | split stringclasses 1
value | star_events_count int64 0 209k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
46301e88ca00c2414752ddb3e5c5785876cd697b | [
"self.name = name\nif labels is None:\n self.labels = []\nelse:\n self.labels = labels",
"cell_labels = np.array([None for x in range(len(sca.cell_sample))])\nfor label in self.labels:\n indices = label.select_cells(sca)\n if len(indices) == 0:\n continue\n cell_labels[indices] = label.name\... | <|body_start_0|>
self.name = name
if labels is None:
self.labels = []
else:
self.labels = labels
<|end_body_0|>
<|body_start_1|>
cell_labels = np.array([None for x in range(len(sca.cell_sample))])
for label in self.labels:
indices = label.sele... | This class represents a custom color map | CustomColorMap | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CustomColorMap:
"""This class represents a custom color map"""
def __init__(self, name, labels=None):
"""Args: name (str) labels (list of CustomLabel objects)"""
<|body_0|>
def label_cells(self, sca):
"""Labels the cells in the given SCAnalysis object."""
... | stack_v2_sparse_classes_36k_train_006000 | 6,289 | no_license | [
{
"docstring": "Args: name (str) labels (list of CustomLabel objects)",
"name": "__init__",
"signature": "def __init__(self, name, labels=None)"
},
{
"docstring": "Labels the cells in the given SCAnalysis object.",
"name": "label_cells",
"signature": "def label_cells(self, sca)"
},
{... | 3 | stack_v2_sparse_classes_30k_train_016905 | Implement the Python class `CustomColorMap` described below.
Class description:
This class represents a custom color map
Method signatures and docstrings:
- def __init__(self, name, labels=None): Args: name (str) labels (list of CustomLabel objects)
- def label_cells(self, sca): Labels the cells in the given SCAnalys... | Implement the Python class `CustomColorMap` described below.
Class description:
This class represents a custom color map
Method signatures and docstrings:
- def __init__(self, name, labels=None): Args: name (str) labels (list of CustomLabel objects)
- def label_cells(self, sca): Labels the cells in the given SCAnalys... | a64425ca5bff57c3fe336e47fddf00fe2bbc1e75 | <|skeleton|>
class CustomColorMap:
"""This class represents a custom color map"""
def __init__(self, name, labels=None):
"""Args: name (str) labels (list of CustomLabel objects)"""
<|body_0|>
def label_cells(self, sca):
"""Labels the cells in the given SCAnalysis object."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CustomColorMap:
"""This class represents a custom color map"""
def __init__(self, name, labels=None):
"""Args: name (str) labels (list of CustomLabel objects)"""
self.name = name
if labels is None:
self.labels = []
else:
self.labels = labels
de... | the_stack_v2_python_sparse | uncurl_analysis/custom_cell_selection.py | yjzhang/uncurl_analysis | train | 1 |
057807310c3dcf027a2c3f41e04b0ad1a290aae2 | [
"Document.__init__(self)\nsession.info('Exporting to NMF XML version 1.0')\nwith session._objslock:\n self.scenarioPlan = ScenarioPlan(self, session)\n if session.getstate() == coreapi.CORE_EVENT_RUNTIME_STATE:\n deployment = CoreDeploymentWriter(self, self.scenarioPlan, session)\n deployment.ad... | <|body_start_0|>
Document.__init__(self)
session.info('Exporting to NMF XML version 1.0')
with session._objslock:
self.scenarioPlan = ScenarioPlan(self, session)
if session.getstate() == coreapi.CORE_EVENT_RUNTIME_STATE:
deployment = CoreDeploymentWriter(s... | Utility class for writing a CoreSession to XML in the NMF scenPlan schema. The init method builds an xml.dom.minidom.Document, and the writexml() method saves the XML file. | CoreDocumentWriter1 | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CoreDocumentWriter1:
"""Utility class for writing a CoreSession to XML in the NMF scenPlan schema. The init method builds an xml.dom.minidom.Document, and the writexml() method saves the XML file."""
def __init__(self, session):
"""Create an empty Scenario XML Document, then populate... | stack_v2_sparse_classes_36k_train_006001 | 37,675 | permissive | [
{
"docstring": "Create an empty Scenario XML Document, then populate it with objects from the given session.",
"name": "__init__",
"signature": "def __init__(self, session)"
},
{
"docstring": "Commit to file",
"name": "writexml",
"signature": "def writexml(self, filename)"
}
] | 2 | null | Implement the Python class `CoreDocumentWriter1` described below.
Class description:
Utility class for writing a CoreSession to XML in the NMF scenPlan schema. The init method builds an xml.dom.minidom.Document, and the writexml() method saves the XML file.
Method signatures and docstrings:
- def __init__(self, sessi... | Implement the Python class `CoreDocumentWriter1` described below.
Class description:
Utility class for writing a CoreSession to XML in the NMF scenPlan schema. The init method builds an xml.dom.minidom.Document, and the writexml() method saves the XML file.
Method signatures and docstrings:
- def __init__(self, sessi... | 9c246b0ae0e9182dcf61acc4faee41841d5cbd51 | <|skeleton|>
class CoreDocumentWriter1:
"""Utility class for writing a CoreSession to XML in the NMF scenPlan schema. The init method builds an xml.dom.minidom.Document, and the writexml() method saves the XML file."""
def __init__(self, session):
"""Create an empty Scenario XML Document, then populate... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CoreDocumentWriter1:
"""Utility class for writing a CoreSession to XML in the NMF scenPlan schema. The init method builds an xml.dom.minidom.Document, and the writexml() method saves the XML file."""
def __init__(self, session):
"""Create an empty Scenario XML Document, then populate it with obje... | the_stack_v2_python_sparse | coreemu-read-only/daemon/core/misc/xmlwriter1.py | ermin-sakic/common-open-research-emulator-CORE | train | 3 |
6ce31067b4a0af641709930a01e204e3f0aa8ee2 | [
"super().__init__()\nself.args = args\nself.q_params = nn.Parameter(self.args.q_delta * torch.randn(self.args.q_depth * self.args.n_qubits))\nself.qai = quant_arc_interface",
"q_in = torch.tanh(input_features) * np.pi / 2.0\nq_in = q_in.to(self.args.device)\nq_out = torch.Tensor(0, self.args.target_class)\nq_out ... | <|body_start_0|>
super().__init__()
self.args = args
self.q_params = nn.Parameter(self.args.q_delta * torch.randn(self.args.q_depth * self.args.n_qubits))
self.qai = quant_arc_interface
<|end_body_0|>
<|body_start_1|>
q_in = torch.tanh(input_features) * np.pi / 2.0
q_in ... | Torch module implementing the *dressed* quantum net. | vqc_net | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class vqc_net:
"""Torch module implementing the *dressed* quantum net."""
def __init__(self, args, quant_arc_interface):
"""Definition of the *dressed* layout."""
<|body_0|>
def forward(self, input_features):
"""Defining how tensors are supposed to move through the *dr... | stack_v2_sparse_classes_36k_train_006002 | 1,518 | permissive | [
{
"docstring": "Definition of the *dressed* layout.",
"name": "__init__",
"signature": "def __init__(self, args, quant_arc_interface)"
},
{
"docstring": "Defining how tensors are supposed to move through the *dressed* quantum net.",
"name": "forward",
"signature": "def forward(self, inpu... | 2 | stack_v2_sparse_classes_30k_train_000085 | Implement the Python class `vqc_net` described below.
Class description:
Torch module implementing the *dressed* quantum net.
Method signatures and docstrings:
- def __init__(self, args, quant_arc_interface): Definition of the *dressed* layout.
- def forward(self, input_features): Defining how tensors are supposed to... | Implement the Python class `vqc_net` described below.
Class description:
Torch module implementing the *dressed* quantum net.
Method signatures and docstrings:
- def __init__(self, args, quant_arc_interface): Definition of the *dressed* layout.
- def forward(self, input_features): Defining how tensors are supposed to... | 8126691b43bddc2b1a96f73ab35d04d1af200d7a | <|skeleton|>
class vqc_net:
"""Torch module implementing the *dressed* quantum net."""
def __init__(self, args, quant_arc_interface):
"""Definition of the *dressed* layout."""
<|body_0|>
def forward(self, input_features):
"""Defining how tensors are supposed to move through the *dr... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class vqc_net:
"""Torch module implementing the *dressed* quantum net."""
def __init__(self, args, quant_arc_interface):
"""Definition of the *dressed* layout."""
super().__init__()
self.args = args
self.q_params = nn.Parameter(self.args.q_delta * torch.randn(self.args.q_depth *... | the_stack_v2_python_sparse | model/vqc_layers.py | zzh237/quanthmc | train | 0 |
7f32d1a6f18eab2d7c3d505ed61740b43e6b7ca7 | [
"import build.api\nimport company.api\nimport order.api\nimport part.api\nimport stock.api\nreturn {'build': build.api.BuildList, 'company': company.api.CompanyList, 'manufacturerpart': company.api.ManufacturerPartList, 'supplierpart': company.api.SupplierPartList, 'part': part.api.PartList, 'partcategory': part.ap... | <|body_start_0|>
import build.api
import company.api
import order.api
import part.api
import stock.api
return {'build': build.api.BuildList, 'company': company.api.CompanyList, 'manufacturerpart': company.api.ManufacturerPartList, 'supplierpart': company.api.SupplierPartL... | A general-purpose 'search' API endpoint Returns hits against a number of different models simultaneously, to consolidate multiple API requests into a single query. Is much more efficient and simplifies code! | APISearchView | [
"MIT",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class APISearchView:
"""A general-purpose 'search' API endpoint Returns hits against a number of different models simultaneously, to consolidate multiple API requests into a single query. Is much more efficient and simplifies code!"""
def get_result_types(self):
"""Construct a list of sear... | stack_v2_sparse_classes_36k_train_006003 | 11,757 | permissive | [
{
"docstring": "Construct a list of search types we can return",
"name": "get_result_types",
"signature": "def get_result_types(self)"
},
{
"docstring": "Perform search query against available models",
"name": "post",
"signature": "def post(self, request, *args, **kwargs)"
}
] | 2 | stack_v2_sparse_classes_30k_train_020681 | Implement the Python class `APISearchView` described below.
Class description:
A general-purpose 'search' API endpoint Returns hits against a number of different models simultaneously, to consolidate multiple API requests into a single query. Is much more efficient and simplifies code!
Method signatures and docstring... | Implement the Python class `APISearchView` described below.
Class description:
A general-purpose 'search' API endpoint Returns hits against a number of different models simultaneously, to consolidate multiple API requests into a single query. Is much more efficient and simplifies code!
Method signatures and docstring... | e88a8e99a5f0b201c67a95cba097c729f090d5e2 | <|skeleton|>
class APISearchView:
"""A general-purpose 'search' API endpoint Returns hits against a number of different models simultaneously, to consolidate multiple API requests into a single query. Is much more efficient and simplifies code!"""
def get_result_types(self):
"""Construct a list of sear... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class APISearchView:
"""A general-purpose 'search' API endpoint Returns hits against a number of different models simultaneously, to consolidate multiple API requests into a single query. Is much more efficient and simplifies code!"""
def get_result_types(self):
"""Construct a list of search types we c... | the_stack_v2_python_sparse | InvenTree/InvenTree/api.py | inventree/InvenTree | train | 3,077 |
561c95ebb895cf6a7c18a8e926aa79f4602efd08 | [
"def dp(i, j, memo):\n if i > j:\n return 0\n if i == j:\n return 1\n if (i, j) not in memo:\n ans = float('inf')\n for k in range(i, j):\n ans = min(ans, dp(i, k, memo) + dp(k + 1, j, memo) - int(s[i] == s[k + 1]))\n memo[i, j] = ans\n return memo[i, j]\nre... | <|body_start_0|>
def dp(i, j, memo):
if i > j:
return 0
if i == j:
return 1
if (i, j) not in memo:
ans = float('inf')
for k in range(i, j):
ans = min(ans, dp(i, k, memo) + dp(k + 1, j, memo) -... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def strangePrinter(self, s: str) -> int:
"""top down"""
<|body_0|>
def strangePrinter(self, s: str) -> int:
"""bottom up"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
def dp(i, j, memo):
if i > j:
return 0
... | stack_v2_sparse_classes_36k_train_006004 | 2,222 | no_license | [
{
"docstring": "top down",
"name": "strangePrinter",
"signature": "def strangePrinter(self, s: str) -> int"
},
{
"docstring": "bottom up",
"name": "strangePrinter",
"signature": "def strangePrinter(self, s: str) -> int"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def strangePrinter(self, s: str) -> int: top down
- def strangePrinter(self, s: str) -> int: bottom up | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def strangePrinter(self, s: str) -> int: top down
- def strangePrinter(self, s: str) -> int: bottom up
<|skeleton|>
class Solution:
def strangePrinter(self, s: str) -> int:... | 6ff1941ff213a843013100ac7033e2d4f90fbd6a | <|skeleton|>
class Solution:
def strangePrinter(self, s: str) -> int:
"""top down"""
<|body_0|>
def strangePrinter(self, s: str) -> int:
"""bottom up"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def strangePrinter(self, s: str) -> int:
"""top down"""
def dp(i, j, memo):
if i > j:
return 0
if i == j:
return 1
if (i, j) not in memo:
ans = float('inf')
for k in range(i, j):
... | the_stack_v2_python_sparse | Leetcode 0664. Strange Printer.py | Chaoran-sjsu/leetcode | train | 0 | |
cec4325b3cb154ce77ab0b3e6d677ba17595c922 | [
"if self.window.editors:\n self.enabled = True\nelse:\n self.enabled = False",
"active_editor = self.window.active_editor\nif self.enabled and active_editor is not None:\n active_editor.save_as()"
] | <|body_start_0|>
if self.window.editors:
self.enabled = True
else:
self.enabled = False
<|end_body_0|>
<|body_start_1|>
active_editor = self.window.active_editor
if self.enabled and active_editor is not None:
active_editor.save_as()
<|end_body_1|>
| Defines an action that save the contents of the current editor to a new name. | SaveAsAction | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SaveAsAction:
"""Defines an action that save the contents of the current editor to a new name."""
def _active_editor_changed_for_window(self):
"""Enables the action if the window has editors."""
<|body_0|>
def perform(self, event):
"""Performs the action."""
... | stack_v2_sparse_classes_36k_train_006005 | 3,865 | permissive | [
{
"docstring": "Enables the action if the window has editors.",
"name": "_active_editor_changed_for_window",
"signature": "def _active_editor_changed_for_window(self)"
},
{
"docstring": "Performs the action.",
"name": "perform",
"signature": "def perform(self, event)"
}
] | 2 | null | Implement the Python class `SaveAsAction` described below.
Class description:
Defines an action that save the contents of the current editor to a new name.
Method signatures and docstrings:
- def _active_editor_changed_for_window(self): Enables the action if the window has editors.
- def perform(self, event): Perform... | Implement the Python class `SaveAsAction` described below.
Class description:
Defines an action that save the contents of the current editor to a new name.
Method signatures and docstrings:
- def _active_editor_changed_for_window(self): Enables the action if the window has editors.
- def perform(self, event): Perform... | e8fc0b2d6b9b08e60389fc4714a5cf51f628b57f | <|skeleton|>
class SaveAsAction:
"""Defines an action that save the contents of the current editor to a new name."""
def _active_editor_changed_for_window(self):
"""Enables the action if the window has editors."""
<|body_0|>
def perform(self, event):
"""Performs the action."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SaveAsAction:
"""Defines an action that save the contents of the current editor to a new name."""
def _active_editor_changed_for_window(self):
"""Enables the action if the window has editors."""
if self.window.editors:
self.enabled = True
else:
self.enabled... | the_stack_v2_python_sparse | puddle/resource/action/save_as_action.py | rwl/puddle | train | 2 |
ae70c7ecca3cafd5d6bdce7dae3694e56b4b5cd6 | [
"import sys\nresult = [0] * len(nums)\nfor i in range(len(nums) - 2, -1, -1):\n if nums[i] == 0:\n result[i] = sys.maxint\n else:\n result[i] = min(result[i + 1:nums[i] + i + 1]) + 1\nreturn result[0]",
"n, start, end, step = (len(nums), 0, 0, 0)\nwhile end < n - 1:\n step += 1\n maxend ... | <|body_start_0|>
import sys
result = [0] * len(nums)
for i in range(len(nums) - 2, -1, -1):
if nums[i] == 0:
result[i] = sys.maxint
else:
result[i] = min(result[i + 1:nums[i] + i + 1]) + 1
return result[0]
<|end_body_0|>
<|body_sta... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def jump(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def jump2(self, nums):
"""https://discuss.leetcode.com/topic/18815/10-lines-c-16ms-python-bfs-solutions-with-explanations/2 This problem has a nice BFS structure. Let’s illustrate it u... | stack_v2_sparse_classes_36k_train_006006 | 2,401 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "jump",
"signature": "def jump(self, nums)"
},
{
"docstring": "https://discuss.leetcode.com/topic/18815/10-lines-c-16ms-python-bfs-solutions-with-explanations/2 This problem has a nice BFS structure. Let’s illustrate it using the exampl... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def jump(self, nums): :type nums: List[int] :rtype: int
- def jump2(self, nums): https://discuss.leetcode.com/topic/18815/10-lines-c-16ms-python-bfs-solutions-with-explanations/2... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def jump(self, nums): :type nums: List[int] :rtype: int
- def jump2(self, nums): https://discuss.leetcode.com/topic/18815/10-lines-c-16ms-python-bfs-solutions-with-explanations/2... | 2526f8c0dec7101123123740e146ee4081e979ee | <|skeleton|>
class Solution:
def jump(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def jump2(self, nums):
"""https://discuss.leetcode.com/topic/18815/10-lines-c-16ms-python-bfs-solutions-with-explanations/2 This problem has a nice BFS structure. Let’s illustrate it u... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def jump(self, nums):
""":type nums: List[int] :rtype: int"""
import sys
result = [0] * len(nums)
for i in range(len(nums) - 2, -1, -1):
if nums[i] == 0:
result[i] = sys.maxint
else:
result[i] = min(result[i + 1:... | the_stack_v2_python_sparse | 045. Jump Game II.py | zhangpengGenedock/leetcode_python | train | 1 | |
728954c7c78b3d24462af871db4ae633d72135aa | [
"super(DiagnosticAuditListener, self).__init__()\nself._config = config\nconnection_string = self._config.get_logging_db_connection_string()\nengine = create_engine(connection_string)\nDiagnostic.__table__.create(bind=engine, checkfirst=True)",
"if type(event) is DiagnosticEvent:\n connection_string = self._co... | <|body_start_0|>
super(DiagnosticAuditListener, self).__init__()
self._config = config
connection_string = self._config.get_logging_db_connection_string()
engine = create_engine(connection_string)
Diagnostic.__table__.create(bind=engine, checkfirst=True)
<|end_body_0|>
<|body_st... | Implementation for the diagnostic listener that saves diagnostic logs to the database. | DiagnosticAuditListener | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DiagnosticAuditListener:
"""Implementation for the diagnostic listener that saves diagnostic logs to the database."""
def __init__(self, config: Configuration):
"""Constructor"""
<|body_0|>
def record_event(self, event: DiagnosticEvent):
"""method for handling au... | stack_v2_sparse_classes_36k_train_006007 | 3,486 | no_license | [
{
"docstring": "Constructor",
"name": "__init__",
"signature": "def __init__(self, config: Configuration)"
},
{
"docstring": "method for handling auditable events to be implemented by listeners. :param event: The event. :type event: :py:class:`lostservice.logging.diagnostic.AuditableEvent`",
... | 2 | stack_v2_sparse_classes_30k_test_000428 | Implement the Python class `DiagnosticAuditListener` described below.
Class description:
Implementation for the diagnostic listener that saves diagnostic logs to the database.
Method signatures and docstrings:
- def __init__(self, config: Configuration): Constructor
- def record_event(self, event: DiagnosticEvent): m... | Implement the Python class `DiagnosticAuditListener` described below.
Class description:
Implementation for the diagnostic listener that saves diagnostic logs to the database.
Method signatures and docstrings:
- def __init__(self, config: Configuration): Constructor
- def record_event(self, event: DiagnosticEvent): m... | 5a41d09a922f0b239893c99ae9a9626f020bf3f9 | <|skeleton|>
class DiagnosticAuditListener:
"""Implementation for the diagnostic listener that saves diagnostic logs to the database."""
def __init__(self, config: Configuration):
"""Constructor"""
<|body_0|>
def record_event(self, event: DiagnosticEvent):
"""method for handling au... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DiagnosticAuditListener:
"""Implementation for the diagnostic listener that saves diagnostic logs to the database."""
def __init__(self, config: Configuration):
"""Constructor"""
super(DiagnosticAuditListener, self).__init__()
self._config = config
connection_string = self... | the_stack_v2_python_sparse | lostservice/logger/diagnosticsaudit.py | ravinash496/lostservice | train | 1 |
0f61feb7419e0c6df1bf35a9b06e8bd84a19f9e5 | [
"super(TorchVisionSSLDCL, self).__init__()\nself.model_function = get_object_from_path(config.cfg['model']['model_function_path'])\nself.pretrained = config.cfg['model']['pretrained']\nself.num_classes = config.cfg['model']['classes_count']\nself.prediction_type = config.cfg['model']['prediction_type']\njigsaw_size... | <|body_start_0|>
super(TorchVisionSSLDCL, self).__init__()
self.model_function = get_object_from_path(config.cfg['model']['model_function_path'])
self.pretrained = config.cfg['model']['pretrained']
self.num_classes = config.cfg['model']['classes_count']
self.prediction_type = con... | The class adds the DCL-SSL task to the standard specified torchvision model. | TorchVisionSSLDCL | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TorchVisionSSLDCL:
"""The class adds the DCL-SSL task to the standard specified torchvision model."""
def __init__(self, config):
"""Constructor, The function parse the config and initialize the layers of the corresponding model. :param config: Configuration class object"""
<... | stack_v2_sparse_classes_36k_train_006008 | 4,500 | permissive | [
{
"docstring": "Constructor, The function parse the config and initialize the layers of the corresponding model. :param config: Configuration class object",
"name": "__init__",
"signature": "def __init__(self, config)"
},
{
"docstring": "The function implements the forward pass of the model. :pa... | 2 | stack_v2_sparse_classes_30k_train_011206 | Implement the Python class `TorchVisionSSLDCL` described below.
Class description:
The class adds the DCL-SSL task to the standard specified torchvision model.
Method signatures and docstrings:
- def __init__(self, config): Constructor, The function parse the config and initialize the layers of the corresponding mode... | Implement the Python class `TorchVisionSSLDCL` described below.
Class description:
The class adds the DCL-SSL task to the standard specified torchvision model.
Method signatures and docstrings:
- def __init__(self, config): Constructor, The function parse the config and initialize the layers of the corresponding mode... | 9a4bf0a112b818caca8794868a903dc736839a43 | <|skeleton|>
class TorchVisionSSLDCL:
"""The class adds the DCL-SSL task to the standard specified torchvision model."""
def __init__(self, config):
"""Constructor, The function parse the config and initialize the layers of the corresponding model. :param config: Configuration class object"""
<... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TorchVisionSSLDCL:
"""The class adds the DCL-SSL task to the standard specified torchvision model."""
def __init__(self, config):
"""Constructor, The function parse the config and initialize the layers of the corresponding model. :param config: Configuration class object"""
super(TorchVis... | the_stack_v2_python_sparse | model/torchvision_ssl_dcl.py | Niousha12/ssl_for_fgvc | train | 0 |
3b94f443693a2e332147080ed39b32323363f3cd | [
"response = super(UploadedFileDetail, self).retrieve(request, *args, **kwargs)\ntemplate_data = {'upload_path': ''}\nreturn services.append_collection_template(response, template_data)",
"user_file = self.get_object()\nrequest.data['fname'] = user_file.fname.file\nreturn super(UploadedFileDetail, self).update(req... | <|body_start_0|>
response = super(UploadedFileDetail, self).retrieve(request, *args, **kwargs)
template_data = {'upload_path': ''}
return services.append_collection_template(response, template_data)
<|end_body_0|>
<|body_start_1|>
user_file = self.get_object()
request.data['fnam... | An uploaded file view. | UploadedFileDetail | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UploadedFileDetail:
"""An uploaded file view."""
def retrieve(self, request, *args, **kwargs):
"""Overriden to append a collection+json template."""
<|body_0|>
def update(self, request, *args, **kwargs):
"""Overriden to include the current fname in the request.""... | stack_v2_sparse_classes_36k_train_006009 | 4,631 | permissive | [
{
"docstring": "Overriden to append a collection+json template.",
"name": "retrieve",
"signature": "def retrieve(self, request, *args, **kwargs)"
},
{
"docstring": "Overriden to include the current fname in the request.",
"name": "update",
"signature": "def update(self, request, *args, *... | 4 | null | Implement the Python class `UploadedFileDetail` described below.
Class description:
An uploaded file view.
Method signatures and docstrings:
- def retrieve(self, request, *args, **kwargs): Overriden to append a collection+json template.
- def update(self, request, *args, **kwargs): Overriden to include the current fn... | Implement the Python class `UploadedFileDetail` described below.
Class description:
An uploaded file view.
Method signatures and docstrings:
- def retrieve(self, request, *args, **kwargs): Overriden to append a collection+json template.
- def update(self, request, *args, **kwargs): Overriden to include the current fn... | 20d3eedf20610af9182f6cca8db8f0b3546b5336 | <|skeleton|>
class UploadedFileDetail:
"""An uploaded file view."""
def retrieve(self, request, *args, **kwargs):
"""Overriden to append a collection+json template."""
<|body_0|>
def update(self, request, *args, **kwargs):
"""Overriden to include the current fname in the request.""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UploadedFileDetail:
"""An uploaded file view."""
def retrieve(self, request, *args, **kwargs):
"""Overriden to append a collection+json template."""
response = super(UploadedFileDetail, self).retrieve(request, *args, **kwargs)
template_data = {'upload_path': ''}
return ser... | the_stack_v2_python_sparse | chris_backend/uploadedfiles/views.py | FNNDSC/ChRIS_ultron_backEnd | train | 36 |
ce67b3fb4b8a39b74756164ff3b12d01115d18b1 | [
"if detection is None:\n if imageWithFaceDetection is None:\n raise ValueError('image and boundingBox or detection must be not None')\n error, ags = self._coreEstimator.estimate(imageWithFaceDetection.image.coreImage, imageWithFaceDetection.boundingBox.coreEstimation)\nelse:\n error, ags = self._cor... | <|body_start_0|>
if detection is None:
if imageWithFaceDetection is None:
raise ValueError('image and boundingBox or detection must be not None')
error, ags = self._coreEstimator.estimate(imageWithFaceDetection.image.coreImage, imageWithFaceDetection.boundingBox.coreEstim... | Approximate garbage score estimator. | AGSEstimator | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AGSEstimator:
"""Approximate garbage score estimator."""
def estimate(self, detection: Optional[FaceDetection]=None, imageWithFaceDetection: Optional[ImageWithFaceDetection]=None) -> float:
"""Estimate ags for single image/detection. Args: detection: face detection imageWithFaceDetec... | stack_v2_sparse_classes_36k_train_006010 | 2,508 | permissive | [
{
"docstring": "Estimate ags for single image/detection. Args: detection: face detection imageWithFaceDetection: image with face detection Returns: estimated ags, float in range[0,1] Raises: LunaSDKException: if estimation failed ValueError: if image and detection are None",
"name": "estimate",
"signatu... | 2 | stack_v2_sparse_classes_30k_train_016650 | Implement the Python class `AGSEstimator` described below.
Class description:
Approximate garbage score estimator.
Method signatures and docstrings:
- def estimate(self, detection: Optional[FaceDetection]=None, imageWithFaceDetection: Optional[ImageWithFaceDetection]=None) -> float: Estimate ags for single image/dete... | Implement the Python class `AGSEstimator` described below.
Class description:
Approximate garbage score estimator.
Method signatures and docstrings:
- def estimate(self, detection: Optional[FaceDetection]=None, imageWithFaceDetection: Optional[ImageWithFaceDetection]=None) -> float: Estimate ags for single image/dete... | 7a4bebc92ae7a96d8d9c18a024208308942f90cd | <|skeleton|>
class AGSEstimator:
"""Approximate garbage score estimator."""
def estimate(self, detection: Optional[FaceDetection]=None, imageWithFaceDetection: Optional[ImageWithFaceDetection]=None) -> float:
"""Estimate ags for single image/detection. Args: detection: face detection imageWithFaceDetec... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AGSEstimator:
"""Approximate garbage score estimator."""
def estimate(self, detection: Optional[FaceDetection]=None, imageWithFaceDetection: Optional[ImageWithFaceDetection]=None) -> float:
"""Estimate ags for single image/detection. Args: detection: face detection imageWithFaceDetection: image w... | the_stack_v2_python_sparse | lunavl/sdk/estimators/face_estimators/ags.py | matemax/lunasdk | train | 16 |
dcc10fed9f7619ff264c9026366aec95116d1125 | [
"logs = None\nlogsDao = LogsDao()\ntry:\n logs = logsDao.add(args)\nexcept Exception as e:\n abort(500, e)\nreturn logs",
"record = None\nlogsDao = LogsDao()\ntry:\n record = logsDao.edit(args)\nexcept Exception as e:\n abort(500, e)\nreturn record",
"record = None\nlogsDao = LogsDao()\nid = args.ge... | <|body_start_0|>
logs = None
logsDao = LogsDao()
try:
logs = logsDao.add(args)
except Exception as e:
abort(500, e)
return logs
<|end_body_0|>
<|body_start_1|>
record = None
logsDao = LogsDao()
try:
record = logsDao.edi... | UserLogsAPI | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserLogsAPI:
def post(self, args):
"""add"""
<|body_0|>
def put(self, args):
"""edit"""
<|body_1|>
def get(self, args):
"""view"""
<|body_2|>
def delete(self, args):
"""del"""
<|body_3|>
<|end_skeleton|>
<|body_star... | stack_v2_sparse_classes_36k_train_006011 | 5,130 | permissive | [
{
"docstring": "add",
"name": "post",
"signature": "def post(self, args)"
},
{
"docstring": "edit",
"name": "put",
"signature": "def put(self, args)"
},
{
"docstring": "view",
"name": "get",
"signature": "def get(self, args)"
},
{
"docstring": "del",
"name": "... | 4 | stack_v2_sparse_classes_30k_train_008499 | Implement the Python class `UserLogsAPI` described below.
Class description:
Implement the UserLogsAPI class.
Method signatures and docstrings:
- def post(self, args): add
- def put(self, args): edit
- def get(self, args): view
- def delete(self, args): del | Implement the Python class `UserLogsAPI` described below.
Class description:
Implement the UserLogsAPI class.
Method signatures and docstrings:
- def post(self, args): add
- def put(self, args): edit
- def get(self, args): view
- def delete(self, args): del
<|skeleton|>
class UserLogsAPI:
def post(self, args):
... | 0fb1b604185a8bd8b72c1d2d527fb94bbaf46a86 | <|skeleton|>
class UserLogsAPI:
def post(self, args):
"""add"""
<|body_0|>
def put(self, args):
"""edit"""
<|body_1|>
def get(self, args):
"""view"""
<|body_2|>
def delete(self, args):
"""del"""
<|body_3|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UserLogsAPI:
def post(self, args):
"""add"""
logs = None
logsDao = LogsDao()
try:
logs = logsDao.add(args)
except Exception as e:
abort(500, e)
return logs
def put(self, args):
"""edit"""
record = None
logsDao... | the_stack_v2_python_sparse | app/modules/logs/resource.py | daitouli/baoaiback | train | 0 | |
8f0bfc2691fb6555ef86be6d3891f0045f14df30 | [
"edit = QLineEdit(parent)\ncompleter = QCompleter()\nedit.setCompleter(completer)\nmodel = QStringListModel()\ncompleter.setModel(model)\nself.setCompleterData(model)\nreturn edit",
"categoryNames = []\nfor category in Categories.all():\n if category.name is not None:\n categoryNames.append(category.nam... | <|body_start_0|>
edit = QLineEdit(parent)
completer = QCompleter()
edit.setCompleter(completer)
model = QStringListModel()
completer.setModel(model)
self.setCompleterData(model)
return edit
<|end_body_0|>
<|body_start_1|>
categoryNames = []
for ca... | Transaction Category View Delegate | TransactionCategoryDelegate | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TransactionCategoryDelegate:
"""Transaction Category View Delegate"""
def createEditor(self, parent, option, index):
"""Should return a LineEdit with all the Category Names as AutoComplete values"""
<|body_0|>
def setCompleterData(self, model):
"""Set Completer D... | stack_v2_sparse_classes_36k_train_006012 | 902 | no_license | [
{
"docstring": "Should return a LineEdit with all the Category Names as AutoComplete values",
"name": "createEditor",
"signature": "def createEditor(self, parent, option, index)"
},
{
"docstring": "Set Completer Data to use Category data",
"name": "setCompleterData",
"signature": "def se... | 2 | null | Implement the Python class `TransactionCategoryDelegate` described below.
Class description:
Transaction Category View Delegate
Method signatures and docstrings:
- def createEditor(self, parent, option, index): Should return a LineEdit with all the Category Names as AutoComplete values
- def setCompleterData(self, mo... | Implement the Python class `TransactionCategoryDelegate` described below.
