blob_id stringlengths 40 40 | bodies listlengths 2 6 | bodies_text stringlengths 196 7.73k | class_docstring stringlengths 0 700 | class_name stringlengths 1 86 | detected_licenses listlengths 0 45 | format_version stringclasses 1
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value | snapshot_source_dir stringclasses 1
value | snapshot_total_rows int64 75.8k 75.8k | solution stringlengths 242 8.3k | source stringclasses 1
value | source_path stringlengths 4 177 | source_repo stringlengths 6 110 | split stringclasses 1
value | star_events_count int64 0 209k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
b2c8849b114ffbfe4722b43a1884203fb935c767 | [
"self._num_classes = num_classes\nself._level = level\nself._num_convs = num_convs\nself._upsample_factor = upsample_factor\nself._upsample_num_filters = upsample_num_filters\nif activation == 'relu':\n self._activation = tf.nn.relu\nelif activation == 'swish':\n self._activation = tf.nn.swish\nelse:\n rai... | <|body_start_0|>
self._num_classes = num_classes
self._level = level
self._num_convs = num_convs
self._upsample_factor = upsample_factor
self._upsample_num_filters = upsample_num_filters
if activation == 'relu':
self._activation = tf.nn.relu
elif activ... | Semantic segmentation head. | SegmentationHead | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SegmentationHead:
"""Semantic segmentation head."""
def __init__(self, num_classes, level, num_convs=2, upsample_factor=1, upsample_num_filters=256, activation='relu', use_batch_norm=True, batch_norm_activation=nn_ops.BatchNormActivation(activation='relu')):
"""Initialize params to b... | stack_v2_sparse_classes_75kplus_train_074500 | 46,218 | permissive | [
{
"docstring": "Initialize params to build segmentation head. Args: num_classes: `int` number of mask classification categories. The number of classes does not include background class. level: `int` feature level used for prediction. num_convs: `int` number of stacked convolution before the last prediction laye... | 2 | stack_v2_sparse_classes_30k_train_027686 | Implement the Python class `SegmentationHead` described below.
Class description:
Semantic segmentation head.
Method signatures and docstrings:
- def __init__(self, num_classes, level, num_convs=2, upsample_factor=1, upsample_num_filters=256, activation='relu', use_batch_norm=True, batch_norm_activation=nn_ops.BatchN... | Implement the Python class `SegmentationHead` described below.
Class description:
Semantic segmentation head.
Method signatures and docstrings:
- def __init__(self, num_classes, level, num_convs=2, upsample_factor=1, upsample_num_filters=256, activation='relu', use_batch_norm=True, batch_norm_activation=nn_ops.BatchN... | 0f7adb97a93ec3e3485c261d030c507eb16b33e4 | <|skeleton|>
class SegmentationHead:
"""Semantic segmentation head."""
def __init__(self, num_classes, level, num_convs=2, upsample_factor=1, upsample_num_filters=256, activation='relu', use_batch_norm=True, batch_norm_activation=nn_ops.BatchNormActivation(activation='relu')):
"""Initialize params to b... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SegmentationHead:
"""Semantic segmentation head."""
def __init__(self, num_classes, level, num_convs=2, upsample_factor=1, upsample_num_filters=256, activation='relu', use_batch_norm=True, batch_norm_activation=nn_ops.BatchNormActivation(activation='relu')):
"""Initialize params to build segmenta... | the_stack_v2_python_sparse | models/official/detection/modeling/architecture/heads.py | tensorflow/tpu | train | 5,627 |
a3a4973963ad168ba9c58b92201168986e1506f2 | [
"self.species = species\nself.danger_level = danger_level\nself.emoji = emoji",
"if self.danger_level == opponent.danger_level:\n return opponent\nelif self.danger_level < opponent.danger_level:\n return opponent\nelse:\n return self"
] | <|body_start_0|>
self.species = species
self.danger_level = danger_level
self.emoji = emoji
<|end_body_0|>
<|body_start_1|>
if self.danger_level == opponent.danger_level:
return opponent
elif self.danger_level < opponent.danger_level:
return opponent
... | Defined Animal class. | Animal | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Animal:
"""Defined Animal class."""
def __init__(self, species: str, danger_level: int, emoji: str):
"""Constructor for the Animal class."""
<|body_0|>
def fight(self, opponent: Animal) -> Animal:
"""Simulates a fight between two animals and returns the one with ... | stack_v2_sparse_classes_75kplus_train_074501 | 3,208 | no_license | [
{
"docstring": "Constructor for the Animal class.",
"name": "__init__",
"signature": "def __init__(self, species: str, danger_level: int, emoji: str)"
},
{
"docstring": "Simulates a fight between two animals and returns the one with the higher danger_level.",
"name": "fight",
"signature"... | 2 | stack_v2_sparse_classes_30k_train_039507 | Implement the Python class `Animal` described below.
Class description:
Defined Animal class.
Method signatures and docstrings:
- def __init__(self, species: str, danger_level: int, emoji: str): Constructor for the Animal class.
- def fight(self, opponent: Animal) -> Animal: Simulates a fight between two animals and ... | Implement the Python class `Animal` described below.
Class description:
Defined Animal class.
Method signatures and docstrings:
- def __init__(self, species: str, danger_level: int, emoji: str): Constructor for the Animal class.
- def fight(self, opponent: Animal) -> Animal: Simulates a fight between two animals and ... | cdc288669d5df9db4f6fe61dd5a9a6bfeb663ae3 | <|skeleton|>
class Animal:
"""Defined Animal class."""
def __init__(self, species: str, danger_level: int, emoji: str):
"""Constructor for the Animal class."""
<|body_0|>
def fight(self, opponent: Animal) -> Animal:
"""Simulates a fight between two animals and returns the one with ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Animal:
"""Defined Animal class."""
def __init__(self, species: str, danger_level: int, emoji: str):
"""Constructor for the Animal class."""
self.species = species
self.danger_level = danger_level
self.emoji = emoji
def fight(self, opponent: Animal) -> Animal:
... | the_stack_v2_python_sparse | exercises/ex11/animal_kingdom.py | kimcha-0/comp110-21ss1-workspace | train | 0 |
bf9588ee2a4af4d9357a51e13ab14a30f1f6561b | [
"self.res = []\nself.dfs(root, [], target)\nreturn self.res",
"if not root:\n return\npath.append(root.val)\ntarget -= root.val\nif target == 0 and (not root.left) and (not root.right):\n self.res.append(path[:])\nself.dfs(root.left, path, target)\nself.dfs(root.right, path, target)\npath.pop()"
] | <|body_start_0|>
self.res = []
self.dfs(root, [], target)
return self.res
<|end_body_0|>
<|body_start_1|>
if not root:
return
path.append(root.val)
target -= root.val
if target == 0 and (not root.left) and (not root.right):
self.res.append... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def pathSum(self, root, target):
"""Args: root: TreeNode target: int Return: list[list[int]]"""
<|body_0|>
def dfs(self, root, path, target):
"""Args: root: TreeNode path: list[int] target: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_75kplus_train_074502 | 902 | no_license | [
{
"docstring": "Args: root: TreeNode target: int Return: list[list[int]]",
"name": "pathSum",
"signature": "def pathSum(self, root, target)"
},
{
"docstring": "Args: root: TreeNode path: list[int] target: int",
"name": "dfs",
"signature": "def dfs(self, root, path, target)"
}
] | 2 | stack_v2_sparse_classes_30k_train_026794 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def pathSum(self, root, target): Args: root: TreeNode target: int Return: list[list[int]]
- def dfs(self, root, path, target): Args: root: TreeNode path: list[int] target: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def pathSum(self, root, target): Args: root: TreeNode target: int Return: list[list[int]]
- def dfs(self, root, path, target): Args: root: TreeNode path: list[int] target: int
<... | 101bce2fac8b188a4eb2f5e017293d21ad0ecb21 | <|skeleton|>
class Solution:
def pathSum(self, root, target):
"""Args: root: TreeNode target: int Return: list[list[int]]"""
<|body_0|>
def dfs(self, root, path, target):
"""Args: root: TreeNode path: list[int] target: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def pathSum(self, root, target):
"""Args: root: TreeNode target: int Return: list[list[int]]"""
self.res = []
self.dfs(root, [], target)
return self.res
def dfs(self, root, path, target):
"""Args: root: TreeNode path: list[int] target: int"""
if n... | the_stack_v2_python_sparse | 剑指offer/剑指 Offer 34. 二叉树中和为某一值的路径.py | AiZhanghan/Leetcode | train | 0 | |
39b2110306ffbf176b3fc00fee4e37696b58f44c | [
"firsts, others = data\nstat = self.ChiSquared(firsts) + self.ChiSquared(others)\nreturn stat",
"hist = thinkstats2.Hist(lengths)\nobserved = np.array(hist.Freqs(self.values))\nexpected = self.expected_probs * len(lengths)\nstat = sum((observed - expected) ** 2 / expected)\nreturn stat",
"firsts, others = self.... | <|body_start_0|>
firsts, others = data
stat = self.ChiSquared(firsts) + self.ChiSquared(others)
return stat
<|end_body_0|>
<|body_start_1|>
hist = thinkstats2.Hist(lengths)
observed = np.array(hist.Freqs(self.values))
expected = self.expected_probs * len(lengths)
... | Tests difference in pregnancy length using a chi-squared statistic. | PregLengthTest | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PregLengthTest:
"""Tests difference in pregnancy length using a chi-squared statistic."""
def TestStatistic(self, data):
"""Computes the test statistic. data: pair of lists of pregnancy lengths"""
<|body_0|>
def ChiSquared(self, lengths):
"""Computes the chi-squa... | stack_v2_sparse_classes_75kplus_train_074503 | 10,162 | permissive | [
{
"docstring": "Computes the test statistic. data: pair of lists of pregnancy lengths",
"name": "TestStatistic",
"signature": "def TestStatistic(self, data)"
},
{
"docstring": "Computes the chi-squared statistic. lengths: sequence of lengths returns: float",
"name": "ChiSquared",
"signat... | 4 | stack_v2_sparse_classes_30k_train_001007 | Implement the Python class `PregLengthTest` described below.
Class description:
Tests difference in pregnancy length using a chi-squared statistic.
Method signatures and docstrings:
- def TestStatistic(self, data): Computes the test statistic. data: pair of lists of pregnancy lengths
- def ChiSquared(self, lengths): ... | Implement the Python class `PregLengthTest` described below.
Class description:
Tests difference in pregnancy length using a chi-squared statistic.
Method signatures and docstrings:
- def TestStatistic(self, data): Computes the test statistic. data: pair of lists of pregnancy lengths
- def ChiSquared(self, lengths): ... | 30a85d5137db95e01461ad21519bc1bdf294044b | <|skeleton|>
class PregLengthTest:
"""Tests difference in pregnancy length using a chi-squared statistic."""
def TestStatistic(self, data):
"""Computes the test statistic. data: pair of lists of pregnancy lengths"""
<|body_0|>
def ChiSquared(self, lengths):
"""Computes the chi-squa... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PregLengthTest:
"""Tests difference in pregnancy length using a chi-squared statistic."""
def TestStatistic(self, data):
"""Computes the test statistic. data: pair of lists of pregnancy lengths"""
firsts, others = data
stat = self.ChiSquared(firsts) + self.ChiSquared(others)
... | the_stack_v2_python_sparse | CompStats/hypothesis.py | sunny2309/scipy_conf_notebooks | train | 2 |
51cf65e373f49fdf7b37f5209164cc2983595586 | [
"if type(other) == Conv2DNode:\n if other.C_IN < 16:\n return False\n macnode = SearchNodeByType.get_next(other, MACNode, ['content', 'next'])\nelif type(other) == MACNode:\n unrolled_op: UnrolledOperation = other.get_node('!content').get_node('!content')\n if unrolled_op.times != 16:\n re... | <|body_start_0|>
if type(other) == Conv2DNode:
if other.C_IN < 16:
return False
macnode = SearchNodeByType.get_next(other, MACNode, ['content', 'next'])
elif type(other) == MACNode:
unrolled_op: UnrolledOperation = other.get_node('!content').get_node('... | Node for a quad multiply and accumulate for SSE3 CPUs. | MACNodeInt8SSE3 | [
"LicenseRef-scancode-unknown-license-reference",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MACNodeInt8SSE3:
"""Node for a quad multiply and accumulate for SSE3 CPUs."""
def applicable(cls, other):
"""Determine if this SSE3 with quantization implementation is applicable as replacement for a simple MACNode. The MACNode must be within an UnrolledOperation. The operands res_va... | stack_v2_sparse_classes_75kplus_train_074504 | 7,547 | permissive | [
{
"docstring": "Determine if this SSE3 with quantization implementation is applicable as replacement for a simple MACNode. The MACNode must be within an UnrolledOperation. The operands res_var and var1 must be accessed in a specific way to be replaceable by this implementation. Also datatype must be Int8. You c... | 2 | stack_v2_sparse_classes_30k_train_007180 | Implement the Python class `MACNodeInt8SSE3` described below.
Class description:
Node for a quad multiply and accumulate for SSE3 CPUs.
Method signatures and docstrings:
- def applicable(cls, other): Determine if this SSE3 with quantization implementation is applicable as replacement for a simple MACNode. The MACNode... | Implement the Python class `MACNodeInt8SSE3` described below.
Class description:
Node for a quad multiply and accumulate for SSE3 CPUs.
Method signatures and docstrings:
- def applicable(cls, other): Determine if this SSE3 with quantization implementation is applicable as replacement for a simple MACNode. The MACNode... | 987b0efeb56cd150b3a34b672fd5eba05e6d491f | <|skeleton|>
class MACNodeInt8SSE3:
"""Node for a quad multiply and accumulate for SSE3 CPUs."""
def applicable(cls, other):
"""Determine if this SSE3 with quantization implementation is applicable as replacement for a simple MACNode. The MACNode must be within an UnrolledOperation. The operands res_va... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MACNodeInt8SSE3:
"""Node for a quad multiply and accumulate for SSE3 CPUs."""
def applicable(cls, other):
"""Determine if this SSE3 with quantization implementation is applicable as replacement for a simple MACNode. The MACNode must be within an UnrolledOperation. The operands res_var and var1 mu... | the_stack_v2_python_sparse | nncg/nodes/macnodeint8sse3.py | iml130/nncg | train | 34 |
7975b3573651fb25a80d784b8ab4bfb806b6f4d9 | [
"self.dataset = dataset\nself.model = model\nself.loss_func = loss_func\nself.optimizer = optimizer",
"report = self._initialize_report()\nfor epoch_index in range(num_epochs):\n report['epoch_index'] = epoch_index\n running_loss, running_accuracy = self._train_epoch(batch_size, device)\n report['train_l... | <|body_start_0|>
self.dataset = dataset
self.model = model
self.loss_func = loss_func
self.optimizer = optimizer
<|end_body_0|>
<|body_start_1|>
report = self._initialize_report()
for epoch_index in range(num_epochs):
report['epoch_index'] = epoch_index
... | Trainer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Trainer:
def __init__(self, dataset, model, loss_func, optimizer):
"""Args: dataset (TwitterDataset): the dataset used for training and evaluation model (SentimentClassifierPerception): the model loss_func (torch.nn.CrossEntropyLoss): the loss function that should be used optimizer (torc... | stack_v2_sparse_classes_75kplus_train_074505 | 7,619 | no_license | [
{
"docstring": "Args: dataset (TwitterDataset): the dataset used for training and evaluation model (SentimentClassifierPerception): the model loss_func (torch.nn.CrossEntropyLoss): the loss function that should be used optimizer (torch.optim.Optimizer): the optimizer that should be used to update model weights"... | 6 | stack_v2_sparse_classes_30k_train_051807 | Implement the Python class `Trainer` described below.
Class description:
Implement the Trainer class.
Method signatures and docstrings:
- def __init__(self, dataset, model, loss_func, optimizer): Args: dataset (TwitterDataset): the dataset used for training and evaluation model (SentimentClassifierPerception): the mo... | Implement the Python class `Trainer` described below.
Class description:
Implement the Trainer class.
Method signatures and docstrings:
- def __init__(self, dataset, model, loss_func, optimizer): Args: dataset (TwitterDataset): the dataset used for training and evaluation model (SentimentClassifierPerception): the mo... | 43a453a03060c2adf6bf16302d5138cfa77a30d1 | <|skeleton|>
class Trainer:
def __init__(self, dataset, model, loss_func, optimizer):
"""Args: dataset (TwitterDataset): the dataset used for training and evaluation model (SentimentClassifierPerception): the model loss_func (torch.nn.CrossEntropyLoss): the loss function that should be used optimizer (torc... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Trainer:
def __init__(self, dataset, model, loss_func, optimizer):
"""Args: dataset (TwitterDataset): the dataset used for training and evaluation model (SentimentClassifierPerception): the model loss_func (torch.nn.CrossEntropyLoss): the loss function that should be used optimizer (torch.optim.Optimi... | the_stack_v2_python_sparse | workshops/sentiment2020/Solution/Trainer.py | Petlja/PSIML | train | 17 | |
9dd4762b3b666d2af38d23b7d6e638dc4cff3af4 | [
"branch_type = self.data.get('type', '').lower()\nif branch_type not in BRANCH_TYPES:\n self.error('invalid_branch_type')\nreturn branch_type",
"children = self.data.get('children')\ncleaned_children = []\nif children:\n for child in children:\n parser = get_parser(child)\n if not parser:\n ... | <|body_start_0|>
branch_type = self.data.get('type', '').lower()
if branch_type not in BRANCH_TYPES:
self.error('invalid_branch_type')
return branch_type
<|end_body_0|>
<|body_start_1|>
children = self.data.get('children')
cleaned_children = []
if children:
... | Parser and validator for context branch nodes. | BranchParser | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BranchParser:
"""Parser and validator for context branch nodes."""
def validate_type(self):
"""Validates the branch type."""
<|body_0|>
def validate_children(self):
"""Recurses validation to children in branch. Note this occurs regardless if this node is disabled... | stack_v2_sparse_classes_75kplus_train_074506 | 5,573 | permissive | [
{
"docstring": "Validates the branch type.",
"name": "validate_type",
"signature": "def validate_type(self)"
},
{
"docstring": "Recurses validation to children in branch. Note this occurs regardless if this node is disabled (or if there are warnings), to enable downstream handling.",
"name":... | 2 | stack_v2_sparse_classes_30k_train_028903 | Implement the Python class `BranchParser` described below.
Class description:
Parser and validator for context branch nodes.
Method signatures and docstrings:
- def validate_type(self): Validates the branch type.
- def validate_children(self): Recurses validation to children in branch. Note this occurs regardless if ... | Implement the Python class `BranchParser` described below.
Class description:
Parser and validator for context branch nodes.
Method signatures and docstrings:
- def validate_type(self): Validates the branch type.
- def validate_children(self): Recurses validation to children in branch. Note this occurs regardless if ... | 655c1a766be616cb1357ddff8bc345ab61ae9e8a | <|skeleton|>
class BranchParser:
"""Parser and validator for context branch nodes."""
def validate_type(self):
"""Validates the branch type."""
<|body_0|>
def validate_children(self):
"""Recurses validation to children in branch. Note this occurs regardless if this node is disabled... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class BranchParser:
"""Parser and validator for context branch nodes."""
def validate_type(self):
"""Validates the branch type."""
branch_type = self.data.get('type', '').lower()
if branch_type not in BRANCH_TYPES:
self.error('invalid_branch_type')
return branch_type... | the_stack_v2_python_sparse | avocado/query/parsers/context.py | rysdyk/avocado | train | 0 |
5199aa44888f5d65d8a268514879cdf0b8bc756b | [
"prompts = []\nfor ancestry in Ancestry.objects.all():\n prompts.append((ancestry.id, _(ancestry.name)))\nreturn prompts",
"if self.value():\n documents = []\n for document in Document.objects.all():\n should_add = False\n for ancestry in document.ancestries():\n if str(ancestry.... | <|body_start_0|>
prompts = []
for ancestry in Ancestry.objects.all():
prompts.append((ancestry.id, _(ancestry.name)))
return prompts
<|end_body_0|>
<|body_start_1|>
if self.value():
documents = []
for document in Document.objects.all():
... | DocumentAncestryFilter | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DocumentAncestryFilter:
def lookups(self, request, model_admin):
"""Returns a list of tuples. The first element in each tuple is the coded value for the option that will appear in the URL query. The second element is the human-readable name for the option that will appear in the right si... | stack_v2_sparse_classes_75kplus_train_074507 | 18,088 | no_license | [
{
"docstring": "Returns a list of tuples. The first element in each tuple is the coded value for the option that will appear in the URL query. The second element is the human-readable name for the option that will appear in the right sidebar.",
"name": "lookups",
"signature": "def lookups(self, request,... | 2 | stack_v2_sparse_classes_30k_train_005952 | Implement the Python class `DocumentAncestryFilter` described below.
Class description:
Implement the DocumentAncestryFilter class.
Method signatures and docstrings:
- def lookups(self, request, model_admin): Returns a list of tuples. The first element in each tuple is the coded value for the option that will appear ... | Implement the Python class `DocumentAncestryFilter` described below.
Class description:
Implement the DocumentAncestryFilter class.
Method signatures and docstrings:
- def lookups(self, request, model_admin): Returns a list of tuples. The first element in each tuple is the coded value for the option that will appear ... | 91a2d43edfad0e675bd1000f16424e434b7de2bf | <|skeleton|>
class DocumentAncestryFilter:
def lookups(self, request, model_admin):
"""Returns a list of tuples. The first element in each tuple is the coded value for the option that will appear in the URL query. The second element is the human-readable name for the option that will appear in the right si... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DocumentAncestryFilter:
def lookups(self, request, model_admin):
"""Returns a list of tuples. The first element in each tuple is the coded value for the option that will appear in the URL query. The second element is the human-readable name for the option that will appear in the right sidebar."""
... | the_stack_v2_python_sparse | smartancestry/data/forms.py | mrommel/SmartAncestry | train | 2 | |
a9539eb0cb975083f52680d21e5875e3d3c28129 | [
"request_command = self.parser_invoker.remote_start_bolus_command_bytes(self.sequence_id, self.product_id, 1)\nresponse_command_content = self.connectObj.send_receive_command(request_command)\nreturn response_command_content",
"request_command = self.parser_invoker.remote_start_bolus_command_bytes(self.sequence_i... | <|body_start_0|>
request_command = self.parser_invoker.remote_start_bolus_command_bytes(self.sequence_id, self.product_id, 1)
response_command_content = self.connectObj.send_receive_command(request_command)
return response_command_content
<|end_body_0|>
<|body_start_1|>
request_command ... | This class is used to define all related methods with bolus. | Bolus | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Bolus:
"""This class is used to define all related methods with bolus."""
def start_bolus(self):
"""This method is used to start bolus. :return: None"""
<|body_0|>
def stop_bolus(self):
"""This method is used to stop bolus. :return: None"""
<|body_1|>
... | stack_v2_sparse_classes_75kplus_train_074508 | 1,581 | permissive | [
{
"docstring": "This method is used to start bolus. :return: None",
"name": "start_bolus",
"signature": "def start_bolus(self)"
},
{
"docstring": "This method is used to stop bolus. :return: None",
"name": "stop_bolus",
"signature": "def stop_bolus(self)"
},
{
"docstring": "This ... | 3 | stack_v2_sparse_classes_30k_train_040425 | Implement the Python class `Bolus` described below.
Class description:
This class is used to define all related methods with bolus.
Method signatures and docstrings:
- def start_bolus(self): This method is used to start bolus. :return: None
- def stop_bolus(self): This method is used to stop bolus. :return: None
- de... | Implement the Python class `Bolus` described below.
Class description:
This class is used to define all related methods with bolus.
Method signatures and docstrings:
- def start_bolus(self): This method is used to start bolus. :return: None
- def stop_bolus(self): This method is used to stop bolus. :return: None
- de... | c2a4884a36f4c6c6552fa942143ae5d21c120b41 | <|skeleton|>
class Bolus:
"""This class is used to define all related methods with bolus."""
def start_bolus(self):
"""This method is used to start bolus. :return: None"""
<|body_0|>
def stop_bolus(self):
"""This method is used to stop bolus. :return: None"""
<|body_1|>
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Bolus:
"""This class is used to define all related methods with bolus."""
def start_bolus(self):
"""This method is used to start bolus. :return: None"""
request_command = self.parser_invoker.remote_start_bolus_command_bytes(self.sequence_id, self.product_id, 1)
response_command_co... | the_stack_v2_python_sparse | Keywords/DeliveryView/bolus.py | cassie01/PumpLibrary | train | 0 |
3dbb8bb4ac8d15146bc7c9f998cf82134bf26ac7 | [
"if keyword == 'employee':\n cr_emp = EmployeeLL()\n cr_emp.create_employee(user_input)\nelif keyword == 'airplane':\n cr_air = AirplanesLL()\n cr_air.create_airplane(user_input)\nelif keyword == 'destination':\n cr_dest = Des1tinationLL()\n cr_dest.create_destination(user_input)\nelif keyword == ... | <|body_start_0|>
if keyword == 'employee':
cr_emp = EmployeeLL()
cr_emp.create_employee(user_input)
elif keyword == 'airplane':
cr_air = AirplanesLL()
cr_air.create_airplane(user_input)
elif keyword == 'destination':
cr_dest = Des1tinat... | LL_API_offii | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LL_API_offii:
def create(self, keyword, user_input):
"""Creates new object and saves to Database. keyword: employee,airplane,destination or worktrip user_input: user input for corresponding item"""
<|body_0|>
def get_list(self, keyword):
"""Gets updated list from dat... | stack_v2_sparse_classes_75kplus_train_074509 | 1,367 | no_license | [
{
"docstring": "Creates new object and saves to Database. keyword: employee,airplane,destination or worktrip user_input: user input for corresponding item",
"name": "create",
"signature": "def create(self, keyword, user_input)"
},
{
"docstring": "Gets updated list from database. keyword: employe... | 2 | null | Implement the Python class `LL_API_offii` described below.
Class description:
Implement the LL_API_offii class.
Method signatures and docstrings:
- def create(self, keyword, user_input): Creates new object and saves to Database. keyword: employee,airplane,destination or worktrip user_input: user input for correspondi... | Implement the Python class `LL_API_offii` described below.
Class description:
Implement the LL_API_offii class.
Method signatures and docstrings:
- def create(self, keyword, user_input): Creates new object and saves to Database. keyword: employee,airplane,destination or worktrip user_input: user input for correspondi... | ee2b2e6c1422ebab40e36ed3ed23f6f70ee7adb2 | <|skeleton|>
class LL_API_offii:
def create(self, keyword, user_input):
"""Creates new object and saves to Database. keyword: employee,airplane,destination or worktrip user_input: user input for corresponding item"""
<|body_0|>
def get_list(self, keyword):
"""Gets updated list from dat... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class LL_API_offii:
def create(self, keyword, user_input):
"""Creates new object and saves to Database. keyword: employee,airplane,destination or worktrip user_input: user input for corresponding item"""
if keyword == 'employee':
cr_emp = EmployeeLL()
cr_emp.create_employee(u... | the_stack_v2_python_sparse | random code snippets/LL_API_offi.py | heidars19/3ja-vikna-verkefni | train | 3 | |
0839426f506813a7fdc630978a8e3e687e4a7d08 | [
"if not root:\n return []\nright = self.rightSideView(root.right)\nleft = self.rightSideView(root.left)\nreturn [root.val] + right + left[len(right):]",
"def collect(node, depth):\n if node:\n if depth == len(view):\n view.append(node.val)\n collect(node.right, depth + 1)\n c... | <|body_start_0|>
if not root:
return []
right = self.rightSideView(root.right)
left = self.rightSideView(root.left)
return [root.val] + right + left[len(right):]
<|end_body_0|>
<|body_start_1|>
def collect(node, depth):
if node:
if depth =... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def rightSideView(self, root):
""":type root: TreeNode :rtype: List[int] Recursive, combine right and left Compute the right view of both right and left left subtree, then combine them. For very unbalanced trees, this can be O(n^2), though. beats 79.79%"""
<|body_0|>
... | stack_v2_sparse_classes_75kplus_train_074510 | 1,757 | no_license | [
{
"docstring": ":type root: TreeNode :rtype: List[int] Recursive, combine right and left Compute the right view of both right and left left subtree, then combine them. For very unbalanced trees, this can be O(n^2), though. beats 79.79%",
"name": "rightSideView",
"signature": "def rightSideView(self, roo... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def rightSideView(self, root): :type root: TreeNode :rtype: List[int] Recursive, combine right and left Compute the right view of both right and left left subtree, then combine t... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def rightSideView(self, root): :type root: TreeNode :rtype: List[int] Recursive, combine right and left Compute the right view of both right and left left subtree, then combine t... | 7e0e917c15d3e35f49da3a00ef395bd5ff180d79 | <|skeleton|>
class Solution:
def rightSideView(self, root):
""":type root: TreeNode :rtype: List[int] Recursive, combine right and left Compute the right view of both right and left left subtree, then combine them. For very unbalanced trees, this can be O(n^2), though. beats 79.79%"""
<|body_0|>
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def rightSideView(self, root):
""":type root: TreeNode :rtype: List[int] Recursive, combine right and left Compute the right view of both right and left left subtree, then combine them. For very unbalanced trees, this can be O(n^2), though. beats 79.79%"""
if not root:
re... | the_stack_v2_python_sparse | LeetCode/199_binary_tree_right_side_view.py | yao23/Machine_Learning_Playground | train | 12 | |
5e3061bed3e73b6a588d1770c23e6cea1441ca5a | [
"self.bed_line = {}\nself.strand = {}\nself.score = {}\nself.chr_start_end = {}\n'Read filebed into a bed dict'\nwith open(filebed) as fh:\n for line in fh:\n mylist = line.rstrip('\\n').split('\\t')\n self.chr, self.start, self.end, self.gene, self.this_score, self.this_strand = mylist[0:6]\n ... | <|body_start_0|>
self.bed_line = {}
self.strand = {}
self.score = {}
self.chr_start_end = {}
'Read filebed into a bed dict'
with open(filebed) as fh:
for line in fh:
mylist = line.rstrip('\n').split('\t')
self.chr, self.start, s... | format the following line into bed information of two sides | BedIO | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BedIO:
"""format the following line into bed information of two sides"""
def __init__(self, filebed):
"""Initialize the values"""
<|body_0|>
def rename(self, re_tobesub, re_subto):
"""Change the keys with re.sub(re_tobesub, re_subto)"""
<|body_1|>
<|end_... | stack_v2_sparse_classes_75kplus_train_074511 | 3,622 | no_license | [
{
"docstring": "Initialize the values",
"name": "__init__",
"signature": "def __init__(self, filebed)"
},
{
"docstring": "Change the keys with re.sub(re_tobesub, re_subto)",
"name": "rename",
"signature": "def rename(self, re_tobesub, re_subto)"
}
] | 2 | stack_v2_sparse_classes_30k_train_037125 | Implement the Python class `BedIO` described below.
Class description:
format the following line into bed information of two sides
Method signatures and docstrings:
- def __init__(self, filebed): Initialize the values
- def rename(self, re_tobesub, re_subto): Change the keys with re.sub(re_tobesub, re_subto) | Implement the Python class `BedIO` described below.
Class description:
format the following line into bed information of two sides
Method signatures and docstrings:
- def __init__(self, filebed): Initialize the values
- def rename(self, re_tobesub, re_subto): Change the keys with re.sub(re_tobesub, re_subto)
<|skele... | e31c8f2f65260ceff110d07b530b67e465e41800 | <|skeleton|>
class BedIO:
"""format the following line into bed information of two sides"""
def __init__(self, filebed):
"""Initialize the values"""
<|body_0|>
def rename(self, re_tobesub, re_subto):
"""Change the keys with re.sub(re_tobesub, re_subto)"""
<|body_1|>
<|end_... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class BedIO:
"""format the following line into bed information of two sides"""
def __init__(self, filebed):
"""Initialize the values"""
self.bed_line = {}
self.strand = {}
self.score = {}
self.chr_start_end = {}
'Read filebed into a bed dict'
with open(fi... | the_stack_v2_python_sparse | lh_bin/merge_bed_to_bedpe.py | lhui2010/bundle | train | 6 |
17f63617387c3b441ab93f51252e403d3f32a010 | [
"tk.Frame.__init__(self, parent, relief=const.DAO_FRAME_RELIEF, padx=const.DAO_FRAME_PADX, pady=const.DAO_FRAME_PADY, bd=const.DAO_FRAME_BD)\nself._cio_output = []\nself._lbl_title = tk.Label(self, font=const.DAO_TITLE_FONT, text=const.DAO_TITLE_TEXT, padx=const.DAO_TITLE_PADX, pady=const.DAO_TITLE_PADY)\nself._f_o... | <|body_start_0|>
tk.Frame.__init__(self, parent, relief=const.DAO_FRAME_RELIEF, padx=const.DAO_FRAME_PADX, pady=const.DAO_FRAME_PADY, bd=const.DAO_FRAME_BD)
self._cio_output = []
self._lbl_title = tk.Label(self, font=const.DAO_TITLE_FONT, text=const.DAO_TITLE_TEXT, padx=const.DAO_TITLE_PADX, pad... | DataAugmentationOutputF | [
"CC-BY-3.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DataAugmentationOutputF:
def __init__(self, parent, disabled=False):
""":param parent: Parent. :param disabled: - Default: False; - If True all the widgets will be disabled."""
<|body_0|>
def update_status(self, data_augmentation_options: DataAugmentation):
"""- Upda... | stack_v2_sparse_classes_75kplus_train_074512 | 3,130 | permissive | [
{
"docstring": ":param parent: Parent. :param disabled: - Default: False; - If True all the widgets will be disabled.",
"name": "__init__",
"signature": "def __init__(self, parent, disabled=False)"
},
{
"docstring": "- Updates the option's state. :param data_augmentation_options: DataAugmentatio... | 4 | stack_v2_sparse_classes_30k_train_014534 | Implement the Python class `DataAugmentationOutputF` described below.
Class description:
Implement the DataAugmentationOutputF class.
Method signatures and docstrings:
- def __init__(self, parent, disabled=False): :param parent: Parent. :param disabled: - Default: False; - If True all the widgets will be disabled.
- ... | Implement the Python class `DataAugmentationOutputF` described below.
Class description:
Implement the DataAugmentationOutputF class.
Method signatures and docstrings:
- def __init__(self, parent, disabled=False): :param parent: Parent. :param disabled: - Default: False; - If True all the widgets will be disabled.
- ... | 138c7fa83e084ccb8f5c2ad8827f1fbb2527c00c | <|skeleton|>
class DataAugmentationOutputF:
def __init__(self, parent, disabled=False):
""":param parent: Parent. :param disabled: - Default: False; - If True all the widgets will be disabled."""
<|body_0|>
def update_status(self, data_augmentation_options: DataAugmentation):
"""- Upda... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DataAugmentationOutputF:
def __init__(self, parent, disabled=False):
""":param parent: Parent. :param disabled: - Default: False; - If True all the widgets will be disabled."""
tk.Frame.__init__(self, parent, relief=const.DAO_FRAME_RELIEF, padx=const.DAO_FRAME_PADX, pady=const.DAO_FRAME_PADY, ... | the_stack_v2_python_sparse | graphics/output/data_augmentation_output_f.py | iliesidaniel/image-classification | train | 0 | |
5d6a72eab05b847c842b48fc198b0ee85e3fac72 | [
"local_domains = load_data('cloud')['domains']\nremote_domains = self.do.get_domains()\nremote_domain_names = [d.name for d in remote_domains]\nmissing_domains = [d for d in local_domains if d['fqdn'] not in remote_domain_names]\nfor domain in missing_domains:\n ui = self.ui.group(domain['fqdn'])\n droplet = ... | <|body_start_0|>
local_domains = load_data('cloud')['domains']
remote_domains = self.do.get_domains()
remote_domain_names = [d.name for d in remote_domains]
missing_domains = [d for d in local_domains if d['fqdn'] not in remote_domain_names]
for domain in missing_domains:
... | A collection of actions for network domains. | Domains | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Domains:
"""A collection of actions for network domains."""
def create(self):
"""Create domains on Digital Ocean from the manifest."""
<|body_0|>
def sync(self):
"""Ensure that the Digital Ocean domains match the manifest."""
<|body_1|>
def prune(sel... | stack_v2_sparse_classes_75kplus_train_074513 | 3,691 | no_license | [
{
"docstring": "Create domains on Digital Ocean from the manifest.",
"name": "create",
"signature": "def create(self)"
},
{
"docstring": "Ensure that the Digital Ocean domains match the manifest.",
"name": "sync",
"signature": "def sync(self)"
},
{
"docstring": "Remove unused rem... | 3 | stack_v2_sparse_classes_30k_val_001585 | Implement the Python class `Domains` described below.
Class description:
A collection of actions for network domains.
Method signatures and docstrings:
- def create(self): Create domains on Digital Ocean from the manifest.
- def sync(self): Ensure that the Digital Ocean domains match the manifest.
- def prune(self): ... | Implement the Python class `Domains` described below.
Class description:
A collection of actions for network domains.
Method signatures and docstrings:
- def create(self): Create domains on Digital Ocean from the manifest.
- def sync(self): Ensure that the Digital Ocean domains match the manifest.
- def prune(self): ... | ca6c408cbc552b21ee0761eb6f34b7e8c2656153 | <|skeleton|>
class Domains:
"""A collection of actions for network domains."""
def create(self):
"""Create domains on Digital Ocean from the manifest."""
<|body_0|>
def sync(self):
"""Ensure that the Digital Ocean domains match the manifest."""
<|body_1|>
def prune(sel... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Domains:
"""A collection of actions for network domains."""
def create(self):
"""Create domains on Digital Ocean from the manifest."""
local_domains = load_data('cloud')['domains']
remote_domains = self.do.get_domains()
remote_domain_names = [d.name for d in remote_domains... | the_stack_v2_python_sparse | infrastructure/fibula/actions/domains.py | justinlocsei/fibula | train | 0 |
13d294af1f0a0e6e4e844d42da07707dd37904d2 | [
"self.big_list = list()\nfor pos in range(PRIME):\n self.big_list.append(list())",
"pos = key % PRIME\nfound = False\nfor pair in self.big_list[pos]:\n if pair[0] == key:\n found = True\n pair[1] = value\nif not found:\n self.big_list[pos].append([key, value])",
"pos = key % PRIME\nfor pa... | <|body_start_0|>
self.big_list = list()
for pos in range(PRIME):
self.big_list.append(list())
<|end_body_0|>
<|body_start_1|>
pos = key % PRIME
found = False
for pair in self.big_list[pos]:
if pair[0] == key:
found = True
p... | MyHashMap | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MyHashMap:
def __init__(self):
"""Initialize your data structure here."""
<|body_0|>
def put(self, key, value):
"""value will always be non-negative. :type key: int :type value: int :rtype: void"""
<|body_1|>
def get(self, key):
"""Returns the va... | stack_v2_sparse_classes_75kplus_train_074514 | 1,553 | no_license | [
{
"docstring": "Initialize your data structure here.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "value will always be non-negative. :type key: int :type value: int :rtype: void",
"name": "put",
"signature": "def put(self, key, value)"
},
{
"docstrin... | 4 | stack_v2_sparse_classes_30k_train_045242 | Implement the Python class `MyHashMap` described below.
Class description:
Implement the MyHashMap class.
Method signatures and docstrings:
- def __init__(self): Initialize your data structure here.
- def put(self, key, value): value will always be non-negative. :type key: int :type value: int :rtype: void
- def get(... | Implement the Python class `MyHashMap` described below.
Class description:
Implement the MyHashMap class.
Method signatures and docstrings:
- def __init__(self): Initialize your data structure here.
- def put(self, key, value): value will always be non-negative. :type key: int :type value: int :rtype: void
- def get(... | 8f88cae7cc982ab8495e185914b1baeceb294060 | <|skeleton|>
class MyHashMap:
def __init__(self):
"""Initialize your data structure here."""
<|body_0|>
def put(self, key, value):
"""value will always be non-negative. :type key: int :type value: int :rtype: void"""
<|body_1|>
def get(self, key):
"""Returns the va... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MyHashMap:
def __init__(self):
"""Initialize your data structure here."""
self.big_list = list()
for pos in range(PRIME):
self.big_list.append(list())
def put(self, key, value):
"""value will always be non-negative. :type key: int :type value: int :rtype: void"... | the_stack_v2_python_sparse | 706. Design HashMap/solution.py | huangruihaocst/leetcode-python | train | 0 | |
71a6f0f730df2831c9dcda704e5ec44c73fd59f1 | [
"super(ResConfigSettings, self).set_values()\nself.env['ir.config_parameter'].sudo().set_param('recruitment.li_username', self.li_username)\nself.env['ir.config_parameter'].sudo().set_param('recruitment.li_password', self.li_password)",
"res = super(ResConfigSettings, self).get_values()\nres.update(li_username=se... | <|body_start_0|>
super(ResConfigSettings, self).set_values()
self.env['ir.config_parameter'].sudo().set_param('recruitment.li_username', self.li_username)
self.env['ir.config_parameter'].sudo().set_param('recruitment.li_password', self.li_password)
<|end_body_0|>
<|body_start_1|>
res = ... | config settings | ResConfigSettings | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ResConfigSettings:
"""config settings"""
def set_values(self):
"""super the config to set the value"""
<|body_0|>
def get_values(self):
"""super the config to get the value"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
super(ResConfigSettings,... | stack_v2_sparse_classes_75kplus_train_074515 | 1,944 | no_license | [
{
"docstring": "super the config to set the value",
"name": "set_values",
"signature": "def set_values(self)"
},
{
"docstring": "super the config to get the value",
"name": "get_values",
"signature": "def get_values(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_014918 | Implement the Python class `ResConfigSettings` described below.
Class description:
config settings
Method signatures and docstrings:
- def set_values(self): super the config to set the value
- def get_values(self): super the config to get the value | Implement the Python class `ResConfigSettings` described below.
Class description:
config settings
Method signatures and docstrings:
- def set_values(self): super the config to set the value
- def get_values(self): super the config to get the value
<|skeleton|>
class ResConfigSettings:
"""config settings"""
... | 4b1bcb8f17aad44fe9c80a8180eb0128e6bb2c14 | <|skeleton|>
class ResConfigSettings:
"""config settings"""
def set_values(self):
"""super the config to set the value"""
<|body_0|>
def get_values(self):
"""super the config to get the value"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ResConfigSettings:
"""config settings"""
def set_values(self):
"""super the config to set the value"""
super(ResConfigSettings, self).set_values()
self.env['ir.config_parameter'].sudo().set_param('recruitment.li_username', self.li_username)
self.env['ir.config_parameter'].... | the_stack_v2_python_sparse | hr_linkedin_recruitment/models/recruitment_config.py | CybroOdoo/CybroAddons | train | 209 |
af9a0485da0352e489101eb0b9a9487f30618c6d | [
"self.kMeans = KMeans(n_clusters=k, init='k-means++').fit(self.affinity)\nself.nClusters = k\nself.clusterLabels = self.kMeans.labels_\nself.confusionMatrix = confusion_matrix(self.trueLabels, self.clusterLabels)\nreturn self.kMeans",
"try:\n trueLabels, clusterLabels = (self.trueLabels, self.clusterLabels)\ne... | <|body_start_0|>
self.kMeans = KMeans(n_clusters=k, init='k-means++').fit(self.affinity)
self.nClusters = k
self.clusterLabels = self.kMeans.labels_
self.confusionMatrix = confusion_matrix(self.trueLabels, self.clusterLabels)
return self.kMeans
<|end_body_0|>
<|body_start_1|>
... | Interface to k-means clustering. | KMeansAnalysis | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class KMeansAnalysis:
"""Interface to k-means clustering."""
def cluster(self, k):
"""Cluster the data using the k-means method. @return: An C{sklearn.cluster.KMeans} instance."""
<|body_0|>
def print_(self, margin='', result=None):
"""Print details of the clustering. ... | stack_v2_sparse_classes_75kplus_train_074516 | 9,448 | no_license | [
{
"docstring": "Cluster the data using the k-means method. @return: An C{sklearn.cluster.KMeans} instance.",
"name": "cluster",
"signature": "def cluster(self, k)"
},
{
"docstring": "Print details of the clustering. @param margin: A C{str} that should be inserted at the start of each line of out... | 2 | null | Implement the Python class `KMeansAnalysis` described below.
Class description:
Interface to k-means clustering.
Method signatures and docstrings:
- def cluster(self, k): Cluster the data using the k-means method. @return: An C{sklearn.cluster.KMeans} instance.
- def print_(self, margin='', result=None): Print detail... | Implement the Python class `KMeansAnalysis` described below.
Class description:
Interface to k-means clustering.
Method signatures and docstrings:
- def cluster(self, k): Cluster the data using the k-means method. @return: An C{sklearn.cluster.KMeans} instance.
- def print_(self, margin='', result=None): Print detail... | 3e848dfa66f5fd07f1fb709abc935baff9f43d87 | <|skeleton|>
class KMeansAnalysis:
"""Interface to k-means clustering."""
def cluster(self, k):
"""Cluster the data using the k-means method. @return: An C{sklearn.cluster.KMeans} instance."""
<|body_0|>
def print_(self, margin='', result=None):
"""Print details of the clustering. ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class KMeansAnalysis:
"""Interface to k-means clustering."""
def cluster(self, k):
"""Cluster the data using the k-means method. @return: An C{sklearn.cluster.KMeans} instance."""
self.kMeans = KMeans(n_clusters=k, init='k-means++').fit(self.affinity)
self.nClusters = k
self.clu... | the_stack_v2_python_sparse | light/performance/cluster.py | acorg/light-matter | train | 0 |
7fa56bbc0d870d32bf47bd7f6c884a9273d26b8a | [
"super(LimitConsumer, self).__init__(columns=columns, consumer=consumer)\nself.limit = limit\nself.count = 0",
"if self.count < self.limit:\n self.count += 1\n return row\nelse:\n raise StopIteration()"
] | <|body_start_0|>
super(LimitConsumer, self).__init__(columns=columns, consumer=consumer)
self.limit = limit
self.count = 0
<|end_body_0|>
<|body_start_1|>
if self.count < self.limit:
self.count += 1
return row
else:
raise StopIteration()
<|end... | Consumer that limits the number of rows that are passed on to a downstream consumer. Raises a StopIteration error when the maximum number of rows is reached. | LimitConsumer | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LimitConsumer:
"""Consumer that limits the number of rows that are passed on to a downstream consumer. Raises a StopIteration error when the maximum number of rows is reached."""
def __init__(self, columns: DatasetSchema, limit: int, consumer: Optional[StreamConsumer]=None):
"""Initi... | stack_v2_sparse_classes_75kplus_train_074517 | 4,564 | permissive | [
{
"docstring": "Initialize the row limit and the downstream consumer. Parameters ---------- columns: list of string Names of columns for the rows that the consumer will receive. limit: int Maximum number of rows that are passed on to the downstream consumer. consumer: openclean.data.stream.base.StreamConsumer, ... | 2 | stack_v2_sparse_classes_30k_train_028255 | Implement the Python class `LimitConsumer` described below.
Class description:
Consumer that limits the number of rows that are passed on to a downstream consumer. Raises a StopIteration error when the maximum number of rows is reached.
Method signatures and docstrings:
- def __init__(self, columns: DatasetSchema, li... | Implement the Python class `LimitConsumer` described below.
Class description:
Consumer that limits the number of rows that are passed on to a downstream consumer. Raises a StopIteration error when the maximum number of rows is reached.
Method signatures and docstrings:
- def __init__(self, columns: DatasetSchema, li... | e3d0e04f90468c49f29ca53edc2feb12465c24d5 | <|skeleton|>
class LimitConsumer:
"""Consumer that limits the number of rows that are passed on to a downstream consumer. Raises a StopIteration error when the maximum number of rows is reached."""
def __init__(self, columns: DatasetSchema, limit: int, consumer: Optional[StreamConsumer]=None):
"""Initi... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class LimitConsumer:
"""Consumer that limits the number of rows that are passed on to a downstream consumer. Raises a StopIteration error when the maximum number of rows is reached."""
def __init__(self, columns: DatasetSchema, limit: int, consumer: Optional[StreamConsumer]=None):
"""Initialize the row... | the_stack_v2_python_sparse | openclean/operator/transform/limit.py | Denisfench/openclean-core | train | 0 |
cd6a17c59a192b74c35039e7d709358552edee49 | [
"num_schools_elementary_laval_xpath = '//*[@id=\"MainContent\"]/div[1]/p[2]/a/@href'\nnum_schools_secondary_laval_xpath = '//*[@id=\"MainContent\"]/div[1]/p[4]/a/@href'\nnum_schools_elementary_lanaudiere1_xpath = '//*[@id=\"MainContent\"]/div[1]/p[8]/a/@href'\nnum_schools_secondary_lanaudiere1_xpath = '//*[@id=\"Ma... | <|body_start_0|>
num_schools_elementary_laval_xpath = '//*[@id="MainContent"]/div[1]/p[2]/a/@href'
num_schools_secondary_laval_xpath = '//*[@id="MainContent"]/div[1]/p[4]/a/@href'
num_schools_elementary_lanaudiere1_xpath = '//*[@id="MainContent"]/div[1]/p[8]/a/@href'
num_schools_secondar... | a scrapy spider to crawl swlauriersb.qc.ca domain to get school_name street_address city province postal_code phone_number school_url school_grades school_language school_type school_board response_url for each school found | MontrealSwlauriersbSpider | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MontrealSwlauriersbSpider:
"""a scrapy spider to crawl swlauriersb.qc.ca domain to get school_name street_address city province postal_code phone_number school_url school_grades school_language school_type school_board response_url for each school found"""
def parse(self, response):
... | stack_v2_sparse_classes_75kplus_train_074518 | 6,134 | no_license | [
{
"docstring": "parse the start urls to get a list of schools urls for all schools types and cities",
"name": "parse",
"signature": "def parse(self, response)"
},
{
"docstring": "get required information for each school this method is called once for each school page",
"name": "parse_school_... | 3 | stack_v2_sparse_classes_30k_train_035804 | Implement the Python class `MontrealSwlauriersbSpider` described below.
Class description:
a scrapy spider to crawl swlauriersb.qc.ca domain to get school_name street_address city province postal_code phone_number school_url school_grades school_language school_type school_board response_url for each school found
Met... | Implement the Python class `MontrealSwlauriersbSpider` described below.
Class description:
a scrapy spider to crawl swlauriersb.qc.ca domain to get school_name street_address city province postal_code phone_number school_url school_grades school_language school_type school_board response_url for each school found
Met... | 350264cf6da323692c2838d8cb235ef61085851b | <|skeleton|>
class MontrealSwlauriersbSpider:
"""a scrapy spider to crawl swlauriersb.qc.ca domain to get school_name street_address city province postal_code phone_number school_url school_grades school_language school_type school_board response_url for each school found"""
def parse(self, response):
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MontrealSwlauriersbSpider:
"""a scrapy spider to crawl swlauriersb.qc.ca domain to get school_name street_address city province postal_code phone_number school_url school_grades school_language school_type school_board response_url for each school found"""
def parse(self, response):
"""parse the ... | the_stack_v2_python_sparse | school_scraping/spiders/montreal_swlauriersb.py | ramadanmostafa/canada_school_scraping | train | 0 |
eba94bc2d5c5c8474948afec4ef725809f540735 | [
"self.row = 0\nself.col = -1\nself.matrix = vec2d",
"if self.hasNext():\n self.col += 1\n return self.matrix[self.row][self.col]\nelse:\n return None",
"if self.row >= len(self.matrix):\n return False\nif self.col >= len(self.matrix[self.row]) - 1:\n self.row += 1\n while self.row < len(self.m... | <|body_start_0|>
self.row = 0
self.col = -1
self.matrix = vec2d
<|end_body_0|>
<|body_start_1|>
if self.hasNext():
self.col += 1
return self.matrix[self.row][self.col]
else:
return None
<|end_body_1|>
<|body_start_2|>
if self.row >= l... | Vector2D | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Vector2D:
def __init__(self, vec2d):
"""Initialize your data structure here. :type vec2d: List[List[int]]"""
<|body_0|>
def next(self):
""":rtype: int"""
<|body_1|>
def hasNext(self):
""":rtype: bool"""
<|body_2|>
<|end_skeleton|>
<|bod... | stack_v2_sparse_classes_75kplus_train_074519 | 795 | no_license | [
{
"docstring": "Initialize your data structure here. :type vec2d: List[List[int]]",
"name": "__init__",
"signature": "def __init__(self, vec2d)"
},
{
"docstring": ":rtype: int",
"name": "next",
"signature": "def next(self)"
},
{
"docstring": ":rtype: bool",
"name": "hasNext",... | 3 | stack_v2_sparse_classes_30k_train_054287 | Implement the Python class `Vector2D` described below.
Class description:
Implement the Vector2D class.
Method signatures and docstrings:
- def __init__(self, vec2d): Initialize your data structure here. :type vec2d: List[List[int]]
- def next(self): :rtype: int
- def hasNext(self): :rtype: bool | Implement the Python class `Vector2D` described below.
Class description:
Implement the Vector2D class.
Method signatures and docstrings:
- def __init__(self, vec2d): Initialize your data structure here. :type vec2d: List[List[int]]
- def next(self): :rtype: int
- def hasNext(self): :rtype: bool
<|skeleton|>
class V... | 15f012927dc34b5d751af6633caa5e8882d26ff7 | <|skeleton|>
class Vector2D:
def __init__(self, vec2d):
"""Initialize your data structure here. :type vec2d: List[List[int]]"""
<|body_0|>
def next(self):
""":rtype: int"""
<|body_1|>
def hasNext(self):
""":rtype: bool"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Vector2D:
def __init__(self, vec2d):
"""Initialize your data structure here. :type vec2d: List[List[int]]"""
self.row = 0
self.col = -1
self.matrix = vec2d
def next(self):
""":rtype: int"""
if self.hasNext():
self.col += 1
return sel... | the_stack_v2_python_sparse | python/251.Flatten2DVector.py | MaxPoon/Leetcode | train | 15 | |
f40c0828f572115de0f53f279116da123beae028 | [
"content = response.xpath(\"//div[@class='dw_table']//div[@class='el']\")\nfor con in content:\n item = {}\n item['work_name'] = con.xpath('./p/span/a/@title').extract_first()\n href = con.xpath('./p/span/a/@href').extract_first()\n item['company_name'] = con.xpath('./span[@class=\"t2\"]/a/@title').extr... | <|body_start_0|>
content = response.xpath("//div[@class='dw_table']//div[@class='el']")
for con in content:
item = {}
item['work_name'] = con.xpath('./p/span/a/@title').extract_first()
href = con.xpath('./p/span/a/@href').extract_first()
item['company_name... | MySpider | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MySpider:
def parse(self, response):
"""获取一级页面数据"""
<|body_0|>
def parse_work_info(self, response):
"""获取二级页面数据"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
content = response.xpath("//div[@class='dw_table']//div[@class='el']")
for con in... | stack_v2_sparse_classes_75kplus_train_074520 | 2,992 | no_license | [
{
"docstring": "获取一级页面数据",
"name": "parse",
"signature": "def parse(self, response)"
},
{
"docstring": "获取二级页面数据",
"name": "parse_work_info",
"signature": "def parse_work_info(self, response)"
}
] | 2 | null | Implement the Python class `MySpider` described below.
Class description:
Implement the MySpider class.
Method signatures and docstrings:
- def parse(self, response): 获取一级页面数据
- def parse_work_info(self, response): 获取二级页面数据 | Implement the Python class `MySpider` described below.
Class description:
Implement the MySpider class.