Class description:
Transaction Category View Delegate
Method signatures and docstrings:
- def createEditor(self, parent, option, index): Should return a LineEdit with all the Category Names as AutoComplete values
- def setCompleterData(self, mo... | 57c909c8581bef3b66388038a1cf5edda426ecf9 | <|skeleton|>
class TransactionCategoryDelegate:
"""Transaction Category View Delegate"""
def createEditor(self, parent, option, index):
"""Should return a LineEdit with all the Category Names as AutoComplete values"""
<|body_0|>
def setCompleterData(self, model):
"""Set Completer D... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TransactionCategoryDelegate:
"""Transaction Category View Delegate"""
def createEditor(self, parent, option, index):
"""Should return a LineEdit with all the Category Names as AutoComplete values"""
edit = QLineEdit(parent)
completer = QCompleter()
edit.setCompleter(comple... | the_stack_v2_python_sparse | src/Qt/GUI/Transaction/Table/Columns/Delegates/transaction_category_delegate.py | cloew/PersonalAccountingSoftware | train | 0 |
7e2841e5b537b7703a023a97c95afe11eba68076 | [
"self.open_tag = open_tag\nself.close_tag = close_tag\nself.content = [content]\nif kwargs:\n self.open_tag = open_tag.strip('>')\n for key in kwargs:\n self.open_tag += ' {}=\"{}\"'.format(key, kwargs[key])\n self.open_tag += '>'",
"if hasattr(content, 'render') and self.content:\n self.conten... | <|body_start_0|>
self.open_tag = open_tag
self.close_tag = close_tag
self.content = [content]
if kwargs:
self.open_tag = open_tag.strip('>')
for key in kwargs:
self.open_tag += ' {}="{}"'.format(key, kwargs[key])
self.open_tag += '>'
<|... | Parent class for all html elements to be created. | Element | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Element:
"""Parent class for all html elements to be created."""
def __init__(self, open_tag='<html>', close_tag='</html>', content=None, **kwargs):
"""Constructor for Element objects. :param open_tag="<html>": set opening tag parameter to html should none be given :param close_tag="... | stack_v2_sparse_classes_36k_train_006013 | 7,157 | no_license | [
{
"docstring": "Constructor for Element objects. :param open_tag=\"<html>\": set opening tag parameter to html should none be given :param close_tag=\"</html>\": set closing tag parameter to html should none be given :param content=None: set content value to NoneType if no content associated",
"name": "__in... | 3 | null | Implement the Python class `Element` described below.
Class description:
Parent class for all html elements to be created.
Method signatures and docstrings:
- def __init__(self, open_tag='<html>', close_tag='</html>', content=None, **kwargs): Constructor for Element objects. :param open_tag="<html>": set opening tag ... | Implement the Python class `Element` described below.
Class description:
Parent class for all html elements to be created.
Method signatures and docstrings:
- def __init__(self, open_tag='<html>', close_tag='</html>', content=None, **kwargs): Constructor for Element objects. :param open_tag="<html>": set opening tag ... | e298b1151dab639659d8dfa56f47bcb43dd3438f | <|skeleton|>
class Element:
"""Parent class for all html elements to be created."""
def __init__(self, open_tag='<html>', close_tag='</html>', content=None, **kwargs):
"""Constructor for Element objects. :param open_tag="<html>": set opening tag parameter to html should none be given :param close_tag="... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Element:
"""Parent class for all html elements to be created."""
def __init__(self, open_tag='<html>', close_tag='</html>', content=None, **kwargs):
"""Constructor for Element objects. :param open_tag="<html>": set opening tag parameter to html should none be given :param close_tag="</html>": set... | the_stack_v2_python_sparse | students/ian_letourneau/Lesson07/html_render.py | UWPCE-PythonCert-ClassRepos/Self_Paced-Online | train | 13 |
76858d8ed3bf6b2c0d6a0bf1ea6101e5ef57a931 | [
"self.datastore_id = datastore_id\nself.file_restore_info = file_restore_info\nself.name = name\nself.objects = objects\nself.protection_source_name = protection_source_name\nself.start_time_usecs = start_time_usecs\nself.mtype = mtype\nself.username = username",
"if dictionary is None:\n return None\ndatastor... | <|body_start_0|>
self.datastore_id = datastore_id
self.file_restore_info = file_restore_info
self.name = name
self.objects = objects
self.protection_source_name = protection_source_name
self.start_time_usecs = start_time_usecs
self.mtype = mtype
self.usern... | Implementation of the 'RestoreSourceSummaryByObjectTypeElement' model. RestoreSourceSummaryByObjectTypeElement represents a recover/clone summary for a single object type. Attributes: datastore_id (long|int): Specifies the datastore where the object's files are recovered to. This field is populated when objects are rec... | RestoreSourceSummaryByObjectTypeElement | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RestoreSourceSummaryByObjectTypeElement:
"""Implementation of the 'RestoreSourceSummaryByObjectTypeElement' model. RestoreSourceSummaryByObjectTypeElement represents a recover/clone summary for a single object type. Attributes: datastore_id (long|int): Specifies the datastore where the object's f... | stack_v2_sparse_classes_36k_train_006014 | 6,343 | permissive | [
{
"docstring": "Constructor for the RestoreSourceSummaryByObjectTypeElement class",
"name": "__init__",
"signature": "def __init__(self, datastore_id=None, file_restore_info=None, name=None, objects=None, protection_source_name=None, start_time_usecs=None, mtype=None, username=None)"
},
{
"docst... | 2 | stack_v2_sparse_classes_30k_train_000582 | Implement the Python class `RestoreSourceSummaryByObjectTypeElement` described below.
Class description:
Implementation of the 'RestoreSourceSummaryByObjectTypeElement' model. RestoreSourceSummaryByObjectTypeElement represents a recover/clone summary for a single object type. Attributes: datastore_id (long|int): Speci... | Implement the Python class `RestoreSourceSummaryByObjectTypeElement` described below.
Class description:
Implementation of the 'RestoreSourceSummaryByObjectTypeElement' model. RestoreSourceSummaryByObjectTypeElement represents a recover/clone summary for a single object type. Attributes: datastore_id (long|int): Speci... | 0093194d125fc6746f55b8499da1270c64f473fc | <|skeleton|>
class RestoreSourceSummaryByObjectTypeElement:
"""Implementation of the 'RestoreSourceSummaryByObjectTypeElement' model. RestoreSourceSummaryByObjectTypeElement represents a recover/clone summary for a single object type. Attributes: datastore_id (long|int): Specifies the datastore where the object's f... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RestoreSourceSummaryByObjectTypeElement:
"""Implementation of the 'RestoreSourceSummaryByObjectTypeElement' model. RestoreSourceSummaryByObjectTypeElement represents a recover/clone summary for a single object type. Attributes: datastore_id (long|int): Specifies the datastore where the object's files are reco... | the_stack_v2_python_sparse | cohesity_management_sdk/models/restore_source_summary_by_object_type_element.py | hsantoyo2/management-sdk-python | train | 0 |
8b237c6d702babcf3abc0ba3bd831ab06bde0d22 | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn InferenceClassificationOverride()",
"from .email_address import EmailAddress\nfrom .entity import Entity\nfrom .inference_classification_type import InferenceClassificationType\nfrom .email_address import EmailAddress\nfrom .entity imp... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return InferenceClassificationOverride()
<|end_body_0|>
<|body_start_1|>
from .email_address import EmailAddress
from .entity import Entity
from .inference_classification_type import In... | InferenceClassificationOverride | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InferenceClassificationOverride:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> InferenceClassificationOverride:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator... | stack_v2_sparse_classes_36k_train_006015 | 2,897 | 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: InferenceClassificationOverride",
"name": "create_from_discriminator_value",
"signature": "def create_from_d... | 3 | null | Implement the Python class `InferenceClassificationOverride` described below.
Class description:
Implement the InferenceClassificationOverride class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> InferenceClassificationOverride: Creates a new instance... | Implement the Python class `InferenceClassificationOverride` described below.
Class description:
Implement the InferenceClassificationOverride class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> InferenceClassificationOverride: Creates a new instance... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class InferenceClassificationOverride:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> InferenceClassificationOverride:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class InferenceClassificationOverride:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> InferenceClassificationOverride:
"""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 cre... | the_stack_v2_python_sparse | msgraph/generated/models/inference_classification_override.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
fbbb0d6a9f0ee144b78aecc0f1a0cd0bad3c45ad | [
"data = self._current_data\nkwargs = super(ClusterSerializer, self).data_info()\nif kwargs and self._detail:\n pass\nreturn kwargs",
"data = self._current_data\nhosts = data.host\nbest_host = None\nbest_perform = 0\nfor host in hosts:\n host_serializer = HostSystemSerializer(host).data\n free_mem_mb = ho... | <|body_start_0|>
data = self._current_data
kwargs = super(ClusterSerializer, self).data_info()
if kwargs and self._detail:
pass
return kwargs
<|end_body_0|>
<|body_start_1|>
data = self._current_data
hosts = data.host
best_host = None
best_per... | 集群数据处理 | ClusterSerializer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ClusterSerializer:
"""集群数据处理"""
def data_info(self):
"""* 返回字段 ** moid ** name"""
<|body_0|>
def best_host_of_mb(self):
"""内存最优主机"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
data = self._current_data
kwargs = super(ClusterSerializer,... | stack_v2_sparse_classes_36k_train_006016 | 12,928 | no_license | [
{
"docstring": "* 返回字段 ** moid ** name",
"name": "data_info",
"signature": "def data_info(self)"
},
{
"docstring": "内存最优主机",
"name": "best_host_of_mb",
"signature": "def best_host_of_mb(self)"
}
] | 2 | stack_v2_sparse_classes_30k_test_000209 | Implement the Python class `ClusterSerializer` described below.
Class description:
集群数据处理
Method signatures and docstrings:
- def data_info(self): * 返回字段 ** moid ** name
- def best_host_of_mb(self): 内存最优主机 | Implement the Python class `ClusterSerializer` described below.
Class description:
集群数据处理
Method signatures and docstrings:
- def data_info(self): * 返回字段 ** moid ** name
- def best_host_of_mb(self): 内存最优主机
<|skeleton|>
class ClusterSerializer:
"""集群数据处理"""
def data_info(self):
"""* 返回字段 ** moid ** n... | 639f11a91ee6e8b72883300cbf297ef4c0494d52 | <|skeleton|>
class ClusterSerializer:
"""集群数据处理"""
def data_info(self):
"""* 返回字段 ** moid ** name"""
<|body_0|>
def best_host_of_mb(self):
"""内存最优主机"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ClusterSerializer:
"""集群数据处理"""
def data_info(self):
"""* 返回字段 ** moid ** name"""
data = self._current_data
kwargs = super(ClusterSerializer, self).data_info()
if kwargs and self._detail:
pass
return kwargs
def best_host_of_mb(self):
"""内存最... | the_stack_v2_python_sparse | ivmware/serializers.py | caijb007/itmsp | train | 0 |
d535846de779f801a29130c99bd4f5bd2d82d873 | [
"assert category in ERROR_CATEGORIES\nself.relpath = relpath\nself.category = category\nself.message = message\nself.fix_it = fix_it\nERROR_COUNTS[category] += 1\nif not FLAGS.counts:\n print(f'{relpath}: {shell.ShellEscapeCodes.YELLOW}{message}{shell.ShellEscapeCodes.END} [{category}]', file=sys.stderr)\n ... | <|body_start_0|>
assert category in ERROR_CATEGORIES
self.relpath = relpath
self.category = category
self.message = message
self.fix_it = fix_it
ERROR_COUNTS[category] += 1
if not FLAGS.counts:
print(f'{relpath}: {shell.ShellEscapeCodes.YELLOW}{messag... | A linter error. | Error | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Error:
"""A linter error."""
def __init__(self, relpath: str, category: str, message: str, fix_it: str=None):
"""Report an error. If --counts flag was passed, this updates the running totals of error counts. If --fix_it flag was passed, the command is printed to stdout. All other out... | stack_v2_sparse_classes_36k_train_006017 | 16,624 | permissive | [
{
"docstring": "Report an error. If --counts flag was passed, this updates the running totals of error counts. If --fix_it flag was passed, the command is printed to stdout. All other output is to stderr.",
"name": "__init__",
"signature": "def __init__(self, relpath: str, category: str, message: str, f... | 2 | null | Implement the Python class `Error` described below.
Class description:
A linter error.
Method signatures and docstrings:
- def __init__(self, relpath: str, category: str, message: str, fix_it: str=None): Report an error. If --counts flag was passed, this updates the running totals of error counts. If --fix_it flag wa... | Implement the Python class `Error` described below.
Class description:
A linter error.
Method signatures and docstrings:
- def __init__(self, relpath: str, category: str, message: str, fix_it: str=None): Report an error. If --counts flag was passed, this updates the running totals of error counts. If --fix_it flag wa... | 22fccacb63b261eade1e1a41ab52a5ea6c542e91 | <|skeleton|>
class Error:
"""A linter error."""
def __init__(self, relpath: str, category: str, message: str, fix_it: str=None):
"""Report an error. If --counts flag was passed, this updates the running totals of error counts. If --fix_it flag was passed, the command is printed to stdout. All other out... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Error:
"""A linter error."""
def __init__(self, relpath: str, category: str, message: str, fix_it: str=None):
"""Report an error. If --counts flag was passed, this updates the running totals of error counts. If --fix_it flag was passed, the command is printed to stdout. All other output is to std... | the_stack_v2_python_sparse | util/photolib/linters.py | 50417/phd | train | 1 |
82459b1f606a4525a12d66682100324516a9b64b | [
"if globals.G_TUNNEL_NUM > len(globals.G_TUNNEL_GROUP_INFO):\n self._TunnelGroupNumber = len(globals.G_TUNNEL_GROUP_INFO)\nelse:\n self._TunnelGroupNumber = globals.G_TUNNEL_NUM\nself._TunnelGroupInfo = globals.G_TUNNEL_GROUP_INFO\nself._TunnelGroupList = tunnelgrouplist\nself._TunnelWorkerQueue = tunnelworke... | <|body_start_0|>
if globals.G_TUNNEL_NUM > len(globals.G_TUNNEL_GROUP_INFO):
self._TunnelGroupNumber = len(globals.G_TUNNEL_GROUP_INFO)
else:
self._TunnelGroupNumber = globals.G_TUNNEL_NUM
self._TunnelGroupInfo = globals.G_TUNNEL_GROUP_INFO
self._TunnelGroupList =... | ListenService服务 监听本地连接，并读取数据存放到队列中 | ListenService | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ListenService:
"""ListenService服务 监听本地连接，并读取数据存放到队列中"""
def __init__(self, tunnelgrouplist, tunnelworkerqueue, tunnelworksmanager):
"""监听服务初始化"""
<|body_0|>
def start(self):
"""监听服务启动"""
<|body_1|>
def stop(self):
"""监听服务停止"""
<|body_... | stack_v2_sparse_classes_36k_train_006018 | 4,968 | no_license | [
{
"docstring": "监听服务初始化",
"name": "__init__",
"signature": "def __init__(self, tunnelgrouplist, tunnelworkerqueue, tunnelworksmanager)"
},
{
"docstring": "监听服务启动",
"name": "start",
"signature": "def start(self)"
},
{
"docstring": "监听服务停止",
"name": "stop",
"signature": "de... | 4 | stack_v2_sparse_classes_30k_train_018941 | Implement the Python class `ListenService` described below.
Class description:
ListenService服务 监听本地连接，并读取数据存放到队列中
Method signatures and docstrings:
- def __init__(self, tunnelgrouplist, tunnelworkerqueue, tunnelworksmanager): 监听服务初始化
- def start(self): 监听服务启动
- def stop(self): 监听服务停止
- def generator(self, tunnelgroup... | Implement the Python class `ListenService` described below.
Class description:
ListenService服务 监听本地连接，并读取数据存放到队列中
Method signatures and docstrings:
- def __init__(self, tunnelgrouplist, tunnelworkerqueue, tunnelworksmanager): 监听服务初始化
- def start(self): 监听服务启动
- def stop(self): 监听服务停止
- def generator(self, tunnelgroup... | c19d8c7ad189b84943abde6684d31f279fca4b21 | <|skeleton|>
class ListenService:
"""ListenService服务 监听本地连接，并读取数据存放到队列中"""
def __init__(self, tunnelgrouplist, tunnelworkerqueue, tunnelworksmanager):
"""监听服务初始化"""
<|body_0|>
def start(self):
"""监听服务启动"""
<|body_1|>
def stop(self):
"""监听服务停止"""
<|body_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ListenService:
"""ListenService服务 监听本地连接，并读取数据存放到队列中"""
def __init__(self, tunnelgrouplist, tunnelworkerqueue, tunnelworksmanager):
"""监听服务初始化"""
if globals.G_TUNNEL_NUM > len(globals.G_TUNNEL_GROUP_INFO):
self._TunnelGroupNumber = len(globals.G_TUNNEL_GROUP_INFO)
else... | the_stack_v2_python_sparse | Client/ListenService.py | lixingke3650/OrTunnel | train | 1 |
f17bc693587f8cf15c9c808117c8599155ca5f19 | [
"self.erase_prob = erase_prob\nself.noise_type = noise_type\nself.use_keys = use_keys\nself.ignore_keys = ignore_keys\nself.num_patches = num_patches\nif not (isinstance(num_patches, tuple) or isinstance(num_patches, list)):\n self.num_patches = (num_patches, num_patches)\nself.patch_size = patch_size\nif len(pa... | <|body_start_0|>
self.erase_prob = erase_prob
self.noise_type = noise_type
self.use_keys = use_keys
self.ignore_keys = ignore_keys
self.num_patches = num_patches
if not (isinstance(num_patches, tuple) or isinstance(num_patches, list)):
self.num_patches = (num_... | Randomly covers a rectangular patch on the second image with noise, to simulate a pseudo-occlusion. The noise_type may be the mean or random. This transform erases patches ONLY FROM THE SECOND IMAGE. | RandomPatchEraser | [
"Apache-2.0",
"CC-BY-NC-SA-4.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RandomPatchEraser:
"""Randomly covers a rectangular patch on the second image with noise, to simulate a pseudo-occlusion. The noise_type may be the mean or random. This transform erases patches ONLY FROM THE SECOND IMAGE."""
def __init__(self, erase_prob: float=0.0, num_patches: Union[int, T... | stack_v2_sparse_classes_36k_train_006019 | 42,078 | permissive | [
{
"docstring": "Initialize RandomPatchEraser. Parameters ---------- erase_prob : float, default 0.0 Probability of applying the transformation. num_patches : Union[int, Tuple[int, int]], default 1 Number of occlusion patches to generate. If it is a tuple, the number will be uniformly sampled from the interval. ... | 2 | stack_v2_sparse_classes_30k_train_016742 | Implement the Python class `RandomPatchEraser` described below.
Class description:
Randomly covers a rectangular patch on the second image with noise, to simulate a pseudo-occlusion. The noise_type may be the mean or random. This transform erases patches ONLY FROM THE SECOND IMAGE.
Method signatures and docstrings:
-... | Implement the Python class `RandomPatchEraser` described below.
Class description:
Randomly covers a rectangular patch on the second image with noise, to simulate a pseudo-occlusion. The noise_type may be the mean or random. This transform erases patches ONLY FROM THE SECOND IMAGE.
Method signatures and docstrings:
-... | d6582a0fd386517fdefbe2c347cef53150b5b1da | <|skeleton|>
class RandomPatchEraser:
"""Randomly covers a rectangular patch on the second image with noise, to simulate a pseudo-occlusion. The noise_type may be the mean or random. This transform erases patches ONLY FROM THE SECOND IMAGE."""
def __init__(self, erase_prob: float=0.0, num_patches: Union[int, T... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RandomPatchEraser:
"""Randomly covers a rectangular patch on the second image with noise, to simulate a pseudo-occlusion. The noise_type may be the mean or random. This transform erases patches ONLY FROM THE SECOND IMAGE."""
def __init__(self, erase_prob: float=0.0, num_patches: Union[int, Tuple[int, int... | the_stack_v2_python_sparse | ptlflow/data/flow_transforms.py | hmorimitsu/ptlflow | train | 140 |
e0e80121ce67196f4800a7c804d9437046661766 | [
"__method_name = inspect.currentframe().f_code.co_name\ntry:\n sentinel_pattern = indicator.get('properties', {}).get('parsedPattern', None)\n if sentinel_pattern:\n sentinel_parsed_pattern_value = sentinel_pattern[0].get('patternTypeValues', None)\n if sentinel_parsed_pattern_value:\n ... | <|body_start_0|>
__method_name = inspect.currentframe().f_code.co_name
try:
sentinel_pattern = indicator.get('properties', {}).get('parsedPattern', None)
if sentinel_pattern:
sentinel_parsed_pattern_value = sentinel_pattern[0].get('patternTypeValues', None)
... | To map field values of Sentinel and defender indicators. | SentinelToDefenderMapping | [
"MIT",
"LicenseRef-scancode-generic-cla"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SentinelToDefenderMapping:
"""To map field values of Sentinel and defender indicators."""
def get_defender_indicator_value(self, indicator):
"""To convert sentinel indicator pattern to threat value."""
<|body_0|>
def get_defender_indicator_type(self, indicator):
... | stack_v2_sparse_classes_36k_train_006020 | 7,343 | permissive | [
{
"docstring": "To convert sentinel indicator pattern to threat value.",
"name": "get_defender_indicator_value",
"signature": "def get_defender_indicator_value(self, indicator)"
},
{
"docstring": "To convert sentinel indicator type to defender accepted indicator type.",
"name": "get_defender... | 5 | null | Implement the Python class `SentinelToDefenderMapping` described below.
Class description:
To map field values of Sentinel and defender indicators.
Method signatures and docstrings:
- def get_defender_indicator_value(self, indicator): To convert sentinel indicator pattern to threat value.
- def get_defender_indicator... | Implement the Python class `SentinelToDefenderMapping` described below.
Class description:
To map field values of Sentinel and defender indicators.
Method signatures and docstrings:
- def get_defender_indicator_value(self, indicator): To convert sentinel indicator pattern to threat value.
- def get_defender_indicator... | 4536a3f6b9bdef902312b3d96f9c2e66b8bf52c1 | <|skeleton|>
class SentinelToDefenderMapping:
"""To map field values of Sentinel and defender indicators."""
def get_defender_indicator_value(self, indicator):
"""To convert sentinel indicator pattern to threat value."""
<|body_0|>
def get_defender_indicator_type(self, indicator):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SentinelToDefenderMapping:
"""To map field values of Sentinel and defender indicators."""
def get_defender_indicator_value(self, indicator):
"""To convert sentinel indicator pattern to threat value."""
__method_name = inspect.currentframe().f_code.co_name
try:
sentinel... | the_stack_v2_python_sparse | Solutions/CofenseIntelligence/Data Connectors/CofenseIntelligenceDataConnector/SentinelToDefender/sentinel_to_defender_mapping.py | Azure/Azure-Sentinel | train | 3,697 |
cf383b0a14facd053a7f82595112f8823ddf2042 | [
"path = '/'.join([self.REQUEST_BASEURL, 'list']) + '?' + '&'.join(['src_rse={}'.format(src_rse), 'dst_rse={}'.format(dst_rse), 'request_states={}'.format(request_states)])\nurl = build_url(choice(self.list_hosts), path=path)\nr = self._send_request(url, type_='GET')\nif r.status_code == codes.ok:\n return self._... | <|body_start_0|>
path = '/'.join([self.REQUEST_BASEURL, 'list']) + '?' + '&'.join(['src_rse={}'.format(src_rse), 'dst_rse={}'.format(dst_rse), 'request_states={}'.format(request_states)])
url = build_url(choice(self.list_hosts), path=path)
r = self._send_request(url, type_='GET')
if r.st... | RequestClient | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RequestClient:
def list_requests(self, src_rse, dst_rse, request_states):
"""Return latest request details :return: request information :rtype: dict"""
<|body_0|>
def list_requests_history(self, src_rse, dst_rse, request_states, offset=0, limit=100):
"""Return histor... | stack_v2_sparse_classes_36k_train_006021 | 4,256 | permissive | [
{
"docstring": "Return latest request details :return: request information :rtype: dict",
"name": "list_requests",
"signature": "def list_requests(self, src_rse, dst_rse, request_states)"
},
{
"docstring": "Return historical request details :return: request information :rtype: dict",
"name":... | 4 | stack_v2_sparse_classes_30k_train_004614 | Implement the Python class `RequestClient` described below.
Class description:
Implement the RequestClient class.
Method signatures and docstrings:
- def list_requests(self, src_rse, dst_rse, request_states): Return latest request details :return: request information :rtype: dict
- def list_requests_history(self, src... | Implement the Python class `RequestClient` described below.
Class description:
Implement the RequestClient class.
Method signatures and docstrings:
- def list_requests(self, src_rse, dst_rse, request_states): Return latest request details :return: request information :rtype: dict
- def list_requests_history(self, src... | 7f0d229ac0b3bc7dec12c6e158bea2b82d414a3b | <|skeleton|>
class RequestClient:
def list_requests(self, src_rse, dst_rse, request_states):
"""Return latest request details :return: request information :rtype: dict"""
<|body_0|>
def list_requests_history(self, src_rse, dst_rse, request_states, offset=0, limit=100):
"""Return histor... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RequestClient:
def list_requests(self, src_rse, dst_rse, request_states):
"""Return latest request details :return: request information :rtype: dict"""
path = '/'.join([self.REQUEST_BASEURL, 'list']) + '?' + '&'.join(['src_rse={}'.format(src_rse), 'dst_rse={}'.format(dst_rse), 'request_states=... | the_stack_v2_python_sparse | lib/rucio/client/requestclient.py | rucio/rucio | train | 232 | |
354f16929366eb40ceaf926254be2c26b1b215f8 | [
"self.m = height\nself.n = width\nself.food = food + [[-1, -1]]\nself.foodIdx = 0\nself.bodyQueue = deque([(0, 0)])\nself.bodySet = {(0, 0)}",
"oldHead = self.bodyQueue[-1]\nnewHead = (oldHead[0] + int(direction == 'D') - int(direction == 'U'), oldHead[1] + int(direction == 'R') - int(direction == 'L'))\nif not (... | <|body_start_0|>
self.m = height
self.n = width
self.food = food + [[-1, -1]]
self.foodIdx = 0
self.bodyQueue = deque([(0, 0)])
self.bodySet = {(0, 0)}
<|end_body_0|>
<|body_start_1|>
oldHead = self.bodyQueue[-1]
newHead = (oldHead[0] + int(direction == '... | SnakeGame | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SnakeGame:
def __init__(self, width, height, food):
"""Initialize your data structure here. @param width - screen width @param height - screen height @param food - A list of food positions E.g food = [[1,1], [1,0]] means the first food is positioned at [1,1], the second is at [1,0]. :typ... | stack_v2_sparse_classes_36k_train_006022 | 3,174 | no_license | [
{
"docstring": "Initialize your data structure here. @param width - screen width @param height - screen height @param food - A list of food positions E.g food = [[1,1], [1,0]] means the first food is positioned at [1,1], the second is at [1,0]. :type width: int :type height: int :type food: List[List[int]]",
... | 2 | stack_v2_sparse_classes_30k_train_007470 | Implement the Python class `SnakeGame` described below.
Class description:
Implement the SnakeGame class.
Method signatures and docstrings:
- def __init__(self, width, height, food): Initialize your data structure here. @param width - screen width @param height - screen height @param food - A list of food positions E... | Implement the Python class `SnakeGame` described below.
Class description:
Implement the SnakeGame class.
Method signatures and docstrings:
- def __init__(self, width, height, food): Initialize your data structure here. @param width - screen width @param height - screen height @param food - A list of food positions E... | 810575368ecffa97677bdb51744d1f716140bbb1 | <|skeleton|>
class SnakeGame:
def __init__(self, width, height, food):
"""Initialize your data structure here. @param width - screen width @param height - screen height @param food - A list of food positions E.g food = [[1,1], [1,0]] means the first food is positioned at [1,1], the second is at [1,0]. :typ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SnakeGame:
def __init__(self, width, height, food):
"""Initialize your data structure here. @param width - screen width @param height - screen height @param food - A list of food positions E.g food = [[1,1], [1,0]] means the first food is positioned at [1,1], the second is at [1,0]. :type width: int :... | the_stack_v2_python_sparse | D/DesignSnakeGame.py | bssrdf/pyleet | train | 2 | |
558d56f7b12cc69848044feba82b7a4fb63f1586 | [
"attrs = {'history': '2018-12-10Z: StaGE Decoupler', 'title': 'Temperature on UK 2 km Standard Grid', 'source': 'Met Office Unified Model'}\nself.cube = set_up_variable_cube(np.ones((11, 11), dtype=np.float32), spatial_grid='equalarea', standard_grid_metadata='uk_det', attributes=attrs)\nself.grid_spacing = np.diff... | <|body_start_0|>
attrs = {'history': '2018-12-10Z: StaGE Decoupler', 'title': 'Temperature on UK 2 km Standard Grid', 'source': 'Met Office Unified Model'}
self.cube = set_up_variable_cube(np.ones((11, 11), dtype=np.float32), spatial_grid='equalarea', standard_grid_metadata='uk_det', attributes=attrs)
... | Tests for the create_cube_with_halo function | Test_create_cube_with_halo | [
"BSD-3-Clause",
"LicenseRef-scancode-proprietary-license"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Test_create_cube_with_halo:
"""Tests for the create_cube_with_halo function"""
def setUp(self):
"""Set up a realistic input cube with lots of metadata. Input cube grid is 1000x1000 km with points spaced 100 km apart."""
<|body_0|>
def test_basic(self):
"""Test fu... | stack_v2_sparse_classes_36k_train_006023 | 25,212 | permissive | [
{
"docstring": "Set up a realistic input cube with lots of metadata. Input cube grid is 1000x1000 km with points spaced 100 km apart.",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "Test function returns a cube with expected metadata",
"name": "test_basic",
"signatur... | 3 | null | Implement the Python class `Test_create_cube_with_halo` described below.
Class description:
Tests for the create_cube_with_halo function
Method signatures and docstrings:
- def setUp(self): Set up a realistic input cube with lots of metadata. Input cube grid is 1000x1000 km with points spaced 100 km apart.
- def test... | Implement the Python class `Test_create_cube_with_halo` described below.
Class description:
Tests for the create_cube_with_halo function
Method signatures and docstrings:
- def setUp(self): Set up a realistic input cube with lots of metadata. Input cube grid is 1000x1000 km with points spaced 100 km apart.
- def test... | cd2c9019944345df1e703bf8f625db537ad9f559 | <|skeleton|>
class Test_create_cube_with_halo:
"""Tests for the create_cube_with_halo function"""
def setUp(self):
"""Set up a realistic input cube with lots of metadata. Input cube grid is 1000x1000 km with points spaced 100 km apart."""
<|body_0|>
def test_basic(self):
"""Test fu... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Test_create_cube_with_halo:
"""Tests for the create_cube_with_halo function"""
def setUp(self):
"""Set up a realistic input cube with lots of metadata. Input cube grid is 1000x1000 km with points spaced 100 km apart."""
attrs = {'history': '2018-12-10Z: StaGE Decoupler', 'title': 'Tempera... | the_stack_v2_python_sparse | improver_tests/utilities/test_pad_spatial.py | metoppv/improver | train | 101 |
c7222a8ee0733ff066067678fac38469350e9325 | [
"super().__init__(*args, **kwargs)\nself.dag_name = dag_name\nself.input_hook = hook_factory.get_input_hook(input_hook, **kwargs)\nself.output_hook = hook_factory.get_output_hook(output_hook, **kwargs)\nself.return_report = return_report\nself.enable_monitoring = enable_monitoring\nself.is_retry = is_retry\nif enab... | <|body_start_0|>
super().__init__(*args, **kwargs)
self.dag_name = dag_name
self.input_hook = hook_factory.get_input_hook(input_hook, **kwargs)
self.output_hook = hook_factory.get_output_hook(output_hook, **kwargs)
self.return_report = return_report
self.enable_monitoring... | Custom Operator to send data from an input hook to an output hook. | DataConnectorOperator | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DataConnectorOperator:
"""Custom Operator to send data from an input hook to an output hook."""
def __init__(self, *args, input_hook: hook_factory.InputHookType, output_hook: hook_factory.OutputHookType, dag_name: str, monitoring_dataset: str='', monitoring_table: str='', monitoring_bq_conn_... | stack_v2_sparse_classes_36k_train_006024 | 5,361 | permissive | [
{
"docstring": "Initiates the DataConnectorOperator. Args: *args: arguments for the operator. input_hook: The type of the input hook. output_hook: The type of the output hook. dag_name: The ID of the current running dag. monitoring_dataset: Dataset id of the monitoring table. monitoring_table: Table name of the... | 2 | stack_v2_sparse_classes_30k_train_000822 | Implement the Python class `DataConnectorOperator` described below.
Class description:
Custom Operator to send data from an input hook to an output hook.
Method signatures and docstrings:
- def __init__(self, *args, input_hook: hook_factory.InputHookType, output_hook: hook_factory.OutputHookType, dag_name: str, monit... | Implement the Python class `DataConnectorOperator` described below.
Class description:
Custom Operator to send data from an input hook to an output hook.
Method signatures and docstrings:
- def __init__(self, *args, input_hook: hook_factory.InputHookType, output_hook: hook_factory.OutputHookType, dag_name: str, monit... | 031f21680c8646c9d2d39d589c581a9bc9796424 | <|skeleton|>
class DataConnectorOperator:
"""Custom Operator to send data from an input hook to an output hook."""
def __init__(self, *args, input_hook: hook_factory.InputHookType, output_hook: hook_factory.OutputHookType, dag_name: str, monitoring_dataset: str='', monitoring_table: str='', monitoring_bq_conn_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DataConnectorOperator:
"""Custom Operator to send data from an input hook to an output hook."""
def __init__(self, *args, input_hook: hook_factory.InputHookType, output_hook: hook_factory.OutputHookType, dag_name: str, monitoring_dataset: str='', monitoring_table: str='', monitoring_bq_conn_id: str='', r... | the_stack_v2_python_sparse | src/dags/dependencies/tcrm/operators/data_connector_operator.py | Ressmann/blockbuster | train | 0 |
bb71b8685d372d2b027f616521e22eafb3cc930b | [
"self.setting = setting\nself.gameActive = False\nself.mainMenu = True\nself.mainGame = False\nself.mainAbout = False\nself.playMenu = False\nself.twoPlayer = False\nself.paused = False\nself.score = 0\nself.level = 1\nself.highScore = 0\nself.resetStats()",
"self.shipsLeft = self.setting.shipLimit\nself.level = ... | <|body_start_0|>
self.setting = setting
self.gameActive = False
self.mainMenu = True
self.mainGame = False
self.mainAbout = False
self.playMenu = False
self.twoPlayer = False
self.paused = False
self.score = 0
self.level = 1
self.hi... | Track stats for alien shooter | GameStats | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GameStats:
"""Track stats for alien shooter"""
def __init__(self, setting):
"""initialize statistics"""
<|body_0|>
def resetStats(self):
"""initialize statistics that can change during the game"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
sel... | stack_v2_sparse_classes_36k_train_006025 | 1,307 | permissive | [
{
"docstring": "initialize statistics",
"name": "__init__",
"signature": "def __init__(self, setting)"
},
{
"docstring": "initialize statistics that can change during the game",
"name": "resetStats",
"signature": "def resetStats(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_014837 | Implement the Python class `GameStats` described below.
Class description:
Track stats for alien shooter
Method signatures and docstrings:
- def __init__(self, setting): initialize statistics
- def resetStats(self): initialize statistics that can change during the game | Implement the Python class `GameStats` described below.
Class description:
Track stats for alien shooter
Method signatures and docstrings:
- def __init__(self, setting): initialize statistics
- def resetStats(self): initialize statistics that can change during the game
<|skeleton|>
class GameStats:
"""Track stat... | 2fda9dc7722f2b1bfd7ea05f77bca20ed017cc2a | <|skeleton|>
class GameStats:
"""Track stats for alien shooter"""
def __init__(self, setting):
"""initialize statistics"""
<|body_0|>
def resetStats(self):
"""initialize statistics that can change during the game"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GameStats:
"""Track stats for alien shooter"""
def __init__(self, setting):
"""initialize statistics"""
self.setting = setting
self.gameActive = False
self.mainMenu = True
self.mainGame = False
self.mainAbout = False
self.playMenu = False
se... | the_stack_v2_python_sparse | gameStats.py | taaeyoon/SourceTree | train | 0 |
daea475924763c804e66a0d0bfe22a5877b1df9e | [
"actions: List[int] = []\nis_wins: List[bool] = []\nfor x in range(BW):\n y, result = cls._action_result(s_ary, x)\n if result != MOVE_ILLEGAL:\n actions.append(y * BW + x)\n is_wins.append(result == MOVE_WIN)\nreturn (actions, is_wins)",
"y = BH - 1\nwhile True:\n if y < 0 or (s_ary[CP, y,... | <|body_start_0|>
actions: List[int] = []
is_wins: List[bool] = []
for x in range(BW):
y, result = cls._action_result(s_ary, x)
if result != MOVE_ILLEGAL:
actions.append(y * BW + x)
is_wins.append(result == MOVE_WIN)
return (actions,... | ActionChecker | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ActionChecker:
def get_action_candidates(cls, s_ary: np.array) -> Tuple[List[int], List[bool]]:
"""合法手およびその手で勝利するか否かを求める"""
<|body_0|>
def _action_result(cls, s_ary: np.array, x: int) -> Tuple[int, int]:
"""その局面でのxに対応するyおよび結果を求める"""
<|body_1|>
def _check... | stack_v2_sparse_classes_36k_train_006026 | 7,788 | no_license | [
{
"docstring": "合法手およびその手で勝利するか否かを求める",
"name": "get_action_candidates",
"signature": "def get_action_candidates(cls, s_ary: np.array) -> Tuple[List[int], List[bool]]"
},
{
"docstring": "その局面でのxに対応するyおよび結果を求める",
"name": "_action_result",
"signature": "def _action_result(cls, s_ary: np.ar... | 3 | stack_v2_sparse_classes_30k_train_014511 | Implement the Python class `ActionChecker` described below.
Class description:
Implement the ActionChecker class.
Method signatures and docstrings:
- def get_action_candidates(cls, s_ary: np.array) -> Tuple[List[int], List[bool]]: 合法手およびその手で勝利するか否かを求める
- def _action_result(cls, s_ary: np.array, x: int) -> Tuple[int, ... | Implement the Python class `ActionChecker` described below.
Class description:
Implement the ActionChecker class.
Method signatures and docstrings:
- def get_action_candidates(cls, s_ary: np.array) -> Tuple[List[int], List[bool]]: 合法手およびその手で勝利するか否かを求める
- def _action_result(cls, s_ary: np.array, x: int) -> Tuple[int, ... | 01e8fb7a5483f6cb209806f1097ce16573694b4d | <|skeleton|>
class ActionChecker:
def get_action_candidates(cls, s_ary: np.array) -> Tuple[List[int], List[bool]]:
"""合法手およびその手で勝利するか否かを求める"""
<|body_0|>
def _action_result(cls, s_ary: np.array, x: int) -> Tuple[int, int]:
"""その局面でのxに対応するyおよび結果を求める"""
<|body_1|>
def _check... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ActionChecker:
def get_action_candidates(cls, s_ary: np.array) -> Tuple[List[int], List[bool]]:
"""合法手およびその手で勝利するか否かを求める"""
actions: List[int] = []
is_wins: List[bool] = []
for x in range(BW):
y, result = cls._action_result(s_ary, x)
if result != MOVE_IL... | the_stack_v2_python_sparse | src/c4_zero/env/solver/solver.py | threecourse/rl-connect4-alpha-zero | train | 0 | |
85acf760cd341998f6f18081fa431b9145d18ffc | [
"self.token = {'access_token': Remark.access_token}\nname = {'openid': Remark.re, 'remark': 'lishouwu'}\nhost = cof.url + '/cgi-bin/user/info/updateremark'\nremarks = ApiDefine().remark(self.session, url=host, params=self.token, data=json.dumps(name))\nself.assertIn('ok', remarks.text)",
"self.token = {'access_to... | <|body_start_0|>
self.token = {'access_token': Remark.access_token}
name = {'openid': Remark.re, 'remark': 'lishouwu'}
host = cof.url + '/cgi-bin/user/info/updateremark'
remarks = ApiDefine().remark(self.session, url=host, params=self.token, data=json.dumps(name))
self.assertIn('... | Remark | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Remark:
def test_remarks(self):
"""修改用户列表"""
<|body_0|>
def test_f_remarks(self):
"""修改用户列表,错误token"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.token = {'access_token': Remark.access_token}
name = {'openid': Remark.re, 'remark': 'li... | stack_v2_sparse_classes_36k_train_006027 | 1,400 | no_license | [
{
"docstring": "修改用户列表",
"name": "test_remarks",
"signature": "def test_remarks(self)"
},
{
"docstring": "修改用户列表,错误token",
"name": "test_f_remarks",
"signature": "def test_f_remarks(self)"
}
] | 2 | null | Implement the Python class `Remark` described below.
Class description:
Implement the Remark class.
Method signatures and docstrings:
- def test_remarks(self): 修改用户列表
- def test_f_remarks(self): 修改用户列表,错误token | Implement the Python class `Remark` described below.
Class description:
Implement the Remark class.
Method signatures and docstrings:
- def test_remarks(self): 修改用户列表
- def test_f_remarks(self): 修改用户列表,错误token
<|skeleton|>
class Remark:
def test_remarks(self):
"""修改用户列表"""
<|body_0|>
def te... | 7b790f675419224bfdbe1542eddc5a638982e68a | <|skeleton|>
class Remark:
def test_remarks(self):
"""修改用户列表"""
<|body_0|>
def test_f_remarks(self):
"""修改用户列表,错误token"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Remark:
def test_remarks(self):
"""修改用户列表"""
self.token = {'access_token': Remark.access_token}
name = {'openid': Remark.re, 'remark': 'lishouwu'}
host = cof.url + '/cgi-bin/user/info/updateremark'
remarks = ApiDefine().remark(self.session, url=host, params=self.token, ... | the_stack_v2_python_sparse | task/weixin_apitest/testcases/weixin_remarks.py | liousAlready/NewDream_learning | train | 0 | |
9b598f467b9969ec07bb85877170609f4431188a | [
"if N <= 1:\n return N\nif N == 2:\n return 1\nprev1 = 1\nprev2 = 1\nfor i in range(2, N + 1):\n prev1, prev2 = (prev1 + prev2, prev1)\nreturn prev1",
"if N <= 1:\n return N\nreturn self.fib(N - 1) + self.fib(N - 2)"
] | <|body_start_0|>
if N <= 1:
return N
if N == 2:
return 1
prev1 = 1
prev2 = 1
for i in range(2, N + 1):
prev1, prev2 = (prev1 + prev2, prev1)
return prev1
<|end_body_0|>
<|body_start_1|>
if N <= 1:
return N
r... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def fib2(self, N: int) -> int:
"""递推 时间复杂度: O(N) 空间复杂度: O(1) Args: N: Returns:"""
<|body_0|>
def fib(self, N: int) -> int:
"""递归 时间复杂度 O(2^N) 空间复杂度 O(N) Args: N: Returns:"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if N <= 1:
... | stack_v2_sparse_classes_36k_train_006028 | 1,011 | no_license | [
{
"docstring": "递推 时间复杂度: O(N) 空间复杂度: O(1) Args: N: Returns:",
"name": "fib2",
"signature": "def fib2(self, N: int) -> int"
},
{
"docstring": "递归 时间复杂度 O(2^N) 空间复杂度 O(N) Args: N: Returns:",
"name": "fib",
"signature": "def fib(self, N: int) -> int"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def fib2(self, N: int) -> int: 递推 时间复杂度: O(N) 空间复杂度: O(1) Args: N: Returns:
- def fib(self, N: int) -> int: 递归 时间复杂度 O(2^N) 空间复杂度 O(N) Args: N: Returns: | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def fib2(self, N: int) -> int: 递推 时间复杂度: O(N) 空间复杂度: O(1) Args: N: Returns:
- def fib(self, N: int) -> int: 递归 时间复杂度 O(2^N) 空间复杂度 O(N) Args: N: Returns:
<|skeleton|>
class Solut... | c0dd577481b46129d950354d567d332a4d091137 | <|skeleton|>
class Solution:
def fib2(self, N: int) -> int:
"""递推 时间复杂度: O(N) 空间复杂度: O(1) Args: N: Returns:"""
<|body_0|>
def fib(self, N: int) -> int:
"""递归 时间复杂度 O(2^N) 空间复杂度 O(N) Args: N: Returns:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def fib2(self, N: int) -> int:
"""递推 时间复杂度: O(N) 空间复杂度: O(1) Args: N: Returns:"""
if N <= 1:
return N
if N == 2:
return 1
prev1 = 1
prev2 = 1
for i in range(2, N + 1):
prev1, prev2 = (prev1 + prev2, prev1)
re... | the_stack_v2_python_sparse | leetcode/509_斐波拉契数.py | tenqaz/crazy_arithmetic | train | 0 | |
fa3d86b057c416802ed490a7c7bf1603492b99f4 | [
"self.n = height\nself.m = width\nself.dirs = {'L': [0, -1], 'U': [-1, 0], 'R': [0, 1], 'D': [1, 0]}\nself.food = collections.deque(food)\nself.snake_set = {(0, 0)}\nself.snake = collections.deque([(0, 0)])",
"x, y = (self.snake[-1][0] + self.dirs[direction][0], self.snake[-1][1] + self.dirs[direction][1])\nif x ... | <|body_start_0|>
self.n = height
self.m = width
self.dirs = {'L': [0, -1], 'U': [-1, 0], 'R': [0, 1], 'D': [1, 0]}
self.food = collections.deque(food)
self.snake_set = {(0, 0)}
self.snake = collections.deque([(0, 0)])
<|end_body_0|>
<|body_start_1|>
x, y = (self.... | SnakeGame | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SnakeGame:
def __init__(self, width: int, height: int, food: List[List[int]]):
"""Initialize your data structure here. @param width - screen width @param height - screen height @param food - A list of food positions E.g food = [[1,1], [1,0]] means the first food is positioned at [1,1], t... | stack_v2_sparse_classes_36k_train_006029 | 1,784 | no_license | [
{
"docstring": "Initialize your data structure here. @param width - screen width @param height - screen height @param food - A list of food positions E.g food = [[1,1], [1,0]] means the first food is positioned at [1,1], the second is at [1,0].",
"name": "__init__",
"signature": "def __init__(self, widt... | 2 | stack_v2_sparse_classes_30k_test_000917 | Implement the Python class `SnakeGame` described below.
Class description:
Implement the SnakeGame class.
Method signatures and docstrings:
- def __init__(self, width: int, height: int, food: List[List[int]]): Initialize your data structure here. @param width - screen width @param height - screen height @param food -... | Implement the Python class `SnakeGame` described below.
Class description:
Implement the SnakeGame class.
Method signatures and docstrings:
- def __init__(self, width: int, height: int, food: List[List[int]]): Initialize your data structure here. @param width - screen width @param height - screen height @param food -... | 59f70dc4466e15df591ba285317e4a1fe808ed60 | <|skeleton|>
class SnakeGame:
def __init__(self, width: int, height: int, food: List[List[int]]):
"""Initialize your data structure here. @param width - screen width @param height - screen height @param food - A list of food positions E.g food = [[1,1], [1,0]] means the first food is positioned at [1,1], t... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SnakeGame:
def __init__(self, width: int, height: int, food: List[List[int]]):
"""Initialize your data structure here. @param width - screen width @param height - screen height @param food - A list of food positions E.g food = [[1,1], [1,0]] means the first food is positioned at [1,1], the second is a... | the_stack_v2_python_sparse | leet/Design/353_Design_Snake_Game.py | arsamigullin/problem_solving_python | train | 0 | |
d52ba227f6b54888b09eb610d738e5972616868b | [
"PROXY_PRIORITY_VALUES = []\nraw_priority_values = settings.proxies.pool.priority\nfor priority in raw_priority_values:\n multiplier = int(priority[0])\n metric = priority[1][0]\n params = []\n if len(priority[1]) > 1:\n params = priority[1][1:]\n value = self.get_metric(metric, *params)\n ... | <|body_start_0|>
PROXY_PRIORITY_VALUES = []
raw_priority_values = settings.proxies.pool.priority
for priority in raw_priority_values:
multiplier = int(priority[0])
metric = priority[1][0]
params = []
if len(priority[1]) > 1:
params ... | ProxyMetrics | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProxyMetrics:
def priority(self, count):
"""We do not need the confirmed fields since they already are factored in based on the separate queues. [!] IMPORTANT: ------------- Tuple comparison for priority in Python3 breaks if two tuples are the same, so we have to use a counter to guarant... | stack_v2_sparse_classes_36k_train_006030 | 13,482 | no_license | [
{
"docstring": "We do not need the confirmed fields since they already are factored in based on the separate queues. [!] IMPORTANT: ------------- Tuple comparison for priority in Python3 breaks if two tuples are the same, so we have to use a counter to guarantee that no two tuples are the same and priority will... | 2 | null | Implement the Python class `ProxyMetrics` described below.
Class description:
Implement the ProxyMetrics class.
Method signatures and docstrings:
- def priority(self, count): We do not need the confirmed fields since they already are factored in based on the separate queues. [!] IMPORTANT: ------------- Tuple compari... | Implement the Python class `ProxyMetrics` described below.
Class description:
Implement the ProxyMetrics class.
Method signatures and docstrings:
- def priority(self, count): We do not need the confirmed fields since they already are factored in based on the separate queues. [!] IMPORTANT: ------------- Tuple compari... | e27d6ab0da018495a4b54e41a15cc84dc0df14ab | <|skeleton|>
class ProxyMetrics:
def priority(self, count):
"""We do not need the confirmed fields since they already are factored in based on the separate queues. [!] IMPORTANT: ------------- Tuple comparison for priority in Python3 breaks if two tuples are the same, so we have to use a counter to guarant... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ProxyMetrics:
def priority(self, count):
"""We do not need the confirmed fields since they already are factored in based on the separate queues. [!] IMPORTANT: ------------- Tuple comparison for priority in Python3 breaks if two tuples are the same, so we have to use a counter to guarantee that no two... | the_stack_v2_python_sparse | instattack/core/models/mixins.py | nickmflorin/instagram-attack | train | 9 | |
16ff5689577916b7fa815c990dfc89d1d36b633f | [
"self.cleaned_data = super(DeleteWaypointForm, self).clean()\nwaypoint = Waypoint.objects.filter(pk=self.cleaned_data['id_waypoint'])\nif not waypoint:\n raise ValidationError('El punto de entrega no existe')\nreturn self.cleaned_data",
"waypoint = Waypoint.objects.get(pk=self.cleaned_data['id_waypoint'])\nway... | <|body_start_0|>
self.cleaned_data = super(DeleteWaypointForm, self).clean()
waypoint = Waypoint.objects.filter(pk=self.cleaned_data['id_waypoint'])
if not waypoint:
raise ValidationError('El punto de entrega no existe')
return self.cleaned_data
<|end_body_0|>
<|body_start_1... | Form that is used to soft-delete (deactivate) a WaypointModel as well as the related user. | DeleteWaypointForm | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DeleteWaypointForm:
"""Form that is used to soft-delete (deactivate) a WaypointModel as well as the related user."""
def clean(self):
"""Override clean data to validate the id corresponds to a real Waypoint."""
<|body_0|>
def save(self, *args, **kwargs):
"""Overr... | stack_v2_sparse_classes_36k_train_006031 | 8,251 | permissive | [
{
"docstring": "Override clean data to validate the id corresponds to a real Waypoint.",
"name": "clean",
"signature": "def clean(self)"
},
{
"docstring": "Override save to soft delete the waypoint.",
"name": "save",
"signature": "def save(self, *args, **kwargs)"
}
] | 2 | null | Implement the Python class `DeleteWaypointForm` described below.
Class description:
Form that is used to soft-delete (deactivate) a WaypointModel as well as the related user.
Method signatures and docstrings:
- def clean(self): Override clean data to validate the id corresponds to a real Waypoint.
- def save(self, *a... | Implement the Python class `DeleteWaypointForm` described below.
Class description:
Form that is used to soft-delete (deactivate) a WaypointModel as well as the related user.
Method signatures and docstrings:
- def clean(self): Override clean data to validate the id corresponds to a real Waypoint.
- def save(self, *a... | 0100435c5d5a5fd12133b376b305e8fa79ddb8f0 | <|skeleton|>
class DeleteWaypointForm:
"""Form that is used to soft-delete (deactivate) a WaypointModel as well as the related user."""
def clean(self):
"""Override clean data to validate the id corresponds to a real Waypoint."""
<|body_0|>
def save(self, *args, **kwargs):
"""Overr... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DeleteWaypointForm:
"""Form that is used to soft-delete (deactivate) a WaypointModel as well as the related user."""
def clean(self):
"""Override clean data to validate the id corresponds to a real Waypoint."""
self.cleaned_data = super(DeleteWaypointForm, self).clean()
waypoint =... | the_stack_v2_python_sparse | waypoints/forms.py | Oswaldinho24k/geo-csv | train | 0 |
942f7e2ac06f33815a91e6f04e0527deb23a6d66 | [
"expected_result = np.array([[0.0, 0.0, 0.1, 0.0, 0.0], [0.0, 0.0, 0.175, 0.0, 0.0], [0.05, 0.125, 0.3375, 0.125, 0.05], [0.025, 0.0625, 0.29375, 0.0625, 0.025], [0.0125, 0.03125, 0.196875, 0.03125, 0.0125]])\nresult = RecursiveFilter(edge_width=1)._recurse_forward(self.cube.data[0, :], self.smoothing_coefficients[... | <|body_start_0|>
expected_result = np.array([[0.0, 0.0, 0.1, 0.0, 0.0], [0.0, 0.0, 0.175, 0.0, 0.0], [0.05, 0.125, 0.3375, 0.125, 0.05], [0.025, 0.0625, 0.29375, 0.0625, 0.025], [0.0125, 0.03125, 0.196875, 0.03125, 0.0125]])
result = RecursiveFilter(edge_width=1)._recurse_forward(self.cube.data[0, :], s... | Test the _recurse_forward method | Test__recurse_forward | [
"BSD-3-Clause",
"LicenseRef-scancode-proprietary-license"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Test__recurse_forward:
"""Test the _recurse_forward method"""
def test_first_axis(self):
"""Test that the returned _recurse_forward array has the expected type and result."""
<|body_0|>
def test_second_axis(self):
"""Test that the returned _recurse_forward array ... | stack_v2_sparse_classes_36k_train_006032 | 22,857 | permissive | [
{
"docstring": "Test that the returned _recurse_forward array has the expected type and result.",
"name": "test_first_axis",
"signature": "def test_first_axis(self)"
},
{
"docstring": "Test that the returned _recurse_forward array has the expected type and result.",
"name": "test_second_axis... | 2 | null | Implement the Python class `Test__recurse_forward` described below.
Class description:
Test the _recurse_forward method
Method signatures and docstrings:
- def test_first_axis(self): Test that the returned _recurse_forward array has the expected type and result.
- def test_second_axis(self): Test that the returned _r... | Implement the Python class `Test__recurse_forward` described below.
Class description:
Test the _recurse_forward method
Method signatures and docstrings:
- def test_first_axis(self): Test that the returned _recurse_forward array has the expected type and result.
- def test_second_axis(self): Test that the returned _r... | cd2c9019944345df1e703bf8f625db537ad9f559 | <|skeleton|>
class Test__recurse_forward:
"""Test the _recurse_forward method"""
def test_first_axis(self):
"""Test that the returned _recurse_forward array has the expected type and result."""
<|body_0|>
def test_second_axis(self):
"""Test that the returned _recurse_forward array ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Test__recurse_forward:
"""Test the _recurse_forward method"""
def test_first_axis(self):
"""Test that the returned _recurse_forward array has the expected type and result."""
expected_result = np.array([[0.0, 0.0, 0.1, 0.0, 0.0], [0.0, 0.0, 0.175, 0.0, 0.0], [0.05, 0.125, 0.3375, 0.125, 0... | the_stack_v2_python_sparse | improver_tests/nbhood/recursive_filter/test_RecursiveFilter.py | metoppv/improver | train | 101 |
ea1aa675ed0a8f74994ab7e1daec79ac202f0702 | [
"super().__init__()\nself.generator = generator_cls(img_size, latent_dim, num_channels)\nself.discriminator = discriminator_cls(num_channels, img_size)\nself._latent_dim = latent_dim\nself.generator.apply(weights_init_normal)\nself.discriminator.apply(weights_init_normal)\nself.lambda_gp = lambda_gp",
"if noise i... | <|body_start_0|>
super().__init__()
self.generator = generator_cls(img_size, latent_dim, num_channels)
self.discriminator = discriminator_cls(num_channels, img_size)
self._latent_dim = latent_dim
self.generator.apply(weights_init_normal)
self.discriminator.apply(weights_i... | Implementation of Generative Adversarial Networks following the convergence and stability guidance of ``On Convergence and Stability of GANs`` References ---------- `Paper <https://arxiv.org/abs/1705.07215>`_ Warnings -------- This Network is designed for training only; if you want to predict from an already trained ne... | DRAGAN | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DRAGAN:
"""Implementation of Generative Adversarial Networks following the convergence and stability guidance of ``On Convergence and Stability of GANs`` References ---------- `Paper <https://arxiv.org/abs/1705.07215>`_ Warnings -------- This Network is designed for training only; if you want to ... | stack_v2_sparse_classes_36k_train_006033 | 5,304 | permissive | [
{
"docstring": "Parameters ---------- latent_dim : int size of the latent dimension num_channels : int number of channels for image generation and discrimination img_size : int number of pixels per image side lambda_gp : float weighting factor for gradient penalty generator_cls : class implementing the actual g... | 2 | stack_v2_sparse_classes_30k_train_003901 | Implement the Python class `DRAGAN` described below.
Class description:
Implementation of Generative Adversarial Networks following the convergence and stability guidance of ``On Convergence and Stability of GANs`` References ---------- `Paper <https://arxiv.org/abs/1705.07215>`_ Warnings -------- This Network is desi... | Implement the Python class `DRAGAN` described below.
Class description:
Implementation of Generative Adversarial Networks following the convergence and stability guidance of ``On Convergence and Stability of GANs`` References ---------- `Paper <https://arxiv.org/abs/1705.07215>`_ Warnings -------- This Network is desi... | 1078f5030b8aac2bf022daf5fa14d66f74c3c893 | <|skeleton|>
class DRAGAN:
"""Implementation of Generative Adversarial Networks following the convergence and stability guidance of ``On Convergence and Stability of GANs`` References ---------- `Paper <https://arxiv.org/abs/1705.07215>`_ Warnings -------- This Network is designed for training only; if you want to ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DRAGAN:
"""Implementation of Generative Adversarial Networks following the convergence and stability guidance of ``On Convergence and Stability of GANs`` References ---------- `Paper <https://arxiv.org/abs/1705.07215>`_ Warnings -------- This Network is designed for training only; if you want to predict from ... | the_stack_v2_python_sparse | dlutils/models/gans/dragan/dragan.py | justusschock/dl-utils | train | 15 |
88f225d86c1b18605129320e5f8bcb6453145bfb | [
"super(EnterpriseCustomerIdentityProviderAdminForm, self).__init__(*args, **kwargs)\nidp_choices = utils.get_idp_choices()\nif idp_choices is not None:\n self.fields['provider_id'] = forms.TypedChoiceField(choices=idp_choices)",
"super(EnterpriseCustomerIdentityProviderAdminForm, self).clean()\nprovider_id = s... | <|body_start_0|>
super(EnterpriseCustomerIdentityProviderAdminForm, self).__init__(*args, **kwargs)
idp_choices = utils.get_idp_choices()
if idp_choices is not None:
self.fields['provider_id'] = forms.TypedChoiceField(choices=idp_choices)
<|end_body_0|>
<|body_start_1|>
supe... | Alternate form for the EnterpriseCustomerIdentityProvider admin page. This form fetches identity providers from lms third_party_auth app. If third_party_auth app is not avilable it displays provider_id as a CharField. | EnterpriseCustomerIdentityProviderAdminForm | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EnterpriseCustomerIdentityProviderAdminForm:
"""Alternate form for the EnterpriseCustomerIdentityProvider admin page. This form fetches identity providers from lms third_party_auth app. If third_party_auth app is not avilable it displays provider_id as a CharField."""
def __init__(self, *arg... | stack_v2_sparse_classes_36k_train_006034 | 14,734 | no_license | [
{
"docstring": "Initialize the form. Substitutes CharField with TypedChoiceField for the provider_id field.",
"name": "__init__",
"signature": "def __init__(self, *args, **kwargs)"
},
{
"docstring": "Final validations of model fields. 1. Validate that selected site for enterprise customer matche... | 2 | stack_v2_sparse_classes_30k_train_001764 | Implement the Python class `EnterpriseCustomerIdentityProviderAdminForm` described below.
Class description:
Alternate form for the EnterpriseCustomerIdentityProvider admin page. This form fetches identity providers from lms third_party_auth app. If third_party_auth app is not avilable it displays provider_id as a Cha... | Implement the Python class `EnterpriseCustomerIdentityProviderAdminForm` described below.
Class description:
Alternate form for the EnterpriseCustomerIdentityProvider admin page. This form fetches identity providers from lms third_party_auth app. If third_party_auth app is not avilable it displays provider_id as a Cha... | de3d1b297fa99d61cf32addb981cdfc55aec9891 | <|skeleton|>
class EnterpriseCustomerIdentityProviderAdminForm:
"""Alternate form for the EnterpriseCustomerIdentityProvider admin page. This form fetches identity providers from lms third_party_auth app. If third_party_auth app is not avilable it displays provider_id as a CharField."""
def __init__(self, *arg... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EnterpriseCustomerIdentityProviderAdminForm:
"""Alternate form for the EnterpriseCustomerIdentityProvider admin page. This form fetches identity providers from lms third_party_auth app. If third_party_auth app is not avilable it displays provider_id as a CharField."""
def __init__(self, *args, **kwargs):... | the_stack_v2_python_sparse | venvs/edxapp/lib/python2.7/site-packages/enterprise/admin/forms.py | UOMx/CITeS-VM-edxapp | train | 0 |
e3f1e91a022165a526299378047d7249c65a6eaa | [
"username = request.GET.get('username', None)\nif username is not None:\n teacher = get_object_or_404(Teacher, user__username=username)\n serializer = TeacherSerializer(teacher)\n return JsonResponse({'teachers': [serializer.data]}, safe=False)\nelse:\n teachers = Teacher.objects.all()\n serializer =... | <|body_start_0|>
username = request.GET.get('username', None)
if username is not None:
teacher = get_object_or_404(Teacher, user__username=username)
serializer = TeacherSerializer(teacher)
return JsonResponse({'teachers': [serializer.data]}, safe=False)
else:
... | 教师view | Teachers | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Teachers:
"""教师view"""
def get(self, request):
"""查询教师"""
<|body_0|>
def post(self, request):
"""增加教师"""
<|body_1|>
def delete(self, request):
"""删除教师"""
<|body_2|>
<|end_skeleton|>
<|body_start_0|>
username = request.GET.ge... | stack_v2_sparse_classes_36k_train_006035 | 16,053 | permissive | [
{
"docstring": "查询教师",
"name": "get",
"signature": "def get(self, request)"
},
{
"docstring": "增加教师",
"name": "post",
"signature": "def post(self, request)"
},
{
"docstring": "删除教师",
"name": "delete",
"signature": "def delete(self, request)"
}
] | 3 | stack_v2_sparse_classes_30k_train_011610 | Implement the Python class `Teachers` described below.
Class description:
教师view
Method signatures and docstrings:
- def get(self, request): 查询教师
- def post(self, request): 增加教师
- def delete(self, request): 删除教师 | Implement the Python class `Teachers` described below.
Class description:
教师view
Method signatures and docstrings:
- def get(self, request): 查询教师
- def post(self, request): 增加教师
- def delete(self, request): 删除教师
<|skeleton|>
class Teachers:
"""教师view"""
def get(self, request):
"""查询教师"""
<|b... | 7aaa1be773718de1beb3ce0080edca7c4114b7ad | <|skeleton|>
class Teachers:
"""教师view"""
def get(self, request):
"""查询教师"""
<|body_0|>
def post(self, request):
"""增加教师"""
<|body_1|>
def delete(self, request):
"""删除教师"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Teachers:
"""教师view"""
def get(self, request):
"""查询教师"""
username = request.GET.get('username', None)
if username is not None:
teacher = get_object_or_404(Teacher, user__username=username)
serializer = TeacherSerializer(teacher)
return JsonResp... | the_stack_v2_python_sparse | user/views.py | MIXISAMA/MIS-backend | train | 0 |
eac14632447e396631a44ba81ee3f9ad8b6ba520 | [
"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. | GradeOutServicer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GradeOutServicer:
"""Missing associated documentation comment in .proto file."""
def CreateGrade(self, request, context):
"""Missing associated documentation comment in .proto file."""
<|body_0|>
def ReadGrade(self, request, context):
"""Missing associated docume... | stack_v2_sparse_classes_36k_train_006036 | 9,091 | no_license | [
{
"docstring": "Missing associated documentation comment in .proto file.",
"name": "CreateGrade",
"signature": "def CreateGrade(self, request, context)"
},
{
"docstring": "Missing associated documentation comment in .proto file.",
"name": "ReadGrade",
"signature": "def ReadGrade(self, re... | 5 | stack_v2_sparse_classes_30k_train_015300 | Implement the Python class `GradeOutServicer` described below.
Class description:
Missing associated documentation comment in .proto file.
Method signatures and docstrings:
- def CreateGrade(self, request, context): Missing associated documentation comment in .proto file.
- def ReadGrade(self, request, context): Miss... | Implement the Python class `GradeOutServicer` described below.
Class description:
Missing associated documentation comment in .proto file.
Method signatures and docstrings:
- def CreateGrade(self, request, context): Missing associated documentation comment in .proto file.
- def ReadGrade(self, request, context): Miss... | de7bc0fa1dc299473e2e63dab58c1d49fde7df2f | <|skeleton|>
class GradeOutServicer:
"""Missing associated documentation comment in .proto file."""
def CreateGrade(self, request, context):
"""Missing associated documentation comment in .proto file."""
<|body_0|>
def ReadGrade(self, request, context):
"""Missing associated docume... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GradeOutServicer:
"""Missing associated documentation comment in .proto file."""
def CreateGrade(self, request, context):
"""Missing associated documentation comment in .proto file."""
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
... | the_stack_v2_python_sparse | gateway/src/logic/protogen/outgoing/grade_out_pb2_grpc.py | Mutestock/mini-project-loner-edition | train | 0 |
ee0e3ebf4d44f9a28a9b547bf8445d17a0153f74 | [
"self.mol = mol\nself.mints = mints\nself.V_nuc = mol.nuclear_repulsion_energy()\nself.T = block_oei(mints.ao_kinetic())\nself.S = block_oei(mints.ao_overlap())\nself.V = block_oei(mints.ao_potential())\nG = block_tei(mints.ao_eri())\nself.g = G.transpose(0, 2, 1, 3) - G.transpose(0, 2, 3, 1)\nself.h = self.T + sel... | <|body_start_0|>
self.mol = mol
self.mints = mints
self.V_nuc = mol.nuclear_repulsion_energy()
self.T = block_oei(mints.ao_kinetic())
self.S = block_oei(mints.ao_overlap())
self.V = block_oei(mints.ao_potential())
G = block_tei(mints.ao_eri())
self.g = G.t... | Unrestricted Hartree-Fock class for obtaining the unrestricted Hartree-Fock energy | UHF | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UHF:
"""Unrestricted Hartree-Fock class for obtaining the unrestricted Hartree-Fock energy"""
def __init__(self, mol, mints):
"""Initialize the uhf :param mol: a psi4 molecule object :param mints: a molecular integrals object (from MintsHelper)"""
<|body_0|>
def compute_... | stack_v2_sparse_classes_36k_train_006037 | 3,614 | no_license | [
{
"docstring": "Initialize the uhf :param mol: a psi4 molecule object :param mints: a molecular integrals object (from MintsHelper)",
"name": "__init__",
"signature": "def __init__(self, mol, mints)"
},
{
"docstring": "Compute the rhf energy :return: energy",
"name": "compute_energy",
"s... | 3 | null | Implement the Python class `UHF` described below.
Class description:
Unrestricted Hartree-Fock class for obtaining the unrestricted Hartree-Fock energy
Method signatures and docstrings:
- def __init__(self, mol, mints): Initialize the uhf :param mol: a psi4 molecule object :param mints: a molecular integrals object (... | Implement the Python class `UHF` described below.