Method signatures and docstrings:
- def parse(self, response): 获取一级页面数据
- def parse_work_info(self, response): 获取二级页面数据
<|skeleton|>
class MySpider:
def parse(self, response):
"""获取一级页面数据"""
<... | 2dd9e53dd53c6a53ef1eeab08593524b4119b25e | <|skeleton|>
class MySpider:
def parse(self, response):
"""获取一级页面数据"""
<|body_0|>
def parse_work_info(self, response):
"""获取二级页面数据"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MySpider:
def parse(self, response):
"""获取一级页面数据"""
content = response.xpath("//div[@class='dw_table']//div[@class='el']")
for con in content:
item = {}
item['work_name'] = con.xpath('./p/span/a/@title').extract_first()
href = con.xpath('./p/span/a/@... | the_stack_v2_python_sparse | curriculum_design_qianchengwuyou/wuyouSpider/wuyouSpider/spiders/mySpider.py | Tiancaichao/MyCrawlerProjects | train | 0 | |
a21c4f14ab80b4b232dec752560d1bcbb74f2f55 | [
"if end_word not in word_list:\n return 0\nlength = len(begin_word)\nall_combo_dict = defaultdict(list)\nfor word in word_list:\n \"\\n 对每个单词，以通配符对应该单词的方式记录下来，比如hot单词，\\n 记录方式为{'*ot':['hot'], 'h*t':['hot'], 'ho*':['hot']}\\n 把所有的单词分别都统计出来\\n \"\n for ... | <|body_start_0|>
if end_word not in word_list:
return 0
length = len(begin_word)
all_combo_dict = defaultdict(list)
for word in word_list:
"\n 对每个单词，以通配符对应该单词的方式记录下来，比如hot单词，\n 记录方式为{'*ot':['hot'], 'h*t':['hot'], 'ho*':['hot']}\n ... | 给定两个单词（beginWord 和 endWord）和一个字典，找到从 beginWord 到 endWord 的最短转换序列的长度。 转换需遵循如下规则： 每次转换只能改变一个字母。 转换过程中的中间单词必须是字典中的单词。 说明: 如果不存在这样的转换序列，返回 0。 所有单词具有相同的长度。 所有单词只由小写字母组成。 字典中不存在重复的单词。 你可以假设 beginWord 和 endWord 是非空的，且二者不相同。 示例 1: 输入: beginWord = "hit", endWord = "cog", wordList = ["hot","dot","dog","lot","log","cog"] 输出: 5 解释... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
"""给定两个单词（beginWord 和 endWord）和一个字典，找到从 beginWord 到 endWord 的最短转换序列的长度。 转换需遵循如下规则： 每次转换只能改变一个字母。 转换过程中的中间单词必须是字典中的单词。 说明: 如果不存在这样的转换序列，返回 0。 所有单词具有相同的长度。 所有单词只由小写字母组成。 字典中不存在重复的单词。 你可以假设 beginWord 和 endWord 是非空的，且二者不相同。 示例 1: 输入: beginWord = "hit", endWord = "cog", wordList = ["hot","do... | stack_v2_sparse_classes_75kplus_train_074521 | 4,754 | no_license | [
{
"docstring": ":type begin_word: str :type end_word: str :type word_list: List[str] :rtype: int 从beginword开始，寻找wordlist中与beginword单词相差一个字母的单词，获取到这些单词，然后再往下分别 寻找与之相差一个字母的单词，直到首先找到endword。",
"name": "ladder_length",
"signature": "def ladder_length(self, begin_word, end_word, word_list)"
},
{
"doc... | 2 | null | Implement the Python class `Solution` described below.
Class description:
给定两个单词（beginWord 和 endWord）和一个字典，找到从 beginWord 到 endWord 的最短转换序列的长度。 转换需遵循如下规则： 每次转换只能改变一个字母。 转换过程中的中间单词必须是字典中的单词。 说明: 如果不存在这样的转换序列，返回 0。 所有单词具有相同的长度。 所有单词只由小写字母组成。 字典中不存在重复的单词。 你可以假设 beginWord 和 endWord 是非空的，且二者不相同。 示例 1: 输入: beginWord = "hit",... | Implement the Python class `Solution` described below.
Class description:
给定两个单词（beginWord 和 endWord）和一个字典，找到从 beginWord 到 endWord 的最短转换序列的长度。 转换需遵循如下规则： 每次转换只能改变一个字母。 转换过程中的中间单词必须是字典中的单词。 说明: 如果不存在这样的转换序列，返回 0。 所有单词具有相同的长度。 所有单词只由小写字母组成。 字典中不存在重复的单词。 你可以假设 beginWord 和 endWord 是非空的，且二者不相同。 示例 1: 输入: beginWord = "hit",... | 2c534185854c1a6f5ffdb2698f9db9989f30a25b | <|skeleton|>
class Solution:
"""给定两个单词（beginWord 和 endWord）和一个字典，找到从 beginWord 到 endWord 的最短转换序列的长度。 转换需遵循如下规则： 每次转换只能改变一个字母。 转换过程中的中间单词必须是字典中的单词。 说明: 如果不存在这样的转换序列，返回 0。 所有单词具有相同的长度。 所有单词只由小写字母组成。 字典中不存在重复的单词。 你可以假设 beginWord 和 endWord 是非空的，且二者不相同。 示例 1: 输入: beginWord = "hit", endWord = "cog", wordList = ["hot","do... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
"""给定两个单词（beginWord 和 endWord）和一个字典，找到从 beginWord 到 endWord 的最短转换序列的长度。 转换需遵循如下规则： 每次转换只能改变一个字母。 转换过程中的中间单词必须是字典中的单词。 说明: 如果不存在这样的转换序列，返回 0。 所有单词具有相同的长度。 所有单词只由小写字母组成。 字典中不存在重复的单词。 你可以假设 beginWord 和 endWord 是非空的，且二者不相同。 示例 1: 输入: beginWord = "hit", endWord = "cog", wordList = ["hot","dot","dog","lot... | the_stack_v2_python_sparse | Week 06/id_668/leetcode_127_668.py | Carryours/algorithm004-03 | train | 2 |
324fda191b914005214da2150294efd4984e6b74 | [
"self._window = window\nself.name = name\nself.view = view",
"try:\n meth = getattr(self._window.scene, self.view)\n meth()\nexcept AttributeError:\n pass"
] | <|body_start_0|>
self._window = window
self.name = name
self.view = view
<|end_body_0|>
<|body_start_1|>
try:
meth = getattr(self._window.scene, self.view)
meth()
except AttributeError:
pass
<|end_body_1|>
| Sets the scene to a particular view. | SpecialViewAction | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SpecialViewAction:
"""Sets the scene to a particular view."""
def __init__(self, window, name, view):
"""Creates a new action."""
<|body_0|>
def perform(self):
"""Performs the action."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self._window ... | stack_v2_sparse_classes_75kplus_train_074522 | 17,920 | no_license | [
{
"docstring": "Creates a new action.",
"name": "__init__",
"signature": "def __init__(self, window, name, view)"
},
{
"docstring": "Performs the action.",
"name": "perform",
"signature": "def perform(self)"
}
] | 2 | stack_v2_sparse_classes_30k_val_000812 | Implement the Python class `SpecialViewAction` described below.
Class description:
Sets the scene to a particular view.
Method signatures and docstrings:
- def __init__(self, window, name, view): Creates a new action.
- def perform(self): Performs the action. | Implement the Python class `SpecialViewAction` described below.
Class description:
Sets the scene to a particular view.
Method signatures and docstrings:
- def __init__(self, window, name, view): Creates a new action.
- def perform(self): Performs the action.
<|skeleton|>
class SpecialViewAction:
"""Sets the sce... | 5466f5858dbd2f1f082fa0d7417b57c8fb068fad | <|skeleton|>
class SpecialViewAction:
"""Sets the scene to a particular view."""
def __init__(self, window, name, view):
"""Creates a new action."""
<|body_0|>
def perform(self):
"""Performs the action."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SpecialViewAction:
"""Sets the scene to a particular view."""
def __init__(self, window, name, view):
"""Creates a new action."""
self._window = window
self.name = name
self.view = view
def perform(self):
"""Performs the action."""
try:
met... | the_stack_v2_python_sparse | maps/build/mayavi/enthought/tvtk/tools/ivtk.py | m-elhussieny/code | train | 0 |
a1a9ba52b07d22412429f349408fae2f564274e2 | [
"if not filename:\n raise ValueError(f'{filename} is not a valid file')\nwith open(filename, encoding='utf8') as fname:\n try:\n self.profile = yaml.safe_load(fname)\n except yaml.YAMLError as ex:\n raise ValueError('f{filename} is not a valid YAML file: {ex}') from ex\n if self.profile is... | <|body_start_0|>
if not filename:
raise ValueError(f'{filename} is not a valid file')
with open(filename, encoding='utf8') as fname:
try:
self.profile = yaml.safe_load(fname)
except yaml.YAMLError as ex:
raise ValueError('f{filename} is... | Manages which scan levels are run for packages. | Profile | [
"CC0-1.0",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Profile:
"""Manages which scan levels are run for packages."""
def __init__(self, filename: str) -> None:
"""Initialize profile."""
<|body_0|>
def get_package_level(self, package: Package) -> Union[str, Any]:
"""Get which scan level to use for a given package."""... | stack_v2_sparse_classes_75kplus_train_074523 | 1,305 | permissive | [
{
"docstring": "Initialize profile.",
"name": "__init__",
"signature": "def __init__(self, filename: str) -> None"
},
{
"docstring": "Get which scan level to use for a given package.",
"name": "get_package_level",
"signature": "def get_package_level(self, package: Package) -> Union[str, ... | 2 | stack_v2_sparse_classes_30k_test_000273 | Implement the Python class `Profile` described below.
Class description:
Manages which scan levels are run for packages.
Method signatures and docstrings:
- def __init__(self, filename: str) -> None: Initialize profile.
- def get_package_level(self, package: Package) -> Union[str, Any]: Get which scan level to use fo... | Implement the Python class `Profile` described below.
Class description:
Manages which scan levels are run for packages.
Method signatures and docstrings:
- def __init__(self, filename: str) -> None: Initialize profile.
- def get_package_level(self, package: Package) -> Union[str, Any]: Get which scan level to use fo... | 25225188b04dbdebb04674d0b3c8af886ccf87c3 | <|skeleton|>
class Profile:
"""Manages which scan levels are run for packages."""
def __init__(self, filename: str) -> None:
"""Initialize profile."""
<|body_0|>
def get_package_level(self, package: Package) -> Union[str, Any]:
"""Get which scan level to use for a given package."""... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Profile:
"""Manages which scan levels are run for packages."""
def __init__(self, filename: str) -> None:
"""Initialize profile."""
if not filename:
raise ValueError(f'{filename} is not a valid file')
with open(filename, encoding='utf8') as fname:
try:
... | the_stack_v2_python_sparse | statick_tool/profile.py | sscpac/statick | train | 73 |
dc31babbf9be1b75cc8b3de77a77242c0080223d | [
"self.keys = keys or []\nself.obj = copy.copy(obj)\nself.hook = can(hook)\nfor key in keys:\n setattr(self.obj, key, can(getattr(obj, key)))\nself.buffers = []",
"if g is None:\n g = {}\nobj = self.obj\nfor key in self.keys:\n setattr(obj, key, uncan(getattr(obj, key), g))\nif self.hook:\n self.hook =... | <|body_start_0|>
self.keys = keys or []
self.obj = copy.copy(obj)
self.hook = can(hook)
for key in keys:
setattr(self.obj, key, can(getattr(obj, key)))
self.buffers = []
<|end_body_0|>
<|body_start_1|>
if g is None:
g = {}
obj = self.obj
... | A canned object. | CannedObject | [
"BSD-3-Clause",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CannedObject:
"""A canned object."""
def __init__(self, obj, keys=None, hook=None):
"""can an object for safe pickling Parameters ---------- obj The object to be canned keys : list (optional) list of attribute names that will be explicitly canned / uncanned hook : callable (optional)... | stack_v2_sparse_classes_75kplus_train_074524 | 13,378 | permissive | [
{
"docstring": "can an object for safe pickling Parameters ---------- obj The object to be canned keys : list (optional) list of attribute names that will be explicitly canned / uncanned hook : callable (optional) An optional extra callable, which can do additional processing of the uncanned object. Notes -----... | 2 | stack_v2_sparse_classes_30k_train_035665 | Implement the Python class `CannedObject` described below.
Class description:
A canned object.
Method signatures and docstrings:
- def __init__(self, obj, keys=None, hook=None): can an object for safe pickling Parameters ---------- obj The object to be canned keys : list (optional) list of attribute names that will b... | Implement the Python class `CannedObject` described below.
Class description:
A canned object.
Method signatures and docstrings:
- def __init__(self, obj, keys=None, hook=None): can an object for safe pickling Parameters ---------- obj The object to be canned keys : list (optional) list of attribute names that will b... | f5042e35b945aded77b23470ead62d7eacefde92 | <|skeleton|>
class CannedObject:
"""A canned object."""
def __init__(self, obj, keys=None, hook=None):
"""can an object for safe pickling Parameters ---------- obj The object to be canned keys : list (optional) list of attribute names that will be explicitly canned / uncanned hook : callable (optional)... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CannedObject:
"""A canned object."""
def __init__(self, obj, keys=None, hook=None):
"""can an object for safe pickling Parameters ---------- obj The object to be canned keys : list (optional) list of attribute names that will be explicitly canned / uncanned hook : callable (optional) An optional ... | the_stack_v2_python_sparse | contrib/python/ipykernel/py3/ipykernel/pickleutil.py | catboost/catboost | train | 8,012 |
c6b0e1e1489fd9a86b00426967ba18a37300a96b | [
"tweet = line.split(',')[1].lower()\ntweet = re.sub('[^a-z 0-9]', '', tweet)\nwords = tweet.split()\nfor word in words:\n yield (word, 1)",
"total = sum(values)\nif total > 10000:\n yield (key, total)"
] | <|body_start_0|>
tweet = line.split(',')[1].lower()
tweet = re.sub('[^a-z 0-9]', '', tweet)
words = tweet.split()
for word in words:
yield (word, 1)
<|end_body_0|>
<|body_start_1|>
total = sum(values)
if total > 10000:
yield (key, total)
<|end_bod... | MRWordFrequencyCount | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MRWordFrequencyCount:
def mapper(self, _, line):
"""Parse tweets from input, remove non-alphanumeric characters and return key,value pair for each word"""
<|body_0|>
def reducer(self, key, values):
"""Aggregate total instances of words, and only return those that app... | stack_v2_sparse_classes_75kplus_train_074525 | 1,406 | no_license | [
{
"docstring": "Parse tweets from input, remove non-alphanumeric characters and return key,value pair for each word",
"name": "mapper",
"signature": "def mapper(self, _, line)"
},
{
"docstring": "Aggregate total instances of words, and only return those that appear more than 10,000 times",
"... | 2 | stack_v2_sparse_classes_30k_train_010693 | Implement the Python class `MRWordFrequencyCount` described below.
Class description:
Implement the MRWordFrequencyCount class.
Method signatures and docstrings:
- def mapper(self, _, line): Parse tweets from input, remove non-alphanumeric characters and return key,value pair for each word
- def reducer(self, key, va... | Implement the Python class `MRWordFrequencyCount` described below.
Class description:
Implement the MRWordFrequencyCount class.
Method signatures and docstrings:
- def mapper(self, _, line): Parse tweets from input, remove non-alphanumeric characters and return key,value pair for each word
- def reducer(self, key, va... | a0706171ec7d502eb85397862b1daf9912ac15a5 | <|skeleton|>
class MRWordFrequencyCount:
def mapper(self, _, line):
"""Parse tweets from input, remove non-alphanumeric characters and return key,value pair for each word"""
<|body_0|>
def reducer(self, key, values):
"""Aggregate total instances of words, and only return those that app... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MRWordFrequencyCount:
def mapper(self, _, line):
"""Parse tweets from input, remove non-alphanumeric characters and return key,value pair for each word"""
tweet = line.split(',')[1].lower()
tweet = re.sub('[^a-z 0-9]', '', tweet)
words = tweet.split()
for word in words:... | the_stack_v2_python_sparse | word_count.py | nickhamlin/MIDS-W205_A4 | train | 0 | |
7fd83ee6c3e489d73a224e09e00cd92c0be79640 | [
"article = get_object_or_404(Articles, slug=article_slug)\ncomments = get_object_or_404(Comments, id=id, article=article)\ncomment = Comments.objects.get(id=id)\nif comment.user != request.user:\n data = {'error': 'You are not allowed to edit this comment'}\n return Response(data, status=status.HTTP_403_FORB... | <|body_start_0|>
article = get_object_or_404(Articles, slug=article_slug)
comments = get_object_or_404(Comments, id=id, article=article)
comment = Comments.objects.get(id=id)
if comment.user != request.user:
data = {'error': 'You are not allowed to edit this comment'}
... | Handles all requests for updating and deleting requests | UpdateDeleteCommentView | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UpdateDeleteCommentView:
"""Handles all requests for updating and deleting requests"""
def put(self, request, article_slug, id):
"""Handles all requests by user to update their comments"""
<|body_0|>
def delete(self, request, article_slug, id):
"""handles all req... | stack_v2_sparse_classes_75kplus_train_074526 | 8,741 | permissive | [
{
"docstring": "Handles all requests by user to update their comments",
"name": "put",
"signature": "def put(self, request, article_slug, id)"
},
{
"docstring": "handles all requests for uses to delete their comments",
"name": "delete",
"signature": "def delete(self, request, article_slu... | 2 | stack_v2_sparse_classes_30k_train_006522 | Implement the Python class `UpdateDeleteCommentView` described below.
Class description:
Handles all requests for updating and deleting requests
Method signatures and docstrings:
- def put(self, request, article_slug, id): Handles all requests by user to update their comments
- def delete(self, request, article_slug,... | Implement the Python class `UpdateDeleteCommentView` described below.
Class description:
Handles all requests for updating and deleting requests
Method signatures and docstrings:
- def put(self, request, article_slug, id): Handles all requests by user to update their comments
- def delete(self, request, article_slug,... | ff4f1ba34d074e68e49f7896848f81b729542e1f | <|skeleton|>
class UpdateDeleteCommentView:
"""Handles all requests for updating and deleting requests"""
def put(self, request, article_slug, id):
"""Handles all requests by user to update their comments"""
<|body_0|>
def delete(self, request, article_slug, id):
"""handles all req... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class UpdateDeleteCommentView:
"""Handles all requests for updating and deleting requests"""
def put(self, request, article_slug, id):
"""Handles all requests by user to update their comments"""
article = get_object_or_404(Articles, slug=article_slug)
comments = get_object_or_404(Commen... | the_stack_v2_python_sparse | authors/apps/comments/views.py | rfpremier/ah-django | train | 0 |
2abaee166f1a4df5b395d72c015ba69770a13432 | [
"self.flow_hash = flow_hash\nself.classified = 0\nself.classification_tag = ''\nself.classification_time = 0\nself.actions = {}\nself.clsfn = clsfn\nself.time_limit = time_limit\nself.logger = logger\ndb_data = {'flow_hash': self.flow_hash}\ndb_data['classification_time'] = {'$gte': datetime.datetime.now() - self.t... | <|body_start_0|>
self.flow_hash = flow_hash
self.classified = 0
self.classification_tag = ''
self.classification_time = 0
self.actions = {}
self.clsfn = clsfn
self.time_limit = time_limit
self.logger = logger
db_data = {'flow_hash': self.flow_hash}... | An object that represents an individual traffic classification | Classification | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Classification:
"""An object that represents an individual traffic classification"""
def __init__(self, flow_hash, clsfn, time_limit, logger):
"""Retrieve classification data from MongoDB collection for a particular flow hash within a time range. time range is from current time backw... | stack_v2_sparse_classes_75kplus_train_074527 | 44,404 | permissive | [
{
"docstring": "Retrieve classification data from MongoDB collection for a particular flow hash within a time range. time range is from current time backwards by number of seconds defined in config for classification_time_limit Setting test returns database query execution statistics",
"name": "__init__",
... | 4 | stack_v2_sparse_classes_30k_train_020632 | Implement the Python class `Classification` described below.
Class description:
An object that represents an individual traffic classification
Method signatures and docstrings:
- def __init__(self, flow_hash, clsfn, time_limit, logger): Retrieve classification data from MongoDB collection for a particular flow hash w... | Implement the Python class `Classification` described below.
Class description:
An object that represents an individual traffic classification
Method signatures and docstrings:
- def __init__(self, flow_hash, clsfn, time_limit, logger): Retrieve classification data from MongoDB collection for a particular flow hash w... | 55cc27e81defc42775ff563bfbef31800e089b14 | <|skeleton|>
class Classification:
"""An object that represents an individual traffic classification"""
def __init__(self, flow_hash, clsfn, time_limit, logger):
"""Retrieve classification data from MongoDB collection for a particular flow hash within a time range. time range is from current time backw... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Classification:
"""An object that represents an individual traffic classification"""
def __init__(self, flow_hash, clsfn, time_limit, logger):
"""Retrieve classification data from MongoDB collection for a particular flow hash within a time range. time range is from current time backwards by numbe... | the_stack_v2_python_sparse | nmeta/flows.py | awesome-nfv/nmeta | train | 0 |
f3647ae0647d46e102b017bec622a593a5338613 | [
"request = self.get_serializer_context()['request']\nif request.query_params.get('brief', False):\n return serializers.NestedDeviceSerializer\nelif 'config_context' in request.query_params.get('exclude', []):\n return serializers.DeviceSerializer\nreturn serializers.DeviceWithConfigContextSerializer",
"devi... | <|body_start_0|>
request = self.get_serializer_context()['request']
if request.query_params.get('brief', False):
return serializers.NestedDeviceSerializer
elif 'config_context' in request.query_params.get('exclude', []):
return serializers.DeviceSerializer
return ... | DeviceViewSet | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DeviceViewSet:
def get_serializer_class(self):
"""Select the specific serializer based on the request context. If the `brief` query param equates to True, return the NestedDeviceSerializer If the `exclude` query param includes `config_context` as a value, return the DeviceSerializer Else... | stack_v2_sparse_classes_75kplus_train_074528 | 24,145 | permissive | [
{
"docstring": "Select the specific serializer based on the request context. If the `brief` query param equates to True, return the NestedDeviceSerializer If the `exclude` query param includes `config_context` as a value, return the DeviceSerializer Else, return the DeviceWithConfigContextSerializer",
"name... | 2 | stack_v2_sparse_classes_30k_train_020392 | Implement the Python class `DeviceViewSet` described below.
Class description:
Implement the DeviceViewSet class.
Method signatures and docstrings:
- def get_serializer_class(self): Select the specific serializer based on the request context. If the `brief` query param equates to True, return the NestedDeviceSerializ... | Implement the Python class `DeviceViewSet` described below.
Class description:
Implement the DeviceViewSet class.
Method signatures and docstrings:
- def get_serializer_class(self): Select the specific serializer based on the request context. If the `brief` query param equates to True, return the NestedDeviceSerializ... | 506884bc4dc70299db3e2a7ad577dd7fd808065e | <|skeleton|>
class DeviceViewSet:
def get_serializer_class(self):
"""Select the specific serializer based on the request context. If the `brief` query param equates to True, return the NestedDeviceSerializer If the `exclude` query param includes `config_context` as a value, return the DeviceSerializer Else... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DeviceViewSet:
def get_serializer_class(self):
"""Select the specific serializer based on the request context. If the `brief` query param equates to True, return the NestedDeviceSerializer If the `exclude` query param includes `config_context` as a value, return the DeviceSerializer Else, return the D... | the_stack_v2_python_sparse | netbox/dcim/api/views.py | netbox-community/netbox | train | 8,122 | |
49b2d4c8b5ae6b6bf4f59b9012f93e34bb741b88 | [
"super(QNetwork, self).__init__()\nself.seed = torch.manual_seed(seed)\nfc2_size = 10 * state_size\nfc3_size = 6 * state_size\nself.fc1 = nn.Linear(state_size, fc2_size)\nself.fc2 = nn.Linear(fc2_size, fc3_size)\nself.fc3 = nn.Linear(fc3_size, action_size)\nself.dropout = nn.Dropout(0.1)",
"x = state\nx = F.leaky... | <|body_start_0|>
super(QNetwork, self).__init__()
self.seed = torch.manual_seed(seed)
fc2_size = 10 * state_size
fc3_size = 6 * state_size
self.fc1 = nn.Linear(state_size, fc2_size)
self.fc2 = nn.Linear(fc2_size, fc3_size)
self.fc3 = nn.Linear(fc3_size, action_siz... | Actor (Policy) Model. | QNetwork | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class QNetwork:
"""Actor (Policy) Model."""
def __init__(self, state_size, action_size, seed):
"""Initialize parameters and build model. Params ====== state_size (int): Dimension of each state action_size (int): Dimension of each action seed (int): Random seed"""
<|body_0|>
de... | stack_v2_sparse_classes_75kplus_train_074529 | 1,262 | permissive | [
{
"docstring": "Initialize parameters and build model. Params ====== state_size (int): Dimension of each state action_size (int): Dimension of each action seed (int): Random seed",
"name": "__init__",
"signature": "def __init__(self, state_size, action_size, seed)"
},
{
"docstring": "Build a net... | 2 | stack_v2_sparse_classes_30k_train_006895 | Implement the Python class `QNetwork` described below.
Class description:
Actor (Policy) Model.
Method signatures and docstrings:
- def __init__(self, state_size, action_size, seed): Initialize parameters and build model. Params ====== state_size (int): Dimension of each state action_size (int): Dimension of each act... | Implement the Python class `QNetwork` described below.
Class description:
Actor (Policy) Model.
Method signatures and docstrings:
- def __init__(self, state_size, action_size, seed): Initialize parameters and build model. Params ====== state_size (int): Dimension of each state action_size (int): Dimension of each act... | 6406714d2ec35746ff8126e7f0773a722c3a6631 | <|skeleton|>
class QNetwork:
"""Actor (Policy) Model."""
def __init__(self, state_size, action_size, seed):
"""Initialize parameters and build model. Params ====== state_size (int): Dimension of each state action_size (int): Dimension of each action seed (int): Random seed"""
<|body_0|>
de... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class QNetwork:
"""Actor (Policy) Model."""
def __init__(self, state_size, action_size, seed):
"""Initialize parameters and build model. Params ====== state_size (int): Dimension of each state action_size (int): Dimension of each action seed (int): Random seed"""
super(QNetwork, self).__init__(... | the_stack_v2_python_sparse | dqn/lunar_lander/model.py | TonysCousin/udacity-reinforcement-learning | train | 0 |
3fbecc85055c7686cc1c130e31580696b39a86dd | [
"email = self.request.get('email')\ndate = self.request.get('date')\nself.hello_request(api_url='timeline/admin/{}/{}'.format(email, date), type='GET', api_info=self.suripu_app)",
"email = self.request.get('email')\ndate = self.request.get('date')\nself.hello_request(api_url='timeline/admin/invalidate/{}/{}'.form... | <|body_start_0|>
email = self.request.get('email')
date = self.request.get('date')
self.hello_request(api_url='timeline/admin/{}/{}'.format(email, date), type='GET', api_info=self.suripu_app)
<|end_body_0|>
<|body_start_1|>
email = self.request.get('email')
date = self.request.g... | TimelineAPI | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TimelineAPI:
def get(self):
"""Retrieve user timeline"""
<|body_0|>
def post(self):
"""Invalidate cache for user timeline"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
email = self.request.get('email')
date = self.request.get('date')
... | stack_v2_sparse_classes_75kplus_train_074530 | 2,336 | no_license | [
{
"docstring": "Retrieve user timeline",
"name": "get",
"signature": "def get(self)"
},
{
"docstring": "Invalidate cache for user timeline",
"name": "post",
"signature": "def post(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_011135 | Implement the Python class `TimelineAPI` described below.
Class description:
Implement the TimelineAPI class.
Method signatures and docstrings:
- def get(self): Retrieve user timeline
- def post(self): Invalidate cache for user timeline | Implement the Python class `TimelineAPI` described below.
Class description:
Implement the TimelineAPI class.
Method signatures and docstrings:
- def get(self): Retrieve user timeline
- def post(self): Invalidate cache for user timeline
<|skeleton|>
class TimelineAPI:
def get(self):
"""Retrieve user tim... | 44a274372d72416d7f7f95d76b6882ca3b4baff7 | <|skeleton|>
class TimelineAPI:
def get(self):
"""Retrieve user timeline"""
<|body_0|>
def post(self):
"""Invalidate cache for user timeline"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TimelineAPI:
def get(self):
"""Retrieve user timeline"""
email = self.request.get('email')
date = self.request.get('date')
self.hello_request(api_url='timeline/admin/{}/{}'.format(email, date), type='GET', api_info=self.suripu_app)
def post(self):
"""Invalidate cac... | the_stack_v2_python_sparse | api/timeline.py | hello/hello-admin | train | 2 | |
55e893dddf6a74c87159007e5157e01239c720da | [
"nn.Module.__init__(self)\nself.res = res\nself.dropout_p = dropout_p\nself.conv_bias = conv_bias\nself.leakiness = leakiness\nself.inst_norm_affine = inst_norm_affine\nself.lrelu_inplace = lrelu_inplace\nself.dropout = nn.Dropout3d(dropout_p)\nself.in_0 = nn.InstanceNorm3d(output_channels, affine=self.inst_norm_af... | <|body_start_0|>
nn.Module.__init__(self)
self.res = res
self.dropout_p = dropout_p
self.conv_bias = conv_bias
self.leakiness = leakiness
self.inst_norm_affine = inst_norm_affine
self.lrelu_inplace = lrelu_inplace
self.dropout = nn.Dropout3d(dropout_p)
... | EncodingModule | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EncodingModule:
def __init__(self, input_channels, output_channels, kernel_size=3, dropout_p=0.3, leakiness=0.01, conv_bias=True, inst_norm_affine=True, res=False, lrelu_inplace=True):
"""[The Encoding convolution module to learn the information and use] [This function will create the Le... | stack_v2_sparse_classes_75kplus_train_074531 | 20,028 | permissive | [
{
"docstring": "[The Encoding convolution module to learn the information and use] [This function will create the Learning convolutions] Arguments: input_channels {[int]} -- [the input number of channels, in our case the number of channels from downsample] output_channels {[int]} -- [the output number of channe... | 2 | null | Implement the Python class `EncodingModule` described below.