Class description:
Unrestricted Hartree-Fock class for obtaining the unrestricted Hartree-Fock energy
Method signatures and docstrings:
- def __init__(self, mol, mints): Initialize the uhf :param mol: a psi4 molecule object :param mints: a molecular integrals object (... | 2e8255ea548f13de6c492f649c4f2c4156f9995f | <|skeleton|>
class UHF:
"""Unrestricted Hartree-Fock class for obtaining the unrestricted Hartree-Fock energy"""
def __init__(self, mol, mints):
"""Initialize the uhf :param mol: a psi4 molecule object :param mints: a molecular integrals object (from MintsHelper)"""
<|body_0|>
def compute_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UHF:
"""Unrestricted Hartree-Fock class for obtaining the unrestricted Hartree-Fock energy"""
def __init__(self, mol, mints):
"""Initialize the uhf :param mol: a psi4 molecule object :param mints: a molecular integrals object (from MintsHelper)"""
self.mol = mol
self.mints = mints... | the_stack_v2_python_sparse | 5/jevandezande/module/uhf.py | CCQC/summer-program | train | 35 |
26c33ec77c16085c7f7e677efaea8f76732eff79 | [
"try:\n branch = Branch.objects.get(id=kwargs['branch_id'], repository_id=kwargs['repository_id'])\nexcept Branch.DoesNotExist:\n raise Http404\nsuper(BranchDetail, self).check_permissions(request, branch)\nreturn branch",
"branch = self.get_object(request, branch_id=kwargs['branch_id'], repository_id=kwarg... | <|body_start_0|>
try:
branch = Branch.objects.get(id=kwargs['branch_id'], repository_id=kwargs['repository_id'])
except Branch.DoesNotExist:
raise Http404
super(BranchDetail, self).check_permissions(request, branch)
return branch
<|end_body_0|>
<|body_start_1|>
... | This view handle all requests what comes on endpoint repositories/(?P<repository_id>[0-9]+)/branches/(?P<branch_id>[0-9]+)/$ | BranchDetail | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BranchDetail:
"""This view handle all requests what comes on endpoint repositories/(?P<repository_id>[0-9]+)/branches/(?P<branch_id>[0-9]+)/$"""
def get_object(self, request, *args, **kwargs) -> Branch:
"""Trying to find branch by branch and repository id in database and return them ... | stack_v2_sparse_classes_36k_train_006038 | 4,560 | permissive | [
{
"docstring": "Trying to find branch by branch and repository id in database and return them :param args: other parameters :param kwargs: dict parsed url variables {\"branch_id\": \"id\", \"repository_id\":\"id\"} :return: Branch object or DoesNotExist exception :raise Branch.DoesNotExist",
"name": "get_ob... | 3 | stack_v2_sparse_classes_30k_train_001854 | Implement the Python class `BranchDetail` described below.
Class description:
This view handle all requests what comes on endpoint repositories/(?P<repository_id>[0-9]+)/branches/(?P<branch_id>[0-9]+)/$
Method signatures and docstrings:
- def get_object(self, request, *args, **kwargs) -> Branch: Trying to find branch... | Implement the Python class `BranchDetail` described below.
Class description:
This view handle all requests what comes on endpoint repositories/(?P<repository_id>[0-9]+)/branches/(?P<branch_id>[0-9]+)/$
Method signatures and docstrings:
- def get_object(self, request, *args, **kwargs) -> Branch: Trying to find branch... | fdb911dfafbd2609b7f96561ab6780b4131a77bd | <|skeleton|>
class BranchDetail:
"""This view handle all requests what comes on endpoint repositories/(?P<repository_id>[0-9]+)/branches/(?P<branch_id>[0-9]+)/$"""
def get_object(self, request, *args, **kwargs) -> Branch:
"""Trying to find branch by branch and repository id in database and return them ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BranchDetail:
"""This view handle all requests what comes on endpoint repositories/(?P<repository_id>[0-9]+)/branches/(?P<branch_id>[0-9]+)/$"""
def get_object(self, request, *args, **kwargs) -> Branch:
"""Trying to find branch by branch and repository id in database and return them :param args: ... | the_stack_v2_python_sparse | branches/views.py | Kh-011-WebUIPython/lit | train | 4 |
da67d24e11a57c0e4929cdc9be7df4c233a96731 | [
"ThreadSlave.__init__(self)\nmyThread = threading.currentThread()\nself.runningFeedersLock = myThread.runningFeedersLock\nself.runningFeeders = myThread.runningFeeders\nself.messageArgs = None",
"ThreadSlave.initInThread(self)\nmyThread = threading.currentThread()\ndaofactory = DAOFactory(package='WMComponent.Fee... | <|body_start_0|>
ThreadSlave.__init__(self)
myThread = threading.currentThread()
self.runningFeedersLock = myThread.runningFeedersLock
self.runningFeeders = myThread.runningFeeders
self.messageArgs = None
<|end_body_0|>
<|body_start_1|>
ThreadSlave.initInThread(self)
... | The default slave for FeederManager messages | DefaultSlave | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DefaultSlave:
"""The default slave for FeederManager messages"""
def __init__(self):
"""Initialise the slave"""
<|body_0|>
def initInThread(self):
"""Load shared queries"""
<|body_1|>
def __call__(self, parameters):
"""Unpickle event payload ... | stack_v2_sparse_classes_36k_train_006039 | 1,685 | no_license | [
{
"docstring": "Initialise the slave",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Load shared queries",
"name": "initInThread",
"signature": "def initInThread(self)"
},
{
"docstring": "Unpickle event payload if it is pickled",
"name": "__call__",... | 3 | null | Implement the Python class `DefaultSlave` described below.
Class description:
The default slave for FeederManager messages
Method signatures and docstrings:
- def __init__(self): Initialise the slave
- def initInThread(self): Load shared queries
- def __call__(self, parameters): Unpickle event payload if it is pickle... | Implement the Python class `DefaultSlave` described below.
Class description:
The default slave for FeederManager messages
Method signatures and docstrings:
- def __init__(self): Initialise the slave
- def initInThread(self): Load shared queries
- def __call__(self, parameters): Unpickle event payload if it is pickle... | 122f9332f2e944154dd0df68b6b3f2875427b032 | <|skeleton|>
class DefaultSlave:
"""The default slave for FeederManager messages"""
def __init__(self):
"""Initialise the slave"""
<|body_0|>
def initInThread(self):
"""Load shared queries"""
<|body_1|>
def __call__(self, parameters):
"""Unpickle event payload ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DefaultSlave:
"""The default slave for FeederManager messages"""
def __init__(self):
"""Initialise the slave"""
ThreadSlave.__init__(self)
myThread = threading.currentThread()
self.runningFeedersLock = myThread.runningFeedersLock
self.runningFeeders = myThread.runn... | the_stack_v2_python_sparse | src/python/WMComponent/FeederManager/Handler/DefaultSlave.py | cinquo/WMCore | train | 1 |
79944e732c2d048d78c44fb00f8607203d9d7080 | [
"self.site = page._link.site\nself.title = page._link.title\nself.loc_title = page._link.canonical_title()\nself.can_title = page._link.ns_title()\nself.outputlang = outputlang\nif outputlang is not None:\n if not hasattr(self, 'onsite'):\n self.onsite = pywikibot.Site(outputlang, self.site.family)\n t... | <|body_start_0|>
self.site = page._link.site
self.title = page._link.title
self.loc_title = page._link.canonical_title()
self.can_title = page._link.ns_title()
self.outputlang = outputlang
if outputlang is not None:
if not hasattr(self, 'onsite'):
... | Structure with Page attributes exposed for formatting from cmd line. | Formatter | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Formatter:
"""Structure with Page attributes exposed for formatting from cmd line."""
def __init__(self, page, outputlang=None, default='******'):
"""Initializer. @param page: the page to be formatted. @type page: Page object. @param outputlang: language code in which namespace befor... | stack_v2_sparse_classes_36k_train_006040 | 9,907 | permissive | [
{
"docstring": "Initializer. @param page: the page to be formatted. @type page: Page object. @param outputlang: language code in which namespace before title should be translated. Page ns will be searched in Site(outputlang, page.site.family) and, if found, its custom name will be used in page.title(). @type ou... | 2 | stack_v2_sparse_classes_30k_train_000666 | Implement the Python class `Formatter` described below.
Class description:
Structure with Page attributes exposed for formatting from cmd line.
Method signatures and docstrings:
- def __init__(self, page, outputlang=None, default='******'): Initializer. @param page: the page to be formatted. @type page: Page object. ... | Implement the Python class `Formatter` described below.
Class description:
Structure with Page attributes exposed for formatting from cmd line.
Method signatures and docstrings:
- def __init__(self, page, outputlang=None, default='******'): Initializer. @param page: the page to be formatted. @type page: Page object. ... | af470904ce62cedae63d285ca15146e9168a0ee6 | <|skeleton|>
class Formatter:
"""Structure with Page attributes exposed for formatting from cmd line."""
def __init__(self, page, outputlang=None, default='******'):
"""Initializer. @param page: the page to be formatted. @type page: Page object. @param outputlang: language code in which namespace befor... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Formatter:
"""Structure with Page attributes exposed for formatting from cmd line."""
def __init__(self, page, outputlang=None, default='******'):
"""Initializer. @param page: the page to be formatted. @type page: Page object. @param outputlang: language code in which namespace before title shoul... | the_stack_v2_python_sparse | scripts/listpages.py | anisayari/pywikibot | train | 3 |
b9d676a34e4a83f592580247ecde07aa85750585 | [
"params = dict(request.query_params)\nparams.update(dict(request.data))\nqueryset = kwargs.get('queryset', None)\nagg_field, group_fields, date_part = self.validate_request(params, queryset)\nif not params.get('show_null_groups', False) and (not params.get('show_nulls', False)):\n q_object = Q()\n for field i... | <|body_start_0|>
params = dict(request.query_params)
params.update(dict(request.data))
queryset = kwargs.get('queryset', None)
agg_field, group_fields, date_part = self.validate_request(params, queryset)
if not params.get('show_null_groups', False) and (not params.get('show_nulls... | Aggregate a queryset. Any pre-aggregation operations on the queryset (e.g. filtering) is already done (it's handled at the view level, in the get_queryset method). | AggregateQuerysetMixin | [
"CC0-1.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AggregateQuerysetMixin:
"""Aggregate a queryset. Any pre-aggregation operations on the queryset (e.g. filtering) is already done (it's handled at the view level, in the get_queryset method)."""
def aggregate(self, request, *args, **kwargs):
"""Perform an aggregate function on a Djang... | stack_v2_sparse_classes_36k_train_006041 | 10,956 | permissive | [
{
"docstring": "Perform an aggregate function on a Django queryset with an optional group by field.",
"name": "aggregate",
"signature": "def aggregate(self, request, *args, **kwargs)"
},
{
"docstring": "F-expression of col, wrapped if needed with SQL function call Assumes that there's an SQL fun... | 3 | stack_v2_sparse_classes_30k_train_011196 | Implement the Python class `AggregateQuerysetMixin` described below.
Class description:
Aggregate a queryset. Any pre-aggregation operations on the queryset (e.g. filtering) is already done (it's handled at the view level, in the get_queryset method).
Method signatures and docstrings:
- def aggregate(self, request, *... | Implement the Python class `AggregateQuerysetMixin` described below.
Class description:
Aggregate a queryset. Any pre-aggregation operations on the queryset (e.g. filtering) is already done (it's handled at the view level, in the get_queryset method).
Method signatures and docstrings:
- def aggregate(self, request, *... | 38f920438697930ae3ac57bbcaae9034877d8fb7 | <|skeleton|>
class AggregateQuerysetMixin:
"""Aggregate a queryset. Any pre-aggregation operations on the queryset (e.g. filtering) is already done (it's handled at the view level, in the get_queryset method)."""
def aggregate(self, request, *args, **kwargs):
"""Perform an aggregate function on a Djang... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AggregateQuerysetMixin:
"""Aggregate a queryset. Any pre-aggregation operations on the queryset (e.g. filtering) is already done (it's handled at the view level, in the get_queryset method)."""
def aggregate(self, request, *args, **kwargs):
"""Perform an aggregate function on a Django queryset wi... | the_stack_v2_python_sparse | usaspending_api/common/mixins.py | fedspendingtransparency/usaspending-api | train | 276 |
5dd58f907904443936d9e2b5a898853b4399a81d | [
"@functools.lru_cache()\ndef recur(m, n):\n if m == 1 and n == 1:\n return grid[0][0]\n elif m == 0 or n == 0:\n return float('inf')\n return grid[m - 1][n - 1] + min(recur(m - 1, n), recur(m, n - 1))\nreturn recur(len(grid), len(grid[0]))",
"grid = [[float('inf')] + x for x in grid]\ngrid.... | <|body_start_0|>
@functools.lru_cache()
def recur(m, n):
if m == 1 and n == 1:
return grid[0][0]
elif m == 0 or n == 0:
return float('inf')
return grid[m - 1][n - 1] + min(recur(m - 1, n), recur(m, n - 1))
return recur(len(grid)... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def minPathSum(self, grid: List[List[int]]) -> int:
"""递归思想， 这一题中，递归方法会慢很多； :param grid: :return:"""
<|body_0|>
def minPathSum_2(self, grid: List[List[int]]) -> int:
"""动态规划思想 :param grid: :return:"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_006042 | 1,164 | no_license | [
{
"docstring": "递归思想， 这一题中，递归方法会慢很多； :param grid: :return:",
"name": "minPathSum",
"signature": "def minPathSum(self, grid: List[List[int]]) -> int"
},
{
"docstring": "动态规划思想 :param grid: :return:",
"name": "minPathSum_2",
"signature": "def minPathSum_2(self, grid: List[List[int]]) -> in... | 2 | stack_v2_sparse_classes_30k_train_009505 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def minPathSum(self, grid: List[List[int]]) -> int: 递归思想， 这一题中，递归方法会慢很多； :param grid: :return:
- def minPathSum_2(self, grid: List[List[int]]) -> int: 动态规划思想 :param grid: :return... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def minPathSum(self, grid: List[List[int]]) -> int: 递归思想， 这一题中，递归方法会慢很多； :param grid: :return:
- def minPathSum_2(self, grid: List[List[int]]) -> int: 动态规划思想 :param grid: :return... | f2c162654a83c51495ebd161f42a1d0b69caf72d | <|skeleton|>
class Solution:
def minPathSum(self, grid: List[List[int]]) -> int:
"""递归思想， 这一题中，递归方法会慢很多； :param grid: :return:"""
<|body_0|>
def minPathSum_2(self, grid: List[List[int]]) -> int:
"""动态规划思想 :param grid: :return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def minPathSum(self, grid: List[List[int]]) -> int:
"""递归思想， 这一题中，递归方法会慢很多； :param grid: :return:"""
@functools.lru_cache()
def recur(m, n):
if m == 1 and n == 1:
return grid[0][0]
elif m == 0 or n == 0:
return float('in... | the_stack_v2_python_sparse | 64 minPathSum.py | ABenxj/leetcode | train | 1 | |
f70ed00cf128e878bbbcc66563038b1dfa630cde | [
"emails = clean_addresses(self.data['emails'])\nif not len(emails):\n raise ValidationError('No Valid Addresses Found')\nemail_string = [formataddr(entry) for entry in emails]\nreturn email_string",
"is_staff = self.cleaned_data.get('is_staff', False)\nis_superuser = self.cleaned_data.get('is_superuser', False... | <|body_start_0|>
emails = clean_addresses(self.data['emails'])
if not len(emails):
raise ValidationError('No Valid Addresses Found')
email_string = [formataddr(entry) for entry in emails]
return email_string
<|end_body_0|>
<|body_start_1|>
is_staff = self.cleaned_dat... | Form for inviting a user. | InviteForm | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InviteForm:
"""Form for inviting a user."""
def clean_emails(self):
"""Clean up email field to only include symantically valid addresses"""
<|body_0|>
def save(self):
"""Save the form."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
emails = cle... | stack_v2_sparse_classes_36k_train_006043 | 8,878 | permissive | [
{
"docstring": "Clean up email field to only include symantically valid addresses",
"name": "clean_emails",
"signature": "def clean_emails(self)"
},
{
"docstring": "Save the form.",
"name": "save",
"signature": "def save(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_005991 | Implement the Python class `InviteForm` described below.
Class description:
Form for inviting a user.
Method signatures and docstrings:
- def clean_emails(self): Clean up email field to only include symantically valid addresses
- def save(self): Save the form. | Implement the Python class `InviteForm` described below.
Class description:
Form for inviting a user.
Method signatures and docstrings:
- def clean_emails(self): Clean up email field to only include symantically valid addresses
- def save(self): Save the form.
<|skeleton|>
class InviteForm:
"""Form for inviting ... | a56c0f89df82694bf5db32a04d8b092974791972 | <|skeleton|>
class InviteForm:
"""Form for inviting a user."""
def clean_emails(self):
"""Clean up email field to only include symantically valid addresses"""
<|body_0|>
def save(self):
"""Save the form."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class InviteForm:
"""Form for inviting a user."""
def clean_emails(self):
"""Clean up email field to only include symantically valid addresses"""
emails = clean_addresses(self.data['emails'])
if not len(emails):
raise ValidationError('No Valid Addresses Found')
email... | the_stack_v2_python_sparse | open_connect/accounts/forms.py | ofa/connect | train | 66 |
3a9f1d6cfcabd6edf49287abd5c0d48ce76d0036 | [
"self.rasterpath = rasterpath\nself.num_chunks = num_chunks\nself.chunk_list = chunk_list\nself.metadata = metadata\nself.force_scv = force_scv\nreturn",
"for chunk_obj in self.chunk_list:\n if chunk_obj.index == index:\n return chunk_obj\nelse:\n raise Exception('No chunk with chunk_id = {0}'.format... | <|body_start_0|>
self.rasterpath = rasterpath
self.num_chunks = num_chunks
self.chunk_list = chunk_list
self.metadata = metadata
self.force_scv = force_scv
return
<|end_body_0|>
<|body_start_1|>
for chunk_obj in self.chunk_list:
if chunk_obj.index == ... | Creates a chunk bundle object. it can be used to pass smaller pieces of raster data to complex functions and reduce memory consumption in those functions. Presently, chunks are not saved individually, but are always bundled to form the undivided raster image. This allows chunks to be passed individually and sequentiall... | chunk_bundle | [
"LicenseRef-scancode-public-domain",
"LicenseRef-scancode-warranty-disclaimer",
"LicenseRef-scancode-us-govt-public-domain",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class chunk_bundle:
"""Creates a chunk bundle object. it can be used to pass smaller pieces of raster data to complex functions and reduce memory consumption in those functions. Presently, chunks are not saved individually, but are always bundled to form the undivided raster image. This allows chunks t... | stack_v2_sparse_classes_36k_train_006044 | 5,063 | permissive | [
{
"docstring": "Creates a chunk bundle. Two probable use cases: 1) loading raster to split into smaller chunks with: inchunk = chunk_bundle(rasterpath, num_chunks = #) inchunk.load() 2) building new chunk_bundle with processed data, passing on old chunks metadata: outchunk = chunk_bundle(rasterpath, chunk_list ... | 5 | stack_v2_sparse_classes_30k_train_019697 | Implement the Python class `chunk_bundle` described below.
Class description:
Creates a chunk bundle object. it can be used to pass smaller pieces of raster data to complex functions and reduce memory consumption in those functions. Presently, chunks are not saved individually, but are always bundled to form the undiv... | Implement the Python class `chunk_bundle` described below.
Class description:
Creates a chunk bundle object. it can be used to pass smaller pieces of raster data to complex functions and reduce memory consumption in those functions. Presently, chunks are not saved individually, but are always bundled to form the undiv... | 372ba1481a155dca102612307a8e354dcf975eaa | <|skeleton|>
class chunk_bundle:
"""Creates a chunk bundle object. it can be used to pass smaller pieces of raster data to complex functions and reduce memory consumption in those functions. Presently, chunks are not saved individually, but are always bundled to form the undivided raster image. This allows chunks t... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class chunk_bundle:
"""Creates a chunk bundle object. it can be used to pass smaller pieces of raster data to complex functions and reduce memory consumption in those functions. Presently, chunks are not saved individually, but are always bundled to form the undivided raster image. This allows chunks to be passed i... | the_stack_v2_python_sparse | dnppy_install/chunking/chunking.py | lmakely/dnppy | train | 0 |
d3ebd052df120a4f43fd5c4cbf7101889991661c | [
"proxy = mgmt_session.proxy(RwsdnalYang)\nsdn_account = RwsdnalYang.YangData_RwProject_Project_SdnAccounts_SdnAccountList(name=sdn_account_name, account_type=sdn_account_type)\nxpath = \"/rw-project:project[rw-project:name='default']/sdn-accounts/sdn-account-list[name=%s]\" % quoted_key(sdn_account_name)\nproxy.rep... | <|body_start_0|>
proxy = mgmt_session.proxy(RwsdnalYang)
sdn_account = RwsdnalYang.YangData_RwProject_Project_SdnAccounts_SdnAccountList(name=sdn_account_name, account_type=sdn_account_type)
xpath = "/rw-project:project[rw-project:name='default']/sdn-accounts/sdn-account-list[name=%s]" % quoted_... | TestSdnSetup | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestSdnSetup:
def test_create_odl_sdn_account(self, mgmt_session, sdn_account_name, sdn_account_type):
"""Configure sdn account Asserts: SDN name and accout type."""
<|body_0|>
def test_create_openstack_sdn_account(self, mgmt_session, openstack_sdn_account_name, cloud_accoun... | stack_v2_sparse_classes_36k_train_006045 | 8,232 | no_license | [
{
"docstring": "Configure sdn account Asserts: SDN name and accout type.",
"name": "test_create_odl_sdn_account",
"signature": "def test_create_odl_sdn_account(self, mgmt_session, sdn_account_name, sdn_account_type)"
},
{
"docstring": "Configure sdn account Asserts: SDN name and account type.",
... | 2 | null | Implement the Python class `TestSdnSetup` described below.
Class description:
Implement the TestSdnSetup class.
Method signatures and docstrings:
- def test_create_odl_sdn_account(self, mgmt_session, sdn_account_name, sdn_account_type): Configure sdn account Asserts: SDN name and accout type.
- def test_create_openst... | Implement the Python class `TestSdnSetup` described below.
Class description:
Implement the TestSdnSetup class.
Method signatures and docstrings:
- def test_create_odl_sdn_account(self, mgmt_session, sdn_account_name, sdn_account_type): Configure sdn account Asserts: SDN name and accout type.
- def test_create_openst... | cdd0abe80a76d533d08a51c7970d8ded06624b7d | <|skeleton|>
class TestSdnSetup:
def test_create_odl_sdn_account(self, mgmt_session, sdn_account_name, sdn_account_type):
"""Configure sdn account Asserts: SDN name and accout type."""
<|body_0|>
def test_create_openstack_sdn_account(self, mgmt_session, openstack_sdn_account_name, cloud_accoun... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestSdnSetup:
def test_create_odl_sdn_account(self, mgmt_session, sdn_account_name, sdn_account_type):
"""Configure sdn account Asserts: SDN name and accout type."""
proxy = mgmt_session.proxy(RwsdnalYang)
sdn_account = RwsdnalYang.YangData_RwProject_Project_SdnAccounts_SdnAccountList(... | the_stack_v2_python_sparse | osm/SO/rwlaunchpad/ra/pytest/test_launchpad.py | dennis-me/Pishahang | train | 2 | |
d83ec030afe80674ea238dddee10e37aba7083de | [
"self.__server_ip = ip\nself.__port = port\nself.__tcp = socket.socket(socket.AF_INET, socket.SOCK_STREAM)",
"endpoint = (self.__server_ip, self.__port)\ntry:\n self.__tcp.connect(endpoint)\n print('conexao realizada com sucesso!')\n self.__method()\nexcept Exception as e:\n print('Erro de conecacao c... | <|body_start_0|>
self.__server_ip = ip
self.__port = port
self.__tcp = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
<|end_body_0|>
<|body_start_1|>
endpoint = (self.__server_ip, self.__port)
try:
self.__tcp.connect(endpoint)
print('conexao realizada ... | Classe cliente | Cliente | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Cliente:
"""Classe cliente"""
def __init__(self, ip, port):
"""costrutor da classe cliente Args: ip : ip do servidor port : [porta do servidor"""
<|body_0|>
def start(self):
"""Metodo de inicializacao do cliente"""
<|body_1|>
def __method(self):
... | stack_v2_sparse_classes_36k_train_006046 | 1,751 | no_license | [
{
"docstring": "costrutor da classe cliente Args: ip : ip do servidor port : [porta do servidor",
"name": "__init__",
"signature": "def __init__(self, ip, port)"
},
{
"docstring": "Metodo de inicializacao do cliente",
"name": "start",
"signature": "def start(self)"
},
{
"docstrin... | 3 | stack_v2_sparse_classes_30k_train_004650 | Implement the Python class `Cliente` described below.
Class description:
Classe cliente
Method signatures and docstrings:
- def __init__(self, ip, port): costrutor da classe cliente Args: ip : ip do servidor port : [porta do servidor
- def start(self): Metodo de inicializacao do cliente
- def __method(self): metodod ... | Implement the Python class `Cliente` described below.
Class description:
Classe cliente
Method signatures and docstrings:
- def __init__(self, ip, port): costrutor da classe cliente Args: ip : ip do servidor port : [porta do servidor
- def start(self): Metodo de inicializacao do cliente
- def __method(self): metodod ... | c7208c4075dc250e348003226c13c47142c05c71 | <|skeleton|>
class Cliente:
"""Classe cliente"""
def __init__(self, ip, port):
"""costrutor da classe cliente Args: ip : ip do servidor port : [porta do servidor"""
<|body_0|>
def start(self):
"""Metodo de inicializacao do cliente"""
<|body_1|>
def __method(self):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Cliente:
"""Classe cliente"""
def __init__(self, ip, port):
"""costrutor da classe cliente Args: ip : ip do servidor port : [porta do servidor"""
self.__server_ip = ip
self.__port = port
self.__tcp = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
def start(self):
... | the_stack_v2_python_sparse | semana_7/cliente/cliente.py | EduardFonseca/InformaticaIndustrial | train | 0 |
2b8d87586eb6662c10256fc004b80eaafe221199 | [
"super(PointNetEstimation, self).__init__()\nself.conv1 = nn.Conv1d(3, 128, 1)\nself.conv2 = nn.Conv1d(128, 128, 1)\nself.conv3 = nn.Conv1d(128, 256, 1)\nself.conv4 = nn.Conv1d(256, 512, 1)\nself.bn1 = nn.BatchNorm1d(128)\nself.bn2 = nn.BatchNorm1d(128)\nself.bn3 = nn.BatchNorm1d(256)\nself.bn4 = nn.BatchNorm1d(512... | <|body_start_0|>
super(PointNetEstimation, self).__init__()
self.conv1 = nn.Conv1d(3, 128, 1)
self.conv2 = nn.Conv1d(128, 128, 1)
self.conv3 = nn.Conv1d(128, 256, 1)
self.conv4 = nn.Conv1d(256, 512, 1)
self.bn1 = nn.BatchNorm1d(128)
self.bn2 = nn.BatchNorm1d(128)
... | PointNetEstimation | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PointNetEstimation:
def __init__(self, n_classes=3):
"""v1 Amodal 3D Box Estimation Pointnet :param n_classes:3 :param one_hot_vec:[bs,n_classes]"""
<|body_0|>
def forward(self, pts, one_hot_vec):
""":param pts: [bs,3,m]: x,y,z after InstanceSeg :return: box_pred: [b... | stack_v2_sparse_classes_36k_train_006047 | 11,900 | permissive | [
{
"docstring": "v1 Amodal 3D Box Estimation Pointnet :param n_classes:3 :param one_hot_vec:[bs,n_classes]",
"name": "__init__",
"signature": "def __init__(self, n_classes=3)"
},
{
"docstring": ":param pts: [bs,3,m]: x,y,z after InstanceSeg :return: box_pred: [bs,3+NUM_HEADING_BIN*2+NUM_SIZE_CLUS... | 2 | stack_v2_sparse_classes_30k_train_013098 | Implement the Python class `PointNetEstimation` described below.
Class description:
Implement the PointNetEstimation class.
Method signatures and docstrings:
- def __init__(self, n_classes=3): v1 Amodal 3D Box Estimation Pointnet :param n_classes:3 :param one_hot_vec:[bs,n_classes]
- def forward(self, pts, one_hot_ve... | Implement the Python class `PointNetEstimation` described below.
Class description:
Implement the PointNetEstimation class.
Method signatures and docstrings:
- def __init__(self, n_classes=3): v1 Amodal 3D Box Estimation Pointnet :param n_classes:3 :param one_hot_vec:[bs,n_classes]
- def forward(self, pts, one_hot_ve... | 64bcfa4b292dacc91f92f2542e11d489b1fa2c8a | <|skeleton|>
class PointNetEstimation:
def __init__(self, n_classes=3):
"""v1 Amodal 3D Box Estimation Pointnet :param n_classes:3 :param one_hot_vec:[bs,n_classes]"""
<|body_0|>
def forward(self, pts, one_hot_vec):
""":param pts: [bs,3,m]: x,y,z after InstanceSeg :return: box_pred: [b... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PointNetEstimation:
def __init__(self, n_classes=3):
"""v1 Amodal 3D Box Estimation Pointnet :param n_classes:3 :param one_hot_vec:[bs,n_classes]"""
super(PointNetEstimation, self).__init__()
self.conv1 = nn.Conv1d(3, 128, 1)
self.conv2 = nn.Conv1d(128, 128, 1)
self.con... | the_stack_v2_python_sparse | frustum_pointnet/models/frustum_pointnets_v1_old.py | ayushjain1144/SeeingByMoving | train | 24 | |
a364a630388234178a62085f8ef09fd6a70e1615 | [
"if not a:\n return list()\nn = len(a)\nm = len(a[0])\nt = list()\nfor x, c in enumerate(self.gen_diagonal_coord(n, m)):\n p = self.traverse_diagonal(c, m, a)\n if x % 2 == 0:\n t.extend(p)\n else:\n t.extend(reversed(p))\nreturn t",
"for i in range(0, n, 1):\n yield (i, 0)\nfor j in ... | <|body_start_0|>
if not a:
return list()
n = len(a)
m = len(a[0])
t = list()
for x, c in enumerate(self.gen_diagonal_coord(n, m)):
p = self.traverse_diagonal(c, m, a)
if x % 2 == 0:
t.extend(p)
else:
... | Iteration over elements in 2D array. Time complexity: O(n) - Iterate over all elements in 2D array Space complexity: O(n) - Collect all elements in 2D array | Solution | [
"Unlicense"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
"""Iteration over elements in 2D array. Time complexity: O(n) - Iterate over all elements in 2D array Space complexity: O(n) - Collect all elements in 2D array"""
def find_diagonal_order(self, a):
"""Traverses all elements of 2D array in alternating diagonal order. :param l... | stack_v2_sparse_classes_36k_train_006048 | 3,214 | permissive | [
{
"docstring": "Traverses all elements of 2D array in alternating diagonal order. :param list[list[int]] a: 2D array of integers :return: array of elements from input array in diagonal order :rtype: list[int]",
"name": "find_diagonal_order",
"signature": "def find_diagonal_order(self, a)"
},
{
"... | 3 | stack_v2_sparse_classes_30k_train_008109 | Implement the Python class `Solution` described below.
Class description:
Iteration over elements in 2D array. Time complexity: O(n) - Iterate over all elements in 2D array Space complexity: O(n) - Collect all elements in 2D array
Method signatures and docstrings:
- def find_diagonal_order(self, a): Traverses all ele... | Implement the Python class `Solution` described below.
Class description:
Iteration over elements in 2D array. Time complexity: O(n) - Iterate over all elements in 2D array Space complexity: O(n) - Collect all elements in 2D array
Method signatures and docstrings:
- def find_diagonal_order(self, a): Traverses all ele... | 69f90877c5466927e8b081c4268cbcda074813ec | <|skeleton|>
class Solution:
"""Iteration over elements in 2D array. Time complexity: O(n) - Iterate over all elements in 2D array Space complexity: O(n) - Collect all elements in 2D array"""
def find_diagonal_order(self, a):
"""Traverses all elements of 2D array in alternating diagonal order. :param l... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
"""Iteration over elements in 2D array. Time complexity: O(n) - Iterate over all elements in 2D array Space complexity: O(n) - Collect all elements in 2D array"""
def find_diagonal_order(self, a):
"""Traverses all elements of 2D array in alternating diagonal order. :param list[list[int]... | the_stack_v2_python_sparse | 0498_diagonal_traverse/python_source.py | arthurdysart/LeetCode | train | 0 |
2c82dd33180a7442607e5cbedf8846bd72b37150 | [
"startTime = datetime.datetime.now()\nclient = dml.pymongo.MongoClient()\nrepo = client.repo\nrepo.authenticate('bmroach', 'bmroach')\nrepo.dropCollection('open_space')\nrepo.createCollection('open_space')\nurl = 'http://bostonopendata-boston.opendata.arcgis.com/datasets/2868d370c55d4d458d4ae2224ef8cddd_7.geojson'\... | <|body_start_0|>
startTime = datetime.datetime.now()
client = dml.pymongo.MongoClient()
repo = client.repo
repo.authenticate('bmroach', 'bmroach')
repo.dropCollection('open_space')
repo.createCollection('open_space')
url = 'http://bostonopendata-boston.opendata.ar... | retrieve_open_space | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class retrieve_open_space:
def execute(trial=False, log=False):
"""Retrieves open spaces in Boston as geoJSON"""
<|body_0|>
def provenance(doc=prov.model.ProvDocument(), startTime=None, endTime=None):
"""Create the provenance document describing everything happening in thi... | stack_v2_sparse_classes_36k_train_006049 | 3,753 | no_license | [
{
"docstring": "Retrieves open spaces in Boston as geoJSON",
"name": "execute",
"signature": "def execute(trial=False, log=False)"
},
{
"docstring": "Create the provenance document describing everything happening in this script. Each run of the script will generate a new document describing that... | 2 | stack_v2_sparse_classes_30k_train_003287 | Implement the Python class `retrieve_open_space` described below.
Class description:
Implement the retrieve_open_space class.
Method signatures and docstrings:
- def execute(trial=False, log=False): Retrieves open spaces in Boston as geoJSON
- def provenance(doc=prov.model.ProvDocument(), startTime=None, endTime=None... | Implement the Python class `retrieve_open_space` described below.
Class description:
Implement the retrieve_open_space class.