Class description:
Implement the EncodingModule class.
Method signatures and docstrings:
- def __init__(self, input_channels, output_channels, kernel_size=3, dropout_p=0.3, leakiness=0.01, conv_bias=True, inst_norm_affine=True, res=False, lrelu_inplace=True... | Implement the Python class `EncodingModule` described below.
Class description:
Implement the EncodingModule class.
Method signatures and docstrings:
- def __init__(self, input_channels, output_channels, kernel_size=3, dropout_p=0.3, leakiness=0.01, conv_bias=True, inst_norm_affine=True, res=False, lrelu_inplace=True... | 9acfe15cce2297ea706f6fb0406796c0e9305ccb | <|skeleton|>
class EncodingModule:
def __init__(self, input_channels, output_channels, kernel_size=3, dropout_p=0.3, leakiness=0.01, conv_bias=True, inst_norm_affine=True, res=False, lrelu_inplace=True):
"""[The Encoding convolution module to learn the information and use] [This function will create the Le... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class EncodingModule:
def __init__(self, input_channels, output_channels, kernel_size=3, dropout_p=0.3, leakiness=0.01, conv_bias=True, inst_norm_affine=True, res=False, lrelu_inplace=True):
"""[The Encoding convolution module to learn the information and use] [This function will create the Learning convolu... | the_stack_v2_python_sparse | BrainMaGe/models/seg_modules.py | AugustKRZhu/BrainMaGe | train | 0 | |
c1714e7ef3d00d6afe4027a59556d247d1d94da8 | [
"if N == 0:\n return 1\nelif N < 0:\n return 0\nelse:\n return self.recursive(N - 1) + self.recursive(N - 2) + self.recursive(N - 3)",
"cache = {0: 1}\n\ndef recurse(N):\n if N < 0:\n return 0\n elif N not in cache:\n cache[N] = recurse(N - 1) + recurse(N - 2) + recurse(N - 3)\n re... | <|body_start_0|>
if N == 0:
return 1
elif N < 0:
return 0
else:
return self.recursive(N - 1) + self.recursive(N - 2) + self.recursive(N - 3)
<|end_body_0|>
<|body_start_1|>
cache = {0: 1}
def recurse(N):
if N < 0:
... | ThreeStepSolution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ThreeStepSolution:
def recursive(self, N):
"""We solve this problem using recursion."""
<|body_0|>
def top_down(self, N):
"""Top down approach using memoization"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if N == 0:
return 1
... | stack_v2_sparse_classes_75kplus_train_074532 | 1,199 | no_license | [
{
"docstring": "We solve this problem using recursion.",
"name": "recursive",
"signature": "def recursive(self, N)"
},
{
"docstring": "Top down approach using memoization",
"name": "top_down",
"signature": "def top_down(self, N)"
}
] | 2 | stack_v2_sparse_classes_30k_train_042517 | Implement the Python class `ThreeStepSolution` described below.
Class description:
Implement the ThreeStepSolution class.
Method signatures and docstrings:
- def recursive(self, N): We solve this problem using recursion.
- def top_down(self, N): Top down approach using memoization | Implement the Python class `ThreeStepSolution` described below.
Class description:
Implement the ThreeStepSolution class.
Method signatures and docstrings:
- def recursive(self, N): We solve this problem using recursion.
- def top_down(self, N): Top down approach using memoization
<|skeleton|>
class ThreeStepSolutio... | 5347a98a61efbfef75e3e27ac564c423c4ec25bb | <|skeleton|>
class ThreeStepSolution:
def recursive(self, N):
"""We solve this problem using recursion."""
<|body_0|>
def top_down(self, N):
"""Top down approach using memoization"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ThreeStepSolution:
def recursive(self, N):
"""We solve this problem using recursion."""
if N == 0:
return 1
elif N < 0:
return 0
else:
return self.recursive(N - 1) + self.recursive(N - 2) + self.recursive(N - 3)
def top_down(self, N):
... | the_stack_v2_python_sparse | dynamic_programming/triple_steps.py | gtang31/algorithms | train | 0 | |
431057602fcb04d8a436df006e349a1e94991180 | [
"super(GANLoss, self).__init__()\nself.register_buffer('real_label', torch.tensor(target_real_label))\nself.register_buffer('fake_label', torch.tensor(target_fake_label))\nself.gan_mode = gan_mode\nif gan_mode == 'lsgan':\n self.loss = nn.MSELoss()\nelif gan_mode == 'vanilla':\n self.loss = nn.BCEWithLogitsLo... | <|body_start_0|>
super(GANLoss, self).__init__()
self.register_buffer('real_label', torch.tensor(target_real_label))
self.register_buffer('fake_label', torch.tensor(target_fake_label))
self.gan_mode = gan_mode
if gan_mode == 'lsgan':
self.loss = nn.MSELoss()
e... | Define different GAN objectives. The GANLoss class abstracts away the need to create the target label tensor that has the same size as the input. | GANLoss | [
"CC0-1.0",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GANLoss:
"""Define different GAN objectives. The GANLoss class abstracts away the need to create the target label tensor that has the same size as the input."""
def __init__(self, gan_mode, target_real_label=1.0, target_fake_label=0.0):
"""Initialize the GANLoss class. Parameters: ga... | stack_v2_sparse_classes_75kplus_train_074533 | 20,630 | permissive | [
{
"docstring": "Initialize the GANLoss class. Parameters: gan_mode (str) - - the type of GAN objective. It currently supports vanilla, lsgan, and wgangp. target_real_label (bool) - - label for a real image target_fake_label (bool) - - label of a fake image Note: Do not use sigmoid as the last layer of Discrimin... | 3 | stack_v2_sparse_classes_30k_train_040846 | Implement the Python class `GANLoss` described below.
Class description:
Define different GAN objectives. The GANLoss class abstracts away the need to create the target label tensor that has the same size as the input.
Method signatures and docstrings:
- def __init__(self, gan_mode, target_real_label=1.0, target_fake... | Implement the Python class `GANLoss` described below.
Class description:
Define different GAN objectives. The GANLoss class abstracts away the need to create the target label tensor that has the same size as the input.
Method signatures and docstrings:
- def __init__(self, gan_mode, target_real_label=1.0, target_fake... | c4a63f89e758eb404688098938d23507733d4514 | <|skeleton|>
class GANLoss:
"""Define different GAN objectives. The GANLoss class abstracts away the need to create the target label tensor that has the same size as the input."""
def __init__(self, gan_mode, target_real_label=1.0, target_fake_label=0.0):
"""Initialize the GANLoss class. Parameters: ga... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class GANLoss:
"""Define different GAN objectives. The GANLoss class abstracts away the need to create the target label tensor that has the same size as the input."""
def __init__(self, gan_mode, target_real_label=1.0, target_fake_label=0.0):
"""Initialize the GANLoss class. Parameters: gan_mode (str) ... | the_stack_v2_python_sparse | derender/GAN.py | tonyman1008/sorderender | train | 0 |
e7489c44e03af5e6654bd85d1647009e2303461e | [
"self.Ch2P2_19a = 10\nself.Ch2P2_19b = 17\nself.Ch2P2_19c = 6\nself.Ch2P2_19d = 8\nself.Ch2P2_20a = 14\nself.Ch2P2_20b = 8\nself.Ch2P2_20c = 13\nself.Ch2P2_20d = 6\nself.Ch2P2_22a = '00010001 11101010 00100010 00001110'\nself.Ch2P2_22b = '00001110 00111000 11101010 00111000'\nself.Ch2P2_22c = '01101110 00001110 001... | <|body_start_0|>
self.Ch2P2_19a = 10
self.Ch2P2_19b = 17
self.Ch2P2_19c = 6
self.Ch2P2_19d = 8
self.Ch2P2_20a = 14
self.Ch2P2_20b = 8
self.Ch2P2_20c = 13
self.Ch2P2_20d = 6
self.Ch2P2_22a = '00010001 11101010 00100010 00001110'
self.Ch2P2_2... | HW02 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HW02:
def ch2(self):
"""請將你計算出來的答案填入以下變數，助教會寫程式自動批改。 Ch2P2_19a = "xxx" 意思是 Ch2 : 第二章 P2_19a: 第二章結尾處的 PRACTICE SET 段落處的 Problems 第 P2-19 題的 a 小題 "xxx" ： 你要填入你的答地方。"""
<|body_0|>
def ch3(self):
"""請將你計算出來的答案填入以下變數，助教會寫程式自動批改。 Ch3P3_28a = "xxx" 意思是 Ch3 : 第三章 P3_28a: 第三章... | stack_v2_sparse_classes_75kplus_train_074534 | 2,811 | no_license | [
{
"docstring": "請將你計算出來的答案填入以下變數，助教會寫程式自動批改。 Ch2P2_19a = \"xxx\" 意思是 Ch2 : 第二章 P2_19a: 第二章結尾處的 PRACTICE SET 段落處的 Problems 第 P2-19 題的 a 小題 \"xxx\" ： 你要填入你的答地方。",
"name": "ch2",
"signature": "def ch2(self)"
},
{
"docstring": "請將你計算出來的答案填入以下變數，助教會寫程式自動批改。 Ch3P3_28a = \"xxx\" 意思是 Ch3 : 第三章 P3_28a: 第... | 2 | stack_v2_sparse_classes_30k_train_048503 | Implement the Python class `HW02` described below.
Class description:
Implement the HW02 class.
Method signatures and docstrings:
- def ch2(self): 請將你計算出來的答案填入以下變數，助教會寫程式自動批改。 Ch2P2_19a = "xxx" 意思是 Ch2 : 第二章 P2_19a: 第二章結尾處的 PRACTICE SET 段落處的 Problems 第 P2-19 題的 a 小題 "xxx" ： 你要填入你的答地方。
- def ch3(self): 請將你計算出來的答案填入以下變... | Implement the Python class `HW02` described below.
Class description:
Implement the HW02 class.
Method signatures and docstrings:
- def ch2(self): 請將你計算出來的答案填入以下變數，助教會寫程式自動批改。 Ch2P2_19a = "xxx" 意思是 Ch2 : 第二章 P2_19a: 第二章結尾處的 PRACTICE SET 段落處的 Problems 第 P2-19 題的 a 小題 "xxx" ： 你要填入你的答地方。
- def ch3(self): 請將你計算出來的答案填入以下變... | 008575d161d48672f906bdaec130f0c5060cd36d | <|skeleton|>
class HW02:
def ch2(self):
"""請將你計算出來的答案填入以下變數，助教會寫程式自動批改。 Ch2P2_19a = "xxx" 意思是 Ch2 : 第二章 P2_19a: 第二章結尾處的 PRACTICE SET 段落處的 Problems 第 P2-19 題的 a 小題 "xxx" ： 你要填入你的答地方。"""
<|body_0|>
def ch3(self):
"""請將你計算出來的答案填入以下變數，助教會寫程式自動批改。 Ch3P3_28a = "xxx" 意思是 Ch3 : 第三章 P3_28a: 第三章... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class HW02:
def ch2(self):
"""請將你計算出來的答案填入以下變數，助教會寫程式自動批改。 Ch2P2_19a = "xxx" 意思是 Ch2 : 第二章 P2_19a: 第二章結尾處的 PRACTICE SET 段落處的 Problems 第 P2-19 題的 a 小題 "xxx" ： 你要填入你的答地方。"""
self.Ch2P2_19a = 10
self.Ch2P2_19b = 17
self.Ch2P2_19c = 6
self.Ch2P2_19d = 8
self.Ch2P2_20a = 1... | the_stack_v2_python_sparse | homework02_b05505009.py | PeterWolf-tw/ESOE-CS101-2016 | train | 21 | |
b7a68df8d5b8c4388036c919d8e044b840e66e87 | [
"UserModel = get_user_model()\nemail = self.cleaned_data['email']\nself.users_cache = UserModel._default_manager.filter(email__iexact=email)\nif not len(self.users_cache):\n raise forms.ValidationError(self.error_messages['unknown'])\nif not any((user.is_active for user in self.users_cache)):\n raise forms.Va... | <|body_start_0|>
UserModel = get_user_model()
email = self.cleaned_data['email']
self.users_cache = UserModel._default_manager.filter(email__iexact=email)
if not len(self.users_cache):
raise forms.ValidationError(self.error_messages['unknown'])
if not any((user.is_act... | PasswordResetForm | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PasswordResetForm:
def clean_email(self):
"""Validates that an active user exists with the given email address."""
<|body_0|>
def save(self, domain_override=None, subject_template_name='registration/password_reset_subject.txt', email_template_name='registration/password_rese... | stack_v2_sparse_classes_75kplus_train_074535 | 3,164 | permissive | [
{
"docstring": "Validates that an active user exists with the given email address.",
"name": "clean_email",
"signature": "def clean_email(self)"
},
{
"docstring": "Generates a one-use only link for resetting password and sends to the user.",
"name": "save",
"signature": "def save(self, d... | 2 | stack_v2_sparse_classes_30k_train_020631 | Implement the Python class `PasswordResetForm` described below.
Class description:
Implement the PasswordResetForm class.
Method signatures and docstrings:
- def clean_email(self): Validates that an active user exists with the given email address.
- def save(self, domain_override=None, subject_template_name='registra... | Implement the Python class `PasswordResetForm` described below.
Class description:
Implement the PasswordResetForm class.
Method signatures and docstrings:
- def clean_email(self): Validates that an active user exists with the given email address.
- def save(self, domain_override=None, subject_template_name='registra... | 8d8f9149b6efeb65202809a5f8916386f58a1b3b | <|skeleton|>
class PasswordResetForm:
def clean_email(self):
"""Validates that an active user exists with the given email address."""
<|body_0|>
def save(self, domain_override=None, subject_template_name='registration/password_reset_subject.txt', email_template_name='registration/password_rese... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PasswordResetForm:
def clean_email(self):
"""Validates that an active user exists with the given email address."""
UserModel = get_user_model()
email = self.cleaned_data['email']
self.users_cache = UserModel._default_manager.filter(email__iexact=email)
if not len(self.u... | the_stack_v2_python_sparse | website/drawquest/apps/drawquest_auth/forms.py | MichaelBechHansen/drawquest-web | train | 0 | |
f626518698d28db912ab31462e56eb87fe8c1caa | [
"super(Policy, self).__init__()\nself.action_bound = action_bound\nself.detector = detector\nself.lut_thetas = lut_info['thetas']\nself.lut_phis = lut_info['phis']\nself.lut_mask = lut_info['mask']\nself.p = local_p\nself.thresh = thresh\nself.name = 'down + proportional + in-bounds'\nself.im_ctr = (agent_cfg.obs_s... | <|body_start_0|>
super(Policy, self).__init__()
self.action_bound = action_bound
self.detector = detector
self.lut_thetas = lut_info['thetas']
self.lut_phis = lut_info['phis']
self.lut_mask = lut_info['mask']
self.p = local_p
self.thresh = thresh
s... | This custom policy combines 'downward' heuristic with information from strawberry detector. | CustomPolicy1 | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CustomPolicy1:
"""This custom policy combines 'downward' heuristic with information from strawberry detector."""
def __init__(self, action_bound, detector, lut_info, local_p=1.0, thresh=0.5):
"""Initialize custom policy."""
<|body_0|>
def best_bb(self, bbs):
"""R... | stack_v2_sparse_classes_75kplus_train_074536 | 45,503 | permissive | [
{
"docstring": "Initialize custom policy.",
"name": "__init__",
"signature": "def __init__(self, action_bound, detector, lut_info, local_p=1.0, thresh=0.5)"
},
{
"docstring": "Returns predicted bounding box for ripe strawberry with highest confidence value.",
"name": "best_bb",
"signatur... | 4 | stack_v2_sparse_classes_30k_train_044681 | Implement the Python class `CustomPolicy1` described below.
Class description:
This custom policy combines 'downward' heuristic with information from strawberry detector.
Method signatures and docstrings:
- def __init__(self, action_bound, detector, lut_info, local_p=1.0, thresh=0.5): Initialize custom policy.
- def ... | Implement the Python class `CustomPolicy1` described below.
Class description:
This custom policy combines 'downward' heuristic with information from strawberry detector.
Method signatures and docstrings:
- def __init__(self, action_bound, detector, lut_info, local_p=1.0, thresh=0.5): Initialize custom policy.
- def ... | c28840e254cdd2a4f3d16fffa6391748f94b7d8c | <|skeleton|>
class CustomPolicy1:
"""This custom policy combines 'downward' heuristic with information from strawberry detector."""
def __init__(self, action_bound, detector, lut_info, local_p=1.0, thresh=0.5):
"""Initialize custom policy."""
<|body_0|>
def best_bb(self, bbs):
"""R... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CustomPolicy1:
"""This custom policy combines 'downward' heuristic with information from strawberry detector."""
def __init__(self, action_bound, detector, lut_info, local_p=1.0, thresh=0.5):
"""Initialize custom policy."""
super(Policy, self).__init__()
self.action_bound = action... | the_stack_v2_python_sparse | ddpg/policy.py | jsather/harvester-python | train | 3 |
163ea2f4e262456a0b1d8f46d0b90ffbfee360c1 | [
"if JWTWrapper.__instance is None:\n JWTWrapper()\nreturn JWTWrapper.__instance",
"if JWTWrapper.__instance is not None:\n raise AuthenticationError('Attempt made to create multiple JWTWrappers')\nJWTWrapper.__instance = JWTAuthenticationBackend()"
] | <|body_start_0|>
if JWTWrapper.__instance is None:
JWTWrapper()
return JWTWrapper.__instance
<|end_body_0|>
<|body_start_1|>
if JWTWrapper.__instance is not None:
raise AuthenticationError('Attempt made to create multiple JWTWrappers')
JWTWrapper.__instance = JWT... | Singleton wrapper for Flask JWTAuthenticationBackend. | JWTWrapper | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class JWTWrapper:
"""Singleton wrapper for Flask JWTAuthenticationBackend."""
def get_instance():
"""Retrieve singleton JWTAuthenticationBackend."""
<|body_0|>
def __init__(self):
"""Virtually private constructor."""
<|body_1|>
<|end_skeleton|>
<|body_start_0... | stack_v2_sparse_classes_75kplus_train_074537 | 7,750 | permissive | [
{
"docstring": "Retrieve singleton JWTAuthenticationBackend.",
"name": "get_instance",
"signature": "def get_instance()"
},
{
"docstring": "Virtually private constructor.",
"name": "__init__",
"signature": "def __init__(self)"
}
] | 2 | stack_v2_sparse_classes_30k_test_001654 | Implement the Python class `JWTWrapper` described below.
Class description:
Singleton wrapper for Flask JWTAuthenticationBackend.
Method signatures and docstrings:
- def get_instance(): Retrieve singleton JWTAuthenticationBackend.
- def __init__(self): Virtually private constructor. | Implement the Python class `JWTWrapper` described below.
Class description:
Singleton wrapper for Flask JWTAuthenticationBackend.
Method signatures and docstrings:
- def get_instance(): Retrieve singleton JWTAuthenticationBackend.
- def __init__(self): Virtually private constructor.
<|skeleton|>
class JWTWrapper:
... | ddff47af77a3596c37b712113d25f39282493a76 | <|skeleton|>
class JWTWrapper:
"""Singleton wrapper for Flask JWTAuthenticationBackend."""
def get_instance():
"""Retrieve singleton JWTAuthenticationBackend."""
<|body_0|>
def __init__(self):
"""Virtually private constructor."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class JWTWrapper:
"""Singleton wrapper for Flask JWTAuthenticationBackend."""
def get_instance():
"""Retrieve singleton JWTAuthenticationBackend."""
if JWTWrapper.__instance is None:
JWTWrapper()
return JWTWrapper.__instance
def __init__(self):
"""Virtually priv... | the_stack_v2_python_sparse | notify-api/src/notify_api/core/jwt.py | pwei1018/sbc-auth | train | 3 |
8e254edc3fe9fe441d9316ae640f7cdc342ba064 | [
"if isinstance(tags, str):\n return tags.split(',')\nreturn list(tags)",
"obj = super().dict(**kwargs)\nif 'tags' in obj:\n obj['tags'] = ','.join(obj['tags'])\nreturn obj"
] | <|body_start_0|>
if isinstance(tags, str):
return tags.split(',')
return list(tags)
<|end_body_0|>
<|body_start_1|>
obj = super().dict(**kwargs)
if 'tags' in obj:
obj['tags'] = ','.join(obj['tags'])
return obj
<|end_body_1|>
| Define a base class for elements and relationships. Attributes: id (str): tags (set of str): properties (dict): perspectives (set of Perspective): | ModelItemIO | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ModelItemIO:
"""Define a base class for elements and relationships. Attributes: id (str): tags (set of str): properties (dict): perspectives (set of Perspective):"""
def split_tags(cls, tags: Union[str, Iterable[str]]) -> List[str]:
"""Convert comma-separated tag list into list if ne... | stack_v2_sparse_classes_75kplus_train_074538 | 3,127 | permissive | [
{
"docstring": "Convert comma-separated tag list into list if needed.",
"name": "split_tags",
"signature": "def split_tags(cls, tags: Union[str, Iterable[str]]) -> List[str]"
},
{
"docstring": "Map this IO into a dictionary suitable for serialisation.",
"name": "dict",
"signature": "def ... | 2 | stack_v2_sparse_classes_30k_val_000264 | Implement the Python class `ModelItemIO` described below.
Class description:
Define a base class for elements and relationships. Attributes: id (str): tags (set of str): properties (dict): perspectives (set of Perspective):
Method signatures and docstrings:
- def split_tags(cls, tags: Union[str, Iterable[str]]) -> Li... | Implement the Python class `ModelItemIO` described below.
Class description:
Define a base class for elements and relationships. Attributes: id (str): tags (set of str): properties (dict): perspectives (set of Perspective):
Method signatures and docstrings:
- def split_tags(cls, tags: Union[str, Iterable[str]]) -> Li... | 31f1dcadb3ff113d8a77ce132657237ea01c307b | <|skeleton|>
class ModelItemIO:
"""Define a base class for elements and relationships. Attributes: id (str): tags (set of str): properties (dict): perspectives (set of Perspective):"""
def split_tags(cls, tags: Union[str, Iterable[str]]) -> List[str]:
"""Convert comma-separated tag list into list if ne... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ModelItemIO:
"""Define a base class for elements and relationships. Attributes: id (str): tags (set of str): properties (dict): perspectives (set of Perspective):"""
def split_tags(cls, tags: Union[str, Iterable[str]]) -> List[str]:
"""Convert comma-separated tag list into list if needed."""
... | the_stack_v2_python_sparse | src/structurizr/model/model_item.py | Midnighter/structurizr-python | train | 61 |
f72c1f467f8ef6a333d83d7e6c8faabf4b458d37 | [
"cell = reference_element.UFCInterval()\npolynomial_space = polynomial_set.ONPolynomialSet(cell, degree)\ndual = TimeElementDualSet(family, degree)\nfinite_element.FiniteElement.__init__(self, polynomial_space, dual, degree)",
"n = len(self.dual.coords)\nif n == 0:\n weights[0] = 2.0\n return weights\nA = e... | <|body_start_0|>
cell = reference_element.UFCInterval()
polynomial_space = polynomial_set.ONPolynomialSet(cell, degree)
dual = TimeElementDualSet(family, degree)
finite_element.FiniteElement.__init__(self, polynomial_space, dual, degree)
<|end_body_0|>
<|body_start_1|>
n = len(s... | . | TimeElement | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TimeElement:
"""."""
def __init__(self, family, degree):
"""Create time element with given (polynomial degree)."""
<|body_0|>
def compute_quadrature_weights(self):
"""Compute the quadrature weights by solving a linear system of equations for exact integration of ... | stack_v2_sparse_classes_75kplus_train_074539 | 4,109 | no_license | [
{
"docstring": "Create time element with given (polynomial degree).",
"name": "__init__",
"signature": "def __init__(self, family, degree)"
},
{
"docstring": "Compute the quadrature weights by solving a linear system of equations for exact integration of polynomials. We compute the integrals ove... | 2 | stack_v2_sparse_classes_30k_train_049308 | Implement the Python class `TimeElement` described below.
Class description:
.
Method signatures and docstrings:
- def __init__(self, family, degree): Create time element with given (polynomial degree).
- def compute_quadrature_weights(self): Compute the quadrature weights by solving a linear system of equations for ... | Implement the Python class `TimeElement` described below.
Class description:
.
Method signatures and docstrings:
- def __init__(self, family, degree): Create time element with given (polynomial degree).
- def compute_quadrature_weights(self): Compute the quadrature weights by solving a linear system of equations for ... | 7af15cd0ab522436ca285f8422faa42675345f55 | <|skeleton|>
class TimeElement:
"""."""
def __init__(self, family, degree):
"""Create time element with given (polynomial degree)."""
<|body_0|>
def compute_quadrature_weights(self):
"""Compute the quadrature weights by solving a linear system of equations for exact integration of ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TimeElement:
"""."""
def __init__(self, family, degree):
"""Create time element with given (polynomial degree)."""
cell = reference_element.UFCInterval()
polynomial_space = polynomial_set.ONPolynomialSet(cell, degree)
dual = TimeElementDualSet(family, degree)
finit... | the_stack_v2_python_sparse | Lib/site-packages/ffc/timeelements.py | maciekswat/dolfin_python_deps | train | 0 |
03f64f92c1acb719fccc439fdc4dd9e85cc91cb2 | [
"n = len(nums)\ntotal = n * (n + 1) // 2\nfor i in range(0, n):\n total -= nums[i]\nreturn total",
"n = len(nums)\nx1 = nums[0]\nx2 = 1\nfor i in range(n):\n x1 ^= nums[i]\nfor i in range(n + 2):\n x2 ^= i\n return x1 ^ x2"
] | <|body_start_0|>
n = len(nums)
total = n * (n + 1) // 2
for i in range(0, n):
total -= nums[i]
return total
<|end_body_0|>
<|body_start_1|>
n = len(nums)
x1 = nums[0]
x2 = 1
for i in range(n):
x1 ^= nums[i]
for i in range(n... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def missingNumber(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def missingNumber2(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
n = len(nums)
total = n * (n + 1... | stack_v2_sparse_classes_75kplus_train_074540 | 756 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "missingNumber",
"signature": "def missingNumber(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "missingNumber2",
"signature": "def missingNumber2(self, nums)"
}
] | 2 | stack_v2_sparse_classes_30k_train_028197 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def missingNumber(self, nums): :type nums: List[int] :rtype: int
- def missingNumber2(self, nums): :type nums: List[int] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def missingNumber(self, nums): :type nums: List[int] :rtype: int
- def missingNumber2(self, nums): :type nums: List[int] :rtype: int
<|skeleton|>
class Solution:
def missin... | 54d3d9530b25272d4a2e5dc33e7035c44f506dc5 | <|skeleton|>
class Solution:
def missingNumber(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def missingNumber2(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def missingNumber(self, nums):
""":type nums: List[int] :rtype: int"""
n = len(nums)
total = n * (n + 1) // 2
for i in range(0, n):
total -= nums[i]
return total
def missingNumber2(self, nums):
""":type nums: List[int] :rtype: int"""
... | the_stack_v2_python_sparse | old/Session002/Arrays/MissingNumber.py | MaxIakovliev/algorithms | train | 0 | |
aec14cbe98e38e118cb5089b82f9947b6b527f9b | [
"self.input_image = input_image\nself.params = params\nself.edge_image = None",
"canny = cv2.Canny(image=self.input_image, threshold1=self.params.hysteresis_min_thresh, threshold2=self.params.hysteresis_max_thresh, apertureSize=3)\nLogger.debug('Canny edges computed')\ndilated = cv2.dilate(canny, self.params.kern... | <|body_start_0|>
self.input_image = input_image
self.params = params
self.edge_image = None
<|end_body_0|>
<|body_start_1|>
canny = cv2.Canny(image=self.input_image, threshold1=self.params.hysteresis_min_thresh, threshold2=self.params.hysteresis_max_thresh, apertureSize=3)
Logge... | Class responsible for detecting edges in greyscale images. The approach taken to detect edges in the input greyscale image is the following: 1. Perform a canny edge detection on the input image. 2. Dilate the resulting binary image for a parametrized number of steps in order to connect short edges and smooth out the ed... | EdgeDetector | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EdgeDetector:
"""Class responsible for detecting edges in greyscale images. The approach taken to detect edges in the input greyscale image is the following: 1. Perform a canny edge detection on the input image. 2. Dilate the resulting binary image for a parametrized number of steps in order to c... | stack_v2_sparse_classes_75kplus_train_074541 | 3,074 | no_license | [
{
"docstring": ":param input_image: Input greyscale image where edges must be detected. :param params: Parameters used for edge detection.",
"name": "__init__",
"signature": "def __init__(self, input_image: np.ndarray, params: EdgeDetectorParams=EdgeDetectorParams())"
},
{
"docstring": "Detects ... | 2 | null | Implement the Python class `EdgeDetector` described below.