Method signatures and docstrings:
- def execute(trial=False, log=False): Retrieves open spaces in Boston as geoJSON
- def provenance(doc=prov.model.ProvDocument(), startTime=None, endTime=None... | 97e72731ffadbeae57d7a332decd58706e7c08de | <|skeleton|>
class retrieve_open_space:
def execute(trial=False, log=False):
"""Retrieves open spaces in Boston as geoJSON"""
<|body_0|>
def provenance(doc=prov.model.ProvDocument(), startTime=None, endTime=None):
"""Create the provenance document describing everything happening in thi... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class retrieve_open_space:
def execute(trial=False, log=False):
"""Retrieves open spaces in Boston as geoJSON"""
startTime = datetime.datetime.now()
client = dml.pymongo.MongoClient()
repo = client.repo
repo.authenticate('bmroach', 'bmroach')
repo.dropCollection('open... | the_stack_v2_python_sparse | bmroach/retrieve_open_space.py | ROODAY/course-2017-fal-proj | train | 3 | |
4465bedab331f4fc1378cddb2d4933ed199d76f4 | [
"super(CA_NET, self).__init__()\nself.t_dim = t_dim\nself.ef_dim = ef_dim\nself.fc = nn.Linear(self.t_dim, self.ef_dim * 4, bias=True)\nself.relu = nn.GLU(1)",
"x = self.relu(self.fc(text_embedding))\nmu = x[:, :self.ef_dim]\nlogvar = x[:, self.ef_dim:]\nreturn (mu, logvar)",
"std = logvar.mul(0.5).exp_()\neps ... | <|body_start_0|>
super(CA_NET, self).__init__()
self.t_dim = t_dim
self.ef_dim = ef_dim
self.fc = nn.Linear(self.t_dim, self.ef_dim * 4, bias=True)
self.relu = nn.GLU(1)
<|end_body_0|>
<|body_start_1|>
x = self.relu(self.fc(text_embedding))
mu = x[:, :self.ef_dim... | Conditioning Augmentation network. Args: - t_dim (int): text dimension - ef_dim (int): embedding dimension | CA_NET | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CA_NET:
"""Conditioning Augmentation network. Args: - t_dim (int): text dimension - ef_dim (int): embedding dimension"""
def __init__(self, t_dim, ef_dim):
"""Initialize the conditioning augmentation."""
<|body_0|>
def encode(self, text_embedding):
"""Encode the ... | stack_v2_sparse_classes_36k_train_006050 | 22,492 | no_license | [
{
"docstring": "Initialize the conditioning augmentation.",
"name": "__init__",
"signature": "def __init__(self, t_dim, ef_dim)"
},
{
"docstring": "Encode the text embedding.",
"name": "encode",
"signature": "def encode(self, text_embedding)"
},
{
"docstring": "Reparametrize the ... | 4 | stack_v2_sparse_classes_30k_train_014791 | Implement the Python class `CA_NET` described below.
Class description:
Conditioning Augmentation network. Args: - t_dim (int): text dimension - ef_dim (int): embedding dimension
Method signatures and docstrings:
- def __init__(self, t_dim, ef_dim): Initialize the conditioning augmentation.
- def encode(self, text_em... | Implement the Python class `CA_NET` described below.
Class description:
Conditioning Augmentation network. Args: - t_dim (int): text dimension - ef_dim (int): embedding dimension
Method signatures and docstrings:
- def __init__(self, t_dim, ef_dim): Initialize the conditioning augmentation.
- def encode(self, text_em... | 70d344d80425e7bbcc7984737dbe50a6638293c9 | <|skeleton|>
class CA_NET:
"""Conditioning Augmentation network. Args: - t_dim (int): text dimension - ef_dim (int): embedding dimension"""
def __init__(self, t_dim, ef_dim):
"""Initialize the conditioning augmentation."""
<|body_0|>
def encode(self, text_embedding):
"""Encode the ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CA_NET:
"""Conditioning Augmentation network. Args: - t_dim (int): text dimension - ef_dim (int): embedding dimension"""
def __init__(self, t_dim, ef_dim):
"""Initialize the conditioning augmentation."""
super(CA_NET, self).__init__()
self.t_dim = t_dim
self.ef_dim = ef_di... | the_stack_v2_python_sparse | TeleGAN/model.py | ails-lab/teleGAN | train | 1 |
39a2bc0cae49bcb98a7c0d80823bdec07d8d8b0b | [
"left = 0\nright = len(nums) - 1\nwhile left < right - 1:\n mid = (left + right) / 2\n if nums[mid] > nums[mid + 1] and nums[mid] > nums[mid - 1]:\n return mid\n if nums[mid] < nums[mid + 1]:\n left = mid\n else:\n right = mid\nreturn left if nums[left] >= nums[right] else right",
... | <|body_start_0|>
left = 0
right = len(nums) - 1
while left < right - 1:
mid = (left + right) / 2
if nums[mid] > nums[mid + 1] and nums[mid] > nums[mid - 1]:
return mid
if nums[mid] < nums[mid + 1]:
left = mid
else:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findPeakElement(self, nums):
"""Lets say you have a mid number at index x, nums[x] if (num[x+1] > nums[x]), that means a peak element HAS to exist on the right half of that array, because (since every number is unique) 1. the numbers keep increasing on the right side, and t... | stack_v2_sparse_classes_36k_train_006051 | 1,862 | no_license | [
{
"docstring": "Lets say you have a mid number at index x, nums[x] if (num[x+1] > nums[x]), that means a peak element HAS to exist on the right half of that array, because (since every number is unique) 1. the numbers keep increasing on the right side, and the peak will be the last element. 2. the numbers stop ... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findPeakElement(self, nums): Lets say you have a mid number at index x, nums[x] if (num[x+1] > nums[x]), that means a peak element HAS to exist on the right half of that arra... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findPeakElement(self, nums): Lets say you have a mid number at index x, nums[x] if (num[x+1] > nums[x]), that means a peak element HAS to exist on the right half of that arra... | 8bb17099be02d997d554519be360ef4aa1c028e3 | <|skeleton|>
class Solution:
def findPeakElement(self, nums):
"""Lets say you have a mid number at index x, nums[x] if (num[x+1] > nums[x]), that means a peak element HAS to exist on the right half of that array, because (since every number is unique) 1. the numbers keep increasing on the right side, and t... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def findPeakElement(self, nums):
"""Lets say you have a mid number at index x, nums[x] if (num[x+1] > nums[x]), that means a peak element HAS to exist on the right half of that array, because (since every number is unique) 1. the numbers keep increasing on the right side, and the peak will b... | the_stack_v2_python_sparse | Google/2. medium/162. Find Peak Element.py | yemao616/summer18 | train | 0 | |
9f6612c20775ec9469ae89dd92f50276327e5a22 | [
"super(PCC_Layer, self).__init__()\nself.alpha = alpha\nself.centroid = centroid",
"z = emb.unsqueeze(1)\nu = self.centroid\nqij = (1.0 + torch.sum((z - u) ** 2, dim=2) / self.alpha) ** (-1)\nqij_normalize = qij.T / torch.sum(qij, dim=1)\nqij_normalize = qij_normalize.T\nreturn qij_normalize"
] | <|body_start_0|>
super(PCC_Layer, self).__init__()
self.alpha = alpha
self.centroid = centroid
<|end_body_0|>
<|body_start_1|>
z = emb.unsqueeze(1)
u = self.centroid
qij = (1.0 + torch.sum((z - u) ** 2, dim=2) / self.alpha) ** (-1)
qij_normalize = qij.T / torch.s... | PCC_Layer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PCC_Layer:
def __init__(self, centroid, alpha=1.0):
""":param centroid: tensor, predefined centroid, shape: (n_class, emb_dim)"""
<|body_0|>
def forward(self, emb):
"""see paper `Unsupervised Deep Embedding for Clustering Analysis` qij = 1/(1+dist(zi, uj)^2), then no... | stack_v2_sparse_classes_36k_train_006052 | 2,727 | no_license | [
{
"docstring": ":param centroid: tensor, predefined centroid, shape: (n_class, emb_dim)",
"name": "__init__",
"signature": "def __init__(self, centroid, alpha=1.0)"
},
{
"docstring": "see paper `Unsupervised Deep Embedding for Clustering Analysis` qij = 1/(1+dist(zi, uj)^2), then normalize it. q... | 2 | null | Implement the Python class `PCC_Layer` described below.
Class description:
Implement the PCC_Layer class.
Method signatures and docstrings:
- def __init__(self, centroid, alpha=1.0): :param centroid: tensor, predefined centroid, shape: (n_class, emb_dim)
- def forward(self, emb): see paper `Unsupervised Deep Embeddin... | Implement the Python class `PCC_Layer` described below.
Class description:
Implement the PCC_Layer class.
Method signatures and docstrings:
- def __init__(self, centroid, alpha=1.0): :param centroid: tensor, predefined centroid, shape: (n_class, emb_dim)
- def forward(self, emb): see paper `Unsupervised Deep Embeddin... | 4e5908eb4c230e80e7d49bdbd77e7ec73de327c6 | <|skeleton|>
class PCC_Layer:
def __init__(self, centroid, alpha=1.0):
""":param centroid: tensor, predefined centroid, shape: (n_class, emb_dim)"""
<|body_0|>
def forward(self, emb):
"""see paper `Unsupervised Deep Embedding for Clustering Analysis` qij = 1/(1+dist(zi, uj)^2), then no... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PCC_Layer:
def __init__(self, centroid, alpha=1.0):
""":param centroid: tensor, predefined centroid, shape: (n_class, emb_dim)"""
super(PCC_Layer, self).__init__()
self.alpha = alpha
self.centroid = centroid
def forward(self, emb):
"""see paper `Unsupervised Deep E... | the_stack_v2_python_sparse | network_torch/Dual_CSA.py | lusccc/Trajectory-Classification-using-Dual-CSA | train | 10 | |
01e855c7d9a293fd79de0a25505cf281760a14b2 | [
"Turtle.__init__(self, shape='square', visible=False)\nself.penup()\nself.shapesize(n * 1.25, 0.75, 1)\nself.sety(12.5 * n)\nself.x = Peg.pos\nself.setx(self.x)\nself.showturtle()\nPeg.pos += 200",
"disk.setx(self.x)\ndisk.sety(10 + len(self) * 25)\nself.append(disk)",
"disk = self.pop()\ndisk.sety(300)\nreturn... | <|body_start_0|>
Turtle.__init__(self, shape='square', visible=False)
self.penup()
self.shapesize(n * 1.25, 0.75, 1)
self.sety(12.5 * n)
self.x = Peg.pos
self.setx(self.x)
self.showturtle()
Peg.pos += 200
<|end_body_0|>
<|body_start_1|>
disk.setx(... | Classe de pino da torre de Hanói, herda de Turtle e list ________________________________________________________ __init__(self, n) Inicializa um pino para n discos pop(self) Remove o disco de cima do pino e o retorna push(self, disk) coloca o disco no pino | Peg | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Peg:
"""Classe de pino da torre de Hanói, herda de Turtle e list ________________________________________________________ __init__(self, n) Inicializa um pino para n discos pop(self) Remove o disco de cima do pino e o retorna push(self, disk) coloca o disco no pino"""
def __init__(self, n):
... | stack_v2_sparse_classes_36k_train_006053 | 2,822 | no_license | [
{
"docstring": "Inicializa um pino para n discos",
"name": "__init__",
"signature": "def __init__(self, n)"
},
{
"docstring": "Coloca disco em torno do pino",
"name": "push",
"signature": "def push(self, disk)"
},
{
"docstring": "Remove disco do topo do pino e o retorna",
"na... | 3 | stack_v2_sparse_classes_30k_train_015896 | Implement the Python class `Peg` described below.
Class description:
Classe de pino da torre de Hanói, herda de Turtle e list ________________________________________________________ __init__(self, n) Inicializa um pino para n discos pop(self) Remove o disco de cima do pino e o retorna push(self, disk) coloca o disco ... | Implement the Python class `Peg` described below.
Class description:
Classe de pino da torre de Hanói, herda de Turtle e list ________________________________________________________ __init__(self, n) Inicializa um pino para n discos pop(self) Remove o disco de cima do pino e o retorna push(self, disk) coloca o disco ... | 5d4eec368be91c18f0ae5c17d342e6eb0f1c79be | <|skeleton|>
class Peg:
"""Classe de pino da torre de Hanói, herda de Turtle e list ________________________________________________________ __init__(self, n) Inicializa um pino para n discos pop(self) Remove o disco de cima do pino e o retorna push(self, disk) coloca o disco no pino"""
def __init__(self, n):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Peg:
"""Classe de pino da torre de Hanói, herda de Turtle e list ________________________________________________________ __init__(self, n) Inicializa um pino para n discos pop(self) Remove o disco de cima do pino e o retorna push(self, disk) coloca o disco no pino"""
def __init__(self, n):
"""In... | the_stack_v2_python_sparse | Semana3/turtle_hanoi.py | ju-c-lopes/Univesp_Algoritmos_II | train | 0 |
fd245947dd9512226f8e90622a907d9a1a639817 | [
"self._z_nodes = z_nodes.astype(np.float64)\nself._redshifts = redshifts.astype(np.float64)\nself._values = values.astype(np.float64)",
"bounds = []\nfor i in range(len(p0)):\n bounds.append([min_val, max_val])\nres = scipy.optimize.minimize(self, p0, method='L-BFGS-B', bounds=bounds, jac=False, options={'maxf... | <|body_start_0|>
self._z_nodes = z_nodes.astype(np.float64)
self._redshifts = redshifts.astype(np.float64)
self._values = values.astype(np.float64)
<|end_body_0|>
<|body_start_1|>
bounds = []
for i in range(len(p0)):
bounds.append([min_val, max_val])
res = sc... | Class to fit a spline to the median value as a function of redshift. This can be the color or magnitude or any quantity. | MedZFitter | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MedZFitter:
"""Class to fit a spline to the median value as a function of redshift. This can be the color or magnitude or any quantity."""
def __init__(self, z_nodes, redshifts, values):
"""Instantiate a MedZFitter object Parameters ---------- z_nodes: `np.array` Float array for reds... | stack_v2_sparse_classes_36k_train_006054 | 45,530 | permissive | [
{
"docstring": "Instantiate a MedZFitter object Parameters ---------- z_nodes: `np.array` Float array for redshift nodes redshifts: `np.array` Float array of input redshifts to fit values: `np.array` Float array of color values to fit",
"name": "__init__",
"signature": "def __init__(self, z_nodes, redsh... | 3 | stack_v2_sparse_classes_30k_train_017443 | Implement the Python class `MedZFitter` described below.
Class description:
Class to fit a spline to the median value as a function of redshift. This can be the color or magnitude or any quantity.
Method signatures and docstrings:
- def __init__(self, z_nodes, redshifts, values): Instantiate a MedZFitter object Param... | Implement the Python class `MedZFitter` described below.
Class description:
Class to fit a spline to the median value as a function of redshift. This can be the color or magnitude or any quantity.
Method signatures and docstrings:
- def __init__(self, z_nodes, redshifts, values): Instantiate a MedZFitter object Param... | d3a8b432c2f3a20aa518a7781c0f2aa315624855 | <|skeleton|>
class MedZFitter:
"""Class to fit a spline to the median value as a function of redshift. This can be the color or magnitude or any quantity."""
def __init__(self, z_nodes, redshifts, values):
"""Instantiate a MedZFitter object Parameters ---------- z_nodes: `np.array` Float array for reds... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MedZFitter:
"""Class to fit a spline to the median value as a function of redshift. This can be the color or magnitude or any quantity."""
def __init__(self, z_nodes, redshifts, values):
"""Instantiate a MedZFitter object Parameters ---------- z_nodes: `np.array` Float array for redshift nodes re... | the_stack_v2_python_sparse | redmapper/fitters.py | erykoff/redmapper | train | 20 |
f7b92c135c678cae08d786fe7507e3ed2b784744 | [
"with self.Session() as session:\n if filter_id is not None:\n f = session.scalars(Filter.select(session.user_or_token, options=[joinedload(Filter.stream)]).where(Filter.id == filter_id)).first()\n if f is None:\n return self.error(f'Cannot find a filter with ID: {filter_id}.')\n ... | <|body_start_0|>
with self.Session() as session:
if filter_id is not None:
f = session.scalars(Filter.select(session.user_or_token, options=[joinedload(Filter.stream)]).where(Filter.id == filter_id)).first()
if f is None:
return self.error(f'Cannot... | FilterHandler | [
"BSD-3-Clause",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FilterHandler:
def get(self, filter_id=None):
"""--- single: description: Retrieve a filter tags: - filters parameters: - in: path name: filter_id required: true schema: type: integer responses: 200: content: application/json: schema: SingleFilter 400: content: application/json: schema: ... | stack_v2_sparse_classes_36k_train_006055 | 5,485 | permissive | [
{
"docstring": "--- single: description: Retrieve a filter tags: - filters parameters: - in: path name: filter_id required: true schema: type: integer responses: 200: content: application/json: schema: SingleFilter 400: content: application/json: schema: Error multiple: description: Retrieve all filters tags: -... | 4 | stack_v2_sparse_classes_30k_train_000880 | Implement the Python class `FilterHandler` described below.
Class description:
Implement the FilterHandler class.
Method signatures and docstrings:
- def get(self, filter_id=None): --- single: description: Retrieve a filter tags: - filters parameters: - in: path name: filter_id required: true schema: type: integer re... | Implement the Python class `FilterHandler` described below.
Class description:
Implement the FilterHandler class.
Method signatures and docstrings:
- def get(self, filter_id=None): --- single: description: Retrieve a filter tags: - filters parameters: - in: path name: filter_id required: true schema: type: integer re... | 161d3532ba3ba059446addcdac58ca96f39e9636 | <|skeleton|>
class FilterHandler:
def get(self, filter_id=None):
"""--- single: description: Retrieve a filter tags: - filters parameters: - in: path name: filter_id required: true schema: type: integer responses: 200: content: application/json: schema: SingleFilter 400: content: application/json: schema: ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FilterHandler:
def get(self, filter_id=None):
"""--- single: description: Retrieve a filter tags: - filters parameters: - in: path name: filter_id required: true schema: type: integer responses: 200: content: application/json: schema: SingleFilter 400: content: application/json: schema: Error multiple... | the_stack_v2_python_sparse | skyportal/handlers/api/filter.py | skyportal/skyportal | train | 80 | |
03edf1a97d3ec2e95b7a9500a951150bf5cbaf95 | [
"input_json = request.data\noutput_json = dict(zip(['AvailabilityDetails', 'AuthenticationDetails', 'SessionDetails', 'Payload'], [input_json['AvailabilityDetails'], input_json['AuthenticationDetails'], input_json['SessionDetails'], None]))\ntry:\n json_params = input_json['APIParams']\n json_params['profile_... | <|body_start_0|>
input_json = request.data
output_json = dict(zip(['AvailabilityDetails', 'AuthenticationDetails', 'SessionDetails', 'Payload'], [input_json['AvailabilityDetails'], input_json['AuthenticationDetails'], input_json['SessionDetails'], None]))
try:
json_params = input_jso... | This API will create a notification | PopulateMyNotificationsAPI | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PopulateMyNotificationsAPI:
"""This API will create a notification"""
def post(self, request):
"""Post function to crete a notification"""
<|body_0|>
def populate_my_notifications_json(self, request):
"""This API will create a notification :param request: { 'prof... | stack_v2_sparse_classes_36k_train_006056 | 3,021 | no_license | [
{
"docstring": "Post function to crete a notification",
"name": "post",
"signature": "def post(self, request)"
},
{
"docstring": "This API will create a notification :param request: { 'profile_id':277 } :return",
"name": "populate_my_notifications_json",
"signature": "def populate_my_not... | 2 | stack_v2_sparse_classes_30k_test_000554 | Implement the Python class `PopulateMyNotificationsAPI` described below.
Class description:
This API will create a notification
Method signatures and docstrings:
- def post(self, request): Post function to crete a notification
- def populate_my_notifications_json(self, request): This API will create a notification :p... | Implement the Python class `PopulateMyNotificationsAPI` described below.
Class description:
This API will create a notification
Method signatures and docstrings:
- def post(self, request): Post function to crete a notification
- def populate_my_notifications_json(self, request): This API will create a notification :p... | 36eb9931f330e64902354c6fc471be2adf4b7049 | <|skeleton|>
class PopulateMyNotificationsAPI:
"""This API will create a notification"""
def post(self, request):
"""Post function to crete a notification"""
<|body_0|>
def populate_my_notifications_json(self, request):
"""This API will create a notification :param request: { 'prof... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PopulateMyNotificationsAPI:
"""This API will create a notification"""
def post(self, request):
"""Post function to crete a notification"""
input_json = request.data
output_json = dict(zip(['AvailabilityDetails', 'AuthenticationDetails', 'SessionDetails', 'Payload'], [input_json['A... | the_stack_v2_python_sparse | Generic/common/notifications_new/api/populate_my_notifications/views_populate_my_notifications.py | archiemb303/common_backend_django | train | 0 |
4cd2442be7be6778bc5050fdc35655dd0eb1d010 | [
"if len(lists) == 0:\n return\nhead = ListNode(0)\nnew_list = head\nK = len(lists)\nres = lists[0]\nfor i in range(1, K):\n res = self.mergeTwoLists(res, lists[i])\nreturn res",
"new_head = ListNode(0)\nnew_list = new_head\nwhile l1 and l2:\n if l1.val < l2.val:\n new_head.next = l1\n l1 = ... | <|body_start_0|>
if len(lists) == 0:
return
head = ListNode(0)
new_list = head
K = len(lists)
res = lists[0]
for i in range(1, K):
res = self.mergeTwoLists(res, lists[i])
return res
<|end_body_0|>
<|body_start_1|>
new_head = ListNo... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def mergeKLists(self, lists):
""":type lists: List[ListNode] :rtype: ListNode"""
<|body_0|>
def mergeTwoLists(self, l1, l2):
""":type l1: ListNode :type l2: ListNode :rtype: ListNode"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if len(l... | stack_v2_sparse_classes_36k_train_006057 | 1,105 | permissive | [
{
"docstring": ":type lists: List[ListNode] :rtype: ListNode",
"name": "mergeKLists",
"signature": "def mergeKLists(self, lists)"
},
{
"docstring": ":type l1: ListNode :type l2: ListNode :rtype: ListNode",
"name": "mergeTwoLists",
"signature": "def mergeTwoLists(self, l1, l2)"
}
] | 2 | stack_v2_sparse_classes_30k_train_016759 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def mergeKLists(self, lists): :type lists: List[ListNode] :rtype: ListNode
- def mergeTwoLists(self, l1, l2): :type l1: ListNode :type l2: ListNode :rtype: ListNode | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def mergeKLists(self, lists): :type lists: List[ListNode] :rtype: ListNode
- def mergeTwoLists(self, l1, l2): :type l1: ListNode :type l2: ListNode :rtype: ListNode
<|skeleton|>... | e00ebc7d83583ffd26c53f48efdd27ebc76a9623 | <|skeleton|>
class Solution:
def mergeKLists(self, lists):
""":type lists: List[ListNode] :rtype: ListNode"""
<|body_0|>
def mergeTwoLists(self, l1, l2):
""":type l1: ListNode :type l2: ListNode :rtype: ListNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def mergeKLists(self, lists):
""":type lists: List[ListNode] :rtype: ListNode"""
if len(lists) == 0:
return
head = ListNode(0)
new_list = head
K = len(lists)
res = lists[0]
for i in range(1, K):
res = self.mergeTwoLists(... | the_stack_v2_python_sparse | 23_Merge-K-Sorted-Lists.py | Coalin/Daily-LeetCode-Exercise | train | 4 | |
a3a777a18022111b81a565503bf9a2246dd90bbb | [
"super().__init__()\nif weights is not None and (not np.isclose(weights.sum(), 1)):\n raise ValueError('Weights must sum to 1.')\nself.weights = weights",
"if self.weights is None:\n m = scores.shape[-1]\n self.weights = torch.ones(m, device=scores.device) / m\nreturn scores @ self.weights"
] | <|body_start_0|>
super().__init__()
if weights is not None and (not np.isclose(weights.sum(), 1)):
raise ValueError('Weights must sum to 1.')
self.weights = weights
<|end_body_0|>
<|body_start_1|>
if self.weights is None:
m = scores.shape[-1]
self.wei... | AverageAggregator | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AverageAggregator:
def __init__(self, weights: Optional[torch.Tensor]=None):
"""Averages the scores of the detectors in an ensemble. Parameters ---------- weights Optional parameter to weight the scores. If `weights` is left ``None`` then will be set to a vector of ones. Raises ------ Va... | stack_v2_sparse_classes_36k_train_006058 | 9,337 | permissive | [
{
"docstring": "Averages the scores of the detectors in an ensemble. Parameters ---------- weights Optional parameter to weight the scores. If `weights` is left ``None`` then will be set to a vector of ones. Raises ------ ValueError If `weights` does not sum to ``1``.",
"name": "__init__",
"signature": ... | 2 | stack_v2_sparse_classes_30k_train_013021 | Implement the Python class `AverageAggregator` described below.
Class description:
Implement the AverageAggregator class.
Method signatures and docstrings:
- def __init__(self, weights: Optional[torch.Tensor]=None): Averages the scores of the detectors in an ensemble. Parameters ---------- weights Optional parameter ... | Implement the Python class `AverageAggregator` described below.
Class description:
Implement the AverageAggregator class.
Method signatures and docstrings:
- def __init__(self, weights: Optional[torch.Tensor]=None): Averages the scores of the detectors in an ensemble. Parameters ---------- weights Optional parameter ... | 4a1b4f74a8590117965421e86c2295bff0f33e89 | <|skeleton|>
class AverageAggregator:
def __init__(self, weights: Optional[torch.Tensor]=None):
"""Averages the scores of the detectors in an ensemble. Parameters ---------- weights Optional parameter to weight the scores. If `weights` is left ``None`` then will be set to a vector of ones. Raises ------ Va... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AverageAggregator:
def __init__(self, weights: Optional[torch.Tensor]=None):
"""Averages the scores of the detectors in an ensemble. Parameters ---------- weights Optional parameter to weight the scores. If `weights` is left ``None`` then will be set to a vector of ones. Raises ------ ValueError If `w... | the_stack_v2_python_sparse | alibi_detect/od/pytorch/ensemble.py | SeldonIO/alibi-detect | train | 1,922 | |
297d24bc2ac40c285d60abb20a14071b3e94fe10 | [
"if not email:\n raise ValueError('The given email must be set')\nemail = self.normalize_email(email)\nuser = self.model(email=email, **extra_fields)\nuser.set_password(password)\nuser.save(using=self._db)\nreturn user",
"extra_fields.setdefault('is_staff', False)\nextra_fields.setdefault('is_superuser', False... | <|body_start_0|>
if not email:
raise ValueError('The given email must be set')
email = self.normalize_email(email)
user = self.model(email=email, **extra_fields)
user.set_password(password)
user.save(using=self._db)
return user
<|end_body_0|>
<|body_start_1|>... | Define a model manager for User model with no username field. | ParticipantManager | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ParticipantManager:
"""Define a model manager for User model with no username field."""
def _create_user(self, email, password, **extra_fields):
"""Create and save a User with the given email and password."""
<|body_0|>
def create_user(self, email, password=None, **extra... | stack_v2_sparse_classes_36k_train_006059 | 3,675 | no_license | [
{
"docstring": "Create and save a User with the given email and password.",
"name": "_create_user",
"signature": "def _create_user(self, email, password, **extra_fields)"
},
{
"docstring": "Create and save a regular User with the given email and password.",
"name": "create_user",
"signat... | 3 | stack_v2_sparse_classes_30k_train_012911 | Implement the Python class `ParticipantManager` described below.
Class description:
Define a model manager for User model with no username field.
Method signatures and docstrings:
- def _create_user(self, email, password, **extra_fields): Create and save a User with the given email and password.
- def create_user(sel... | Implement the Python class `ParticipantManager` described below.
Class description:
Define a model manager for User model with no username field.
Method signatures and docstrings:
- def _create_user(self, email, password, **extra_fields): Create and save a User with the given email and password.
- def create_user(sel... | a57b9fe5b73e58e703f15b6f3c55a9dde8102496 | <|skeleton|>
class ParticipantManager:
"""Define a model manager for User model with no username field."""
def _create_user(self, email, password, **extra_fields):
"""Create and save a User with the given email and password."""
<|body_0|>
def create_user(self, email, password=None, **extra... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ParticipantManager:
"""Define a model manager for User model with no username field."""
def _create_user(self, email, password, **extra_fields):
"""Create and save a User with the given email and password."""
if not email:
raise ValueError('The given email must be set')
... | the_stack_v2_python_sparse | meetings/models.py | gsoosk/Jalas-Backend | train | 0 |
9be28398bae2e72073be7df5197abfc079264fe9 | [
"k = k % len(nums)\nfor i in range(len(nums) - k):\n nums.append(nums[0])\n nums.pop(0)\nreturn nums",
"k = k % len(nums)\nfor _ in range(k):\n nums.insert(0, nums.pop())\nreturn nums",
"k = k % len(nums)\nnums[:] = nums[-k:] + nums[:-k]\nreturn nums"
] | <|body_start_0|>
k = k % len(nums)
for i in range(len(nums) - k):
nums.append(nums[0])
nums.pop(0)
return nums
<|end_body_0|>
<|body_start_1|>
k = k % len(nums)
for _ in range(k):
nums.insert(0, nums.pop())
return nums
<|end_body_1|>
... | Solution | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def rotate(self, nums: list, k: int) -> None:
"""Do not return anything, modify nums in-place instead."""
<|body_0|>
def rotate2(self, nums: list, k: int) -> None:
"""Do not return anything, modify nums in-place instead."""
<|body_1|>
def rotat... | stack_v2_sparse_classes_36k_train_006060 | 1,053 | permissive | [
{
"docstring": "Do not return anything, modify nums in-place instead.",
"name": "rotate",
"signature": "def rotate(self, nums: list, k: int) -> None"
},
{
"docstring": "Do not return anything, modify nums in-place instead.",
"name": "rotate2",
"signature": "def rotate2(self, nums: list, ... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def rotate(self, nums: list, k: int) -> None: Do not return anything, modify nums in-place instead.
- def rotate2(self, nums: list, k: int) -> None: Do not return anything, modif... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def rotate(self, nums: list, k: int) -> None: Do not return anything, modify nums in-place instead.
- def rotate2(self, nums: list, k: int) -> None: Do not return anything, modif... | e32439a76968d67f99881b6d07fb16e21c979c9e | <|skeleton|>
class Solution:
def rotate(self, nums: list, k: int) -> None:
"""Do not return anything, modify nums in-place instead."""
<|body_0|>
def rotate2(self, nums: list, k: int) -> None:
"""Do not return anything, modify nums in-place instead."""
<|body_1|>
def rotat... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def rotate(self, nums: list, k: int) -> None:
"""Do not return anything, modify nums in-place instead."""
k = k % len(nums)
for i in range(len(nums) - k):
nums.append(nums[0])
nums.pop(0)
return nums
def rotate2(self, nums: list, k: int) -... | the_stack_v2_python_sparse | python/189.py | HymEric/LeetCode | train | 2 | |
73e052d3dbc62d41812b3604abf98d9540c48977 | [
"Strategy.__init__(self)\nself._spread_size_indicator = SpreadSize(minimum_return, market_fee)\nself.default_position = default_position\nself.current_position = default_position\nself._first_time_unprofitable = True\nwith localcontext() as context:\n context.prec = 8\n self.undercut_market_by = Decimal(under... | <|body_start_0|>
Strategy.__init__(self)
self._spread_size_indicator = SpreadSize(minimum_return, market_fee)
self.default_position = default_position
self.current_position = default_position
self._first_time_unprofitable = True
with localcontext() as context:
... | SpreadSizeStrategy | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SpreadSizeStrategy:
def __init__(self, default_position, undercut_market_by=0.01, minimum_return=1.005, market_fee=0.005):
"""default_position is whether the Strategy should hold the minor currency (sell, False) or the major currency (buy / True) after scalping the market. For example, i... | stack_v2_sparse_classes_36k_train_006061 | 4,149 | no_license | [
{
"docstring": "default_position is whether the Strategy should hold the minor currency (sell, False) or the major currency (buy / True) after scalping the market. For example, in a USD-CAD market True would mean CAD is held after scalping and False would mean USD is held after scalping. It is assumed that the ... | 2 | stack_v2_sparse_classes_30k_train_016997 | Implement the Python class `SpreadSizeStrategy` described below.
Class description:
Implement the SpreadSizeStrategy class.
Method signatures and docstrings:
- def __init__(self, default_position, undercut_market_by=0.01, minimum_return=1.005, market_fee=0.005): default_position is whether the Strategy should hold th... | Implement the Python class `SpreadSizeStrategy` described below.
Class description:
Implement the SpreadSizeStrategy class.
Method signatures and docstrings:
- def __init__(self, default_position, undercut_market_by=0.01, minimum_return=1.005, market_fee=0.005): default_position is whether the Strategy should hold th... | e0e08d1811d84a90cd62d762c6444e54de0c3da4 | <|skeleton|>
class SpreadSizeStrategy:
def __init__(self, default_position, undercut_market_by=0.01, minimum_return=1.005, market_fee=0.005):
"""default_position is whether the Strategy should hold the minor currency (sell, False) or the major currency (buy / True) after scalping the market. For example, i... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SpreadSizeStrategy:
def __init__(self, default_position, undercut_market_by=0.01, minimum_return=1.005, market_fee=0.005):
"""default_position is whether the Strategy should hold the minor currency (sell, False) or the major currency (buy / True) after scalping the market. For example, in a USD-CAD ma... | the_stack_v2_python_sparse | cryptotrader/tradesignals/strategies/spread_size_strategy.py | SPLT12/cryptocurrency-trader | train | 0 | |
73e2e2d32a970b297706cefd49903747f9c9867d | [
"super().__init__(filterFineData, universeSettings)\nself.NumberOfSymbolsCoarse = 500\nself.NumberOfSymbolsFine = 20\nself.NumberOfSymbolsInPortfolio = 10\nself.lastMonth = -1\nself.dollarVolumeBySymbol = {}",
"month = algorithm.Time.month\nif month == self.lastMonth:\n return Universe.Unchanged\nself.lastMont... | <|body_start_0|>
super().__init__(filterFineData, universeSettings)
self.NumberOfSymbolsCoarse = 500
self.NumberOfSymbolsFine = 20
self.NumberOfSymbolsInPortfolio = 10
self.lastMonth = -1
self.dollarVolumeBySymbol = {}
<|end_body_0|>
<|body_start_1|>
month = algo... | Defines a universe according to Joel Greenblatt's Magic Formula, as a universe selection model for the framework algorithm. From the universe QC500, stocks are ranked using the valuation ratios, Enterprise Value to EBITDA (EV/EBITDA) and Return on Assets (ROA). | GreenBlattMagicFormulaUniverseSelectionModel | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GreenBlattMagicFormulaUniverseSelectionModel:
"""Defines a universe according to Joel Greenblatt's Magic Formula, as a universe selection model for the framework algorithm. From the universe QC500, stocks are ranked using the valuation ratios, Enterprise Value to EBITDA (EV/EBITDA) and Return on ... | stack_v2_sparse_classes_36k_train_006062 | 9,868 | permissive | [
{
"docstring": "Initializes a new default instance of the MagicFormulaUniverseSelectionModel",
"name": "__init__",
"signature": "def __init__(self, filterFineData=True, universeSettings=None)"
},
{
"docstring": "Performs coarse selection for constituents. The stocks must have fundamental data",
... | 3 | stack_v2_sparse_classes_30k_train_017342 | Implement the Python class `GreenBlattMagicFormulaUniverseSelectionModel` described below.
Class description:
Defines a universe according to Joel Greenblatt's Magic Formula, as a universe selection model for the framework algorithm. From the universe QC500, stocks are ranked using the valuation ratios, Enterprise Val... | Implement the Python class `GreenBlattMagicFormulaUniverseSelectionModel` described below.
Class description:
Defines a universe according to Joel Greenblatt's Magic Formula, as a universe selection model for the framework algorithm. From the universe QC500, stocks are ranked using the valuation ratios, Enterprise Val... | b33dd3bc140e14b883f39ecf848a793cf7292277 | <|skeleton|>
class GreenBlattMagicFormulaUniverseSelectionModel:
"""Defines a universe according to Joel Greenblatt's Magic Formula, as a universe selection model for the framework algorithm. From the universe QC500, stocks are ranked using the valuation ratios, Enterprise Value to EBITDA (EV/EBITDA) and Return on ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GreenBlattMagicFormulaUniverseSelectionModel:
"""Defines a universe according to Joel Greenblatt's Magic Formula, as a universe selection model for the framework algorithm. From the universe QC500, stocks are ranked using the valuation ratios, Enterprise Value to EBITDA (EV/EBITDA) and Return on Assets (ROA).... | the_stack_v2_python_sparse | Algorithm.Python/Alphas/GreenblattMagicFormulaAlpha.py | Capnode/Algoloop | train | 87 |
82d177ae8f7f7354f839b0adefe649a66694de7f | [
"import numpy as np\nif sina is not None:\n cosa = cosa + 1j * sina\nreturn np.angle(cosa) % (2 * np.pi)",
"import numpy as np\nfrom jizhipy.Array import Asarray\nfrom jizhipy.Basic import Raise\nangle, axis = (npfmt(angle1), int(axis))\nif axis < 0:\n axis += len(angle.shape)\nif axis > len(angle.shape):\n... | <|body_start_0|>
import numpy as np
if sina is not None:
cosa = cosa + 1j * sina
return np.angle(cosa) % (2 * np.pi)
<|end_body_0|>
<|body_start_1|>
import numpy as np
from jizhipy.Array import Asarray
from jizhipy.Basic import Raise
angle, axis = (np... | Angle | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Angle:
def Angle(self, cosa, sina=None):
"""return the phase (case 1) cosa = A*np.cos(a) sina = A*np.sin(a) return a (case 2) cosa = np.complex (real + 1j*imag) sina = None"""
<|body_0|>
def AngleMean(self, angle1, angle2=None, axis=0):
"""return: angle.mean(axis) an... | stack_v2_sparse_classes_36k_train_006063 | 1,967 | no_license | [
{
"docstring": "return the phase (case 1) cosa = A*np.cos(a) sina = A*np.sin(a) return a (case 2) cosa = np.complex (real + 1j*imag) sina = None",
"name": "Angle",
"signature": "def Angle(self, cosa, sina=None)"
},
{
"docstring": "return: angle.mean(axis) angle1: [rad] Any shape array angle2: (1... | 3 | stack_v2_sparse_classes_30k_train_017177 | Implement the Python class `Angle` described below.
Class description:
Implement the Angle class.
Method signatures and docstrings:
- def Angle(self, cosa, sina=None): return the phase (case 1) cosa = A*np.cos(a) sina = A*np.sin(a) return a (case 2) cosa = np.complex (real + 1j*imag) sina = None
- def AngleMean(self,... | Implement the Python class `Angle` described below.
Class description:
Implement the Angle class.
Method signatures and docstrings:
- def Angle(self, cosa, sina=None): return the phase (case 1) cosa = A*np.cos(a) sina = A*np.sin(a) return a (case 2) cosa = np.complex (real + 1j*imag) sina = None
- def AngleMean(self,... | b49777105a76b5ae03555a9f93f116454c8245a9 | <|skeleton|>
class Angle:
def Angle(self, cosa, sina=None):
"""return the phase (case 1) cosa = A*np.cos(a) sina = A*np.sin(a) return a (case 2) cosa = np.complex (real + 1j*imag) sina = None"""
<|body_0|>
def AngleMean(self, angle1, angle2=None, axis=0):
"""return: angle.mean(axis) an... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Angle:
def Angle(self, cosa, sina=None):
"""return the phase (case 1) cosa = A*np.cos(a) sina = A*np.sin(a) return a (case 2) cosa = np.complex (real + 1j*imag) sina = None"""
import numpy as np
if sina is not None:
cosa = cosa + 1j * sina
return np.angle(cosa) % (2... | the_stack_v2_python_sparse | Basic/Angle.py | jizhi/jizhipy | train | 1 | |
ada8ccf58df8e113b632e5dda96b142d18234d1e | [
"self.k = k\nself.nums = nums\nheapq.heapify(self.nums)\nwhile len(self.nums) > k:\n heapq.heappop(self.nums)",
"if len(self.nums) < self.k:\n heapq.heappush(self.nums, val)\nelif val > self.nums[0]:\n heapq.heapreplace(self.nums, val)\nreturn self.nums[0]"
] | <|body_start_0|>
self.k = k
self.nums = nums
heapq.heapify(self.nums)
while len(self.nums) > k:
heapq.heappop(self.nums)
<|end_body_0|>
<|body_start_1|>
if len(self.nums) < self.k:
heapq.heappush(self.nums, val)
elif val > self.nums[0]:
... | KthLargest1 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class KthLargest1:
def __init__(self, k, nums):
""":type k: int :type nums: List[int]"""
<|body_0|>
def add(self, val):
""":type val: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.k = k
self.nums = nums
heapq.heapify... | stack_v2_sparse_classes_36k_train_006064 | 1,362 | no_license | [
{
"docstring": ":type k: int :type nums: List[int]",
"name": "__init__",
"signature": "def __init__(self, k, nums)"
},
{
"docstring": ":type val: int :rtype: int",
"name": "add",
"signature": "def add(self, val)"
}
] | 2 | stack_v2_sparse_classes_30k_train_011197 | Implement the Python class `KthLargest1` described below.
Class description:
Implement the KthLargest1 class.
Method signatures and docstrings:
- def __init__(self, k, nums): :type k: int :type nums: List[int]
- def add(self, val): :type val: int :rtype: int | Implement the Python class `KthLargest1` described below.
Class description:
Implement the KthLargest1 class.
Method signatures and docstrings:
- def __init__(self, k, nums): :type k: int :type nums: List[int]
- def add(self, val): :type val: int :rtype: int
<|skeleton|>
class KthLargest1:
def __init__(self, k,... | d4a33dc28a6d3f99d5179fdb6a83b2ab8c5a0beb | <|skeleton|>
class KthLargest1:
def __init__(self, k, nums):
""":type k: int :type nums: List[int]"""
<|body_0|>
def add(self, val):
""":type val: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class KthLargest1:
def __init__(self, k, nums):
""":type k: int :type nums: List[int]"""
self.k = k
self.nums = nums
heapq.heapify(self.nums)
while len(self.nums) > k:
heapq.heappop(self.nums)
def add(self, val):
""":type val: int :rtype: int"""
... | the_stack_v2_python_sparse | leetcode/703_kth_largest_num.py | 294150302hxq/python_learn | train | 0 | |
9fde606ade16252bad5d05584853b2c887c4def4 | [
"endpoint = '/models/{}/features-importances/download'.format(self._id)\nresponse = client.request(endpoint=endpoint, method=requests.get, message_prefix='Fetch feature importance')\ndf_feat_importance = zip_to_pandas(response)\nreturn df_feat_importance.sort_values(by='importance', ascending=False)",
"logger.deb... | <|body_start_0|>
endpoint = '/models/{}/features-importances/download'.format(self._id)
response = client.request(endpoint=endpoint, method=requests.get, message_prefix='Fetch feature importance')
df_feat_importance = zip_to_pandas(response)
return df_feat_importance.sort_values(by='impo... | ClassicModel | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ClassicModel:
def feature_importance(self) -> pd.DataFrame:
"""Return a dataframe of feature importances for the given model features, with their corresponding scores (sorted by descending feature importance scores). Returns: ``pd.DataFrame``: Dataframe of feature importances Raises: Pre... | stack_v2_sparse_classes_36k_train_006065 | 22,476 | permissive | [
{
"docstring": "Return a dataframe of feature importances for the given model features, with their corresponding scores (sorted by descending feature importance scores). Returns: ``pd.DataFrame``: Dataframe of feature importances Raises: PrevisionException: Any error while fetching data from the platform or par... | 4 | stack_v2_sparse_classes_30k_train_019300 | Implement the Python class `ClassicModel` described below.
Class description:
Implement the ClassicModel class.
Method signatures and docstrings:
- def feature_importance(self) -> pd.DataFrame: Return a dataframe of feature importances for the given model features, with their corresponding scores (sorted by descendin... | Implement the Python class `ClassicModel` described below.
Class description:
Implement the ClassicModel class.
Method signatures and docstrings:
- def feature_importance(self) -> pd.DataFrame: Return a dataframe of feature importances for the given model features, with their corresponding scores (sorted by descendin... | 0860c931e2b466ac4be910350890085111ae32ce | <|skeleton|>
class ClassicModel:
def feature_importance(self) -> pd.DataFrame:
"""Return a dataframe of feature importances for the given model features, with their corresponding scores (sorted by descending feature importance scores). Returns: ``pd.DataFrame``: Dataframe of feature importances Raises: Pre... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ClassicModel:
def feature_importance(self) -> pd.DataFrame:
"""Return a dataframe of feature importances for the given model features, with their corresponding scores (sorted by descending feature importance scores). Returns: ``pd.DataFrame``: Dataframe of feature importances Raises: PrevisionExceptio... | the_stack_v2_python_sparse | previsionio/model.py | FrancoisA-prevision/prevision-python | train | 0 | |
14f229d21cf6ef1b3df5017db0273fd6874a0179 | [
"result = []\nif not root:\n return result\nqueue = collections.deque([root])\nwhile queue:\n root = queue.pop()\n result.append('#')\n if root:\n result.append(str(root.val))\n queue.appendleft(root.left)\n queue.appendleft(root.right)\nreturn ''.join(result[1:])",
"index = 0\nif... | <|body_start_0|>
result = []
if not root:
return result
queue = collections.deque([root])
while queue:
root = queue.pop()
result.append('#')
if root:
result.append(str(root.val))
queue.appendleft(root.left)
... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|>
<|body_... | stack_v2_sparse_classes_36k_train_006066 | 3,899 | no_license | [
{
"docstring": "Encodes a tree to a single string. :type root: TreeNode :rtype: str",
"name": "serialize",
"signature": "def serialize(self, root)"
},
{
"docstring": "Decodes your encoded data to tree. :type data: str :rtype: TreeNode",
"name": "deserialize",
"signature": "def deserializ... | 2 | stack_v2_sparse_classes_30k_val_000238 | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | d953abe2c9680f636563e76287d2f907e90ced63 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
result = []
if not root:
return result
queue = collections.deque([root])
while queue:
root = queue.pop()
result.append('#')
... | the_stack_v2_python_sparse | Python_leetcode/297_serialize_and_deserialize.py | xiangcao/Leetcode | train | 0 | |
d8bbe49eaa15dda5785235839a66a1ab96be2b34 | [
"def search(left, right):\n while left >= 0 and right < len(s) and (s[left] == s[right]):\n if left == 0:\n cuts[right] = 0\n else:\n cuts[right] = min(cuts[right], cuts[left - 1] + 1)\n left -= 1\n right += 1\ncuts = [x for x in range(len(s))]\nfor i in range(le... | <|body_start_0|>
def search(left, right):
while left >= 0 and right < len(s) and (s[left] == s[right]):
if left == 0:
cuts[right] = 0
else:
cuts[right] = min(cuts[right], cuts[left - 1] + 1)
left -= 1
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def minCut(self, s):
""":type s: str :rtype: int"""
<|body_0|>
def minCut_v2(self, s):
""":type s: str :rtype: int"""
<|body_1|>
def minCut_TLE(self, s):
""":type s: str :rtype: int"""
<|body_2|>
<|end_skeleton|>
<|body_start_... | stack_v2_sparse_classes_36k_train_006067 | 3,592 | no_license | [
{
"docstring": ":type s: str :rtype: int",
"name": "minCut",
"signature": "def minCut(self, s)"
},
{
"docstring": ":type s: str :rtype: int",
"name": "minCut_v2",
"signature": "def minCut_v2(self, s)"
},
{
"docstring": ":type s: str :rtype: int",
"name": "minCut_TLE",
"si... | 3 | stack_v2_sparse_classes_30k_test_001164 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def minCut(self, s): :type s: str :rtype: int
- def minCut_v2(self, s): :type s: str :rtype: int
- def minCut_TLE(self, s): :type s: str :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def minCut(self, s): :type s: str :rtype: int
- def minCut_v2(self, s): :type s: str :rtype: int
- def minCut_TLE(self, s): :type s: str :rtype: int
<|skeleton|>
class Solution:... | e60ba45fe2f2e5e3b3abfecec3db76f5ce1fde59 | <|skeleton|>
class Solution:
def minCut(self, s):
""":type s: str :rtype: int"""
<|body_0|>
def minCut_v2(self, s):
""":type s: str :rtype: int"""
<|body_1|>
def minCut_TLE(self, s):
""":type s: str :rtype: int"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def minCut(self, s):
""":type s: str :rtype: int"""
def search(left, right):
while left >= 0 and right < len(s) and (s[left] == s[right]):
if left == 0:
cuts[right] = 0
else:
cuts[right] = min(cuts[ri... | the_stack_v2_python_sparse | src/lt_132.py | oxhead/CodingYourWay | train | 0 | |
ca939a619343cbcd5044ff5497207ae832849471 | [
"self.name = name\nself.sequence = sequence\nself.metadata = {} if metadata is None else metadata",
"ind = sequence.find(self.sequence)\nstrand = 1\nif ind == -1:\n ind = sequence.find(reverse_complement(self.sequence))\n if ind == -1:\n return None\n else:\n ind = len(sequence) - ind - len... | <|body_start_0|>
self.name = name
self.sequence = sequence
self.metadata = {} if metadata is None else metadata
<|end_body_0|>
<|body_start_1|>
ind = sequence.find(self.sequence)
strand = 1
if ind == -1:
ind = sequence.find(reverse_complement(self.sequence))
... | Class representing a sequencing primer Parameters ---------- name Name (label) of the primer sequence An ATGC string metadata A dictionnary {field, value} | Primer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Primer:
"""Class representing a sequencing primer Parameters ---------- name Name (label) of the primer sequence An ATGC string metadata A dictionnary {field, value}"""
def __init__(self, name=None, sequence=None, metadata=None):
"""Initialize"""
<|body_0|>
def find_loca... | stack_v2_sparse_classes_36k_train_006068 | 8,770 | no_license | [
{
"docstring": "Initialize",
"name": "__init__",
"signature": "def __init__(self, name=None, sequence=None, metadata=None)"
},
{
"docstring": "Return the (start, end, strand) of the primer in the sequence. The convention is that always (start < end), the strand indicates the direction of the hom... | 2 | stack_v2_sparse_classes_30k_train_008056 | Implement the Python class `Primer` described below.
Class description:
Class representing a sequencing primer Parameters ---------- name Name (label) of the primer sequence An ATGC string metadata A dictionnary {field, value}
Method signatures and docstrings:
- def __init__(self, name=None, sequence=None, metadata=N... | Implement the Python class `Primer` described below.
Class description:
Class representing a sequencing primer Parameters ---------- name Name (label) of the primer sequence An ATGC string metadata A dictionnary {field, value}
Method signatures and docstrings:
- def __init__(self, name=None, sequence=None, metadata=N... | cf957678ae4be24d6eddaae82754767ab06b905e | <|skeleton|>
class Primer:
"""Class representing a sequencing primer Parameters ---------- name Name (label) of the primer sequence An ATGC string metadata A dictionnary {field, value}"""
def __init__(self, name=None, sequence=None, metadata=None):
"""Initialize"""
<|body_0|>
def find_loca... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Primer:
"""Class representing a sequencing primer Parameters ---------- name Name (label) of the primer sequence An ATGC string metadata A dictionnary {field, value}"""
def __init__(self, name=None, sequence=None, metadata=None):
"""Initialize"""
self.name = name
self.sequence = s... | the_stack_v2_python_sparse | biomek/function/annealing.py | frba/biomek | train | 1 |
9b9f18f543b5a9b3dc35b7683c7ff351bbc727f5 | [
"super(GripperPositionDetector, self).__init__(robot_name=robot_name, tf_buffer=tf_buffer)\nself._topic = joint_topic\nself.timeout = rospy.Duration(2)\nself.wrench_sub = self.create_subscriber(self._topic, JointState, self._joint_callback, queue_size=1)\nself.current_position = None\nself.store_position = False\ns... | <|body_start_0|>
super(GripperPositionDetector, self).__init__(robot_name=robot_name, tf_buffer=tf_buffer)
self._topic = joint_topic
self.timeout = rospy.Duration(2)
self.wrench_sub = self.create_subscriber(self._topic, JointState, self._joint_callback, queue_size=1)
self.current... | GripperPositionDetector | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GripperPositionDetector:
def __init__(self, robot_name: str, tf_buffer: str, joint_topic: str) -> None:
"""Class for getting the position of the hand motor joint (how much the gripper is open or closed) Values go from 1 (open) to -1 (closed) :param robot_name: Name of the robot :param tf... | stack_v2_sparse_classes_36k_train_006069 | 2,238 | no_license | [
{
"docstring": "Class for getting the position of the hand motor joint (how much the gripper is open or closed) Values go from 1 (open) to -1 (closed) :param robot_name: Name of the robot :param tf_buffer: tf2_ros.Buffer for use in RobotPart :param joint_topic: Topic to use for measurement",
"name": "__init... | 3 | null | Implement the Python class `GripperPositionDetector` described below.
Class description:
Implement the GripperPositionDetector class.
Method signatures and docstrings:
- def __init__(self, robot_name: str, tf_buffer: str, joint_topic: str) -> None: Class for getting the position of the hand motor joint (how much the ... | Implement the Python class `GripperPositionDetector` described below.
Class description:
Implement the GripperPositionDetector class.
Method signatures and docstrings:
- def __init__(self, robot_name: str, tf_buffer: str, joint_topic: str) -> None: Class for getting the position of the hand motor joint (how much the ... | 092a354315b9b2c08e32cdc049791d82dfd47745 | <|skeleton|>
class GripperPositionDetector:
def __init__(self, robot_name: str, tf_buffer: str, joint_topic: str) -> None:
"""Class for getting the position of the hand motor joint (how much the gripper is open or closed) Values go from 1 (open) to -1 (closed) :param robot_name: Name of the robot :param tf... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GripperPositionDetector:
def __init__(self, robot_name: str, tf_buffer: str, joint_topic: str) -> None:
"""Class for getting the position of the hand motor joint (how much the gripper is open or closed) Values go from 1 (open) to -1 (closed) :param robot_name: Name of the robot :param tf_buffer: tf2_r... | the_stack_v2_python_sparse | robot_skills/src/robot_skills/arm/gripper_position_detector.py | tue-robotics/tue_robocup | train | 39 | |
bc04c695a5d736ea33cb4d4dd5ab497c4f46238f | [
"if [v for v in pattern if v > 10]:\n raise Exception('Maximum 10 views per ddoc allowed')\nif len(pattern) > 10:\n raise Exception('Maximum 10 design documents allowed')\nddocs = dict()\nfor number_of_views in pattern:\n ddoc_name = next(self.ddocs)\n ddocs[ddoc_name] = {'views': {}}\n for index_of_... | <|body_start_0|>
if [v for v in pattern if v > 10]:
raise Exception('Maximum 10 views per ddoc allowed')
if len(pattern) > 10:
raise Exception('Maximum 10 design documents allowed')
ddocs = dict()
for number_of_views in pattern:
ddoc_name = next(self.d... | ViewGen | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ViewGen:
def generate_ddocs(self, pattern=None, options=None):
"""Generate dictionary with design documents and views. Pattern looks like: [8, 8, 8] -- 8 ddocs (8 views, 8 views, 8 views) [2, 2, 4] -- 3 ddocs (2 views, 2 views, 4 views) [8] -- 1 ddoc (8 views) [1, 1, 1, 1] -- 4 ddocs (1 ... | stack_v2_sparse_classes_36k_train_006070 | 6,494 | permissive | [
{
"docstring": "Generate dictionary with design documents and views. Pattern looks like: [8, 8, 8] -- 8 ddocs (8 views, 8 views, 8 views) [2, 2, 4] -- 3 ddocs (2 views, 2 views, 4 views) [8] -- 1 ddoc (8 views) [1, 1, 1, 1] -- 4 ddocs (1 view per ddoc)",
"name": "generate_ddocs",
"signature": "def gener... | 3 | stack_v2_sparse_classes_30k_train_016589 | Implement the Python class `ViewGen` described below.
Class description:
Implement the ViewGen class.
Method signatures and docstrings:
- def generate_ddocs(self, pattern=None, options=None): Generate dictionary with design documents and views. Pattern looks like: [8, 8, 8] -- 8 ddocs (8 views, 8 views, 8 views) [2, ... | Implement the Python class `ViewGen` described below.
Class description:
Implement the ViewGen class.
Method signatures and docstrings:
- def generate_ddocs(self, pattern=None, options=None): Generate dictionary with design documents and views. Pattern looks like: [8, 8, 8] -- 8 ddocs (8 views, 8 views, 8 views) [2, ... | 9d8220a0925327bddf0e10887e22b57c5d6adb37 | <|skeleton|>
class ViewGen:
def generate_ddocs(self, pattern=None, options=None):
"""Generate dictionary with design documents and views. Pattern looks like: [8, 8, 8] -- 8 ddocs (8 views, 8 views, 8 views) [2, 2, 4] -- 3 ddocs (2 views, 2 views, 4 views) [8] -- 1 ddoc (8 views) [1, 1, 1, 1] -- 4 ddocs (1 ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ViewGen:
def generate_ddocs(self, pattern=None, options=None):
"""Generate dictionary with design documents and views. Pattern looks like: [8, 8, 8] -- 8 ddocs (8 views, 8 views, 8 views) [2, 2, 4] -- 3 ddocs (2 views, 2 views, 4 views) [8] -- 1 ddoc (8 views) [1, 1, 1, 1] -- 4 ddocs (1 view per ddoc)... | the_stack_v2_python_sparse | pytests/performance/viewgen.py | couchbase/testrunner | train | 18 | |
790d03b54f8aeffadcf587f0f79de7a2b2e9b81e | [
"parser.display_info.AddFormat(vmware_constants.VMWARE_CLUSTERS_FORMAT)\nflags.AddClusterResourceArg(parser, 'to update', True)\nbase.ASYNC_FLAG.AddToParser(parser)\nflags.AddValidationOnly(parser)\nflags.AddAllowMissingUpdateCluster(parser)\nflags.AddDescription(parser)\nflags.AddVersion(parser)\nflags.AddVmwareCo... | <|body_start_0|>
parser.display_info.AddFormat(vmware_constants.VMWARE_CLUSTERS_FORMAT)
flags.AddClusterResourceArg(parser, 'to update', True)
base.ASYNC_FLAG.AddToParser(parser)
flags.AddValidationOnly(parser)
flags.AddAllowMissingUpdateCluster(parser)
flags.AddDescripti... | Update an Anthos cluster on VMware. | UpdateBeta | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UpdateBeta:
"""Update an Anthos cluster on VMware."""
def Args(parser: parser_arguments.ArgumentInterceptor):
"""Gathers command line arguments for the update command. Args: parser: The argparse parser to add the flag to."""
<|body_0|>
def Run(self, args):
"""Run... | stack_v2_sparse_classes_36k_train_006071 | 6,033 | permissive | [
{
"docstring": "Gathers command line arguments for the update command. Args: parser: The argparse parser to add the flag to.",
"name": "Args",
"signature": "def Args(parser: parser_arguments.ArgumentInterceptor)"
},
{
"docstring": "Runs the update command. Args: args: The arguments received from... | 2 | null | Implement the Python class `UpdateBeta` described below.
Class description:
Update an Anthos cluster on VMware.
Method signatures and docstrings:
- def Args(parser: parser_arguments.ArgumentInterceptor): Gathers command line arguments for the update command. Args: parser: The argparse parser to add the flag to.
- def... | Implement the Python class `UpdateBeta` described below.
Class description:
Update an Anthos cluster on VMware.
Method signatures and docstrings:
- def Args(parser: parser_arguments.ArgumentInterceptor): Gathers command line arguments for the update command. Args: parser: The argparse parser to add the flag to.
- def... | 392abf004b16203030e6efd2f0af24db7c8d669e | <|skeleton|>
class UpdateBeta:
"""Update an Anthos cluster on VMware."""
def Args(parser: parser_arguments.ArgumentInterceptor):
"""Gathers command line arguments for the update command. Args: parser: The argparse parser to add the flag to."""
<|body_0|>
def Run(self, args):
"""Run... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UpdateBeta:
"""Update an Anthos cluster on VMware."""
def Args(parser: parser_arguments.ArgumentInterceptor):
"""Gathers command line arguments for the update command. Args: parser: The argparse parser to add the flag to."""
parser.display_info.AddFormat(vmware_constants.VMWARE_CLUSTERS_F... | the_stack_v2_python_sparse | lib/surface/container/vmware/clusters/update.py | google-cloud-sdk-unofficial/google-cloud-sdk | train | 9 |
453df5d56509724e346bede1f95801d911a90861 | [
"if not root:\n return\nl = self.invertTree(root.left)\nr = self.invertTree(root.right)\nroot.left = r\nroot.right = l\nreturn root",
"if root:\n self.invertTree(root.left)\n self.invertTree(root.right)\n root.left, root.right = (root.right, root.left)\nreturn root"
] | <|body_start_0|>
if not root:
return
l = self.invertTree(root.left)
r = self.invertTree(root.right)
root.left = r
root.right = l
return root
<|end_body_0|>
<|body_start_1|>
if root:
self.invertTree(root.left)
self.invertTree(ro... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def invertTree(self, root: Optional[TreeNode]) -> Optional[TreeNode]:
"""Nov 05, 2021 13:16"""
<|body_0|>
def invertTree(self, root: Optional[TreeNode]) -> Optional[TreeNode]:
"""Mar 20, 2023 23:41"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_006072 | 1,710 | no_license | [
{
"docstring": "Nov 05, 2021 13:16",
"name": "invertTree",
"signature": "def invertTree(self, root: Optional[TreeNode]) -> Optional[TreeNode]"
},
{
"docstring": "Mar 20, 2023 23:41",
"name": "invertTree",
"signature": "def invertTree(self, root: Optional[TreeNode]) -> Optional[TreeNode]"... | 2 | stack_v2_sparse_classes_30k_train_005082 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def invertTree(self, root: Optional[TreeNode]) -> Optional[TreeNode]: Nov 05, 2021 13:16
- def invertTree(self, root: Optional[TreeNode]) -> Optional[TreeNode]: Mar 20, 2023 23:4... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def invertTree(self, root: Optional[TreeNode]) -> Optional[TreeNode]: Nov 05, 2021 13:16
- def invertTree(self, root: Optional[TreeNode]) -> Optional[TreeNode]: Mar 20, 2023 23:4... | 1389a009a02e90e8700a7a00e0b7f797c129cdf4 | <|skeleton|>
class Solution:
def invertTree(self, root: Optional[TreeNode]) -> Optional[TreeNode]:
"""Nov 05, 2021 13:16"""
<|body_0|>
def invertTree(self, root: Optional[TreeNode]) -> Optional[TreeNode]:
"""Mar 20, 2023 23:41"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def invertTree(self, root: Optional[TreeNode]) -> Optional[TreeNode]:
"""Nov 05, 2021 13:16"""
if not root:
return
l = self.invertTree(root.left)
r = self.invertTree(root.right)
root.left = r
root.right = l
return root
def inve... | the_stack_v2_python_sparse | leetcode/solved/226_Invert_Binary_Tree/solution.py | sungminoh/algorithms | train | 0 | |
af654de217ccde843a7cbc4b733baef5a304df93 | [
"auth = tw.OAuthHandler(CONSUMER_KEY, CONSUMER_SECRET)\nauth.set_access_token(ACCESS_TOKEN, ACCESS_SECRET)\napi = tw.API(auth)\nself.extractor = api\nreturn",
"tweets = self.extractor.user_timeline(screen_name=user, count=200, tweet_mode='extended')\nprint('Number of tweets extracted: {}.\\n'.format(len(tweets)))... | <|body_start_0|>
auth = tw.OAuthHandler(CONSUMER_KEY, CONSUMER_SECRET)
auth.set_access_token(ACCESS_TOKEN, ACCESS_SECRET)
api = tw.API(auth)
self.extractor = api
return
<|end_body_0|>
<|body_start_1|>
tweets = self.extractor.user_timeline(screen_name=user, count=200, twe... | TweetsExtractor | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TweetsExtractor:
def __init__(self):
"""Constructor function to setup the Twitter's API with our access keys provided."""
<|body_0|>
def extract(self, user):
"""Function to extract latest 200 tweets from a user provided."""
<|body_1|>
<|end_skeleton|>
<|bod... | stack_v2_sparse_classes_36k_train_006073 | 2,119 | no_license | [
{
"docstring": "Constructor function to setup the Twitter's API with our access keys provided.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Function to extract latest 200 tweets from a user provided.",
"name": "extract",
"signature": "def extract(self, user)... | 2 | null | Implement the Python class `TweetsExtractor` described below.
Class description:
Implement the TweetsExtractor class.
Method signatures and docstrings:
- def __init__(self): Constructor function to setup the Twitter's API with our access keys provided.
- def extract(self, user): Function to extract latest 200 tweets ... | Implement the Python class `TweetsExtractor` described below.
Class description:
Implement the TweetsExtractor class.
Method signatures and docstrings:
- def __init__(self): Constructor function to setup the Twitter's API with our access keys provided.
- def extract(self, user): Function to extract latest 200 tweets ... | 02b77652d0901e6e06cb9b1e7cb3e59c675445c2 | <|skeleton|>
class TweetsExtractor:
def __init__(self):
"""Constructor function to setup the Twitter's API with our access keys provided."""
<|body_0|>
def extract(self, user):
"""Function to extract latest 200 tweets from a user provided."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TweetsExtractor:
def __init__(self):
"""Constructor function to setup the Twitter's API with our access keys provided."""
auth = tw.OAuthHandler(CONSUMER_KEY, CONSUMER_SECRET)
auth.set_access_token(ACCESS_TOKEN, ACCESS_SECRET)
api = tw.API(auth)
self.extractor = api
... | the_stack_v2_python_sparse | 47/RodolfoFerro/scripts/extractor.py | pybites/challenges | train | 764 | |
92ded508134e88b411bac6c1ce170937a24aa1ec | [
"self.kernel_type = kernel_type\nself.dim = dim\nself.lamb = lamb\nself.gamma = gamma\nif clf == 'knn':\n self.clf = KNeighborsClassifier(n_neighbors=1)\nelif clf == 'svm':\n self.clf = svm.SVC(C=1, gamma='auto', kernel='rbf', decision_function_shape='ovr')\nprint('kernel_type:[{}], dimension:[{}], classifier... | <|body_start_0|>
self.kernel_type = kernel_type
self.dim = dim
self.lamb = lamb
self.gamma = gamma
if clf == 'knn':
self.clf = KNeighborsClassifier(n_neighbors=1)
elif clf == 'svm':
self.clf = svm.SVC(C=1, gamma='auto', kernel='rbf', decision_funct... | TCA | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TCA:
def __init__(self, kernel_type='primal', dim=30, lamb=1, gamma=1, clf='knn'):
"""Init func :param kernel_type: kernel, values: 'primal' | 'linear' | 'rbf' :param dim: dimension after transfer :param lamb: lambda value in equation :param gamma: kernel bandwidth for rbf kernel"""
... | stack_v2_sparse_classes_36k_train_006074 | 10,474 | no_license | [
{
"docstring": "Init func :param kernel_type: kernel, values: 'primal' | 'linear' | 'rbf' :param dim: dimension after transfer :param lamb: lambda value in equation :param gamma: kernel bandwidth for rbf kernel",
"name": "__init__",
"signature": "def __init__(self, kernel_type='primal', dim=30, lamb=1, ... | 3 | stack_v2_sparse_classes_30k_train_013992 | Implement the Python class `TCA` described below.
Class description:
Implement the TCA class.
Method signatures and docstrings:
- def __init__(self, kernel_type='primal', dim=30, lamb=1, gamma=1, clf='knn'): Init func :param kernel_type: kernel, values: 'primal' | 'linear' | 'rbf' :param dim: dimension after transfer... | Implement the Python class `TCA` described below.
Class description:
Implement the TCA class.
Method signatures and docstrings:
- def __init__(self, kernel_type='primal', dim=30, lamb=1, gamma=1, clf='knn'): Init func :param kernel_type: kernel, values: 'primal' | 'linear' | 'rbf' :param dim: dimension after transfer... | ea0ff8204cd6649892704c90909eb08e8102fc11 | <|skeleton|>
class TCA:
def __init__(self, kernel_type='primal', dim=30, lamb=1, gamma=1, clf='knn'):
"""Init func :param kernel_type: kernel, values: 'primal' | 'linear' | 'rbf' :param dim: dimension after transfer :param lamb: lambda value in equation :param gamma: kernel bandwidth for rbf kernel"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TCA:
def __init__(self, kernel_type='primal', dim=30, lamb=1, gamma=1, clf='knn'):
"""Init func :param kernel_type: kernel, values: 'primal' | 'linear' | 'rbf' :param dim: dimension after transfer :param lamb: lambda value in equation :param gamma: kernel bandwidth for rbf kernel"""
self.kerne... | the_stack_v2_python_sparse | Comparison_model/venv/Include/TCA.py | yephm/DASMN | train | 0 | |
d1f6321444eebb293c4c5b7e242eeb6170c23217 | [
"time = timezone.now() + datetime.timedelta(days=30)\nfuture_question = Question(pub_date=time)\nself.assertIs(future_question.was_published_recently(), False)",
"time = timezone.now() - datetime.timedelta(days=2)\npast_question = Question(pub_date=time)\nself.assertIs(past_question.was_published_recently(), Fals... | <|body_start_0|>
time = timezone.now() + datetime.timedelta(days=30)
future_question = Question(pub_date=time)
self.assertIs(future_question.was_published_recently(), False)
<|end_body_0|>
<|body_start_1|>
time = timezone.now() - datetime.timedelta(days=2)
past_question = Questi... | QuestionMethodTests | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class QuestionMethodTests:
def test_was_published_recently_with_future_question(self):
"""was_published_recently() should return False for questions whose pub_date is in the future."""