Class description:
Class responsible for detecting edges in greyscale images. The approach taken to detect edges in the input greyscale image is the following: 1. Perform a canny edge detection on the input image. 2. Dilate the resulting binary image for a par... | Implement the Python class `EdgeDetector` described below.
Class description:
Class responsible for detecting edges in greyscale images. The approach taken to detect edges in the input greyscale image is the following: 1. Perform a canny edge detection on the input image. 2. Dilate the resulting binary image for a par... | 25bc6f52a89b73e6a38488171c106f947f4e70ef | <|skeleton|>
class EdgeDetector:
"""Class responsible for detecting edges in greyscale images. The approach taken to detect edges in the input greyscale image is the following: 1. Perform a canny edge detection on the input image. 2. Dilate the resulting binary image for a parametrized number of steps in order to c... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class EdgeDetector:
"""Class responsible for detecting edges in greyscale images. The approach taken to detect edges in the input greyscale image is the following: 1. Perform a canny edge detection on the input image. 2. Dilate the resulting binary image for a parametrized number of steps in order to connect short ... | the_stack_v2_python_sparse | thermography/detection/edge_detection.py | PaoloC68/thermography | train | 1 |
0d410143fff9028a90a7737d843cd9f2d9cf5625 | [
"super(SimpleScheduler, self).__init__(trainer)\nself._iter = 0\nself._patience = patience",
"self._iter += 1\nlogging.info('{} epochs left to run'.format(self._patience - self._iter))\nif self._iter >= self._patience:\n return True\nelse:\n return False"
] | <|body_start_0|>
super(SimpleScheduler, self).__init__(trainer)
self._iter = 0
self._patience = patience
<|end_body_0|>
<|body_start_1|>
self._iter += 1
logging.info('{} epochs left to run'.format(self._patience - self._iter))
if self._iter >= self._patience:
... | Simple scheduler with maximum patience. | SimpleScheduler | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SimpleScheduler:
"""Simple scheduler with maximum patience."""
def __init__(self, trainer, patience=10):
""":type trainer: deepy.trainers.base.NeuralTrainer"""
<|body_0|>
def invoke(self):
"""Run it, return whether to end training."""
<|body_1|>
<|end_sk... | stack_v2_sparse_classes_75kplus_train_074542 | 4,722 | permissive | [
{
"docstring": ":type trainer: deepy.trainers.base.NeuralTrainer",
"name": "__init__",
"signature": "def __init__(self, trainer, patience=10)"
},
{
"docstring": "Run it, return whether to end training.",
"name": "invoke",
"signature": "def invoke(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_012026 | Implement the Python class `SimpleScheduler` described below.
Class description:
Simple scheduler with maximum patience.
Method signatures and docstrings:
- def __init__(self, trainer, patience=10): :type trainer: deepy.trainers.base.NeuralTrainer
- def invoke(self): Run it, return whether to end training. | Implement the Python class `SimpleScheduler` described below.
Class description:
Simple scheduler with maximum patience.
Method signatures and docstrings:
- def __init__(self, trainer, patience=10): :type trainer: deepy.trainers.base.NeuralTrainer
- def invoke(self): Run it, return whether to end training.
<|skeleto... | 9b4f9ebda7f6f1e03dad7ef7374e36c3d0cd754a | <|skeleton|>
class SimpleScheduler:
"""Simple scheduler with maximum patience."""
def __init__(self, trainer, patience=10):
""":type trainer: deepy.trainers.base.NeuralTrainer"""
<|body_0|>
def invoke(self):
"""Run it, return whether to end training."""
<|body_1|>
<|end_sk... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SimpleScheduler:
"""Simple scheduler with maximum patience."""
def __init__(self, trainer, patience=10):
""":type trainer: deepy.trainers.base.NeuralTrainer"""
super(SimpleScheduler, self).__init__(trainer)
self._iter = 0
self._patience = patience
def invoke(self):
... | the_stack_v2_python_sparse | deepy/trainers/annealers.py | fahad92virgo/deepy | train | 1 |
65d32b24360987dc07225a4d1a2c127bb8ab0486 | [
"self.config = config\nself.cookie = cookie\nself.quotas = quotas",
"if dictionary is None:\n return None\nconfig = cohesity_management_sdk.models.dir_quota_config.DirQuotaConfig.from_dictionary(dictionary.get('config')) if dictionary.get('config') else None\ncookie = dictionary.get('cookie')\nquotas = None\ni... | <|body_start_0|>
self.config = config
self.cookie = cookie
self.quotas = quotas
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
config = cohesity_management_sdk.models.dir_quota_config.DirQuotaConfig.from_dictionary(dictionary.get('config')) if dic... | Implementation of the 'DirQuotaInfo' model. Specifies the configuration and policy details for directory quota in a view. Attributes: config (DirQuotaConfig): Specifies the directory quota configuration. cookie (long|int): This cookie can be used in the succeeding call to list user quotas and usages to get the next set... | DirQuotaInfo | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DirQuotaInfo:
"""Implementation of the 'DirQuotaInfo' model. Specifies the configuration and policy details for directory quota in a view. Attributes: config (DirQuotaConfig): Specifies the directory quota configuration. cookie (long|int): This cookie can be used in the succeeding call to list us... | stack_v2_sparse_classes_75kplus_train_074543 | 2,492 | permissive | [
{
"docstring": "Constructor for the DirQuotaInfo class",
"name": "__init__",
"signature": "def __init__(self, config=None, cookie=None, quotas=None)"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: dictionary (dictionary): A dictionary representation of the object as... | 2 | stack_v2_sparse_classes_30k_train_004018 | Implement the Python class `DirQuotaInfo` described below.
Class description:
Implementation of the 'DirQuotaInfo' model. Specifies the configuration and policy details for directory quota in a view. Attributes: config (DirQuotaConfig): Specifies the directory quota configuration. cookie (long|int): This cookie can be... | Implement the Python class `DirQuotaInfo` described below.
Class description:
Implementation of the 'DirQuotaInfo' model. Specifies the configuration and policy details for directory quota in a view. Attributes: config (DirQuotaConfig): Specifies the directory quota configuration. cookie (long|int): This cookie can be... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class DirQuotaInfo:
"""Implementation of the 'DirQuotaInfo' model. Specifies the configuration and policy details for directory quota in a view. Attributes: config (DirQuotaConfig): Specifies the directory quota configuration. cookie (long|int): This cookie can be used in the succeeding call to list us... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DirQuotaInfo:
"""Implementation of the 'DirQuotaInfo' model. Specifies the configuration and policy details for directory quota in a view. Attributes: config (DirQuotaConfig): Specifies the directory quota configuration. cookie (long|int): This cookie can be used in the succeeding call to list user quotas and... | the_stack_v2_python_sparse | cohesity_management_sdk/models/dir_quota_info.py | cohesity/management-sdk-python | train | 24 |
294168f6d843a00ff2f3e6b6bb67a4d11cea1ad3 | [
"choices = QuestionChoice.objects.filter(question_id=pk)\nserializer = QuestionChoiceSerializer(choices, many=True)\nreturn Response(serializer.data)",
"serializer = QuestionSerializer(data=request.data, many=True)\nif serializer.is_valid(raise_exception=True):\n serializer.save()\n return Response(serializ... | <|body_start_0|>
choices = QuestionChoice.objects.filter(question_id=pk)
serializer = QuestionChoiceSerializer(choices, many=True)
return Response(serializer.data)
<|end_body_0|>
<|body_start_1|>
serializer = QuestionSerializer(data=request.data, many=True)
if serializer.is_vali... | QuestionViewSet | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class QuestionViewSet:
def choices(self, _, pk=None):
"""Returns All the choices available for a question"""
<|body_0|>
def bulk_create(self, request):
"""This Endpoint is Used to Create Questions in bulk."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
c... | stack_v2_sparse_classes_75kplus_train_074544 | 6,078 | no_license | [
{
"docstring": "Returns All the choices available for a question",
"name": "choices",
"signature": "def choices(self, _, pk=None)"
},
{
"docstring": "This Endpoint is Used to Create Questions in bulk.",
"name": "bulk_create",
"signature": "def bulk_create(self, request)"
}
] | 2 | stack_v2_sparse_classes_30k_train_018595 | Implement the Python class `QuestionViewSet` described below.
Class description:
Implement the QuestionViewSet class.
Method signatures and docstrings:
- def choices(self, _, pk=None): Returns All the choices available for a question
- def bulk_create(self, request): This Endpoint is Used to Create Questions in bulk. | Implement the Python class `QuestionViewSet` described below.
Class description:
Implement the QuestionViewSet class.
Method signatures and docstrings:
- def choices(self, _, pk=None): Returns All the choices available for a question
- def bulk_create(self, request): This Endpoint is Used to Create Questions in bulk.... | 71f80648a765cd9a943ba49dd64da7a0c525e0b6 | <|skeleton|>
class QuestionViewSet:
def choices(self, _, pk=None):
"""Returns All the choices available for a question"""
<|body_0|>
def bulk_create(self, request):
"""This Endpoint is Used to Create Questions in bulk."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class QuestionViewSet:
def choices(self, _, pk=None):
"""Returns All the choices available for a question"""
choices = QuestionChoice.objects.filter(question_id=pk)
serializer = QuestionChoiceSerializer(choices, many=True)
return Response(serializer.data)
def bulk_create(self, r... | the_stack_v2_python_sparse | api/views.py | nikmalviya/HRSurveyRESTAPI | train | 0 | |
be7342d4d522fe53a2f90341b2dbc94c9739f4c6 | [
"current_directory = os.path.dirname(os.path.abspath(__file__))\ntest_access_file = os.path.join(current_directory, 'TestData.json')\nwith open(test_access_file, 'r') as f:\n cls._data = json.load(f)\ncls._hostname = cls._data['organizations']['name']",
"user_rest_v1_failure = self._data['systemusers']['user_r... | <|body_start_0|>
current_directory = os.path.dirname(os.path.abspath(__file__))
test_access_file = os.path.join(current_directory, 'TestData.json')
with open(test_access_file, 'r') as f:
cls._data = json.load(f)
cls._hostname = cls._data['organizations']['name']
<|end_body_0|... | Test the Access module. | TestAccess | [
"GPL-3.0-only",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestAccess:
"""Test the Access module."""
def setUpClass(cls):
"""Prepare test class. Get the Test Data from JSON (JavaScript Object Notation) file."""
<|body_0|>
def test_login_rest_v1_failure(self):
"""Test a failure of REST (REpresentational State Transfer) lo... | stack_v2_sparse_classes_75kplus_train_074545 | 2,569 | permissive | [
{
"docstring": "Prepare test class. Get the Test Data from JSON (JavaScript Object Notation) file.",
"name": "setUpClass",
"signature": "def setUpClass(cls)"
},
{
"docstring": "Test a failure of REST (REpresentational State Transfer) login method. Get the failure username and password (user_rest... | 3 | stack_v2_sparse_classes_30k_train_009120 | Implement the Python class `TestAccess` described below.
Class description:
Test the Access module.
Method signatures and docstrings:
- def setUpClass(cls): Prepare test class. Get the Test Data from JSON (JavaScript Object Notation) file.
- def test_login_rest_v1_failure(self): Test a failure of REST (REpresentation... | Implement the Python class `TestAccess` described below.
Class description:
Test the Access module.
Method signatures and docstrings:
- def setUpClass(cls): Prepare test class. Get the Test Data from JSON (JavaScript Object Notation) file.
- def test_login_rest_v1_failure(self): Test a failure of REST (REpresentation... | 15d00019d496a2a401961e66e3fbb3876a9c6c9d | <|skeleton|>
class TestAccess:
"""Test the Access module."""
def setUpClass(cls):
"""Prepare test class. Get the Test Data from JSON (JavaScript Object Notation) file."""
<|body_0|>
def test_login_rest_v1_failure(self):
"""Test a failure of REST (REpresentational State Transfer) lo... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TestAccess:
"""Test the Access module."""
def setUpClass(cls):
"""Prepare test class. Get the Test Data from JSON (JavaScript Object Notation) file."""
current_directory = os.path.dirname(os.path.abspath(__file__))
test_access_file = os.path.join(current_directory, 'TestData.json'... | the_stack_v2_python_sparse | projects/Python-D365API/D365API/TestAccess.py | rakasiwisurya/CodeWithFriends-Spring2020 | train | 1 |
eff8fe34670ee19cc6c3c3d3003fed17729860bd | [
"print('Constructing trajectory network for time: {}'.format(stream.time), end='\\r')\nG = Graph()\nparticles = list(stream)\nif save_position:\n G.add_nodes_from(((p.id, {'pos': p.position}) for p in particles))\nelse:\n G.add_nodes_from((p.id for p in particles))\npos = np.array([p.position for p in particl... | <|body_start_0|>
print('Constructing trajectory network for time: {}'.format(stream.time), end='\r')
G = Graph()
particles = list(stream)
if save_position:
G.add_nodes_from(((p.id, {'pos': p.position}) for p in particles))
else:
G.add_nodes_from((p.id for ... | Trajectory network constructor singleton class. | TrajectoryNetConstructor | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TrajectoryNetConstructor:
"""Trajectory network constructor singleton class."""
def get_proximitynet(self, stream, distance, save_position=False):
"""Get the proximity network for a single timestamp. Params ------ stream : ParticleStream The iterator over Particles in that timestep d... | stack_v2_sparse_classes_75kplus_train_074546 | 2,890 | no_license | [
{
"docstring": "Get the proximity network for a single timestamp. Params ------ stream : ParticleStream The iterator over Particles in that timestep distance : int or float The distance threshold within which objects are considered connected. save_position : boolean (optional, default: False) Whether to save pa... | 2 | stack_v2_sparse_classes_30k_train_052531 | Implement the Python class `TrajectoryNetConstructor` described below.
Class description:
Trajectory network constructor singleton class.
Method signatures and docstrings:
- def get_proximitynet(self, stream, distance, save_position=False): Get the proximity network for a single timestamp. Params ------ stream : Part... | Implement the Python class `TrajectoryNetConstructor` described below.
Class description:
Trajectory network constructor singleton class.
Method signatures and docstrings:
- def get_proximitynet(self, stream, distance, save_position=False): Get the proximity network for a single timestamp. Params ------ stream : Part... | 0394980efc628bfedd4fd504079a534418cbb89a | <|skeleton|>
class TrajectoryNetConstructor:
"""Trajectory network constructor singleton class."""
def get_proximitynet(self, stream, distance, save_position=False):
"""Get the proximity network for a single timestamp. Params ------ stream : ParticleStream The iterator over Particles in that timestep d... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TrajectoryNetConstructor:
"""Trajectory network constructor singleton class."""
def get_proximitynet(self, stream, distance, save_position=False):
"""Get the proximity network for a single timestamp. Params ------ stream : ParticleStream The iterator over Particles in that timestep distance : int... | the_stack_v2_python_sparse | generators/trajectories/trajectory_net_constructor.py | tipech/spatialnet | train | 1 |
0a72abdba9127984b8f02202b6930c340c901c4d | [
"pattern = '[%d/%b/%Y:%H:%M:%S'\ntime_struct = time.strptime(timestamp, pattern)\nformatted = time.strftime('%Y/%m/%d %H:%M:%S', time_struct)\nreturn formatted",
"document = {'source': info['name'], 'timestamp': None, 'user': None, 'client_ip': None, 'method': None, 'url': None, 'status_code': None, 'user_agent':... | <|body_start_0|>
pattern = '[%d/%b/%Y:%H:%M:%S'
time_struct = time.strptime(timestamp, pattern)
formatted = time.strftime('%Y/%m/%d %H:%M:%S', time_struct)
return formatted
<|end_body_0|>
<|body_start_1|>
document = {'source': info['name'], 'timestamp': None, 'user': None, 'clie... | Handles processing the web logs and then uploading data to ElasticSearch | WebLogWorker | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WebLogWorker:
"""Handles processing the web logs and then uploading data to ElasticSearch"""
def format_timestamp(timestamp):
"""Covernt an Apache-style timestamp to one ElasticSearch likes"""
<|body_0|>
def format_info(self, info):
"""Extract the handy bits of d... | stack_v2_sparse_classes_75kplus_train_074547 | 2,838 | no_license | [
{
"docstring": "Covernt an Apache-style timestamp to one ElasticSearch likes",
"name": "format_timestamp",
"signature": "def format_timestamp(timestamp)"
},
{
"docstring": "Extract the handy bits of data into a JSON document",
"name": "format_info",
"signature": "def format_info(self, in... | 2 | null | Implement the Python class `WebLogWorker` described below.
Class description:
Handles processing the web logs and then uploading data to ElasticSearch
Method signatures and docstrings:
- def format_timestamp(timestamp): Covernt an Apache-style timestamp to one ElasticSearch likes
- def format_info(self, info): Extrac... | Implement the Python class `WebLogWorker` described below.
Class description:
Handles processing the web logs and then uploading data to ElasticSearch
Method signatures and docstrings:
- def format_timestamp(timestamp): Covernt an Apache-style timestamp to one ElasticSearch likes
- def format_info(self, info): Extrac... | 576bdb1983eb950e507ba5719eae4c75c6a59bc7 | <|skeleton|>
class WebLogWorker:
"""Handles processing the web logs and then uploading data to ElasticSearch"""
def format_timestamp(timestamp):
"""Covernt an Apache-style timestamp to one ElasticSearch likes"""
<|body_0|>
def format_info(self, info):
"""Extract the handy bits of d... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class WebLogWorker:
"""Handles processing the web logs and then uploading data to ElasticSearch"""
def format_timestamp(timestamp):
"""Covernt an Apache-style timestamp to one ElasticSearch likes"""
pattern = '[%d/%b/%Y:%H:%M:%S'
time_struct = time.strptime(timestamp, pattern)
f... | the_stack_v2_python_sparse | kafka/log_processor/processors/weblog.py | willnx/autobox | train | 1 |
71db5cbd70964ce4d7cedfda878d3e4ca3ba9c12 | [
"data_format = {'nickName': fields.String, 'national_id': fields.String, 'mobile': fields.String, 'sex': fields.Integer, 'language': fields.String, 'birthday': fields.String, 'status': fields.Integer}\nargs = uid_token_parser.parse_args()\ntry:\n member = check_token(uid=args['uid'], token=args['token'], fake=Fa... | <|body_start_0|>
data_format = {'nickName': fields.String, 'national_id': fields.String, 'mobile': fields.String, 'sex': fields.Integer, 'language': fields.String, 'birthday': fields.String, 'status': fields.Integer}
args = uid_token_parser.parse_args()
try:
member = check_token(uid=... | MemberInfoApi | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MemberInfoApi:
def get(self):
"""获取会员信息 获取昵称、头像、性别、状态、数等个人信息 --- tags: - 会员接口 parameters: - name: uid in: query required: true description: 用户id schema: type: string - name: token in: query required: true description: AccessToken schema: type: string responses: 200: description: code=0为正... | stack_v2_sparse_classes_75kplus_train_074548 | 26,273 | no_license | [
{
"docstring": "获取会员信息 获取昵称、头像、性别、状态、数等个人信息 --- tags: - 会员接口 parameters: - name: uid in: query required: true description: 用户id schema: type: string - name: token in: query required: true description: AccessToken schema: type: string responses: 200: description: code=0为正常，返回用户信息；code不等于0请查看message中的错误信息； nickna... | 2 | stack_v2_sparse_classes_30k_train_018776 | Implement the Python class `MemberInfoApi` described below.
Class description:
Implement the MemberInfoApi class.
Method signatures and docstrings:
- def get(self): 获取会员信息 获取昵称、头像、性别、状态、数等个人信息 --- tags: - 会员接口 parameters: - name: uid in: query required: true description: 用户id schema: type: string - name: token in: qu... | Implement the Python class `MemberInfoApi` described below.
Class description:
Implement the MemberInfoApi class.
Method signatures and docstrings:
- def get(self): 获取会员信息 获取昵称、头像、性别、状态、数等个人信息 --- tags: - 会员接口 parameters: - name: uid in: query required: true description: 用户id schema: type: string - name: token in: qu... | 91a23ac732b85b62072720deca9f3796d0af4a2d | <|skeleton|>
class MemberInfoApi:
def get(self):
"""获取会员信息 获取昵称、头像、性别、状态、数等个人信息 --- tags: - 会员接口 parameters: - name: uid in: query required: true description: 用户id schema: type: string - name: token in: query required: true description: AccessToken schema: type: string responses: 200: description: code=0为正... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MemberInfoApi:
def get(self):
"""获取会员信息 获取昵称、头像、性别、状态、数等个人信息 --- tags: - 会员接口 parameters: - name: uid in: query required: true description: 用户id schema: type: string - name: token in: query required: true description: AccessToken schema: type: string responses: 200: description: code=0为正常，返回用户信息；code不... | the_stack_v2_python_sparse | main/controllers/api/member.py | maxcl730/my-scaffold | train | 0 | |
135bcce517075c3ac2229ca1cca207b404282879 | [
"if len(prices) < 2:\n return 0\ndp = [[0 for _ in range(2)] for _ in range(len(prices))]\ndp[0][0] = 0\ndp[0][1] = -prices[0]\nfor i in range(1, len(prices)):\n dp[i][0] = max(dp[i - 1][0], dp[i - 1][1] + prices[i])\n dp[i][1] = max(dp[i - 1][1], dp[i - 1][0] - prices[i])\nreturn dp[-1][0]",
"if len(pri... | <|body_start_0|>
if len(prices) < 2:
return 0
dp = [[0 for _ in range(2)] for _ in range(len(prices))]
dp[0][0] = 0
dp[0][1] = -prices[0]
for i in range(1, len(prices)):
dp[i][0] = max(dp[i - 1][0], dp[i - 1][1] + prices[i])
dp[i][1] = max(dp[i... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxProfit(self, prices: List[int]) -> int:
"""动态规划 股票可以多次交易，在再次购买前需要出售掉之前的股票，同一天不能同时卖出买入 以i表示天数，用0、1表示未持股 或者 持股状态，方程表示为dp[i][0]、dp[i][1] dp[i][0] 表示第i天未持股，分为两种情况: 1. 昨天未持股，今天未持股 2. 昨天持股，今天卖出 方程表示为 dp[i][0] = max(dp[i - 1][0], dp[i - 1][1] + prices[i]) dp[i][1] 表示第i天持股，分为两种情... | stack_v2_sparse_classes_75kplus_train_074549 | 2,732 | no_license | [
{
"docstring": "动态规划 股票可以多次交易，在再次购买前需要出售掉之前的股票，同一天不能同时卖出买入 以i表示天数，用0、1表示未持股 或者 持股状态，方程表示为dp[i][0]、dp[i][1] dp[i][0] 表示第i天未持股，分为两种情况: 1. 昨天未持股，今天未持股 2. 昨天持股，今天卖出 方程表示为 dp[i][0] = max(dp[i - 1][0], dp[i - 1][1] + prices[i]) dp[i][1] 表示第i天持股，分为两种情况 1. 昨天未持股，今天买入 2. 昨天持股，今天不动 因为可以多次买卖，使用前面的利润减去今天买入的价格，为当前持有现金 方程表示为... | 2 | stack_v2_sparse_classes_30k_train_023777 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxProfit(self, prices: List[int]) -> int: 动态规划 股票可以多次交易，在再次购买前需要出售掉之前的股票，同一天不能同时卖出买入 以i表示天数，用0、1表示未持股 或者 持股状态，方程表示为dp[i][0]、dp[i][1] dp[i][0] 表示第i天未持股，分为两种情况: 1. 昨天未持股，今天未持股... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxProfit(self, prices: List[int]) -> int: 动态规划 股票可以多次交易，在再次购买前需要出售掉之前的股票，同一天不能同时卖出买入 以i表示天数，用0、1表示未持股 或者 持股状态，方程表示为dp[i][0]、dp[i][1] dp[i][0] 表示第i天未持股，分为两种情况: 1. 昨天未持股，今天未持股... | 9acba92695c06406f12f997a720bfe1deb9464a8 | <|skeleton|>
class Solution:
def maxProfit(self, prices: List[int]) -> int:
"""动态规划 股票可以多次交易，在再次购买前需要出售掉之前的股票，同一天不能同时卖出买入 以i表示天数，用0、1表示未持股 或者 持股状态，方程表示为dp[i][0]、dp[i][1] dp[i][0] 表示第i天未持股，分为两种情况: 1. 昨天未持股，今天未持股 2. 昨天持股，今天卖出 方程表示为 dp[i][0] = max(dp[i - 1][0], dp[i - 1][1] + prices[i]) dp[i][1] 表示第i天持股，分为两种情... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def maxProfit(self, prices: List[int]) -> int:
"""动态规划 股票可以多次交易，在再次购买前需要出售掉之前的股票，同一天不能同时卖出买入 以i表示天数，用0、1表示未持股 或者 持股状态，方程表示为dp[i][0]、dp[i][1] dp[i][0] 表示第i天未持股，分为两种情况: 1. 昨天未持股，今天未持股 2. 昨天持股，今天卖出 方程表示为 dp[i][0] = max(dp[i - 1][0], dp[i - 1][1] + prices[i]) dp[i][1] 表示第i天持股，分为两种情况 1. 昨天未持股，今天买... | the_stack_v2_python_sparse | datastructure/dp_exercise/MaxProfit2.py | yinhuax/leet_code | train | 0 | |
2a4d6f68db9b63d5d26253d58fb1b43cdb25206e | [
"last_comment_by = self.data.get('last_comment_by', None)\nif last_comment_by is None:\n last_comment_by = self.BASE_LAST_COMMENT_BY.copy()\nnow = datetime.datetime.utcnow().isoformat()\nif is_public is True:\n last_comment_by['public']['name'] = user.get_initials()\n last_comment_by['public']['date_of'] =... | <|body_start_0|>
last_comment_by = self.data.get('last_comment_by', None)
if last_comment_by is None:
last_comment_by = self.BASE_LAST_COMMENT_BY.copy()
now = datetime.datetime.utcnow().isoformat()
if is_public is True:
last_comment_by['public']['name'] = user.get... | Save the last comment (public|privileged) in the data field | ItemLastCommentByMixin | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ItemLastCommentByMixin:
"""Save the last comment (public|privileged) in the data field"""
def set_last_comment_by(self, is_public, user):
"""Save in our data field the appropriate last user info for whoever commented take note that college comments should not be shown to normal users... | stack_v2_sparse_classes_75kplus_train_074550 | 17,116 | no_license | [
{
"docstring": "Save in our data field the appropriate last user info for whoever commented take note that college comments should not be shown to normal users",
"name": "set_last_comment_by",
"signature": "def set_last_comment_by(self, is_public, user)"
},
{
"docstring": "So get the last commen... | 2 | stack_v2_sparse_classes_30k_train_000800 | Implement the Python class `ItemLastCommentByMixin` described below.
Class description:
Save the last comment (public|privileged) in the data field
Method signatures and docstrings:
- def set_last_comment_by(self, is_public, user): Save in our data field the appropriate last user info for whoever commented take note ... | Implement the Python class `ItemLastCommentByMixin` described below.