<|body_0|>
def test_was_published_recently_with_old_question(self):
"""was_published_rec... | stack_v2_sparse_classes_36k_train_006075 | 7,438 | no_license | [
{
"docstring": "was_published_recently() should return False for questions whose pub_date is in the future.",
"name": "test_was_published_recently_with_future_question",
"signature": "def test_was_published_recently_with_future_question(self)"
},
{
"docstring": "was_published_recently() should r... | 3 | stack_v2_sparse_classes_30k_train_008153 | Implement the Python class `QuestionMethodTests` described below.
Class description:
Implement the QuestionMethodTests class.
Method signatures and docstrings:
- def test_was_published_recently_with_future_question(self): was_published_recently() should return False for questions whose pub_date is in the future.
- de... | Implement the Python class `QuestionMethodTests` described below.
Class description:
Implement the QuestionMethodTests class.
Method signatures and docstrings:
- def test_was_published_recently_with_future_question(self): was_published_recently() should return False for questions whose pub_date is in the future.
- de... | a7e7fc72abe357172f5aa49b03c5b9298d92d6e8 | <|skeleton|>
class QuestionMethodTests:
def test_was_published_recently_with_future_question(self):
"""was_published_recently() should return False for questions whose pub_date is in the future."""
<|body_0|>
def test_was_published_recently_with_old_question(self):
"""was_published_rec... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class QuestionMethodTests:
def test_was_published_recently_with_future_question(self):
"""was_published_recently() should return False for questions whose pub_date is in the future."""
time = timezone.now() + datetime.timedelta(days=30)
future_question = Question(pub_date=time)
self.... | the_stack_v2_python_sparse | firstdjango/polls/tests.py | thewritingstew/lpthw | train | 0 | |
b6778c6aa65d4e23a684bd278a51c00b4fe8e3c4 | [
"post_body = json.dumps({'OS-KSADM:service': kwargs})\nresp, body = self.post('/OS-KSADM/services', post_body)\nself.expected_success(200, resp.status)\nbody = json.loads(body)\nreturn rest_client.ResponseBody(resp, body)",
"url = '/OS-KSADM/services/%s' % service_id\nresp, body = self.get(url)\nself.expected_suc... | <|body_start_0|>
post_body = json.dumps({'OS-KSADM:service': kwargs})
resp, body = self.post('/OS-KSADM/services', post_body)
self.expected_success(200, resp.status)
body = json.loads(body)
return rest_client.ResponseBody(resp, body)
<|end_body_0|>
<|body_start_1|>
url =... | ServicesClient | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ServicesClient:
def create_service(self, **kwargs):
"""Create a service. For a full list of available parameters, please refer to the official API reference: https://docs.openstack.org/api-ref/identity/v2-ext/#create-service-admin-extension"""
<|body_0|>
def show_service(sel... | stack_v2_sparse_classes_36k_train_006076 | 2,419 | permissive | [
{
"docstring": "Create a service. For a full list of available parameters, please refer to the official API reference: https://docs.openstack.org/api-ref/identity/v2-ext/#create-service-admin-extension",
"name": "create_service",
"signature": "def create_service(self, **kwargs)"
},
{
"docstring"... | 4 | null | Implement the Python class `ServicesClient` described below.
Class description:
Implement the ServicesClient class.
Method signatures and docstrings:
- def create_service(self, **kwargs): Create a service. For a full list of available parameters, please refer to the official API reference: https://docs.openstack.org/... | Implement the Python class `ServicesClient` described below.
Class description:
Implement the ServicesClient class.
Method signatures and docstrings:
- def create_service(self, **kwargs): Create a service. For a full list of available parameters, please refer to the official API reference: https://docs.openstack.org/... | 3932a799e620a20d7abf7b89e21b520683a1809b | <|skeleton|>
class ServicesClient:
def create_service(self, **kwargs):
"""Create a service. For a full list of available parameters, please refer to the official API reference: https://docs.openstack.org/api-ref/identity/v2-ext/#create-service-admin-extension"""
<|body_0|>
def show_service(sel... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ServicesClient:
def create_service(self, **kwargs):
"""Create a service. For a full list of available parameters, please refer to the official API reference: https://docs.openstack.org/api-ref/identity/v2-ext/#create-service-admin-extension"""
post_body = json.dumps({'OS-KSADM:service': kwargs... | the_stack_v2_python_sparse | tempest/lib/services/identity/v2/services_client.py | openstack/tempest | train | 270 | |
a653bb09a47780f0cb6911ed039f330ccc90b336 | [
"self.link = L\nif L is None:\n self.head = None\n self.tail = None\n return\nif not len(L[:1]):\n self.head = None\n self.tail = None\n return\nnode = Node(L[0])\nself.head = node\nfor e in L[1:]:\n node.next_node = Node(e)\n node.next_node.previous_node = node\n node = node.next_node\ns... | <|body_start_0|>
self.link = L
if L is None:
self.head = None
self.tail = None
return
if not len(L[:1]):
self.head = None
self.tail = None
return
node = Node(L[0])
self.head = node
for e in L[1:]:
... | DoublyLinkedList | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DoublyLinkedList:
def __init__(self, L=None):
"""Creates an empty list or a list built from a subscriptable object. >>> DoublyLinkedList().print_from_head_to_tail() >>> DoublyLinkedList().print_from_tail_to_head() >>> DoublyLinkedList([]).print_from_head_to_tail() >>> DoublyLinkedList([]... | stack_v2_sparse_classes_36k_train_006077 | 4,348 | no_license | [
{
"docstring": "Creates an empty list or a list built from a subscriptable object. >>> DoublyLinkedList().print_from_head_to_tail() >>> DoublyLinkedList().print_from_tail_to_head() >>> DoublyLinkedList([]).print_from_head_to_tail() >>> DoublyLinkedList([]).print_from_tail_to_head() >>> DoublyLinkedList((0,)).pr... | 4 | stack_v2_sparse_classes_30k_train_015199 | Implement the Python class `DoublyLinkedList` described below.
Class description:
Implement the DoublyLinkedList class.
Method signatures and docstrings:
- def __init__(self, L=None): Creates an empty list or a list built from a subscriptable object. >>> DoublyLinkedList().print_from_head_to_tail() >>> DoublyLinkedLi... | Implement the Python class `DoublyLinkedList` described below.
Class description:
Implement the DoublyLinkedList class.
Method signatures and docstrings:
- def __init__(self, L=None): Creates an empty list or a list built from a subscriptable object. >>> DoublyLinkedList().print_from_head_to_tail() >>> DoublyLinkedLi... | 4d0d4a2d719745528bf84ed0dfb88a43f858be7e | <|skeleton|>
class DoublyLinkedList:
def __init__(self, L=None):
"""Creates an empty list or a list built from a subscriptable object. >>> DoublyLinkedList().print_from_head_to_tail() >>> DoublyLinkedList().print_from_tail_to_head() >>> DoublyLinkedList([]).print_from_head_to_tail() >>> DoublyLinkedList([]... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DoublyLinkedList:
def __init__(self, L=None):
"""Creates an empty list or a list built from a subscriptable object. >>> DoublyLinkedList().print_from_head_to_tail() >>> DoublyLinkedList().print_from_tail_to_head() >>> DoublyLinkedList([]).print_from_head_to_tail() >>> DoublyLinkedList([]).print_from_t... | the_stack_v2_python_sparse | Sample_Exam_Questions_2/sample_5.py | gakkistyle/comp9021 | train | 14 | |
6d2de5513d705d907b408c7d549fff9ea2b0635a | [
"if not isinstance(actions, dict):\n raise ValueError('actions.yaml is not a valid actions configuration')\nfor action in actions:\n if keyword.iskeyword(action):\n raise ValueError(f\"'{action}' is a reserved keyword and cannot be used as an action name\")\n if cls._action_name_regex.match(action) ... | <|body_start_0|>
if not isinstance(actions, dict):
raise ValueError('actions.yaml is not a valid actions configuration')
for action in actions:
if keyword.iskeyword(action):
raise ValueError(f"'{action}' is a reserved keyword and cannot be used as an action name")... | Juju actions for charms. See also: https://juju.is/docs/sdk/actions | JujuActions | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class JujuActions:
"""Juju actions for charms. See also: https://juju.is/docs/sdk/actions"""
def validate_actions(cls, actions, values):
"""Verify actions names and descriptions."""
<|body_0|>
def validate_each_action(cls, action, values):
"""Verify actions names and d... | stack_v2_sparse_classes_36k_train_006078 | 2,092 | permissive | [
{
"docstring": "Verify actions names and descriptions.",
"name": "validate_actions",
"signature": "def validate_actions(cls, actions, values)"
},
{
"docstring": "Verify actions names and descriptions.",
"name": "validate_each_action",
"signature": "def validate_each_action(cls, action, v... | 2 | stack_v2_sparse_classes_30k_train_014880 | Implement the Python class `JujuActions` described below.
Class description:
Juju actions for charms. See also: https://juju.is/docs/sdk/actions
Method signatures and docstrings:
- def validate_actions(cls, actions, values): Verify actions names and descriptions.
- def validate_each_action(cls, action, values): Verif... | Implement the Python class `JujuActions` described below.
Class description:
Juju actions for charms. See also: https://juju.is/docs/sdk/actions
Method signatures and docstrings:
- def validate_actions(cls, actions, values): Verify actions names and descriptions.
- def validate_each_action(cls, action, values): Verif... | 6f49f8334888947955d133cde6dc0fea10edb74c | <|skeleton|>
class JujuActions:
"""Juju actions for charms. See also: https://juju.is/docs/sdk/actions"""
def validate_actions(cls, actions, values):
"""Verify actions names and descriptions."""
<|body_0|>
def validate_each_action(cls, action, values):
"""Verify actions names and d... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class JujuActions:
"""Juju actions for charms. See also: https://juju.is/docs/sdk/actions"""
def validate_actions(cls, actions, values):
"""Verify actions names and descriptions."""
if not isinstance(actions, dict):
raise ValueError('actions.yaml is not a valid actions configuration... | the_stack_v2_python_sparse | charmcraft/models/actions.py | canonical/charmcraft | train | 56 |
0126f64812040aae7c9392b31cee9eae8dc1bc8e | [
"self.azdeg = azdeg\nself.altdeg = altdeg\nself.hsv_min_val = hsv_min_val\nself.hsv_max_val = hsv_max_val\nself.hsv_min_sat = hsv_min_sat\nself.hsv_max_sat = hsv_max_sat",
"if minval == None:\n minval = data.min()\nnormdata = (data - minval) / (data.max() - minval)\nrgb0 = cmap(normdata)\nrgb1 = self.shade_rgb... | <|body_start_0|>
self.azdeg = azdeg
self.altdeg = altdeg
self.hsv_min_val = hsv_min_val
self.hsv_max_val = hsv_max_val
self.hsv_min_sat = hsv_min_sat
self.hsv_max_sat = hsv_max_sat
<|end_body_0|>
<|body_start_1|>
if minval == None:
minval = data.min()... | Create a light source coming from the specified azimuth and elevation. Angles are in degrees, with the azimuth measured clockwise from north and elevation up from the zero plane of the surface. The :meth:`shade` is used to produce rgb values for a shaded relief image given a data array. Original in matplotlib.colors, m... | LightSource | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LightSource:
"""Create a light source coming from the specified azimuth and elevation. Angles are in degrees, with the azimuth measured clockwise from north and elevation up from the zero plane of the surface. The :meth:`shade` is used to produce rgb values for a shaded relief image given a data ... | stack_v2_sparse_classes_36k_train_006079 | 5,066 | no_license | [
{
"docstring": "Specify the azimuth (measured clockwise from south) and altitude (measured up from the plane of the surface) of the light source in degrees. The color of the resulting image will be darkened by moving the (s,v) values (in hsv colorspace) toward (hsv_min_sat, hsv_min_val) in the shaded regions, o... | 3 | stack_v2_sparse_classes_30k_train_006728 | Implement the Python class `LightSource` described below.
Class description:
Create a light source coming from the specified azimuth and elevation. Angles are in degrees, with the azimuth measured clockwise from north and elevation up from the zero plane of the surface. The :meth:`shade` is used to produce rgb values ... | Implement the Python class `LightSource` described below.
Class description:
Create a light source coming from the specified azimuth and elevation. Angles are in degrees, with the azimuth measured clockwise from north and elevation up from the zero plane of the surface. The :meth:`shade` is used to produce rgb values ... | 6e39008842de8a0fb4a9879b53b8a67339b37aff | <|skeleton|>
class LightSource:
"""Create a light source coming from the specified azimuth and elevation. Angles are in degrees, with the azimuth measured clockwise from north and elevation up from the zero plane of the surface. The :meth:`shade` is used to produce rgb values for a shaded relief image given a data ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LightSource:
"""Create a light source coming from the specified azimuth and elevation. Angles are in degrees, with the azimuth measured clockwise from north and elevation up from the zero plane of the surface. The :meth:`shade` is used to produce rgb values for a shaded relief image given a data array. Origin... | the_stack_v2_python_sparse | python/lib/myLightSource.py | gutmann/scripted_sufferin_succotash | train | 2 |
306bb63a9a9736adeca689c32d7a154dbca7bea1 | [
"min_price = prices[0]\nmax_profit = 0\nprofits = []\nfor price in prices:\n min_price = min(price, min_price)\n max_profit = max(max_profit, price - min_price)\n profits.append(max_profit)\ncurr_max_price = 0\nmax_profit = 0\nfor i in range(len(prices) - 1, 0, -1):\n curr_max_price = max(curr_max_price... | <|body_start_0|>
min_price = prices[0]
max_profit = 0
profits = []
for price in prices:
min_price = min(price, min_price)
max_profit = max(max_profit, price - min_price)
profits.append(max_profit)
curr_max_price = 0
max_profit = 0
... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxProfit(self, prices: List[int]) -> int:
"""https://leetcode.com/problems/best-time-to-buy-and-sell-stock-iii/discuss/39743/Python-DP-solution-120ms Runtime: 1383 ms, faster than 44.21% Memory Usage: 27.8 MB, less than 87.46% 1 <= prices.length <= 10**5 0 <= prices[i] <= ... | stack_v2_sparse_classes_36k_train_006080 | 2,529 | permissive | [
{
"docstring": "https://leetcode.com/problems/best-time-to-buy-and-sell-stock-iii/discuss/39743/Python-DP-solution-120ms Runtime: 1383 ms, faster than 44.21% Memory Usage: 27.8 MB, less than 87.46% 1 <= prices.length <= 10**5 0 <= prices[i] <= 10**5 :param prices: :return:",
"name": "maxProfit",
"signat... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxProfit(self, prices: List[int]) -> int: https://leetcode.com/problems/best-time-to-buy-and-sell-stock-iii/discuss/39743/Python-DP-solution-120ms Runtime: 1383 ms, faster t... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxProfit(self, prices: List[int]) -> int: https://leetcode.com/problems/best-time-to-buy-and-sell-stock-iii/discuss/39743/Python-DP-solution-120ms Runtime: 1383 ms, faster t... | 4dd1e54d8d08f7e6590bc76abd08ecaacaf775e5 | <|skeleton|>
class Solution:
def maxProfit(self, prices: List[int]) -> int:
"""https://leetcode.com/problems/best-time-to-buy-and-sell-stock-iii/discuss/39743/Python-DP-solution-120ms Runtime: 1383 ms, faster than 44.21% Memory Usage: 27.8 MB, less than 87.46% 1 <= prices.length <= 10**5 0 <= prices[i] <= ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def maxProfit(self, prices: List[int]) -> int:
"""https://leetcode.com/problems/best-time-to-buy-and-sell-stock-iii/discuss/39743/Python-DP-solution-120ms Runtime: 1383 ms, faster than 44.21% Memory Usage: 27.8 MB, less than 87.46% 1 <= prices.length <= 10**5 0 <= prices[i] <= 10**5 :param p... | the_stack_v2_python_sparse | src/123-BestTimetoBuyandSellStockIII.py | Jiezhi/myleetcode | train | 1 | |
11a50ac987686c78d1b2bfb67de1ea896bb36e8a | [
"if not root:\n return None\nparent, left, right = (root, root.left, root.right)\nif left:\n ret = self.upsideDownBinaryTree(left)\n left.left = right\n left.right = parent\n return ret\nreturn root",
"if not root:\n return None\nstack = []\nnode, left, right = (root, None, None)\nwhile node.lef... | <|body_start_0|>
if not root:
return None
parent, left, right = (root, root.left, root.right)
if left:
ret = self.upsideDownBinaryTree(left)
left.left = right
left.right = parent
return ret
return root
<|end_body_0|>
<|body_sta... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def upsideDownBinaryTree(self, root):
"""解法一：将左子树递归颠倒，然后原来的左孩子的左右孩子指针分别指向原来的右兄弟和原来的根节点 这个题目可以这样做的关键是树的任何一个右孩子都没有枝节，基本就是一个梳子的形状，所以不用递归右子树"""
<|body_0|>
def upsideDownBinaryTree1(self, root):
"""解法二：迭代方法，借助stack做中序遍历"""
<|body_1|>
<|end_skeleton|>
<... | stack_v2_sparse_classes_36k_train_006081 | 1,660 | no_license | [
{
"docstring": "解法一：将左子树递归颠倒，然后原来的左孩子的左右孩子指针分别指向原来的右兄弟和原来的根节点 这个题目可以这样做的关键是树的任何一个右孩子都没有枝节，基本就是一个梳子的形状，所以不用递归右子树",
"name": "upsideDownBinaryTree",
"signature": "def upsideDownBinaryTree(self, root)"
},
{
"docstring": "解法二：迭代方法，借助stack做中序遍历",
"name": "upsideDownBinaryTree1",
"signature": "... | 2 | stack_v2_sparse_classes_30k_train_013091 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def upsideDownBinaryTree(self, root): 解法一：将左子树递归颠倒，然后原来的左孩子的左右孩子指针分别指向原来的右兄弟和原来的根节点 这个题目可以这样做的关键是树的任何一个右孩子都没有枝节，基本就是一个梳子的形状，所以不用递归右子树
- def upsideDownBinaryTree1(self, root): 解法二... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def upsideDownBinaryTree(self, root): 解法一：将左子树递归颠倒，然后原来的左孩子的左右孩子指针分别指向原来的右兄弟和原来的根节点 这个题目可以这样做的关键是树的任何一个右孩子都没有枝节，基本就是一个梳子的形状，所以不用递归右子树
- def upsideDownBinaryTree1(self, root): 解法二... | 54191d08bc42e5b1d403246a7486fca69d9ae30b | <|skeleton|>
class Solution:
def upsideDownBinaryTree(self, root):
"""解法一：将左子树递归颠倒，然后原来的左孩子的左右孩子指针分别指向原来的右兄弟和原来的根节点 这个题目可以这样做的关键是树的任何一个右孩子都没有枝节，基本就是一个梳子的形状，所以不用递归右子树"""
<|body_0|>
def upsideDownBinaryTree1(self, root):
"""解法二：迭代方法，借助stack做中序遍历"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def upsideDownBinaryTree(self, root):
"""解法一：将左子树递归颠倒，然后原来的左孩子的左右孩子指针分别指向原来的右兄弟和原来的根节点 这个题目可以这样做的关键是树的任何一个右孩子都没有枝节，基本就是一个梳子的形状，所以不用递归右子树"""
if not root:
return None
parent, left, right = (root, root.left, root.right)
if left:
ret = self.upsideD... | the_stack_v2_python_sparse | algo/156_Binary_Tree_Upside_Down/Q156.py | dionwang88/lc1 | train | 0 | |
4b4e7277606bf97672736ffe0a2e2cdb68e1f5fc | [
"self.strike = kwargs['strike']\nself.rate = kwargs['rate']\nself.dividend = kwargs['dividend']\nself.maturity = kwargs['maturity']\nself.volatility = kwargs['volatility']\nself.cp = kwargs['cp']\nself.date_type = kwargs['date_type']\nself.nominal_num = kwargs['nominal_num']\nself.factor_name = '{}:strike_{}'.forma... | <|body_start_0|>
self.strike = kwargs['strike']
self.rate = kwargs['rate']
self.dividend = kwargs['dividend']
self.maturity = kwargs['maturity']
self.volatility = kwargs['volatility']
self.cp = kwargs['cp']
self.date_type = kwargs['date_type']
self.nominal... | 示例正向对冲买入择时类，混入BuyCallMixin，即向上突破触发买入event, 适用于看涨期权 | AbuFactorBuyEuroOptionHedge | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AbuFactorBuyEuroOptionHedge:
"""示例正向对冲买入择时类，混入BuyCallMixin，即向上突破触发买入event, 适用于看涨期权"""
def _init_self(self, **kwargs):
"""kwargs中必须包含: 期权各参数"""
<|body_0|>
def fit_day(self, today, holding_cnt):
"""针对每一个交易日拟合买入交易策略，寻找向上突破买入机会 :param today: 当前驱动的交易日金融时间序列数据 :param h... | stack_v2_sparse_classes_36k_train_006082 | 3,898 | no_license | [
{
"docstring": "kwargs中必须包含: 期权各参数",
"name": "_init_self",
"signature": "def _init_self(self, **kwargs)"
},
{
"docstring": "针对每一个交易日拟合买入交易策略，寻找向上突破买入机会 :param today: 当前驱动的交易日金融时间序列数据 :param holding_cnt: 交易发生之前的持仓量 :return:",
"name": "fit_day",
"signature": "def fit_day(self, today, holdi... | 2 | stack_v2_sparse_classes_30k_train_017830 | Implement the Python class `AbuFactorBuyEuroOptionHedge` described below.
Class description:
示例正向对冲买入择时类，混入BuyCallMixin，即向上突破触发买入event, 适用于看涨期权
Method signatures and docstrings:
- def _init_self(self, **kwargs): kwargs中必须包含: 期权各参数
- def fit_day(self, today, holding_cnt): 针对每一个交易日拟合买入交易策略，寻找向上突破买入机会 :param today: 当前驱动... | Implement the Python class `AbuFactorBuyEuroOptionHedge` described below.
Class description:
示例正向对冲买入择时类，混入BuyCallMixin，即向上突破触发买入event, 适用于看涨期权
Method signatures and docstrings:
- def _init_self(self, **kwargs): kwargs中必须包含: 期权各参数
- def fit_day(self, today, holding_cnt): 针对每一个交易日拟合买入交易策略，寻找向上突破买入机会 :param today: 当前驱动... | 6f9dabecb17b65a02a370134e178722c169b2cd2 | <|skeleton|>
class AbuFactorBuyEuroOptionHedge:
"""示例正向对冲买入择时类，混入BuyCallMixin，即向上突破触发买入event, 适用于看涨期权"""
def _init_self(self, **kwargs):
"""kwargs中必须包含: 期权各参数"""
<|body_0|>
def fit_day(self, today, holding_cnt):
"""针对每一个交易日拟合买入交易策略，寻找向上突破买入机会 :param today: 当前驱动的交易日金融时间序列数据 :param h... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AbuFactorBuyEuroOptionHedge:
"""示例正向对冲买入择时类，混入BuyCallMixin，即向上突破触发买入event, 适用于看涨期权"""
def _init_self(self, **kwargs):
"""kwargs中必须包含: 期权各参数"""
self.strike = kwargs['strike']
self.rate = kwargs['rate']
self.dividend = kwargs['dividend']
self.maturity = kwargs['matur... | the_stack_v2_python_sparse | abupy/FactorBuyBu/ABuFactorBuyEuroOptionHedge.py | Leo70kg/Backtesting | train | 1 |
d834640f05fce79682538d143639c783972b6f2b | [
"if set(s) & set(''.join(wordDict)) != set(s):\n return (False, {})\ndic_head, table, max_len = ({}, [0] * len(s) + [1], max(map(len, wordDict)))\nfor word in wordDict:\n if word[0] not in dic_head:\n dic_head[word[0]] = set([word])\n else:\n dic_head[word[0]].add(word)\nfor i in range(len(s)... | <|body_start_0|>
if set(s) & set(''.join(wordDict)) != set(s):
return (False, {})
dic_head, table, max_len = ({}, [0] * len(s) + [1], max(map(len, wordDict)))
for word in wordDict:
if word[0] not in dic_head:
dic_head[word[0]] = set([word])
els... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def wordBreak1(self, s, wordDict):
""":type s: str :type wordDict: List[str] :rtype: bool"""
<|body_0|>
def wordBreak(self, s, wordDict):
""":type s: str :type wordDict: List[str] :rtype: List[str]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_006083 | 1,679 | no_license | [
{
"docstring": ":type s: str :type wordDict: List[str] :rtype: bool",
"name": "wordBreak1",
"signature": "def wordBreak1(self, s, wordDict)"
},
{
"docstring": ":type s: str :type wordDict: List[str] :rtype: List[str]",
"name": "wordBreak",
"signature": "def wordBreak(self, s, wordDict)"
... | 2 | stack_v2_sparse_classes_30k_train_020519 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def wordBreak1(self, s, wordDict): :type s: str :type wordDict: List[str] :rtype: bool
- def wordBreak(self, s, wordDict): :type s: str :type wordDict: List[str] :rtype: List[str... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def wordBreak1(self, s, wordDict): :type s: str :type wordDict: List[str] :rtype: bool
- def wordBreak(self, s, wordDict): :type s: str :type wordDict: List[str] :rtype: List[str... | c767e3794455c5105ca34714a3e15101f4962f4d | <|skeleton|>
class Solution:
def wordBreak1(self, s, wordDict):
""":type s: str :type wordDict: List[str] :rtype: bool"""
<|body_0|>
def wordBreak(self, s, wordDict):
""":type s: str :type wordDict: List[str] :rtype: List[str]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def wordBreak1(self, s, wordDict):
""":type s: str :type wordDict: List[str] :rtype: bool"""
if set(s) & set(''.join(wordDict)) != set(s):
return (False, {})
dic_head, table, max_len = ({}, [0] * len(s) + [1], max(map(len, wordDict)))
for word in wordDict:... | the_stack_v2_python_sparse | 140/WordBreakII.py | basto11/leetcode | train | 0 | |
38375e40dce2429d177981b42b4f75f67b1ee96c | [
"Block.__init__(self, scenario, args)\nif self.language is None:\n raise LoadingException('Language must be defined!')",
"ttree = zone.ttree\natree = zone.create_atree()\nself.copy_subtree(ttree, atree)",
"for tnode in troot.get_children(ordered=1):\n lemma = tnode.t_lemma or ''\n lemma = re.sub('_s[ei... | <|body_start_0|>
Block.__init__(self, scenario, args)
if self.language is None:
raise LoadingException('Language must be defined!')
<|end_body_0|>
<|body_start_1|>
ttree = zone.ttree
atree = zone.create_atree()
self.copy_subtree(ttree, atree)
<|end_body_1|>
<|body_s... | This block creates an a-tree based on a t-tree in the same zone. Arguments: language: the language of the target zone selector: the selector of the target zone | CopyTTree | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CopyTTree:
"""This block creates an a-tree based on a t-tree in the same zone. Arguments: language: the language of the target zone selector: the selector of the target zone"""
def __init__(self, scenario, args):
"""Constructor, checking the argument values"""
<|body_0|>
... | stack_v2_sparse_classes_36k_train_006084 | 2,289 | permissive | [
{
"docstring": "Constructor, checking the argument values",
"name": "__init__",
"signature": "def __init__(self, scenario, args)"
},
{
"docstring": "Starting tree copy",
"name": "process_zone",
"signature": "def process_zone(self, zone)"
},
{
"docstring": "Deep-copy a subtree, cr... | 3 | null | Implement the Python class `CopyTTree` described below.
Class description:
This block creates an a-tree based on a t-tree in the same zone. Arguments: language: the language of the target zone selector: the selector of the target zone
Method signatures and docstrings:
- def __init__(self, scenario, args): Constructor... | Implement the Python class `CopyTTree` described below.
Class description:
This block creates an a-tree based on a t-tree in the same zone. Arguments: language: the language of the target zone selector: the selector of the target zone
Method signatures and docstrings:
- def __init__(self, scenario, args): Constructor... | 73af644ec35c8a1cd0c37cd478c2afc1db717e0b | <|skeleton|>
class CopyTTree:
"""This block creates an a-tree based on a t-tree in the same zone. Arguments: language: the language of the target zone selector: the selector of the target zone"""
def __init__(self, scenario, args):
"""Constructor, checking the argument values"""
<|body_0|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CopyTTree:
"""This block creates an a-tree based on a t-tree in the same zone. Arguments: language: the language of the target zone selector: the selector of the target zone"""
def __init__(self, scenario, args):
"""Constructor, checking the argument values"""
Block.__init__(self, scenari... | the_stack_v2_python_sparse | alex/components/nlg/tectotpl/block/t2a/copyttree.py | oplatek/alex | train | 0 |
7fbfb585c88985c884158b8557b9908ca5c21ec3 | [
"def dfs(cur_node):\n if not cur_node:\n return 'None,'\n to_return = str(cur_node.val) + ','\n left_sub_tree = dfs(cur_node.left)\n right_sub_tree = dfs(cur_node.right)\n return to_return + left_sub_tree + right_sub_tree\nreturn dfs(root)",
"def rdeserialize(l):\n \"\"\" 이게 핵심... !\"\"\"... | <|body_start_0|>
def dfs(cur_node):
if not cur_node:
return 'None,'
to_return = str(cur_node.val) + ','
left_sub_tree = dfs(cur_node.left)
right_sub_tree = dfs(cur_node.right)
return to_return + left_sub_tree + right_sub_tree
re... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""From Official answer key..."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
def dfs(cur_node):
... | stack_v2_sparse_classes_36k_train_006085 | 4,141 | no_license | [
{
"docstring": "Encodes a tree to a single string. :type root: TreeNode :rtype: str",
"name": "serialize",
"signature": "def serialize(self, root)"
},
{
"docstring": "From Official answer key...",
"name": "deserialize",
"signature": "def deserialize(self, data)"
}
] | 2 | null | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): From Official answer key... | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): From Official answer key...
<|skeleton|>
class Codec:
... | a5635356953df472e71d49c8db3b493ac59b860f | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""From Official answer key..."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
def dfs(cur_node):
if not cur_node:
return 'None,'
to_return = str(cur_node.val) + ','
left_sub_tree = dfs(cur_node.left)
... | the_stack_v2_python_sparse | python/q297.py | ksparkje/leetcode-practice | train | 1 | |
72de027ad380186edcd59b98e76f4f1eb3effbe9 | [
"self.action_n = env.action_space.n\nself.obs_low = env.observation_space.low\nself.obs_scale = env.observation_space.high - env.observation_space.low\nself.encoder = TileCoder(layers, features)\nself.w = np.zeros(features)\nself.feature_list = []\nself.trajectory = []\nself.gamma = gamma\nself.learning_rate = lear... | <|body_start_0|>
self.action_n = env.action_space.n
self.obs_low = env.observation_space.low
self.obs_scale = env.observation_space.high - env.observation_space.low
self.encoder = TileCoder(layers, features)
self.w = np.zeros(features)
self.feature_list = []
self.... | 回合更新策略梯度算法寻找最优策略 | VPGAgent | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VPGAgent:
"""回合更新策略梯度算法寻找最优策略"""
def __init__(self, env, layers=8, features=1893, gamma=1.0, learning_rate=0.03, epsilon=0.001, baseline=True):
"""学习函数 env 环境 layers 要用到几层砖瓦编码 features 砖瓦编码应该得到多少特征 总特征数 8*8 + (8+1) * (8+1) * (8-1) gamma 收益衰减速率 learning_rate 学习速率 epsilon 执行探索策略概率"""
... | stack_v2_sparse_classes_36k_train_006086 | 22,277 | no_license | [
{
"docstring": "学习函数 env 环境 layers 要用到几层砖瓦编码 features 砖瓦编码应该得到多少特征 总特征数 8*8 + (8+1) * (8+1) * (8-1) gamma 收益衰减速率 learning_rate 学习速率 epsilon 执行探索策略概率",
"name": "__init__",
"signature": "def __init__(self, env, layers=8, features=1893, gamma=1.0, learning_rate=0.03, epsilon=0.001, baseline=True)"
},
{... | 3 | stack_v2_sparse_classes_30k_val_000935 | Implement the Python class `VPGAgent` described below.
Class description:
回合更新策略梯度算法寻找最优策略
Method signatures and docstrings:
- def __init__(self, env, layers=8, features=1893, gamma=1.0, learning_rate=0.03, epsilon=0.001, baseline=True): 学习函数 env 环境 layers 要用到几层砖瓦编码 features 砖瓦编码应该得到多少特征 总特征数 8*8 + (8+1) * (8+1) * (8... | Implement the Python class `VPGAgent` described below.
Class description:
回合更新策略梯度算法寻找最优策略
Method signatures and docstrings:
- def __init__(self, env, layers=8, features=1893, gamma=1.0, learning_rate=0.03, epsilon=0.001, baseline=True): 学习函数 env 环境 layers 要用到几层砖瓦编码 features 砖瓦编码应该得到多少特征 总特征数 8*8 + (8+1) * (8+1) * (8... | e6526e9e38fcb5be91b46cb40715c15242198a0b | <|skeleton|>
class VPGAgent:
"""回合更新策略梯度算法寻找最优策略"""
def __init__(self, env, layers=8, features=1893, gamma=1.0, learning_rate=0.03, epsilon=0.001, baseline=True):
"""学习函数 env 环境 layers 要用到几层砖瓦编码 features 砖瓦编码应该得到多少特征 总特征数 8*8 + (8+1) * (8+1) * (8-1) gamma 收益衰减速率 learning_rate 学习速率 epsilon 执行探索策略概率"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class VPGAgent:
"""回合更新策略梯度算法寻找最优策略"""
def __init__(self, env, layers=8, features=1893, gamma=1.0, learning_rate=0.03, epsilon=0.001, baseline=True):
"""学习函数 env 环境 layers 要用到几层砖瓦编码 features 砖瓦编码应该得到多少特征 总特征数 8*8 + (8+1) * (8+1) * (8-1) gamma 收益衰减速率 learning_rate 学习速率 epsilon 执行探索策略概率"""
self.a... | the_stack_v2_python_sparse | mountain_car/function_approx.py | lwzswufe/gym_learning | train | 0 |
295aec760f5d3f0cc015b0597f71a1c1eec88a59 | [
"sd = np.square(inputs - x)\nmses = np.mean(sd, axis=tuple(range(1, sd.ndim)))\nindex = np.argmin(mses)\nif mses[index] > 0:\n raise ValueError('Could not find a precomputed adversarial for this input')\nreturn outputs[index]",
"assert candidate_inputs.shape == candidate_outputs.shape\nx = a.unperturbed\nadver... | <|body_start_0|>
sd = np.square(inputs - x)
mses = np.mean(sd, axis=tuple(range(1, sd.ndim)))
index = np.argmin(mses)
if mses[index] > 0:
raise ValueError('Could not find a precomputed adversarial for this input')
return outputs[index]
<|end_body_0|>
<|body_start_1|>... | Attacks a model using precomputed adversarial candidates. | PrecomputedAdversarialsAttack | [
"MIT",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PrecomputedAdversarialsAttack:
"""Attacks a model using precomputed adversarial candidates."""
def _get_output(self, a, x, inputs, outputs):
"""Looks up the precomputed adversarial for a given input."""