Class description:
Save the last comment (public|privileged) in the data field
Method signatures and docstrings:
- def set_last_comment_by(self, is_public, user): Save in our data field the appropriate last user info for whoever commented take note ... | cdda3dd17a776bf2a07fe093304160bf3c43199b | <|skeleton|>
class ItemLastCommentByMixin:
"""Save the last comment (public|privileged) in the data field"""
def set_last_comment_by(self, is_public, user):
"""Save in our data field the appropriate last user info for whoever commented take note that college comments should not be shown to normal users... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ItemLastCommentByMixin:
"""Save the last comment (public|privileged) in the data field"""
def set_last_comment_by(self, is_public, user):
"""Save in our data field the appropriate last user info for whoever commented take note that college comments should not be shown to normal users"""
l... | the_stack_v2_python_sparse | toolkit/core/item/mixins.py | rosscdh/toolkit | train | 1 |
43a27f38ee70629ed5aa7de8bcacfda8c8146891 | [
"self.public_key_hash = public_key_hash\nself.ephemeral_public_key = ephemeral_public_key\nself.transaction_id = transaction_id",
"if dictionary is None:\n return None\nephemeral_public_key = dictionary.get('ephemeral_public_key')\npublic_key_hash = dictionary.get('public_key_hash')\ntransaction_id = dictionar... | <|body_start_0|>
self.public_key_hash = public_key_hash
self.ephemeral_public_key = ephemeral_public_key
self.transaction_id = transaction_id
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
ephemeral_public_key = dictionary.get('ephemeral_public_ke... | Implementation of the 'CreateApplePayHeaderRequest' model. The ApplePay header request Attributes: public_key_hash (string): SHA–256 hash, Base64 string codified ephemeral_public_key (string): X.509 encoded key bytes, Base64 encoded as a string transaction_id (string): Transaction identifier, generated on Device | CreateApplePayHeaderRequest | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CreateApplePayHeaderRequest:
"""Implementation of the 'CreateApplePayHeaderRequest' model. The ApplePay header request Attributes: public_key_hash (string): SHA–256 hash, Base64 string codified ephemeral_public_key (string): X.509 encoded key bytes, Base64 encoded as a string transaction_id (stri... | stack_v2_sparse_classes_75kplus_train_074551 | 2,190 | permissive | [
{
"docstring": "Constructor for the CreateApplePayHeaderRequest class",
"name": "__init__",
"signature": "def __init__(self, ephemeral_public_key=None, public_key_hash=None, transaction_id=None)"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: dictionary (dictionary)... | 2 | stack_v2_sparse_classes_30k_train_046009 | Implement the Python class `CreateApplePayHeaderRequest` described below.
Class description:
Implementation of the 'CreateApplePayHeaderRequest' model. The ApplePay header request Attributes: public_key_hash (string): SHA–256 hash, Base64 string codified ephemeral_public_key (string): X.509 encoded key bytes, Base64 e... | Implement the Python class `CreateApplePayHeaderRequest` described below.
Class description:
Implementation of the 'CreateApplePayHeaderRequest' model. The ApplePay header request Attributes: public_key_hash (string): SHA–256 hash, Base64 string codified ephemeral_public_key (string): X.509 encoded key bytes, Base64 e... | 95c80c35dd57bb2a238faeaf30d1e3b4544d2298 | <|skeleton|>
class CreateApplePayHeaderRequest:
"""Implementation of the 'CreateApplePayHeaderRequest' model. The ApplePay header request Attributes: public_key_hash (string): SHA–256 hash, Base64 string codified ephemeral_public_key (string): X.509 encoded key bytes, Base64 encoded as a string transaction_id (stri... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CreateApplePayHeaderRequest:
"""Implementation of the 'CreateApplePayHeaderRequest' model. The ApplePay header request Attributes: public_key_hash (string): SHA–256 hash, Base64 string codified ephemeral_public_key (string): X.509 encoded key bytes, Base64 encoded as a string transaction_id (string): Transact... | the_stack_v2_python_sparse | mundiapi/models/create_apple_pay_header_request.py | mundipagg/MundiAPI-PYTHON | train | 10 |
4dac33b2d008d235362c4a7055977c2ecf27fc2f | [
"study_id = root._get_study_id(info)\ninvited_by = Membership.objects.get(collaborator=root.node.id, study=study_id).invited_by\nreturn invited_by",
"study_id = root._get_study_id(info)\njoined_on = Membership.objects.get(collaborator=root.node.id, study=study_id).joined_on\nreturn joined_on",
"study_id = root.... | <|body_start_0|>
study_id = root._get_study_id(info)
invited_by = Membership.objects.get(collaborator=root.node.id, study=study_id).invited_by
return invited_by
<|end_body_0|>
<|body_start_1|>
study_id = root._get_study_id(info)
joined_on = Membership.objects.get(collaborator=ro... | Extends relay edges on study-collaborator relationships to include information from the 'Membership' through-table. | Edge | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Edge:
"""Extends relay edges on study-collaborator relationships to include information from the 'Membership' through-table."""
def resolve_invited_by(root, info, **kwargs):
"""Returns the user that invited this collaborator to the study."""
<|body_0|>
def resolve_joined... | stack_v2_sparse_classes_75kplus_train_074552 | 5,435 | permissive | [
{
"docstring": "Returns the user that invited this collaborator to the study.",
"name": "resolve_invited_by",
"signature": "def resolve_invited_by(root, info, **kwargs)"
},
{
"docstring": "Returns the date the collaborator joined the study.",
"name": "resolve_joined_on",
"signature": "de... | 4 | stack_v2_sparse_classes_30k_train_044541 | Implement the Python class `Edge` described below.
Class description:
Extends relay edges on study-collaborator relationships to include information from the 'Membership' through-table.
Method signatures and docstrings:
- def resolve_invited_by(root, info, **kwargs): Returns the user that invited this collaborator to... | Implement the Python class `Edge` described below.
Class description:
Extends relay edges on study-collaborator relationships to include information from the 'Membership' through-table.
Method signatures and docstrings:
- def resolve_invited_by(root, info, **kwargs): Returns the user that invited this collaborator to... | ba62b369e6464259ea92dbb9ba49876513f37fba | <|skeleton|>
class Edge:
"""Extends relay edges on study-collaborator relationships to include information from the 'Membership' through-table."""
def resolve_invited_by(root, info, **kwargs):
"""Returns the user that invited this collaborator to the study."""
<|body_0|>
def resolve_joined... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Edge:
"""Extends relay edges on study-collaborator relationships to include information from the 'Membership' through-table."""
def resolve_invited_by(root, info, **kwargs):
"""Returns the user that invited this collaborator to the study."""
study_id = root._get_study_id(info)
inv... | the_stack_v2_python_sparse | creator/users/schema.py | kids-first/kf-api-study-creator | train | 3 |
b193964771e915d36308ed16fb9105f49ee8ca8b | [
"Parametre.__init__(self, 'descendre', 'lower')\nself.schema = '<texte_libre>'\nself.aide_courte = 'descend un canot'\nself.aide_longue = \"Cette commande permet de descendre un canot qui se trouve sur le pont du navire où vous vous trouvez. Vous devez vous tenir près d'un bossoir, permettant de faire descendre le ... | <|body_start_0|>
Parametre.__init__(self, 'descendre', 'lower')
self.schema = '<texte_libre>'
self.aide_courte = 'descend un canot'
self.aide_longue = "Cette commande permet de descendre un canot qui se trouve sur le pont du navire où vous vous trouvez. Vous devez vous tenir près d'un bo... | Commande 'canot descendre'. | PrmDescendre | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PrmDescendre:
"""Commande 'canot descendre'."""
def __init__(self):
"""Constructeur du paramètre"""
<|body_0|>
def interpreter(self, personnage, dic_masques):
"""Interprétation du paramètre."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
Parame... | stack_v2_sparse_classes_75kplus_train_074553 | 3,513 | permissive | [
{
"docstring": "Constructeur du paramètre",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Interprétation du paramètre.",
"name": "interpreter",
"signature": "def interpreter(self, personnage, dic_masques)"
}
] | 2 | stack_v2_sparse_classes_30k_train_040499 | Implement the Python class `PrmDescendre` described below.
Class description:
Commande 'canot descendre'.
Method signatures and docstrings:
- def __init__(self): Constructeur du paramètre
- def interpreter(self, personnage, dic_masques): Interprétation du paramètre. | Implement the Python class `PrmDescendre` described below.
Class description:
Commande 'canot descendre'.
Method signatures and docstrings:
- def __init__(self): Constructeur du paramètre
- def interpreter(self, personnage, dic_masques): Interprétation du paramètre.
<|skeleton|>
class PrmDescendre:
"""Commande '... | 7e93bff08cdf891352efba587e89c40f3b4a2301 | <|skeleton|>
class PrmDescendre:
"""Commande 'canot descendre'."""
def __init__(self):
"""Constructeur du paramètre"""
<|body_0|>
def interpreter(self, personnage, dic_masques):
"""Interprétation du paramètre."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PrmDescendre:
"""Commande 'canot descendre'."""
def __init__(self):
"""Constructeur du paramètre"""
Parametre.__init__(self, 'descendre', 'lower')
self.schema = '<texte_libre>'
self.aide_courte = 'descend un canot'
self.aide_longue = "Cette commande permet de desce... | the_stack_v2_python_sparse | src/secondaires/navigation/commandes/canot/descendre.py | vincent-lg/tsunami | train | 5 |
9ed1c21bf475e216d2be29f34e067f263c906c73 | [
"self.file_path = file_path\nif not os.path.isfile(self.file_path):\n raise ValueError('File path %s is not a valid file' % self.file_path)\ntry:\n import extract_msg\nexcept ImportError:\n raise ImportError('extract_msg is not installed. Please install it with `pip install extract_msg`')",
"import extra... | <|body_start_0|>
self.file_path = file_path
if not os.path.isfile(self.file_path):
raise ValueError('File path %s is not a valid file' % self.file_path)
try:
import extract_msg
except ImportError:
raise ImportError('extract_msg is not installed. Please... | Loader that loads Outlook Message files using extract_msg. https://github.com/TeamMsgExtractor/msg-extractor | OutlookMessageLoader | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OutlookMessageLoader:
"""Loader that loads Outlook Message files using extract_msg. https://github.com/TeamMsgExtractor/msg-extractor"""
def __init__(self, file_path: str):
"""Initialize with file path."""
<|body_0|>
def load(self) -> List[Document]:
"""Load data... | stack_v2_sparse_classes_75kplus_train_074554 | 2,270 | no_license | [
{
"docstring": "Initialize with file path.",
"name": "__init__",
"signature": "def __init__(self, file_path: str)"
},
{
"docstring": "Load data into document objects.",
"name": "load",
"signature": "def load(self) -> List[Document]"
}
] | 2 | stack_v2_sparse_classes_30k_train_035818 | Implement the Python class `OutlookMessageLoader` described below.
Class description:
Loader that loads Outlook Message files using extract_msg. https://github.com/TeamMsgExtractor/msg-extractor
Method signatures and docstrings:
- def __init__(self, file_path: str): Initialize with file path.
- def load(self) -> List... | Implement the Python class `OutlookMessageLoader` described below.
Class description:
Loader that loads Outlook Message files using extract_msg. https://github.com/TeamMsgExtractor/msg-extractor
Method signatures and docstrings:
- def __init__(self, file_path: str): Initialize with file path.
- def load(self) -> List... | b7aaa920a52613e3f1f04fa5cd7568ad37302d11 | <|skeleton|>
class OutlookMessageLoader:
"""Loader that loads Outlook Message files using extract_msg. https://github.com/TeamMsgExtractor/msg-extractor"""
def __init__(self, file_path: str):
"""Initialize with file path."""
<|body_0|>
def load(self) -> List[Document]:
"""Load data... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class OutlookMessageLoader:
"""Loader that loads Outlook Message files using extract_msg. https://github.com/TeamMsgExtractor/msg-extractor"""
def __init__(self, file_path: str):
"""Initialize with file path."""
self.file_path = file_path
if not os.path.isfile(self.file_path):
... | the_stack_v2_python_sparse | openai/venv/lib64/python3.10/site-packages/langchain/document_loaders/email.py | henrymendez/garage | train | 0 |
c83223d4b0ecbaa9b38d97d701a5af57169bb9b8 | [
"self.features = []\nself.feature_vectors = []\nself.__select_features(weights)\nfor feature_set in self.features:\n self.__generate_dataset(weights, documents, feature_set)",
"features = set()\nscores = dict([])\nfor doc, doc_dict in weights.iteritems():\n top = dict(sorted(doc_dict.iteritems(), key=operat... | <|body_start_0|>
self.features = []
self.feature_vectors = []
self.__select_features(weights)
for feature_set in self.features:
self.__generate_dataset(weights, documents, feature_set)
<|end_body_0|>
<|body_start_1|>
features = set()
scores = dict([])
... | FeatureSelector | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FeatureSelector:
def __init__(self, weights, documents):
"""function: constructor --------------------- select features and generate feature vector sets from @documents :param weights: table of (document,word) tf-idf scores :param documents: list of document objects"""
<|body_0|>... | stack_v2_sparse_classes_75kplus_train_074555 | 4,307 | no_license | [
{
"docstring": "function: constructor --------------------- select features and generate feature vector sets from @documents :param weights: table of (document,word) tf-idf scores :param documents: list of document objects",
"name": "__init__",
"signature": "def __init__(self, weights, documents)"
},
... | 3 | stack_v2_sparse_classes_30k_train_023647 | Implement the Python class `FeatureSelector` described below.
Class description:
Implement the FeatureSelector class.
Method signatures and docstrings:
- def __init__(self, weights, documents): function: constructor --------------------- select features and generate feature vector sets from @documents :param weights:... | Implement the Python class `FeatureSelector` described below.
Class description:
Implement the FeatureSelector class.
Method signatures and docstrings:
- def __init__(self, weights, documents): function: constructor --------------------- select features and generate feature vector sets from @documents :param weights:... | 068662ed9399b136b3098c7706ee89717eef0bf5 | <|skeleton|>
class FeatureSelector:
def __init__(self, weights, documents):
"""function: constructor --------------------- select features and generate feature vector sets from @documents :param weights: table of (document,word) tf-idf scores :param documents: list of document objects"""
<|body_0|>... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class FeatureSelector:
def __init__(self, weights, documents):
"""function: constructor --------------------- select features and generate feature vector sets from @documents :param weights: table of (document,word) tf-idf scores :param documents: list of document objects"""
self.features = []
... | the_stack_v2_python_sparse | preprocessing/feature/featureselect.py | ankailou/reuters-minwisehash | train | 0 | |
a3c6ecf3305b909da69994f315b291aa05268f44 | [
"self._block_args = block_args\nself._batch_norm_momentum = global_params.batch_norm_momentum\nself._batch_norm_epsilon = global_params.batch_norm_epsilon\nif global_params.data_format == 'channels_first':\n self._channel_axis = 1\n self._spatial_dims = [2, 3]\nelse:\n self._channel_axis = -1\n self._sp... | <|body_start_0|>
self._block_args = block_args
self._batch_norm_momentum = global_params.batch_norm_momentum
self._batch_norm_epsilon = global_params.batch_norm_epsilon
if global_params.data_format == 'channels_first':
self._channel_axis = 1
self._spatial_dims = [... | A class of MnasNet/MobileNetV2 Inveretd Residual Bottleneck. Attributes: has_se: boolean. Whether the block contains a Squeeze and Excitation layer inside. endpoints: dict. A list of internal tensors. | MBConvBlock | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MBConvBlock:
"""A class of MnasNet/MobileNetV2 Inveretd Residual Bottleneck. Attributes: has_se: boolean. Whether the block contains a Squeeze and Excitation layer inside. endpoints: dict. A list of internal tensors."""
def __init__(self, block_args, global_params, layer_runtimes, dropout_ra... | stack_v2_sparse_classes_75kplus_train_074556 | 18,413 | permissive | [
{
"docstring": "Initializes a MBConv block. Args: block_args: BlockArgs, arguments to create a MnasBlock. global_params: GlobalParams, a set of global parameters.",
"name": "__init__",
"signature": "def __init__(self, block_args, global_params, layer_runtimes, dropout_rate)"
},
{
"docstring": "B... | 4 | null | Implement the Python class `MBConvBlock` described below.
Class description:
A class of MnasNet/MobileNetV2 Inveretd Residual Bottleneck. Attributes: has_se: boolean. Whether the block contains a Squeeze and Excitation layer inside. endpoints: dict. A list of internal tensors.
Method signatures and docstrings:
- def ... | Implement the Python class `MBConvBlock` described below.
Class description:
A class of MnasNet/MobileNetV2 Inveretd Residual Bottleneck. Attributes: has_se: boolean. Whether the block contains a Squeeze and Excitation layer inside. endpoints: dict. A list of internal tensors.
Method signatures and docstrings:
- def ... | 5c3090487c7222e20f62df02aac910482b15877c | <|skeleton|>
class MBConvBlock:
"""A class of MnasNet/MobileNetV2 Inveretd Residual Bottleneck. Attributes: has_se: boolean. Whether the block contains a Squeeze and Excitation layer inside. endpoints: dict. A list of internal tensors."""
def __init__(self, block_args, global_params, layer_runtimes, dropout_ra... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MBConvBlock:
"""A class of MnasNet/MobileNetV2 Inveretd Residual Bottleneck. Attributes: has_se: boolean. Whether the block contains a Squeeze and Excitation layer inside. endpoints: dict. A list of internal tensors."""
def __init__(self, block_args, global_params, layer_runtimes, dropout_rate):
... | the_stack_v2_python_sparse | nas-search/singlepath_supernet.py | RoxaneFis/single-path-nas | train | 1 |
1718fd0de16a4973603bc47f724bde41fbcbc2fe | [
"p = prehead = ListNode()\ncarry = 0\nwhile l1 or l2:\n s = carry\n if l1:\n s += l1.val\n l1 = l1.next\n if l2:\n s += l2.val\n l2 = l2.next\n carry = s // 10\n p.next = ListNode(s % 10)\n p = p.next\nif carry:\n p.next = ListNode(carry)\nreturn prehead.next",
"de... | <|body_start_0|>
p = prehead = ListNode()
carry = 0
while l1 or l2:
s = carry
if l1:
s += l1.val
l1 = l1.next
if l2:
s += l2.val
l2 = l2.next
carry = s // 10
p.next = ListN... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def addTwoNumbers_v1(self, l1: ListNode, l2: ListNode) -> ListNode:
"""Use a "prehead" to simplify the logic. LeatCode: 64 ms, 14 MB; beats 94.54%"""
<|body_0|>
def addTwoNumbers_v2(self, l1: ListNode, l2: ListNode) -> ListNode:
"""Convert lists to integers... | stack_v2_sparse_classes_75kplus_train_074557 | 3,213 | no_license | [
{
"docstring": "Use a \"prehead\" to simplify the logic. LeatCode: 64 ms, 14 MB; beats 94.54%",
"name": "addTwoNumbers_v1",
"signature": "def addTwoNumbers_v1(self, l1: ListNode, l2: ListNode) -> ListNode"
},
{
"docstring": "Convert lists to integers and then conver the sume of integers back to ... | 2 | stack_v2_sparse_classes_30k_train_035054 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def addTwoNumbers_v1(self, l1: ListNode, l2: ListNode) -> ListNode: Use a "prehead" to simplify the logic. LeatCode: 64 ms, 14 MB; beats 94.54%
- def addTwoNumbers_v2(self, l1: L... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def addTwoNumbers_v1(self, l1: ListNode, l2: ListNode) -> ListNode: Use a "prehead" to simplify the logic. LeatCode: 64 ms, 14 MB; beats 94.54%
- def addTwoNumbers_v2(self, l1: L... | 97a2386f5e3adbd7138fd123810c3232bdf7f622 | <|skeleton|>
class Solution:
def addTwoNumbers_v1(self, l1: ListNode, l2: ListNode) -> ListNode:
"""Use a "prehead" to simplify the logic. LeatCode: 64 ms, 14 MB; beats 94.54%"""
<|body_0|>
def addTwoNumbers_v2(self, l1: ListNode, l2: ListNode) -> ListNode:
"""Convert lists to integers... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def addTwoNumbers_v1(self, l1: ListNode, l2: ListNode) -> ListNode:
"""Use a "prehead" to simplify the logic. LeatCode: 64 ms, 14 MB; beats 94.54%"""
p = prehead = ListNode()
carry = 0
while l1 or l2:
s = carry
if l1:
s += l1.va... | the_stack_v2_python_sparse | python3/linked_list/add_two_numbers.py | victorchu/algorithms | train | 0 | |
ef1008c216a3347395c0a47a991cb0e09208f576 | [
"super(BaseModule, self).__init__()\nself.cfg = cfg\nself.id = 0\nif self.cfg.VISUALIZATION.ENABLE and self.cfg.VISUALIZATION.FEATURE_MAPS.ENABLE:\n self.base_output_dir = self.cfg.VISUALIZATION.FEATURE_MAPS.BASE_OUTPUT_DIR\n self.register_forward_hook(self.visualize_features)",
"b, c, t, h, w = output_x.sh... | <|body_start_0|>
super(BaseModule, self).__init__()
self.cfg = cfg
self.id = 0
if self.cfg.VISUALIZATION.ENABLE and self.cfg.VISUALIZATION.FEATURE_MAPS.ENABLE:
self.base_output_dir = self.cfg.VISUALIZATION.FEATURE_MAPS.BASE_OUTPUT_DIR
self.register_forward_hook(se... | Constructs base module that contains basic visualization function and corresponding hooks. Note: The visualization function has only tested in the single GPU scenario. By default, the visualization is disabled. | BaseModule | [
"MIT",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BaseModule:
"""Constructs base module that contains basic visualization function and corresponding hooks. Note: The visualization function has only tested in the single GPU scenario. By default, the visualization is disabled."""
def __init__(self, cfg):
"""Args: cfg (Config): global ... | stack_v2_sparse_classes_75kplus_train_074558 | 17,711 | permissive | [
{
"docstring": "Args: cfg (Config): global config object.",
"name": "__init__",
"signature": "def __init__(self, cfg)"
},
{
"docstring": "Visualizes and saves the normalized output features for the module.",
"name": "visualize_features",
"signature": "def visualize_features(self, module,... | 2 | stack_v2_sparse_classes_30k_train_003441 | Implement the Python class `BaseModule` described below.
Class description:
Constructs base module that contains basic visualization function and corresponding hooks. Note: The visualization function has only tested in the single GPU scenario. By default, the visualization is disabled.
Method signatures and docstring... | Implement the Python class `BaseModule` described below.
Class description:
Constructs base module that contains basic visualization function and corresponding hooks. Note: The visualization function has only tested in the single GPU scenario. By default, the visualization is disabled.
Method signatures and docstring... | cfb49fa51a13373e4afc74f8800ec8284c41b8d2 | <|skeleton|>
class BaseModule:
"""Constructs base module that contains basic visualization function and corresponding hooks. Note: The visualization function has only tested in the single GPU scenario. By default, the visualization is disabled."""
def __init__(self, cfg):
"""Args: cfg (Config): global ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class BaseModule:
"""Constructs base module that contains basic visualization function and corresponding hooks. Note: The visualization function has only tested in the single GPU scenario. By default, the visualization is disabled."""
def __init__(self, cfg):
"""Args: cfg (Config): global config object... | the_stack_v2_python_sparse | papers/pytorch-video-understanding/models/base/base_blocks.py | hrb518/EssentialMC2 | train | 1 |
0be23cd4be2fc403cd795bb78123df42e96342de | [
"if user_id is None:\n return None\nsession_id = super().create_session(user_id)\nif session_id is None:\n return None\nuser_session = UserSession(**{'user_id': user_id, 'session_id': session_id})\nuser_session.save()\nreturn session_id",
"if session_id is None:\n return None\nUserSession.load_from_file(... | <|body_start_0|>
if user_id is None:
return None
session_id = super().create_session(user_id)
if session_id is None:
return None
user_session = UserSession(**{'user_id': user_id, 'session_id': session_id})
user_session.save()
return session_id
<|en... | Session to use a DB | SessionDBAuth | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SessionDBAuth:
"""Session to use a DB"""
def create_session(self, user_id=None):
"""Create Session"""
<|body_0|>
def user_id_for_session_id(self, session_id=None):
"""Get the user id for session"""
<|body_1|>
def destroy_session(self, request=None):
... | stack_v2_sparse_classes_75kplus_train_074559 | 1,931 | no_license | [
{
"docstring": "Create Session",
"name": "create_session",
"signature": "def create_session(self, user_id=None)"
},
{
"docstring": "Get the user id for session",
"name": "user_id_for_session_id",
"signature": "def user_id_for_session_id(self, session_id=None)"
},
{
"docstring": "... | 3 | null | Implement the Python class `SessionDBAuth` described below.
Class description:
Session to use a DB
Method signatures and docstrings:
- def create_session(self, user_id=None): Create Session
- def user_id_for_session_id(self, session_id=None): Get the user id for session
- def destroy_session(self, request=None): Dest... | Implement the Python class `SessionDBAuth` described below.
Class description:
Session to use a DB
Method signatures and docstrings:
- def create_session(self, user_id=None): Create Session
- def user_id_for_session_id(self, session_id=None): Get the user id for session
- def destroy_session(self, request=None): Dest... | c37b81be36c1094de838b6ed1e954c635785fabc | <|skeleton|>
class SessionDBAuth:
"""Session to use a DB"""
def create_session(self, user_id=None):
"""Create Session"""
<|body_0|>
def user_id_for_session_id(self, session_id=None):
"""Get the user id for session"""
<|body_1|>
def destroy_session(self, request=None):
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SessionDBAuth:
"""Session to use a DB"""
def create_session(self, user_id=None):
"""Create Session"""
if user_id is None:
return None
session_id = super().create_session(user_id)
if session_id is None:
return None
user_session = UserSession(... | the_stack_v2_python_sparse | 0x07-Session_authentication/api/v1/auth/session_db_auth.py | TzStrikerYT/holbertonschool-web_back_end | train | 2 |
b0a38bf5898cc135cadfdfe9ce0dd37de6983675 | [
"super().__init__()\nself.traverse_edges = ['next']\nself.imdb = imdb\nself.max_error = 0\nself.dtype_required = dtype_required",
"t = edge.get_target()\nif type(t) is KerasLayerNode and callable(t.func):\n l = t.func([np.array(self.imdb)])\n t.out_max = np.max(l)\n t.out_min = np.min(l)\nreturn True",
... | <|body_start_0|>
super().__init__()
self.traverse_edges = ['next']
self.imdb = imdb
self.max_error = 0
self.dtype_required = dtype_required
<|end_body_0|>
<|body_start_1|>
t = edge.get_target()
if type(t) is KerasLayerNode and callable(t.func):
l = t.... | Action to apply quantization where possible | QuantizeAction | [
"LicenseRef-scancode-unknown-license-reference",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class QuantizeAction:
"""Action to apply quantization where possible"""
def __init__(self, imdb, dtype_required):
"""Init this class."""
<|body_0|>
def _pre_action(self, edge) -> bool:
"""Called on every visited edge. Used to determine what values actual appear. Max an... | stack_v2_sparse_classes_75kplus_train_074560 | 2,075 | permissive | [
{
"docstring": "Init this class.",
"name": "__init__",
"signature": "def __init__(self, imdb, dtype_required)"
},
{
"docstring": "Called on every visited edge. Used to determine what values actual appear. Max and min of these values are used later to determine the scaling factor. :param edge: Th... | 3 | null | Implement the Python class `QuantizeAction` described below.
Class description:
Action to apply quantization where possible
Method signatures and docstrings:
- def __init__(self, imdb, dtype_required): Init this class.
- def _pre_action(self, edge) -> bool: Called on every visited edge. Used to determine what values ... | Implement the Python class `QuantizeAction` described below.
Class description:
Action to apply quantization where possible
Method signatures and docstrings:
- def __init__(self, imdb, dtype_required): Init this class.
- def _pre_action(self, edge) -> bool: Called on every visited edge. Used to determine what values ... | 987b0efeb56cd150b3a34b672fd5eba05e6d491f | <|skeleton|>
class QuantizeAction:
"""Action to apply quantization where possible"""
def __init__(self, imdb, dtype_required):
"""Init this class."""