<|body_0|>
def as_generator(self, a, candidate_inputs, candidate_out... | stack_v2_sparse_classes_36k_train_006087 | 1,928 | permissive | [
{
"docstring": "Looks up the precomputed adversarial for a given input.",
"name": "_get_output",
"signature": "def _get_output(self, a, x, inputs, outputs)"
},
{
"docstring": "Attacks a model using precomputed adversarial candidates. Parameters ---------- input_or_adv : `numpy.ndarray` or :class... | 2 | null | Implement the Python class `PrecomputedAdversarialsAttack` described below.
Class description:
Attacks a model using precomputed adversarial candidates.
Method signatures and docstrings:
- def _get_output(self, a, x, inputs, outputs): Looks up the precomputed adversarial for a given input.
- def as_generator(self, a,... | Implement the Python class `PrecomputedAdversarialsAttack` described below.
Class description:
Attacks a model using precomputed adversarial candidates.
Method signatures and docstrings:
- def _get_output(self, a, x, inputs, outputs): Looks up the precomputed adversarial for a given input.
- def as_generator(self, a,... | 81aaa27f1dd9ea3d7d62b661dac40cac6c1ef77a | <|skeleton|>
class PrecomputedAdversarialsAttack:
"""Attacks a model using precomputed adversarial candidates."""
def _get_output(self, a, x, inputs, outputs):
"""Looks up the precomputed adversarial for a given input."""
<|body_0|>
def as_generator(self, a, candidate_inputs, candidate_out... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PrecomputedAdversarialsAttack:
"""Attacks a model using precomputed adversarial candidates."""
def _get_output(self, a, x, inputs, outputs):
"""Looks up the precomputed adversarial for a given input."""
sd = np.square(inputs - x)
mses = np.mean(sd, axis=tuple(range(1, sd.ndim)))
... | the_stack_v2_python_sparse | cnns/foolbox/foolbox_2_3_0/attacks/precomputed.py | adam-dziedzic/bandlimited-cnns | train | 17 |
6ebc981c8923efdf2ca411d525d43343bedb2764 | [
"super(RNNDecoder, self).__init__()\nself.embedding = tf.keras.layers.Embedding(vocab, embedding)\nself.gru = tf.keras.layers.GRU(units, return_sequences=True, return_state=True, recurrent_initializer='glorot_uniform')\nself.F = tf.keras.layers.Dense(vocab)",
"context, _ = SelfAttention(s_prev.shape[1])(s_prev, h... | <|body_start_0|>
super(RNNDecoder, self).__init__()
self.embedding = tf.keras.layers.Embedding(vocab, embedding)
self.gru = tf.keras.layers.GRU(units, return_sequences=True, return_state=True, recurrent_initializer='glorot_uniform')
self.F = tf.keras.layers.Dense(vocab)
<|end_body_0|>
<... | to decode for machine translation | RNNDecoder | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RNNDecoder:
"""to decode for machine translation"""
def __init__(self, vocab, embedding, units, batch):
"""constructor @untis: int representing the number of hidden units in the allignement model * sets the following public instance attributes @embedding: keras Embedding layer that c... | stack_v2_sparse_classes_36k_train_006088 | 2,304 | no_license | [
{
"docstring": "constructor @untis: int representing the number of hidden units in the allignement model * sets the following public instance attributes @embedding: keras Embedding layer that converts words from the vocabulary into embedding vector @gru: keras GRU layer with units as units @F: Dense layer with ... | 2 | stack_v2_sparse_classes_30k_train_021134 | Implement the Python class `RNNDecoder` described below.
Class description:
to decode for machine translation
Method signatures and docstrings:
- def __init__(self, vocab, embedding, units, batch): constructor @untis: int representing the number of hidden units in the allignement model * sets the following public ins... | Implement the Python class `RNNDecoder` described below.
Class description:
to decode for machine translation
Method signatures and docstrings:
- def __init__(self, vocab, embedding, units, batch): constructor @untis: int representing the number of hidden units in the allignement model * sets the following public ins... | e20b284d5f1841952104d7d9a0274cff80eb304d | <|skeleton|>
class RNNDecoder:
"""to decode for machine translation"""
def __init__(self, vocab, embedding, units, batch):
"""constructor @untis: int representing the number of hidden units in the allignement model * sets the following public instance attributes @embedding: keras Embedding layer that c... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RNNDecoder:
"""to decode for machine translation"""
def __init__(self, vocab, embedding, units, batch):
"""constructor @untis: int representing the number of hidden units in the allignement model * sets the following public instance attributes @embedding: keras Embedding layer that converts words... | the_stack_v2_python_sparse | supervised_learning/0x11-attention/2-rnn_decoder.py | jgadelugo/holbertonschool-machine_learning | train | 1 |
d28575762b6e8e8c7851bc0f116c6bf04d856577 | [
"max_val = float('-inf')\nsum = 0\nfor i, num in enumerate(nums, 1):\n sum += num\n if i > k:\n sum -= nums[i - k - 1]\n if i >= k:\n max_val = max(max_val, sum)\nreturn float(max_val) / k",
"sum_list = [0]\nfor num in nums:\n sum_list.append(sum_list[-1] + num)\nmax_val = max((sum_list[... | <|body_start_0|>
max_val = float('-inf')
sum = 0
for i, num in enumerate(nums, 1):
sum += num
if i > k:
sum -= nums[i - k - 1]
if i >= k:
max_val = max(max_val, sum)
return float(max_val) / k
<|end_body_0|>
<|body_start... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findMaxAverage(self, nums, k):
""":type nums: List[int] :type k: int :rtype: float"""
<|body_0|>
def findMaxAverage(self, nums, k):
""":type nums: List[int] :type k: int :rtype: float"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
max... | stack_v2_sparse_classes_36k_train_006089 | 1,398 | no_license | [
{
"docstring": ":type nums: List[int] :type k: int :rtype: float",
"name": "findMaxAverage",
"signature": "def findMaxAverage(self, nums, k)"
},
{
"docstring": ":type nums: List[int] :type k: int :rtype: float",
"name": "findMaxAverage",
"signature": "def findMaxAverage(self, nums, k)"
... | 2 | stack_v2_sparse_classes_30k_train_008070 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findMaxAverage(self, nums, k): :type nums: List[int] :type k: int :rtype: float
- def findMaxAverage(self, nums, k): :type nums: List[int] :type k: int :rtype: float | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findMaxAverage(self, nums, k): :type nums: List[int] :type k: int :rtype: float
- def findMaxAverage(self, nums, k): :type nums: List[int] :type k: int :rtype: float
<|skele... | f0fe37f489a8dc9867b774bfa22a8d73c322cb79 | <|skeleton|>
class Solution:
def findMaxAverage(self, nums, k):
""":type nums: List[int] :type k: int :rtype: float"""
<|body_0|>
def findMaxAverage(self, nums, k):
""":type nums: List[int] :type k: int :rtype: float"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def findMaxAverage(self, nums, k):
""":type nums: List[int] :type k: int :rtype: float"""
max_val = float('-inf')
sum = 0
for i, num in enumerate(nums, 1):
sum += num
if i > k:
sum -= nums[i - k - 1]
if i >= k:
... | the_stack_v2_python_sparse | dp/643_Maximum_Average_Subarray_I.py | AsterWang/leecode | train | 0 | |
59cb629ba2c0377424c24dad821472ceb67d22e2 | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn NetworkConnection()",
"from .connection_direction import ConnectionDirection\nfrom .connection_status import ConnectionStatus\nfrom .security_network_protocol import SecurityNetworkProtocol\nfrom .connection_direction import Connection... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return NetworkConnection()
<|end_body_0|>
<|body_start_1|>
from .connection_direction import ConnectionDirection
from .connection_status import ConnectionStatus
from .security_network_p... | NetworkConnection | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NetworkConnection:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> NetworkConnection:
"""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... | stack_v2_sparse_classes_36k_train_006090 | 9,109 | 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: NetworkConnection",
"name": "create_from_discriminator_value",
"signature": "def create_from_discriminator_v... | 3 | stack_v2_sparse_classes_30k_train_006894 | Implement the Python class `NetworkConnection` described below.
Class description:
Implement the NetworkConnection class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> NetworkConnection: Creates a new instance of the appropriate class based on discrim... | Implement the Python class `NetworkConnection` described below.
Class description:
Implement the NetworkConnection class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> NetworkConnection: Creates a new instance of the appropriate class based on discrim... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class NetworkConnection:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> NetworkConnection:
"""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... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NetworkConnection:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> NetworkConnection:
"""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: Netw... | the_stack_v2_python_sparse | msgraph/generated/models/network_connection.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
a70986140e73e6933c8e6e586eb79065fbc2430d | [
"start_url = 'https://ip.jiangxianli.com/?page={}&country=%E4%B8%AD%E5%9B%BD'\npage_count = 10\nurls = [start_url.format(page) for page in range(1, page_count + 1)]\ntime.sleep(3)\nfor url in urls:\n try:\n print('Crawing', url)\n html = requests.get(url).content.decode('utf8')\n if html:\n ... | <|body_start_0|>
start_url = 'https://ip.jiangxianli.com/?page={}&country=%E4%B8%AD%E5%9B%BD'
page_count = 10
urls = [start_url.format(page) for page in range(1, page_count + 1)]
time.sleep(3)
for url in urls:
try:
print('Crawing', url)
... | 代理爬取 | Crawler | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Crawler:
"""代理爬取"""
def crawl_jiangxianli(self):
"""ip.jiangxianli.com网站代理爬取"""
<|body_0|>
def crawl_kuaidaili(self):
"""https://www.kuaidaili.com/free/inha/1/ 快代理网站爬取"""
<|body_1|>
def crawl_ip66(self):
"""http://www.66ip.cn/"""
<|bo... | stack_v2_sparse_classes_36k_train_006091 | 5,528 | no_license | [
{
"docstring": "ip.jiangxianli.com网站代理爬取",
"name": "crawl_jiangxianli",
"signature": "def crawl_jiangxianli(self)"
},
{
"docstring": "https://www.kuaidaili.com/free/inha/1/ 快代理网站爬取",
"name": "crawl_kuaidaili",
"signature": "def crawl_kuaidaili(self)"
},
{
"docstring": "http://www... | 4 | null | Implement the Python class `Crawler` described below.
Class description:
代理爬取
Method signatures and docstrings:
- def crawl_jiangxianli(self): ip.jiangxianli.com网站代理爬取
- def crawl_kuaidaili(self): https://www.kuaidaili.com/free/inha/1/ 快代理网站爬取
- def crawl_ip66(self): http://www.66ip.cn/
- def get_proxies(self, callba... | Implement the Python class `Crawler` described below.
Class description:
代理爬取
Method signatures and docstrings:
- def crawl_jiangxianli(self): ip.jiangxianli.com网站代理爬取
- def crawl_kuaidaili(self): https://www.kuaidaili.com/free/inha/1/ 快代理网站爬取
- def crawl_ip66(self): http://www.66ip.cn/
- def get_proxies(self, callba... | f49a93c1cab5716d4dafecb7479a3be2a4af91ad | <|skeleton|>
class Crawler:
"""代理爬取"""
def crawl_jiangxianli(self):
"""ip.jiangxianli.com网站代理爬取"""
<|body_0|>
def crawl_kuaidaili(self):
"""https://www.kuaidaili.com/free/inha/1/ 快代理网站爬取"""
<|body_1|>
def crawl_ip66(self):
"""http://www.66ip.cn/"""
<|bo... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Crawler:
"""代理爬取"""
def crawl_jiangxianli(self):
"""ip.jiangxianli.com网站代理爬取"""
start_url = 'https://ip.jiangxianli.com/?page={}&country=%E4%B8%AD%E5%9B%BD'
page_count = 10
urls = [start_url.format(page) for page in range(1, page_count + 1)]
time.sleep(3)
f... | the_stack_v2_python_sparse | Sec_9/9.2/crawler.py | WiconWang/spider_project | train | 0 |
12785624fc17e46206298c852a59b171e80949af | [
"if fmtr is None:\n pass\nself.formatter = fmtr",
"tid = threading.current_thread().ident()\ntime_stamp = helper_time.get_time_millionsec()\nnew_msg = '[%s] [%s] [%d] [%s] %s' % (time_stamp, lvl.name, tid, loggername, msg)\nif exc is not None:\n new_msg = new_msg + '\\r\\nex:%s' % exc.args\nreturn new_msg"
... | <|body_start_0|>
if fmtr is None:
pass
self.formatter = fmtr
<|end_body_0|>
<|body_start_1|>
tid = threading.current_thread().ident()
time_stamp = helper_time.get_time_millionsec()
new_msg = '[%s] [%s] [%d] [%s] %s' % (time_stamp, lvl.name, tid, loggername, msg)
... | The settings for log message formatting. The 'fmtr' should be a method that returns a string | MsLogMessageConfig | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MsLogMessageConfig:
"""The settings for log message formatting. The 'fmtr' should be a method that returns a string"""
def __init__(self, fmtr=None):
"""The 'fmtr' should be a method that returns a string fmtr: A method that returns string"""
<|body_0|>
def __default_for... | stack_v2_sparse_classes_36k_train_006092 | 5,666 | permissive | [
{
"docstring": "The 'fmtr' should be a method that returns a string fmtr: A method that returns string",
"name": "__init__",
"signature": "def __init__(self, fmtr=None)"
},
{
"docstring": "msg: The log message. exc: The Exception object(if exists) 格式符 说明 %a 星期的英文单词的缩写：如星期一， 则返回 Mon %A 星期的英文单词的全拼... | 2 | null | Implement the Python class `MsLogMessageConfig` described below.
Class description:
The settings for log message formatting. The 'fmtr' should be a method that returns a string
Method signatures and docstrings:
- def __init__(self, fmtr=None): The 'fmtr' should be a method that returns a string fmtr: A method that re... | Implement the Python class `MsLogMessageConfig` described below.
Class description:
The settings for log message formatting. The 'fmtr' should be a method that returns a string
Method signatures and docstrings:
- def __init__(self, fmtr=None): The 'fmtr' should be a method that returns a string fmtr: A method that re... | 8f05a6b91fc205960edd57f9076facec04f49a1a | <|skeleton|>
class MsLogMessageConfig:
"""The settings for log message formatting. The 'fmtr' should be a method that returns a string"""
def __init__(self, fmtr=None):
"""The 'fmtr' should be a method that returns a string fmtr: A method that returns string"""
<|body_0|>
def __default_for... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MsLogMessageConfig:
"""The settings for log message formatting. The 'fmtr' should be a method that returns a string"""
def __init__(self, fmtr=None):
"""The 'fmtr' should be a method that returns a string fmtr: A method that returns string"""
if fmtr is None:
pass
self... | the_stack_v2_python_sparse | savecode/pythonpackages/commonbaby/mslog/mslogconfig.py | cbbbbbbbb/sspywork | train | 0 |
45523495bc3da9db151001805a1b8bcced3de2da | [
"mn = float('inf')\n\ndef dfs(d, i, cur):\n nonlocal mn\n if d == len(triangle):\n mn = min(mn, cur)\n return\n cur += triangle[d][i]\n dfs(d + 1, i, cur)\n dfs(d + 1, i + 1, cur)\ndfs(0, 0, 0)\nreturn mn",
"@lru_cache(None)\ndef dp(d, i):\n if d == 0:\n assert i == 0\n ... | <|body_start_0|>
mn = float('inf')
def dfs(d, i, cur):
nonlocal mn
if d == len(triangle):
mn = min(mn, cur)
return
cur += triangle[d][i]
dfs(d + 1, i, cur)
dfs(d + 1, i + 1, cur)
dfs(0, 0, 0)
ret... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def minimumTotal(self, triangle: List[List[int]]) -> int:
"""Bruteforce dfs Time complexity: O(n!) Space complexity: O(n) # callstack"""
<|body_0|>
def minimumTotal(self, triangle: List[List[int]]) -> int:
"""Recursive DP Time complexity: O(n^2) Space compl... | stack_v2_sparse_classes_36k_train_006093 | 3,847 | no_license | [
{
"docstring": "Bruteforce dfs Time complexity: O(n!) Space complexity: O(n) # callstack",
"name": "minimumTotal",
"signature": "def minimumTotal(self, triangle: List[List[int]]) -> int"
},
{
"docstring": "Recursive DP Time complexity: O(n^2) Space complexity: O(n^2)",
"name": "minimumTotal"... | 5 | stack_v2_sparse_classes_30k_test_000955 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def minimumTotal(self, triangle: List[List[int]]) -> int: Bruteforce dfs Time complexity: O(n!) Space complexity: O(n) # callstack
- def minimumTotal(self, triangle: List[List[in... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def minimumTotal(self, triangle: List[List[int]]) -> int: Bruteforce dfs Time complexity: O(n!) Space complexity: O(n) # callstack
- def minimumTotal(self, triangle: List[List[in... | 1389a009a02e90e8700a7a00e0b7f797c129cdf4 | <|skeleton|>
class Solution:
def minimumTotal(self, triangle: List[List[int]]) -> int:
"""Bruteforce dfs Time complexity: O(n!) Space complexity: O(n) # callstack"""
<|body_0|>
def minimumTotal(self, triangle: List[List[int]]) -> int:
"""Recursive DP Time complexity: O(n^2) Space compl... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def minimumTotal(self, triangle: List[List[int]]) -> int:
"""Bruteforce dfs Time complexity: O(n!) Space complexity: O(n) # callstack"""
mn = float('inf')
def dfs(d, i, cur):
nonlocal mn
if d == len(triangle):
mn = min(mn, cur)
... | the_stack_v2_python_sparse | leetcode/solved/120_Triangle/solution.py | sungminoh/algorithms | train | 0 | |
96e610726135a19eb6f822ee8ce941396166ac3a | [
"if not isinstance(process_num, int):\n raise ValueError('AKG kernel compiling process number must be of type int, but got {} with type {}'.format(process_num, type(wait_time)))\nif not isinstance(wait_time, int):\n raise ValueError('AKG kernel compiling wait time must be of type int, but got {} with type {}'... | <|body_start_0|>
if not isinstance(process_num, int):
raise ValueError('AKG kernel compiling process number must be of type int, but got {} with type {}'.format(process_num, type(wait_time)))
if not isinstance(wait_time, int):
raise ValueError('AKG kernel compiling wait time must... | akg kernel parallel process | AkgProcess | [
"Apache-2.0",
"LicenseRef-scancode-proprietary-license",
"MPL-1.0",
"OpenSSL",
"LGPL-3.0-only",
"LicenseRef-scancode-warranty-disclaimer",
"BSD-3-Clause-Open-MPI",
"MIT",
"MPL-2.0-no-copyleft-exception",
"NTP",
"BSD-3-Clause",
"GPL-1.0-or-later",
"0BSD",
"MPL-2.0",
"LicenseRef-scancode-f... | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AkgProcess:
"""akg kernel parallel process"""
def __init__(self, process_num, wait_time, platform):
"""Args: process_num: int. processes number wait_time: int. max time the function blocked"""
<|body_0|>
def compile(self, attrs=None):
"""compile kernel by multi p... | stack_v2_sparse_classes_36k_train_006094 | 7,760 | permissive | [
{
"docstring": "Args: process_num: int. processes number wait_time: int. max time the function blocked",
"name": "__init__",
"signature": "def __init__(self, process_num, wait_time, platform)"
},
{
"docstring": "compile kernel by multi processes Return: True for all compile success, False for so... | 3 | stack_v2_sparse_classes_30k_train_012900 | Implement the Python class `AkgProcess` described below.
Class description:
akg kernel parallel process
Method signatures and docstrings:
- def __init__(self, process_num, wait_time, platform): Args: process_num: int. processes number wait_time: int. max time the function blocked
- def compile(self, attrs=None): comp... | Implement the Python class `AkgProcess` described below.
Class description:
akg kernel parallel process
Method signatures and docstrings:
- def __init__(self, process_num, wait_time, platform): Args: process_num: int. processes number wait_time: int. max time the function blocked
- def compile(self, attrs=None): comp... | 54acb15d435533c815ee1bd9f6dc0b56b4d4cf83 | <|skeleton|>
class AkgProcess:
"""akg kernel parallel process"""
def __init__(self, process_num, wait_time, platform):
"""Args: process_num: int. processes number wait_time: int. max time the function blocked"""
<|body_0|>
def compile(self, attrs=None):
"""compile kernel by multi p... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AkgProcess:
"""akg kernel parallel process"""
def __init__(self, process_num, wait_time, platform):
"""Args: process_num: int. processes number wait_time: int. max time the function blocked"""
if not isinstance(process_num, int):
raise ValueError('AKG kernel compiling process ... | the_stack_v2_python_sparse | mindspore/python/mindspore/_extends/parallel_compile/akg_compiler/akg_process.py | mindspore-ai/mindspore | train | 4,178 |
387debdfcbfb6cbd032b5f4d00345a5d893ff4aa | [
"threading.Thread.__init__(self)\nself.threadName = name\nself.people = people",
"print('开始线程: ' + self.threadName)\nchiHuoGuo(self.people)\nprint('qq交流群：226296743')\nprint('结束线程: ' + self.name)"
] | <|body_start_0|>
threading.Thread.__init__(self)
self.threadName = name
self.people = people
<|end_body_0|>
<|body_start_1|>
print('开始线程: ' + self.threadName)
chiHuoGuo(self.people)
print('qq交流群：226296743')
print('结束线程: ' + self.name)
<|end_body_1|>
| myThread | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class myThread:
def __init__(self, people, name):
"""重写threading.Thread初始化内容"""
<|body_0|>
def run(self):
"""重写run方法"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
threading.Thread.__init__(self)
self.threadName = name
self.people = peopl... | stack_v2_sparse_classes_36k_train_006095 | 5,122 | permissive | [
{
"docstring": "重写threading.Thread初始化内容",
"name": "__init__",
"signature": "def __init__(self, people, name)"
},
{
"docstring": "重写run方法",
"name": "run",
"signature": "def run(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_007503 | Implement the Python class `myThread` described below.
Class description:
Implement the myThread class.
Method signatures and docstrings:
- def __init__(self, people, name): 重写threading.Thread初始化内容
- def run(self): 重写run方法 | Implement the Python class `myThread` described below.
Class description:
Implement the myThread class.
Method signatures and docstrings:
- def __init__(self, people, name): 重写threading.Thread初始化内容
- def run(self): 重写run方法
<|skeleton|>
class myThread:
def __init__(self, people, name):
"""重写threading.Thr... | e046cdd35bd63e9430416ea6954b1aaef4bc50d5 | <|skeleton|>
class myThread:
def __init__(self, people, name):
"""重写threading.Thread初始化内容"""
<|body_0|>
def run(self):
"""重写run方法"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class myThread:
def __init__(self, people, name):
"""重写threading.Thread初始化内容"""
threading.Thread.__init__(self)
self.threadName = name
self.people = people
def run(self):
"""重写run方法"""
print('开始线程: ' + self.threadName)
chiHuoGuo(self.people)
print... | the_stack_v2_python_sparse | 第一期/北京-菜鸟渣渣/Fast_Learning_python3/thread/thread_join&setDeamon.py | beidou9313/deeptest | train | 0 | |
c979fb8409696f1d1e25d2716c8f6b0404e5ad1f | [
"from .wrapper import NCNNWrapper\nif deploy_cfg:\n backend_config = get_backend_config(deploy_cfg)\n use_vulkan = backend_config.get('use_vulkan', False)\nelse:\n use_vulkan = False\nreturn NCNNWrapper(param_file=backend_files[0], bin_file=backend_files[1], output_names=output_names, use_vulkan=use_vulkan... | <|body_start_0|>
from .wrapper import NCNNWrapper
if deploy_cfg:
backend_config = get_backend_config(deploy_cfg)
use_vulkan = backend_config.get('use_vulkan', False)
else:
use_vulkan = False
return NCNNWrapper(param_file=backend_files[0], bin_file=back... | NCNNManager | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NCNNManager:
def build_wrapper(cls, backend_files: Sequence[str], device: str='cpu', input_names: Optional[Sequence[str]]=None, output_names: Optional[Sequence[str]]=None, deploy_cfg: Optional[Any]=None, **kwargs):
"""Build the wrapper for the backend model. Args: backend_files (Sequence... | stack_v2_sparse_classes_36k_train_006096 | 5,173 | permissive | [
{
"docstring": "Build the wrapper for the backend model. Args: backend_files (Sequence[str]): Backend files. device (str, optional): The device info. Defaults to 'cpu'. input_names (Optional[Sequence[str]], optional): input names. Defaults to None. output_names (Optional[Sequence[str]], optional): output names.... | 5 | stack_v2_sparse_classes_30k_train_017549 | Implement the Python class `NCNNManager` described below.
Class description:
Implement the NCNNManager class.
Method signatures and docstrings:
- def build_wrapper(cls, backend_files: Sequence[str], device: str='cpu', input_names: Optional[Sequence[str]]=None, output_names: Optional[Sequence[str]]=None, deploy_cfg: O... | Implement the Python class `NCNNManager` described below.
Class description:
Implement the NCNNManager class.
Method signatures and docstrings:
- def build_wrapper(cls, backend_files: Sequence[str], device: str='cpu', input_names: Optional[Sequence[str]]=None, output_names: Optional[Sequence[str]]=None, deploy_cfg: O... | 5479c8774f5b88d7ed9d399d4e305cb42cc2e73a | <|skeleton|>
class NCNNManager:
def build_wrapper(cls, backend_files: Sequence[str], device: str='cpu', input_names: Optional[Sequence[str]]=None, output_names: Optional[Sequence[str]]=None, deploy_cfg: Optional[Any]=None, **kwargs):
"""Build the wrapper for the backend model. Args: backend_files (Sequence... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NCNNManager:
def build_wrapper(cls, backend_files: Sequence[str], device: str='cpu', input_names: Optional[Sequence[str]]=None, output_names: Optional[Sequence[str]]=None, deploy_cfg: Optional[Any]=None, **kwargs):
"""Build the wrapper for the backend model. Args: backend_files (Sequence[str]): Backen... | the_stack_v2_python_sparse | mmdeploy/backend/ncnn/backend_manager.py | open-mmlab/mmdeploy | train | 2,164 | |
04b7bf40bd026bd05b05434303f1fdb39d00ddf6 | [
"paddle.set_device('cpu')\npaddle.seed(2020)\npaddle.framework.random._manual_program_seed(2020)\nffn_fc1_act = 'relu'\n[batch_size, d_model, n_head, dim_feedforward, dropout, attn_dropout, act_dropout, sequence_length] = generate_basic_params(mode='encoder_layer')\nsrc = np.random.rand(batch_size, sequence_length,... | <|body_start_0|>
paddle.set_device('cpu')
paddle.seed(2020)
paddle.framework.random._manual_program_seed(2020)
ffn_fc1_act = 'relu'
[batch_size, d_model, n_head, dim_feedforward, dropout, attn_dropout, act_dropout, sequence_length] = generate_basic_params(mode='encoder_layer')
... | test | Test | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Test:
"""test"""
def test_transformer_encoder_layer(self):
"""test_transformer_encoder_layer"""
<|body_0|>
def test_main(self):
"""test"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
paddle.set_device('cpu')
paddle.seed(2020)
pa... | stack_v2_sparse_classes_36k_train_006097 | 2,699 | no_license | [
{
"docstring": "test_transformer_encoder_layer",
"name": "test_transformer_encoder_layer",
"signature": "def test_transformer_encoder_layer(self)"
},
{
"docstring": "test",
"name": "test_main",
"signature": "def test_main(self)"
}
] | 2 | null | Implement the Python class `Test` described below.
Class description:
test
Method signatures and docstrings:
- def test_transformer_encoder_layer(self): test_transformer_encoder_layer
- def test_main(self): test | Implement the Python class `Test` described below.
Class description:
test
Method signatures and docstrings:
- def test_transformer_encoder_layer(self): test_transformer_encoder_layer
- def test_main(self): test
<|skeleton|>
class Test:
"""test"""
def test_transformer_encoder_layer(self):
"""test_tr... | bd3790ce72a2a26611b5eda3901651b5a809348f | <|skeleton|>
class Test:
"""test"""
def test_transformer_encoder_layer(self):
"""test_transformer_encoder_layer"""
<|body_0|>
def test_main(self):
"""test"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Test:
"""test"""
def test_transformer_encoder_layer(self):
"""test_transformer_encoder_layer"""
paddle.set_device('cpu')
paddle.seed(2020)
paddle.framework.random._manual_program_seed(2020)
ffn_fc1_act = 'relu'
[batch_size, d_model, n_head, dim_feedforward,... | the_stack_v2_python_sparse | framework/api/nn/test_TransformerEncoderLayer.py | PaddlePaddle/PaddleTest | train | 42 |
64a5f112c5691a5790b0e304e8ab9318df9d7f05 | [
"checkout = zeit.cms.checkout.interfaces.ICheckoutManager(self.context)\nif checkout.canCheckout:\n return _('View')\nreturn _('Edit contents')",
"selected = self.request.getURL().endswith('@@edit.html')\nselected = selected or self.request.getURL().endswith('@@view.html')\nreturn selected"
] | <|body_start_0|>
checkout = zeit.cms.checkout.interfaces.ICheckoutManager(self.context)
if checkout.canCheckout:
return _('View')
return _('Edit contents')
<|end_body_0|>
<|body_start_1|>
selected = self.request.getURL().endswith('@@edit.html')
selected = selected or... | EditContentsMenuItem | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EditContentsMenuItem:
def title(self):
"""Changes wheter item is checked out or checked in"""
<|body_0|>
def selected(self):
"""We are selected when no other item is selected."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
checkout = zeit.cms.check... | stack_v2_sparse_classes_36k_train_006098 | 831 | permissive | [
{
"docstring": "Changes wheter item is checked out or checked in",
"name": "title",
"signature": "def title(self)"
},
{
"docstring": "We are selected when no other item is selected.",
"name": "selected",
"signature": "def selected(self)"
}
] | 2 | null | Implement the Python class `EditContentsMenuItem` described below.
Class description:
Implement the EditContentsMenuItem class.
Method signatures and docstrings:
- def title(self): Changes wheter item is checked out or checked in
- def selected(self): We are selected when no other item is selected. | Implement the Python class `EditContentsMenuItem` described below.
Class description:
Implement the EditContentsMenuItem class.
Method signatures and docstrings:
- def title(self): Changes wheter item is checked out or checked in
- def selected(self): We are selected when no other item is selected.
<|skeleton|>
clas... | 3cc213b873d527127aa6f0dd3c79a542299a8a0e | <|skeleton|>
class EditContentsMenuItem:
def title(self):
"""Changes wheter item is checked out or checked in"""
<|body_0|>
def selected(self):
"""We are selected when no other item is selected."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EditContentsMenuItem:
def title(self):
"""Changes wheter item is checked out or checked in"""
checkout = zeit.cms.checkout.interfaces.ICheckoutManager(self.context)
if checkout.canCheckout:
return _('View')
return _('Edit contents')
def selected(self):
... | the_stack_v2_python_sparse | core/src/zeit/content/article/browser/menu.py | louika/vivi | train | 0 | |
dd2684e1dc89d205bdedf6166a3db20446c0fb81 | [
"if start == end:\n return\nfor i in range(int((end - start + 1) / 2)):\n nums[start + i], nums[end - i] = (nums[end - i], nums[start + i])",
"for i in range(len(nums) - 1, 0, -1):\n if nums[i - 1] < nums[i]:\n self.reverse_sublist(nums, i, len(nums) - 1)\n for j in range(i, len(nums)):\n ... | <|body_start_0|>
if start == end:
return
for i in range(int((end - start + 1) / 2)):
nums[start + i], nums[end - i] = (nums[end - i], nums[start + i])
<|end_body_0|>
<|body_start_1|>
for i in range(len(nums) - 1, 0, -1):
if nums[i - 1] < nums[i]:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def reverse_sublist(self, nums, start, end):
"""Reverse order of sublist from start to end (both inclusive indices)."""
<|body_0|>
def nextPermutation(self, nums: List[int]) -> None:
"""Do not return anything, modify nums in-place instead."""
<|body... | stack_v2_sparse_classes_36k_train_006099 | 1,113 | no_license | [
{
"docstring": "Reverse order of sublist from start to end (both inclusive indices).",
"name": "reverse_sublist",
"signature": "def reverse_sublist(self, nums, start, end)"
},
{
"docstring": "Do not return anything, modify nums in-place instead.",
"name": "nextPermutation",
"signature": ... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def reverse_sublist(self, nums, start, end): Reverse order of sublist from start to end (both inclusive indices).
- def nextPermutation(self, nums: List[int]) -> None: Do not ret... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def reverse_sublist(self, nums, start, end): Reverse order of sublist from start to end (both inclusive indices).
- def nextPermutation(self, nums: List[int]) -> None: Do not ret... | de2b8bbc7cd744bb28ff9dcfe1d1cdc388c3fe8d | <|skeleton|>
class Solution:
def reverse_sublist(self, nums, start, end):
"""Reverse order of sublist from start to end (both inclusive indices)."""
<|body_0|>
def nextPermutation(self, nums: List[int]) -> None:
"""Do not return anything, modify nums in-place instead."""
<|body... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def reverse_sublist(self, nums, start, end):
"""Reverse order of sublist from start to end (both inclusive indices)."""
if start == end:
return
for i in range(int((end - start + 1) / 2)):
nums[start + i], nums[end - i] = (nums[end - i], nums[start + i]... | the_stack_v2_python_sparse | solutions/31.py | Anshul1196/leetcode | train | 0 |
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