<|body_0|>
def _pre_action(self, edge) -> bool:
"""Called on every visited edge. Used to determine what values actual appear. Max an... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class QuantizeAction:
"""Action to apply quantization where possible"""
def __init__(self, imdb, dtype_required):
"""Init this class."""
super().__init__()
self.traverse_edges = ['next']
self.imdb = imdb
self.max_error = 0
self.dtype_required = dtype_required
... | the_stack_v2_python_sparse | nncg/traverse/actions/quantizeaction.py | iml130/nncg | train | 34 |
454ebd2873a32f9884ad44db5f2932cc849af4d9 | [
"\"\"\"\n _ h o r s e\n _ 0 1 2 3 4 5\n o 1 1 1 2 3 4\n r 2 2 2 1 2 3\n s 3 3 2 2 1 2\n\n \"\"\"\nif not word1 or not word2:\n return max(len(word1), len(word2))\nmemo = [j + 1 for j in range(len(word2))]\nfor i in range(len(word1)):\n new_memo = []\n for j in ra... | <|body_start_0|>
"""
_ h o r s e
_ 0 1 2 3 4 5
o 1 1 1 2 3 4
r 2 2 2 1 2 3
s 3 3 2 2 1 2
"""
if not word1 or not word2:
return max(len(word1), len(word2))
memo = [j + 1 for j in range(l... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def minDistance(self, word1, word2):
"""Aug 11, 2018 05:20 :type word1: str :type word2: str :rtype: int"""
<|body_0|>
def minDistance(self, word1: str, word2: str) -> int:
"""Apr 02, 2023 14:14"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_75kplus_train_074561 | 2,724 | no_license | [
{
"docstring": "Aug 11, 2018 05:20 :type word1: str :type word2: str :rtype: int",
"name": "minDistance",
"signature": "def minDistance(self, word1, word2)"
},
{
"docstring": "Apr 02, 2023 14:14",
"name": "minDistance",
"signature": "def minDistance(self, word1: str, word2: str) -> int"
... | 2 | stack_v2_sparse_classes_30k_val_001480 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def minDistance(self, word1, word2): Aug 11, 2018 05:20 :type word1: str :type word2: str :rtype: int
- def minDistance(self, word1: str, word2: str) -> int: Apr 02, 2023 14:14 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def minDistance(self, word1, word2): Aug 11, 2018 05:20 :type word1: str :type word2: str :rtype: int
- def minDistance(self, word1: str, word2: str) -> int: Apr 02, 2023 14:14
... | 1389a009a02e90e8700a7a00e0b7f797c129cdf4 | <|skeleton|>
class Solution:
def minDistance(self, word1, word2):
"""Aug 11, 2018 05:20 :type word1: str :type word2: str :rtype: int"""
<|body_0|>
def minDistance(self, word1: str, word2: str) -> int:
"""Apr 02, 2023 14:14"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def minDistance(self, word1, word2):
"""Aug 11, 2018 05:20 :type word1: str :type word2: str :rtype: int"""
"""
_ h o r s e
_ 0 1 2 3 4 5
o 1 1 1 2 3 4
r 2 2 2 1 2 3
s 3 3 2 2 1 2
"""
... | the_stack_v2_python_sparse | leetcode/solved/72_Edit_Distance/solution.py | sungminoh/algorithms | train | 0 | |
854d7a1d91d77c75110ba04b006e9c230305f6b1 | [
"receiver = cls()\nactivity = receiver.__app__.widget\nreceiver.setReceiver(receiver.getId())\n\ndef on_receive(ctx, intent):\n callback(intent)\nreceiver.onReceive.connect(on_receive)\nactivity.registerReceiver(receiver, IntentFilter(action))\nreturn receiver",
"activity = self.__app__.widget\nactivity.unregi... | <|body_start_0|>
receiver = cls()
activity = receiver.__app__.widget
receiver.setReceiver(receiver.getId())
def on_receive(ctx, intent):
callback(intent)
receiver.onReceive.connect(on_receive)
activity.registerReceiver(receiver, IntentFilter(action))
... | A BroadcastReceiver that delegates to a listener | BroadcastReceiver | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BroadcastReceiver:
"""A BroadcastReceiver that delegates to a listener"""
def for_action(cls, action, callback, single_shot=True):
"""Create a BroadcastReceiver that is invoked when the given action is received. Parameters ---------- action: String Action to receive callback: Callabl... | stack_v2_sparse_classes_75kplus_train_074562 | 10,095 | permissive | [
{
"docstring": "Create a BroadcastReceiver that is invoked when the given action is received. Parameters ---------- action: String Action to receive callback: Callable Callback to invoke when the action is received single_shot: Bool Cleanup after one callback Returns ------- receiver: BroadcastReceiver The rece... | 2 | stack_v2_sparse_classes_30k_train_029643 | Implement the Python class `BroadcastReceiver` described below.
Class description:
A BroadcastReceiver that delegates to a listener
Method signatures and docstrings:
- def for_action(cls, action, callback, single_shot=True): Create a BroadcastReceiver that is invoked when the given action is received. Parameters ----... | Implement the Python class `BroadcastReceiver` described below.
Class description:
A BroadcastReceiver that delegates to a listener
Method signatures and docstrings:
- def for_action(cls, action, callback, single_shot=True): Create a BroadcastReceiver that is invoked when the given action is received. Parameters ----... | 04c3a015bcd649f374c5ecd98fcddba5e4fbdbdc | <|skeleton|>
class BroadcastReceiver:
"""A BroadcastReceiver that delegates to a listener"""
def for_action(cls, action, callback, single_shot=True):
"""Create a BroadcastReceiver that is invoked when the given action is received. Parameters ---------- action: String Action to receive callback: Callabl... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class BroadcastReceiver:
"""A BroadcastReceiver that delegates to a listener"""
def for_action(cls, action, callback, single_shot=True):
"""Create a BroadcastReceiver that is invoked when the given action is received. Parameters ---------- action: String Action to receive callback: Callable Callback to... | the_stack_v2_python_sparse | src/enamlnative/android/android_content.py | mfkiwl/enaml-native | train | 0 |
c64bf9ad1b0ed6a9c98fce6714301bc0819ad185 | [
"def memoize(N: int) -> int:\n if N <= 1:\n return N\n if N in self.cache.keys():\n return self.cache[N]\n self.cache[N] = memoize(N - 1) + memoize(N - 2)\n return memoize(N)\nself.cache = {0: 0, 1: 1}\nreturn memoize(N)",
"if N < 2:\n return N\ndp = [0] * (N + 1)\ndp[0], dp[1] = (0, ... | <|body_start_0|>
def memoize(N: int) -> int:
if N <= 1:
return N
if N in self.cache.keys():
return self.cache[N]
self.cache[N] = memoize(N - 1) + memoize(N - 2)
return memoize(N)
self.cache = {0: 0, 1: 1}
return memo... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def fib(self, N: int) -> int:
"""递归超时，记忆化递归实现(数组/哈希表)"""
<|body_0|>
def fib1(self, N: int) -> int:
"""递归(自上而下)超时，循环实现(自下而上)"""
<|body_1|>
def fib2(self, N: int) -> int:
"""空间复杂度：O(1)"""
<|body_2|>
<|end_skeleton|>
<|body_start... | stack_v2_sparse_classes_75kplus_train_074563 | 1,986 | permissive | [
{
"docstring": "递归超时，记忆化递归实现(数组/哈希表)",
"name": "fib",
"signature": "def fib(self, N: int) -> int"
},
{
"docstring": "递归(自上而下)超时，循环实现(自下而上)",
"name": "fib1",
"signature": "def fib1(self, N: int) -> int"
},
{
"docstring": "空间复杂度：O(1)",
"name": "fib2",
"signature": "def fib2... | 3 | stack_v2_sparse_classes_30k_train_036512 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def fib(self, N: int) -> int: 递归超时，记忆化递归实现(数组/哈希表)
- def fib1(self, N: int) -> int: 递归(自上而下)超时，循环实现(自下而上)
- def fib2(self, N: int) -> int: 空间复杂度：O(1) | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def fib(self, N: int) -> int: 递归超时，记忆化递归实现(数组/哈希表)
- def fib1(self, N: int) -> int: 递归(自上而下)超时，循环实现(自下而上)
- def fib2(self, N: int) -> int: 空间复杂度：O(1)
<|skeleton|>
class Solution... | e8a1c6cae6547cbcb6e8494be6df685f3e7c837c | <|skeleton|>
class Solution:
def fib(self, N: int) -> int:
"""递归超时，记忆化递归实现(数组/哈希表)"""
<|body_0|>
def fib1(self, N: int) -> int:
"""递归(自上而下)超时，循环实现(自下而上)"""
<|body_1|>
def fib2(self, N: int) -> int:
"""空间复杂度：O(1)"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def fib(self, N: int) -> int:
"""递归超时，记忆化递归实现(数组/哈希表)"""
def memoize(N: int) -> int:
if N <= 1:
return N
if N in self.cache.keys():
return self.cache[N]
self.cache[N] = memoize(N - 1) + memoize(N - 2)
ret... | the_stack_v2_python_sparse | 509-fibonacci-number.py | yuenliou/leetcode | train | 0 | |
4c3ff1408f9a92cb5cfab61546b39836426ebd02 | [
"super(AnalysisStorage, self).__init__(filename=filename, mode='r')\nself.set_caching_mode(caching_mode)\nAnalysisStorage.cache_for_analysis(self)",
"with AnalysisStorage.CacheTimer('Cached all CVs'):\n for cv, cv_store in storage.snapshots.attribute_list.items():\n if cv_store:\n cv_store.ca... | <|body_start_0|>
super(AnalysisStorage, self).__init__(filename=filename, mode='r')
self.set_caching_mode(caching_mode)
AnalysisStorage.cache_for_analysis(self)
<|end_body_0|>
<|body_start_1|>
with AnalysisStorage.CacheTimer('Cached all CVs'):
for cv, cv_store in storage.sna... | Open a storage in read-only and do caching useful for analysis. | AnalysisStorage | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AnalysisStorage:
"""Open a storage in read-only and do caching useful for analysis."""
def __init__(self, filename, caching_mode='analysis'):
"""Open a storage in read-only and do caching useful for analysis. Parameters ---------- filename : str The filename of the storage to be open... | stack_v2_sparse_classes_75kplus_train_074564 | 17,720 | permissive | [
{
"docstring": "Open a storage in read-only and do caching useful for analysis. Parameters ---------- filename : str The filename of the storage to be opened caching_mode : str The caching mode to be used. Default is `analysis` which will cache lots of usually relevant object. If you have a decent size system a... | 2 | stack_v2_sparse_classes_30k_train_015058 | Implement the Python class `AnalysisStorage` described below.
Class description:
Open a storage in read-only and do caching useful for analysis.
Method signatures and docstrings:
- def __init__(self, filename, caching_mode='analysis'): Open a storage in read-only and do caching useful for analysis. Parameters -------... | Implement the Python class `AnalysisStorage` described below.
Class description:
Open a storage in read-only and do caching useful for analysis.
Method signatures and docstrings:
- def __init__(self, filename, caching_mode='analysis'): Open a storage in read-only and do caching useful for analysis. Parameters -------... | 3d02df4ccdeb6d62030a28e371a6b4ea9aaee5fe | <|skeleton|>
class AnalysisStorage:
"""Open a storage in read-only and do caching useful for analysis."""
def __init__(self, filename, caching_mode='analysis'):
"""Open a storage in read-only and do caching useful for analysis. Parameters ---------- filename : str The filename of the storage to be open... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AnalysisStorage:
"""Open a storage in read-only and do caching useful for analysis."""
def __init__(self, filename, caching_mode='analysis'):
"""Open a storage in read-only and do caching useful for analysis. Parameters ---------- filename : str The filename of the storage to be opened caching_mo... | the_stack_v2_python_sparse | openpathsampling/storage/storage.py | dwhswenson/openpathsampling | train | 3 |
e0e78dbfe4fd009bfd60945323fdb6255f4c53fb | [
"self._header_state = {}\nheader_key_list = DEFAULT_HEADER_KEY_LIST\nfor header_key in header_key_list:\n self._header_state[header_key] = None\nself._metadata_extracted = False\nif DataSetDriverConfigKeys.PARTICLE_CLASSES_DICT in config:\n particle_classes_dict = config.get(DataSetDriverConfigKeys.PARTICLE_C... | <|body_start_0|>
self._header_state = {}
header_key_list = DEFAULT_HEADER_KEY_LIST
for header_key in header_key_list:
self._header_state[header_key] = None
self._metadata_extracted = False
if DataSetDriverConfigKeys.PARTICLE_CLASSES_DICT in config:
particl... | NutnrJCsppParser | [
"BSD-2-Clause",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NutnrJCsppParser:
def __init__(self, config, stream_handle, exception_callback):
"""This the constructor which instantiates the NutnrJCsppParser"""
<|body_0|>
def _process_data_match(self, data_match):
"""This method processes a data match. It will extract a metadata... | stack_v2_sparse_classes_75kplus_train_074565 | 17,304 | permissive | [
{
"docstring": "This the constructor which instantiates the NutnrJCsppParser",
"name": "__init__",
"signature": "def __init__(self, config, stream_handle, exception_callback)"
},
{
"docstring": "This method processes a data match. It will extract a metadata particle and insert it into the record... | 3 | stack_v2_sparse_classes_30k_train_048176 | Implement the Python class `NutnrJCsppParser` described below.
Class description:
Implement the NutnrJCsppParser class.
Method signatures and docstrings:
- def __init__(self, config, stream_handle, exception_callback): This the constructor which instantiates the NutnrJCsppParser
- def _process_data_match(self, data_m... | Implement the Python class `NutnrJCsppParser` described below.
Class description:
Implement the NutnrJCsppParser class.
Method signatures and docstrings:
- def __init__(self, config, stream_handle, exception_callback): This the constructor which instantiates the NutnrJCsppParser
- def _process_data_match(self, data_m... | bdbf01f5614e7188ce19596704794466e5683b30 | <|skeleton|>
class NutnrJCsppParser:
def __init__(self, config, stream_handle, exception_callback):
"""This the constructor which instantiates the NutnrJCsppParser"""
<|body_0|>
def _process_data_match(self, data_match):
"""This method processes a data match. It will extract a metadata... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class NutnrJCsppParser:
def __init__(self, config, stream_handle, exception_callback):
"""This the constructor which instantiates the NutnrJCsppParser"""
self._header_state = {}
header_key_list = DEFAULT_HEADER_KEY_LIST
for header_key in header_key_list:
self._header_stat... | the_stack_v2_python_sparse | mi/dataset/parser/nutnr_j_cspp.py | oceanobservatories/mi-instrument | train | 1 | |
ca3c97b1a69cc1d58d0352eb7863ea5b0761474f | [
"super(AdamWeightDecayOptimizer, self).__init__(False, name)\nself.learning_rate = tf.identity(learning_rate, 'learning_rate')\nself.weight_decay_rate = weight_decay_rate\nself.beta_1 = beta_1\nself.beta_2 = beta_2\nself.epsilon = epsilon\nself.exclude_from_weight_decay = exclude_from_weight_decay",
"assignments ... | <|body_start_0|>
super(AdamWeightDecayOptimizer, self).__init__(False, name)
self.learning_rate = tf.identity(learning_rate, 'learning_rate')
self.weight_decay_rate = weight_decay_rate
self.beta_1 = beta_1
self.beta_2 = beta_2
self.epsilon = epsilon
self.exclude_f... | A basic Adam optimizer that includes "correct" L2 weight decay. | AdamWeightDecayOptimizer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AdamWeightDecayOptimizer:
"""A basic Adam optimizer that includes "correct" L2 weight decay."""
def __init__(self, learning_rate, weight_decay_rate=0.0, beta_1=0.9, beta_2=0.999, epsilon=1e-06, exclude_from_weight_decay=None, name='AdamWeightDecayOptimizer'):
"""Constructs a AdamWeig... | stack_v2_sparse_classes_75kplus_train_074566 | 27,721 | permissive | [
{
"docstring": "Constructs a AdamWeightDecayOptimizer.",
"name": "__init__",
"signature": "def __init__(self, learning_rate, weight_decay_rate=0.0, beta_1=0.9, beta_2=0.999, epsilon=1e-06, exclude_from_weight_decay=None, name='AdamWeightDecayOptimizer')"
},
{
"docstring": "See base class.",
... | 4 | null | Implement the Python class `AdamWeightDecayOptimizer` described below.
Class description:
A basic Adam optimizer that includes "correct" L2 weight decay.
Method signatures and docstrings:
- def __init__(self, learning_rate, weight_decay_rate=0.0, beta_1=0.9, beta_2=0.999, epsilon=1e-06, exclude_from_weight_decay=None... | Implement the Python class `AdamWeightDecayOptimizer` described below.
Class description:
A basic Adam optimizer that includes "correct" L2 weight decay.
Method signatures and docstrings:
- def __init__(self, learning_rate, weight_decay_rate=0.0, beta_1=0.9, beta_2=0.999, epsilon=1e-06, exclude_from_weight_decay=None... | 4bd9f94d0f34d2a2846c5d892ca16121b18b6e10 | <|skeleton|>
class AdamWeightDecayOptimizer:
"""A basic Adam optimizer that includes "correct" L2 weight decay."""
def __init__(self, learning_rate, weight_decay_rate=0.0, beta_1=0.9, beta_2=0.999, epsilon=1e-06, exclude_from_weight_decay=None, name='AdamWeightDecayOptimizer'):
"""Constructs a AdamWeig... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AdamWeightDecayOptimizer:
"""A basic Adam optimizer that includes "correct" L2 weight decay."""
def __init__(self, learning_rate, weight_decay_rate=0.0, beta_1=0.9, beta_2=0.999, epsilon=1e-06, exclude_from_weight_decay=None, name='AdamWeightDecayOptimizer'):
"""Constructs a AdamWeightDecayOptimi... | the_stack_v2_python_sparse | LatticeBERT/optimization.py | RunxinXu/AliceMind | train | 0 |
8b09716a2aa886b93b7002878d1d8558d790cf45 | [
"self.id_nodo = id_nodo\nself.padre = padre\nself.valor = valor\nself.hijos = {}",
"if self.id_nodo == id_nodo:\n return self\nfor hijo in self.hijos.values():\n nodo = hijo.obtener_nodo(id_nodo)\n if nodo is not None:\n return nodo\nreturn None",
"padre = self.obtener_nodo(id_padre)\nif padre i... | <|body_start_0|>
self.id_nodo = id_nodo
self.padre = padre
self.valor = valor
self.hijos = {}
<|end_body_0|>
<|body_start_1|>
if self.id_nodo == id_nodo:
return self
for hijo in self.hijos.values():
nodo = hijo.obtener_nodo(id_nodo)
if... | Esta clase representa un árbol La estructura es recursiva, de manera que cada nodo es la raíz de un sub-árbol. Los nodos hijos pueden ser guardados en una estructura, como lista o diccionario. En este ejemplo, los nodos hijos serán guardados en un diccionario. | Arbol | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Arbol:
"""Esta clase representa un árbol La estructura es recursiva, de manera que cada nodo es la raíz de un sub-árbol. Los nodos hijos pueden ser guardados en una estructura, como lista o diccionario. En este ejemplo, los nodos hijos serán guardados en un diccionario."""
def __init__(self,... | stack_v2_sparse_classes_75kplus_train_074567 | 5,113 | no_license | [
{
"docstring": "Inicializa la estructura básica del árbol. Tiene un identificador propio, la referencia a su padre, el valor almacenado y una estructura con sus hijos.",
"name": "__init__",
"signature": "def __init__(self, id_nodo, valor=None, padre=None)"
},
{
"docstring": "Obtiene el nodo con ... | 4 | stack_v2_sparse_classes_30k_train_045890 | Implement the Python class `Arbol` described below.
Class description:
Esta clase representa un árbol La estructura es recursiva, de manera que cada nodo es la raíz de un sub-árbol. Los nodos hijos pueden ser guardados en una estructura, como lista o diccionario. En este ejemplo, los nodos hijos serán guardados en un ... | Implement the Python class `Arbol` described below.
Class description:
Esta clase representa un árbol La estructura es recursiva, de manera que cada nodo es la raíz de un sub-árbol. Los nodos hijos pueden ser guardados en una estructura, como lista o diccionario. En este ejemplo, los nodos hijos serán guardados en un ... | 54f55b9da9d0fa3f976466b3bef19e488c45bef8 | <|skeleton|>
class Arbol:
"""Esta clase representa un árbol La estructura es recursiva, de manera que cada nodo es la raíz de un sub-árbol. Los nodos hijos pueden ser guardados en una estructura, como lista o diccionario. En este ejemplo, los nodos hijos serán guardados en un diccionario."""
def __init__(self,... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Arbol:
"""Esta clase representa un árbol La estructura es recursiva, de manera que cada nodo es la raíz de un sub-árbol. Los nodos hijos pueden ser guardados en una estructura, como lista o diccionario. En este ejemplo, los nodos hijos serán guardados en un diccionario."""
def __init__(self, id_nodo, val... | the_stack_v2_python_sparse | Semana 11/arboles.py | TMagini/Apuntes-Progra-Avanzada | train | 0 |
ed009c01180f071657fb1680dff2aaf765af10d5 | [
"super(MultiHeadedAttention, self).__init__()\nassert d_model % h == 0\nself.d_k = d_model // h\nself.h = h\nself.linears = clones(nn.Linear(d_model, d_model), 4)\nself.attn = None\nself.dropout = nn.Dropout(p=dropout)",
"d_k = query.size(-1)\nscores = torch.matmul(query, key.transpose(-2, -1)) / math.sqrt(d_k)\n... | <|body_start_0|>
super(MultiHeadedAttention, self).__init__()
assert d_model % h == 0
self.d_k = d_model // h
self.h = h
self.linears = clones(nn.Linear(d_model, d_model), 4)
self.attn = None
self.dropout = nn.Dropout(p=dropout)
<|end_body_0|>
<|body_start_1|>
... | MultiHeadedAttention | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MultiHeadedAttention:
def __init__(self, h, d_model, dropout=0.1):
"""Take in model size and number of heads."""
<|body_0|>
def attention(self, query, key, value, mask=None, dropout=None):
"""Compute 'Scaled Dot Product Attention'"""
<|body_1|>
def forwa... | stack_v2_sparse_classes_75kplus_train_074568 | 14,213 | no_license | [
{
"docstring": "Take in model size and number of heads.",
"name": "__init__",
"signature": "def __init__(self, h, d_model, dropout=0.1)"
},
{
"docstring": "Compute 'Scaled Dot Product Attention'",
"name": "attention",
"signature": "def attention(self, query, key, value, mask=None, dropou... | 3 | stack_v2_sparse_classes_30k_train_014184 | Implement the Python class `MultiHeadedAttention` described below.
Class description:
Implement the MultiHeadedAttention class.
Method signatures and docstrings:
- def __init__(self, h, d_model, dropout=0.1): Take in model size and number of heads.
- def attention(self, query, key, value, mask=None, dropout=None): Co... | Implement the Python class `MultiHeadedAttention` described below.
Class description:
Implement the MultiHeadedAttention class.
Method signatures and docstrings:
- def __init__(self, h, d_model, dropout=0.1): Take in model size and number of heads.
- def attention(self, query, key, value, mask=None, dropout=None): Co... | 7c389dd416c67f382c9a5d3e1661a5bd89aecc47 | <|skeleton|>
class MultiHeadedAttention:
def __init__(self, h, d_model, dropout=0.1):
"""Take in model size and number of heads."""
<|body_0|>
def attention(self, query, key, value, mask=None, dropout=None):
"""Compute 'Scaled Dot Product Attention'"""
<|body_1|>
def forwa... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MultiHeadedAttention:
def __init__(self, h, d_model, dropout=0.1):
"""Take in model size and number of heads."""
super(MultiHeadedAttention, self).__init__()
assert d_model % h == 0
self.d_k = d_model // h
self.h = h
self.linears = clones(nn.Linear(d_model, d_mo... | the_stack_v2_python_sparse | models/AttModel.py | Shiyang-Yan/ParaCNN | train | 2 | |
a48fc3b122b969497f56d7536a169137a0ccb30d | [
"self._discovery_info: BluetoothServiceInfoBleak | None = None\nself._discovered_device: DeviceData | None = None\nself._discovered_devices: dict[str, str] = {}",
"await self.async_set_unique_id(discovery_info.address)\nself._abort_if_unique_id_configured()\ndevice = DeviceData()\nif not device.supported(discover... | <|body_start_0|>
self._discovery_info: BluetoothServiceInfoBleak | None = None
self._discovered_device: DeviceData | None = None
self._discovered_devices: dict[str, str] = {}
<|end_body_0|>
<|body_start_1|>
await self.async_set_unique_id(discovery_info.address)
self._abort_if_un... | Handle a config flow for sensorpro. | SensorProConfigFlow | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SensorProConfigFlow:
"""Handle a config flow for sensorpro."""
def __init__(self) -> None:
"""Initialize the config flow."""
<|body_0|>
async def async_step_bluetooth(self, discovery_info: BluetoothServiceInfoBleak) -> FlowResult:
"""Handle the bluetooth discover... | stack_v2_sparse_classes_75kplus_train_074569 | 3,548 | permissive | [
{
"docstring": "Initialize the config flow.",
"name": "__init__",
"signature": "def __init__(self) -> None"
},
{
"docstring": "Handle the bluetooth discovery step.",
"name": "async_step_bluetooth",
"signature": "async def async_step_bluetooth(self, discovery_info: BluetoothServiceInfoBle... | 4 | stack_v2_sparse_classes_30k_train_029392 | Implement the Python class `SensorProConfigFlow` described below.
Class description:
Handle a config flow for sensorpro.
Method signatures and docstrings:
- def __init__(self) -> None: Initialize the config flow.
- async def async_step_bluetooth(self, discovery_info: BluetoothServiceInfoBleak) -> FlowResult: Handle t... | Implement the Python class `SensorProConfigFlow` described below.
Class description:
Handle a config flow for sensorpro.
Method signatures and docstrings:
- def __init__(self) -> None: Initialize the config flow.
- async def async_step_bluetooth(self, discovery_info: BluetoothServiceInfoBleak) -> FlowResult: Handle t... | 80caeafcb5b6e2f9da192d0ea6dd1a5b8244b743 | <|skeleton|>
class SensorProConfigFlow:
"""Handle a config flow for sensorpro."""
def __init__(self) -> None:
"""Initialize the config flow."""
<|body_0|>
async def async_step_bluetooth(self, discovery_info: BluetoothServiceInfoBleak) -> FlowResult:
"""Handle the bluetooth discover... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SensorProConfigFlow:
"""Handle a config flow for sensorpro."""
def __init__(self) -> None:
"""Initialize the config flow."""
self._discovery_info: BluetoothServiceInfoBleak | None = None
self._discovered_device: DeviceData | None = None
self._discovered_devices: dict[str, ... | the_stack_v2_python_sparse | homeassistant/components/sensorpro/config_flow.py | home-assistant/core | train | 35,501 |
2ec684892d645d3aca020594e5a47c91fb68adbe | [
"a = 10.0\nf = self.dtype_f(self.init)\nf[:] = (-du[0] + (a - 1 / (2 - t)) * u[0] + (2 - t) * a * u[2] + np.exp(t) * (3 - t) / (2 - t), -du[1] + (1 - a) / (t - 2) * u[0] - u[1] + (a - 1) * u[2] + 2 * np.exp(t), (t + 2) * u[0] + (t ** 2 - 4) * u[1] - (t ** 2 + t - 2) * np.exp(t))\nreturn f",
"me = self.dtype_u(sel... | <|body_start_0|>
a = 10.0
f = self.dtype_f(self.init)
f[:] = (-du[0] + (a - 1 / (2 - t)) * u[0] + (2 - t) * a * u[2] + np.exp(t) * (3 - t) / (2 - t), -du[1] + (1 - a) / (t - 2) * u[0] - u[1] + (a - 1) * u[2] + 2 * np.exp(t), (t + 2) * u[0] + (t ** 2 - 4) * u[1] - (t ** 2 + t - 2) * np.exp(t))
... | Example implementing a smooth linear index-2 differential-algebraic equation (DAE) with known analytical solution. The DAE system is given by .. math:: \\frac{d u_1 (t)}{dt} = (\\alpha - \\frac{1}{2 - t}) u_1 (t) + (2-t) \\alpha z (t) + \\frac{3 - t}{2 - t}, .. math:: \\frac{d u_2 (t)}{dt} = \\frac{1 - \\alpha}{t - 2} ... | simple_dae_1 | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class simple_dae_1:
"""Example implementing a smooth linear index-2 differential-algebraic equation (DAE) with known analytical solution. The DAE system is given by .. math:: \\frac{d u_1 (t)}{dt} = (\\alpha - \\frac{1}{2 - t}) u_1 (t) + (2-t) \\alpha z (t) + \\frac{3 - t}{2 - t}, .. math:: \\frac{d u_... | stack_v2_sparse_classes_75kplus_train_074570 | 8,326 | permissive | [
{
"docstring": "Routine to evaluate the implicit representation of the problem, i.e., :math:`F(u, u', t)`. Parameters ---------- u : dtype_u Current values of the numerical solution at time t. du : dtype_u Current values of the derivative of the numerical solution at time t. t : float Current time of the numeri... | 2 | null | Implement the Python class `simple_dae_1` described below.
Class description:
Example implementing a smooth linear index-2 differential-algebraic equation (DAE) with known analytical solution. The DAE system is given by .. math:: \\frac{d u_1 (t)}{dt} = (\\alpha - \\frac{1}{2 - t}) u_1 (t) + (2-t) \\alpha z (t) + \\fr... | Implement the Python class `simple_dae_1` described below.
Class description:
Example implementing a smooth linear index-2 differential-algebraic equation (DAE) with known analytical solution. The DAE system is given by .. math:: \\frac{d u_1 (t)}{dt} = (\\alpha - \\frac{1}{2 - t}) u_1 (t) + (2-t) \\alpha z (t) + \\fr... | 1a51834bedffd4472e344bed28f4d766614b1537 | <|skeleton|>
class simple_dae_1:
"""Example implementing a smooth linear index-2 differential-algebraic equation (DAE) with known analytical solution. The DAE system is given by .. math:: \\frac{d u_1 (t)}{dt} = (\\alpha - \\frac{1}{2 - t}) u_1 (t) + (2-t) \\alpha z (t) + \\frac{3 - t}{2 - t}, .. math:: \\frac{d u_... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class simple_dae_1:
"""Example implementing a smooth linear index-2 differential-algebraic equation (DAE) with known analytical solution. The DAE system is given by .. math:: \\frac{d u_1 (t)}{dt} = (\\alpha - \\frac{1}{2 - t}) u_1 (t) + (2-t) \\alpha z (t) + \\frac{3 - t}{2 - t}, .. math:: \\frac{d u_2 (t)}{dt} = ... | the_stack_v2_python_sparse | pySDC/projects/DAE/problems/simple_DAE.py | Parallel-in-Time/pySDC | train | 30 |
d3bea7e63cc6cb5ab792c258b8c1ca7382e47c76 | [
"if not isinstance(uid, str) or not bool(uid.strip()):\n message: str = 'uid cannot be Null'\n raise InputError(status=error_codes.input_error_code, description=message)\nif not isinstance(organization_id, str) or not bool(organization_id.strip()):\n message: str = 'organization_id cannot be Null'\n rai... | <|body_start_0|>
if not isinstance(uid, str) or not bool(uid.strip()):
message: str = 'uid cannot be Null'
raise InputError(status=error_codes.input_error_code, description=message)
if not isinstance(organization_id, str) or not bool(organization_id.strip()):
message:... | UserValidators | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserValidators:
def is_user_valid(organization_id: str, uid: str) -> Optional[bool]:
"""**is_user_valid** returns true if user_instance is found and user_instance.is_active :param organization_id: :param uid: :return:"""
<|body_0|>
async def is_user_valid_async(organization_... | stack_v2_sparse_classes_75kplus_train_074571 | 14,108 | permissive | [
{
"docstring": "**is_user_valid** returns true if user_instance is found and user_instance.is_active :param organization_id: :param uid: :return:",
"name": "is_user_valid",
"signature": "def is_user_valid(organization_id: str, uid: str) -> Optional[bool]"
},
{
"docstring": "**is_user_valid_async... | 4 | stack_v2_sparse_classes_30k_train_020280 | Implement the Python class `UserValidators` described below.
Class description:
Implement the UserValidators class.
Method signatures and docstrings:
- def is_user_valid(organization_id: str, uid: str) -> Optional[bool]: **is_user_valid** returns true if user_instance is found and user_instance.is_active :param organ... | Implement the Python class `UserValidators` described below.
Class description:
Implement the UserValidators class.
Method signatures and docstrings:
- def is_user_valid(organization_id: str, uid: str) -> Optional[bool]: **is_user_valid** returns true if user_instance is found and user_instance.is_active :param organ... | e8cf1df3f061c9745977e207568ffed2abdc70fc | <|skeleton|>
class UserValidators:
def is_user_valid(organization_id: str, uid: str) -> Optional[bool]:
"""**is_user_valid** returns true if user_instance is found and user_instance.is_active :param organization_id: :param uid: :return:"""
<|body_0|>
async def is_user_valid_async(organization_... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class UserValidators:
def is_user_valid(organization_id: str, uid: str) -> Optional[bool]:
"""**is_user_valid** returns true if user_instance is found and user_instance.is_active :param organization_id: :param uid: :return:"""
if not isinstance(uid, str) or not bool(uid.strip()):
message... | the_stack_v2_python_sparse | database/users.py | saaiiravi/membership_and_affiliate_api | train | 0 | |
e9c8e1e7bac6a3cfbda4361740dd0679f25e23ca | [
"if isinstance(obj.data, pint.Quantity):\n if obj.shape == (1,):\n return {'units': obj.units, 'value': obj.data.magnitude[0]}\n return {'time': obj.time, 'units': obj.units, 'shape': obj.shape, 'interpolation': obj.interpolation, 'values': obj.data.magnitude}\nreturn {'expression': obj.data, 'units': ... | <|body_start_0|>
if isinstance(obj.data, pint.Quantity):
if obj.shape == (1,):
return {'units': obj.units, 'value': obj.data.magnitude[0]}
return {'time': obj.time, 'units': obj.units, 'shape': obj.shape, 'interpolation': obj.interpolation, 'values': obj.data.magnitude}
... | Serialization class for weldx.core.TimeSeries | TimeSeriesConverter | [
"BSD-3-Clause",
"LicenseRef-scancode-free-unknown"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TimeSeriesConverter:
"""Serialization class for weldx.core.TimeSeries"""
def to_yaml_tree(self, obj: TimeSeries, tag: str, ctx) -> dict:
"""Convert to python dict."""
<|body_0|>
def from_yaml_tree(self, node: dict, tag: str, ctx):
"""Construct from tree."""
... | stack_v2_sparse_classes_75kplus_train_074572 | 1,913 | permissive | [
{
"docstring": "Convert to python dict.",
"name": "to_yaml_tree",
"signature": "def to_yaml_tree(self, obj: TimeSeries, tag: str, ctx) -> dict"
},
{
"docstring": "Construct from tree.",
"name": "from_yaml_tree",
"signature": "def from_yaml_tree(self, node: dict, tag: str, ctx)"
},
{
... | 3 | stack_v2_sparse_classes_30k_train_027884 | Implement the Python class `TimeSeriesConverter` described below.
Class description:
Serialization class for weldx.core.TimeSeries
Method signatures and docstrings:
- def to_yaml_tree(self, obj: TimeSeries, tag: str, ctx) -> dict: Convert to python dict.
- def from_yaml_tree(self, node: dict, tag: str, ctx): Construc... | Implement the Python class `TimeSeriesConverter` described below.
Class description:
Serialization class for weldx.core.TimeSeries
Method signatures and docstrings:
- def to_yaml_tree(self, obj: TimeSeries, tag: str, ctx) -> dict: Convert to python dict.
- def from_yaml_tree(self, node: dict, tag: str, ctx): Construc... | 7bc16a196ee669822f3663f3c7a08f6bbd0c76d5 | <|skeleton|>
class TimeSeriesConverter:
"""Serialization class for weldx.core.TimeSeries"""
def to_yaml_tree(self, obj: TimeSeries, tag: str, ctx) -> dict:
"""Convert to python dict."""
<|body_0|>
def from_yaml_tree(self, node: dict, tag: str, ctx):
"""Construct from tree."""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TimeSeriesConverter:
"""Serialization class for weldx.core.TimeSeries"""
def to_yaml_tree(self, obj: TimeSeries, tag: str, ctx) -> dict:
"""Convert to python dict."""
if isinstance(obj.data, pint.Quantity):
if obj.shape == (1,):
return {'units': obj.units, 'val... | the_stack_v2_python_sparse | weldx/tags/core/time_series.py | BAMWelDX/weldx | train | 20 |
4eaea7c902d88f512c2271637650d6b419295afe | [
"sql = super(MySQLQueryGrammar, self).compile_select(query)\nif query.unions:\n sql = '(%s) %s' % (sql, self._compile_unions(query))\nreturn sql",
"if union['all']:\n joiner = ' UNION ALL '\nelse:\n joiner = ' UNION '\nreturn '%s(%s)' % (joiner, union['query'].to_sql())",
"if isinstance(value, basestri... | <|body_start_0|>
sql = super(MySQLQueryGrammar, self).compile_select(query)
if query.unions:
sql = '(%s) %s' % (sql, self._compile_unions(query))
return sql
<|end_body_0|>
<|body_start_1|>
if union['all']:
joiner = ' UNION ALL '
else:
joiner =... | MySQLQueryGrammar | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MySQLQueryGrammar:
def compile_select(self, query):
"""Compile a select query into SQL :param query: A QueryBuilder instance :type query: QueryBuilder :return: The compiled sql :rtype: str"""
<|body_0|>
def _compile_union(self, union):
"""Compile a single union state... | stack_v2_sparse_classes_75kplus_train_074573 | 3,559 | permissive | [
{
"docstring": "Compile a select query into SQL :param query: A QueryBuilder instance :type query: QueryBuilder :return: The compiled sql :rtype: str",
"name": "compile_select",
"signature": "def compile_select(self, query)"
},
{
"docstring": "Compile a single union statement :param union: The u... | 6 | null | Implement the Python class `MySQLQueryGrammar` described below.
Class description:
Implement the MySQLQueryGrammar class.
Method signatures and docstrings:
- def compile_select(self, query): Compile a select query into SQL :param query: A QueryBuilder instance :type query: QueryBuilder :return: The compiled sql :rtyp... | Implement the Python class `MySQLQueryGrammar` described below.
Class description:
Implement the MySQLQueryGrammar class.
Method signatures and docstrings:
- def compile_select(self, query): Compile a select query into SQL :param query: A QueryBuilder instance :type query: QueryBuilder :return: The compiled sql :rtyp... | 375ffeb9b519ca1ac4cc5be4b61e87c0a82d1be4 | <|skeleton|>
class MySQLQueryGrammar:
def compile_select(self, query):
"""Compile a select query into SQL :param query: A QueryBuilder instance :type query: QueryBuilder :return: The compiled sql :rtype: str"""
<|body_0|>
def _compile_union(self, union):
"""Compile a single union state... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MySQLQueryGrammar:
def compile_select(self, query):
"""Compile a select query into SQL :param query: A QueryBuilder instance :type query: QueryBuilder :return: The compiled sql :rtype: str"""
sql = super(MySQLQueryGrammar, self).compile_select(query)
if query.unions:
sql = ... | the_stack_v2_python_sparse | orator/query/grammars/mysql_grammar.py | MasoniteFramework/orator | train | 1 | |
f167bc0b98d2f132359136156770754348c98299 | [
"validate = Validate()\nname = self.cleaned_data['name']\nif not validate.check_name(name):\n raise ValidationError(u\"Некоректно введено ім'я.\")\nreturn name",
"validate = Validate()\nlogin = self.cleaned_data['login']\nif not validate.check_login(login):\n raise ValidationError(u'Некоректно введно логін.... | <|body_start_0|>
validate = Validate()
name = self.cleaned_data['name']
if not validate.check_name(name):
raise ValidationError(u"Некоректно введено ім'я.")
return name
<|end_body_0|>
<|body_start_1|>
validate = Validate()
login = self.cleaned_data['login']
... | This class is the form class for teachers. | TeacherForm | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TeacherForm:
"""This class is the form class for teachers."""
def clean_name(self):
"""Validate name field."""
<|body_0|>
def clean_login(self):
"""Validate login field."""
<|body_1|>
def clean_email(self):
"""Validate email field."""
... | stack_v2_sparse_classes_75kplus_train_074574 | 1,418 | permissive | [
{
"docstring": "Validate name field.",
"name": "clean_name",
"signature": "def clean_name(self)"
},
{
"docstring": "Validate login field.",
"name": "clean_login",
"signature": "def clean_login(self)"
},
{
"docstring": "Validate email field.",
"name": "clean_email",
"signa... | 3 | stack_v2_sparse_classes_30k_train_013579 | Implement the Python class `TeacherForm` described below.
Class description:
This class is the form class for teachers.
Method signatures and docstrings:
- def clean_name(self): Validate name field.
- def clean_login(self): Validate login field.
- def clean_email(self): Validate email field. | Implement the Python class `TeacherForm` described below.
Class description:
This class is the form class for teachers.
Method signatures and docstrings:
- def clean_name(self): Validate name field.
- def clean_login(self): Validate login field.
- def clean_email(self): Validate email field.
<|skeleton|>
class Teach... | 3bdfa3dac95590036be8f33f8cd1f8831e872ef0 | <|skeleton|>
class TeacherForm:
"""This class is the form class for teachers."""
def clean_name(self):
"""Validate name field."""
<|body_0|>
def clean_login(self):
"""Validate login field."""
<|body_1|>
def clean_email(self):
"""Validate email field."""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TeacherForm:
"""This class is the form class for teachers."""
def clean_name(self):
"""Validate name field."""
validate = Validate()
name = self.cleaned_data['name']
if not validate.check_name(name):
raise ValidationError(u"Некоректно введено ім'я.")
re... | the_stack_v2_python_sparse | SMS/apps/mainteacher/forms.py | Social-projects-Rivne/SMS_autotesting | train | 0 |
63674f287632baa99b4736c3f1e17aaff0840a6a | [
"seller = Shop_Seller(id=shopId).get()\nif seller:\n itemList = Shop_Seller(id=shopId).get().itemList\n itemList = [marshal(item, output_shopItem) for item in itemList]\n return Response(data=itemList)\nelse:\n return Response(code=HttpStatus.HTTP_404_NOT_FOUND, message='无符合条件的商家')",
"if not current_u... | <|body_start_0|>
seller = Shop_Seller(id=shopId).get()
if seller:
itemList = Shop_Seller(id=shopId).get().itemList
itemList = [marshal(item, output_shopItem) for item in itemList]
return Response(data=itemList)
else:
return Response(code=HttpStatus... | Menu | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Menu:
def get(self, shopId):
"""获取商家商品列表 :return:"""
<|body_0|>
def post(self, shopId):
"""添加商品 :param shopId: :return:"""
<|body_1|>
def put(self, shopId):
"""修改商品信息,可进行部分字段更新 :param shopId: :return:"""
<|body_2|>
def delete(self, s... | stack_v2_sparse_classes_75kplus_train_074575 | 14,722 | no_license | [
{
"docstring": "获取商家商品列表 :return:",
"name": "get",
"signature": "def get(self, shopId)"
},
{
"docstring": "添加商品 :param shopId: :return:",
"name": "post",
"signature": "def post(self, shopId)"
},
{
"docstring": "修改商品信息,可进行部分字段更新 :param shopId: :return:",
"name": "put",
"si... | 4 | stack_v2_sparse_classes_30k_train_046090 | Implement the Python class `Menu` described below.
Class description:
Implement the Menu class.
Method signatures and docstrings:
- def get(self, shopId): 获取商家商品列表 :return:
- def post(self, shopId): 添加商品 :param shopId: :return:
- def put(self, shopId): 修改商品信息,可进行部分字段更新 :param shopId: :return:
- def delete(self, shopI... | Implement the Python class `Menu` described below.
Class description:
Implement the Menu class.
Method signatures and docstrings:
- def get(self, shopId): 获取商家商品列表 :return:
- def post(self, shopId): 添加商品 :param shopId: :return:
- def put(self, shopId): 修改商品信息,可进行部分字段更新 :param shopId: :return:
- def delete(self, shopI... | 34a2bf4a51cc40a22dd43cb5eb88af7c2f2c5120 | <|skeleton|>
class Menu:
def get(self, shopId):
"""获取商家商品列表 :return:"""
<|body_0|>
def post(self, shopId):
"""添加商品 :param shopId: :return:"""
<|body_1|>
def put(self, shopId):
"""修改商品信息,可进行部分字段更新 :param shopId: :return:"""
<|body_2|>
def delete(self, s... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Menu:
def get(self, shopId):
"""获取商家商品列表 :return:"""
seller = Shop_Seller(id=shopId).get()
if seller:
itemList = Shop_Seller(id=shopId).get().itemList
itemList = [marshal(item, output_shopItem) for item in itemList]
return Response(data=itemList)
... | the_stack_v2_python_sparse | App/Shop/Controller/ShopResource.py | Vulcanhy/api.grooo-master | train | 0 | |
f25c4ca8f74cd3079a0809aba38c573067e943f0 | [
"t_min, t_max, t_increment = (200.15, 220.15, 10.0)\nresult = SaturatedVapourPressureTable(t_min=t_min, t_max=t_max, t_increment=t_increment).process()\nself.assertEqual(result.attributes['minimum_temperature'], t_min)\nself.assertEqual(result.attributes['maximum_temperature'], t_max)\nself.assertEqual(result.attri... | <|body_start_0|>
t_min, t_max, t_increment = (200.15, 220.15, 10.0)
result = SaturatedVapourPressureTable(t_min=t_min, t_max=t_max, t_increment=t_increment).process()
self.assertEqual(result.attributes['minimum_temperature'], t_min)
self.assertEqual(result.attributes['maximum_temperature... | Test that the plugin functions as expected. | Test_process | [
"BSD-3-Clause",
"LicenseRef-scancode-proprietary-license"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Test_process:
"""Test that the plugin functions as expected."""
def test_cube_attributes(self):
"""Test that returned cube has appropriate attributes."""
<|body_0|>
def test_cube_values(self):
"""Test that returned cube has expected values."""
<|body_1|>
... | stack_v2_sparse_classes_75kplus_train_074576 | 4,810 | permissive | [
{
"docstring": "Test that returned cube has appropriate attributes.",
"name": "test_cube_attributes",
"signature": "def test_cube_attributes(self)"
},
{
"docstring": "Test that returned cube has expected values.",
"name": "test_cube_values",
"signature": "def test_cube_values(self)"
},... | 3 | stack_v2_sparse_classes_30k_train_040953 | Implement the Python class `Test_process` described below.
Class description:
Test that the plugin functions as expected.
Method signatures and docstrings:
- def test_cube_attributes(self): Test that returned cube has appropriate attributes.
- def test_cube_values(self): Test that returned cube has expected values.
-... | Implement the Python class `Test_process` described below.
Class description:
Test that the plugin functions as expected.
Method signatures and docstrings:
- def test_cube_attributes(self): Test that returned cube has appropriate attributes.
- def test_cube_values(self): Test that returned cube has expected values.
-... | cd2c9019944345df1e703bf8f625db537ad9f559 | <|skeleton|>
class Test_process:
"""Test that the plugin functions as expected."""
def test_cube_attributes(self):
"""Test that returned cube has appropriate attributes."""
<|body_0|>
def test_cube_values(self):
"""Test that returned cube has expected values."""
<|body_1|>
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Test_process:
"""Test that the plugin functions as expected."""
def test_cube_attributes(self):
"""Test that returned cube has appropriate attributes."""
t_min, t_max, t_increment = (200.15, 220.15, 10.0)
result = SaturatedVapourPressureTable(t_min=t_min, t_max=t_max, t_increment=... | the_stack_v2_python_sparse | improver_tests/generate_ancillaries/test_SaturatedVapourPressureTable.py | metoppv/improver | train | 101 |
7e48fa0a2351d2e7756ea00f4a61380b1d10f6a0 | [
"if n_sigma_z and z_cuts:\n raise ValueError('Both arguments n_sigma_z and z_cuts are' + ' given while only one is accepted!')\nmode = 'uniform_charge'\nself.config = (mode, n_slices, n_sigma_z, z_cuts)",
"z_cut_tail, z_cut_head = self.get_long_cuts(beam)\nn_part = len(beam.z)\nid_new = np.argsort(beam.z)\nid_... | <|body_start_0|>
if n_sigma_z and z_cuts:
raise ValueError('Both arguments n_sigma_z and z_cuts are' + ' given while only one is accepted!')
mode = 'uniform_charge'
self.config = (mode, n_slices, n_sigma_z, z_cuts)
<|end_body_0|>
<|body_start_1|>
z_cut_tail, z_cut_head = sel... | Slices with respect to uniform charge for each bin along the slicing region. | UniformChargeSlicer | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UniformChargeSlicer:
"""Slices with respect to uniform charge for each bin along the slicing region."""
def __init__(self, n_slices, n_sigma_z=None, z_cuts=None, *args, **kwargs):
"""Return a UniformChargeSlicer object. Set and store the corresponding slicing configuration in self.co... | stack_v2_sparse_classes_75kplus_train_074577 | 27,870 | permissive | [
{
"docstring": "Return a UniformChargeSlicer object. Set and store the corresponding slicing configuration in self.config . Note that either n_sigma_z or z_cuts can be set. If both are given, a ValueError will be raised.",
"name": "__init__",
"signature": "def __init__(self, n_slices, n_sigma_z=None, z_... | 2 | null | Implement the Python class `UniformChargeSlicer` described below.
Class description:
Slices with respect to uniform charge for each bin along the slicing region.
Method signatures and docstrings:
- def __init__(self, n_slices, n_sigma_z=None, z_cuts=None, *args, **kwargs): Return a UniformChargeSlicer object. Set and... | Implement the Python class `UniformChargeSlicer` described below.
Class description:
Slices with respect to uniform charge for each bin along the slicing region.
Method signatures and docstrings:
- def __init__(self, n_slices, n_sigma_z=None, z_cuts=None, *args, **kwargs): Return a UniformChargeSlicer object. Set and... | b238bf3fbea02fcfaf8795ee54cc0e3134de477a | <|skeleton|>
class UniformChargeSlicer:
"""Slices with respect to uniform charge for each bin along the slicing region."""
def __init__(self, n_slices, n_sigma_z=None, z_cuts=None, *args, **kwargs):
"""Return a UniformChargeSlicer object. Set and store the corresponding slicing configuration in self.co... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class UniformChargeSlicer:
"""Slices with respect to uniform charge for each bin along the slicing region."""
def __init__(self, n_slices, n_sigma_z=None, z_cuts=None, *args, **kwargs):
"""Return a UniformChargeSlicer object. Set and store the corresponding slicing configuration in self.config . Note t... | the_stack_v2_python_sparse | PyHEADTAIL/particles/slicing.py | PyCOMPLETE/PyHEADTAIL | train | 39 |
1e023cefc27669de2717b7a35d426c2ec757767d | [
"if matrix == [[]] or matrix == []:\n return False\nrow_index = self.bin_search_row(0, len(matrix) - 1, matrix, target)\nif row_index == -1:\n return False\nreturn self.bin_search_column(0, len(matrix[row_index]) - 1, matrix[row_index], target)",
"if start > end:\n return -1\nmid = (start + end) // 2\nif... | <|body_start_0|>
if matrix == [[]] or matrix == []:
return False
row_index = self.bin_search_row(0, len(matrix) - 1, matrix, target)
if row_index == -1:
return False
return self.bin_search_column(0, len(matrix[row_index]) - 1, matrix[row_index], target)
<|end_body... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def searchMatrix(self, matrix, target):
""":type matrix: List[List[int]] :type target: int :rtype: bool"""
<|body_0|>
def bin_search_row(self, start, end, matrix, target) -> int:
""":type start: int :type end: int :type matrix: List[List[int]] :type target:... | stack_v2_sparse_classes_75kplus_train_074578 | 2,192 | no_license | [
{
"docstring": ":type matrix: List[List[int]] :type target: int :rtype: bool",
"name": "searchMatrix",
"signature": "def searchMatrix(self, matrix, target)"
},
{
"docstring": ":type start: int :type end: int :type matrix: List[List[int]] :type target: int :rtype: int",
"name": "bin_search_ro... | 3 | stack_v2_sparse_classes_30k_train_006743 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def searchMatrix(self, matrix, target): :type matrix: List[List[int]] :type target: int :rtype: bool
- def bin_search_row(self, start, end, matrix, target) -> int: :type start: i... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def searchMatrix(self, matrix, target): :type matrix: List[List[int]] :type target: int :rtype: bool
- def bin_search_row(self, start, end, matrix, target) -> int: :type start: i... | f832227c4d0e0b1c0cc326561187004ef24e2a68 | <|skeleton|>
class Solution:
def searchMatrix(self, matrix, target):
""":type matrix: List[List[int]] :type target: int :rtype: bool"""
<|body_0|>
def bin_search_row(self, start, end, matrix, target) -> int:
""":type start: int :type end: int :type matrix: List[List[int]] :type target:... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def searchMatrix(self, matrix, target):
""":type matrix: List[List[int]] :type target: int :rtype: bool"""
if matrix == [[]] or matrix == []:
return False
row_index = self.bin_search_row(0, len(matrix) - 1, matrix, target)
if row_index == -1:
r... | the_stack_v2_python_sparse | 74.py | Gackle/leetcode_practice | train | 0 | |
4cd5a2a5c2a2f607697be5c27adebf8fea3cade6 | [
"self.data_train = PrepareData().create_training_and_test_data_sets()[0]\nself.data_test = PrepareData().create_training_and_test_data_sets()[1]\nself.label_train = PrepareData().create_training_and_test_data_sets()[2]\nself.label_test = PrepareData().create_training_and_test_data_sets()[3]",
"logistic_regresion_... | <|body_start_0|>
self.data_train = PrepareData().create_training_and_test_data_sets()[0]
self.data_test = PrepareData().create_training_and_test_data_sets()[1]
self.label_train = PrepareData().create_training_and_test_data_sets()[2]
self.label_test = PrepareData().create_training_and_tes... | LogisticRegresionAlgorithm | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LogisticRegresionAlgorithm:
def __init__(self):
"""Constructor method that keeps the data and labels in two sets for training and testing."""
<|body_0|>
def make_predictions(self, label_train):
"""Make predictions of one of the labels using the Logistic Regression cl... | stack_v2_sparse_classes_75kplus_train_074579 | 1,538 | permissive | [
{
"docstring": "Constructor method that keeps the data and labels in two sets for training and testing.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Make predictions of one of the labels using the Logistic Regression classifier algorithm. Returns: label_prediction (... | 3 | stack_v2_sparse_classes_30k_val_000671 | Implement the Python class `LogisticRegresionAlgorithm` described below.
Class description:
Implement the LogisticRegresionAlgorithm class.
Method signatures and docstrings:
- def __init__(self): Constructor method that keeps the data and labels in two sets for training and testing.
- def make_predictions(self, label... | Implement the Python class `LogisticRegresionAlgorithm` described below.
Class description:
Implement the LogisticRegresionAlgorithm class.
Method signatures and docstrings:
- def __init__(self): Constructor method that keeps the data and labels in two sets for training and testing.
- def make_predictions(self, label... | 2d941a92280422b5c2054259780e015b938dca29 | <|skeleton|>
class LogisticRegresionAlgorithm:
def __init__(self):
"""Constructor method that keeps the data and labels in two sets for training and testing."""
<|body_0|>
def make_predictions(self, label_train):
"""Make predictions of one of the labels using the Logistic Regression cl... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class LogisticRegresionAlgorithm:
def __init__(self):
"""Constructor method that keeps the data and labels in two sets for training and testing."""
self.data_train = PrepareData().create_training_and_test_data_sets()[0]
self.data_test = PrepareData().create_training_and_test_data_sets()[1]
... | the_stack_v2_python_sparse | ML/logistic_regresion_algorithm.py | khatabi-abderrahim/breast_cancer_detection | train | 1 | |
3d371f2dfa59640fb9cfe26fe51cfd6e77559d72 | [
"self.mean = mean\nself.scale = scale\nself.upper = upper\nself.lower = lower\nstats.rv_continuous.__init__(self, momtype=0, a=self.lower, b=self.upper, name='mydist')",
"sample = self.rvs(size=n)\nsample = [s + self.mean for s in sample]\nsample = [s * self.scale for s in sample]\nreturn sample"
] | <|body_start_0|>
self.mean = mean
self.scale = scale
self.upper = upper
self.lower = lower
stats.rv_continuous.__init__(self, momtype=0, a=self.lower, b=self.upper, name='mydist')
<|end_body_0|>
<|body_start_1|>
sample = self.rvs(size=n)
sample = [s + self.mean f... | A generic class to provide common features to my distributions. | MyDist | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MyDist:
"""A generic class to provide common features to my distributions."""
def __init__(self, mean=0, scale=1, upper=None, lower=None):
"""Wraps the important parameters we want to vary to the initialization function."""
<|body_0|>
def getSample(self, n):
"""G... | stack_v2_sparse_classes_75kplus_train_074580 | 6,517 | no_license | [
{
"docstring": "Wraps the important parameters we want to vary to the initialization function.",
"name": "__init__",
"signature": "def __init__(self, mean=0, scale=1, upper=None, lower=None)"
},
{
"docstring": "Get a sample of n values returned as a list.",
"name": "getSample",
"signatur... | 2 | stack_v2_sparse_classes_30k_train_046346 | Implement the Python class `MyDist` described below.
Class description:
A generic class to provide common features to my distributions.
Method signatures and docstrings:
- def __init__(self, mean=0, scale=1, upper=None, lower=None): Wraps the important parameters we want to vary to the initialization function.
- def ... | Implement the Python class `MyDist` described below.
Class description:
A generic class to provide common features to my distributions.
Method signatures and docstrings:
- def __init__(self, mean=0, scale=1, upper=None, lower=None): Wraps the important parameters we want to vary to the initialization function.
- def ... | ba1786f427e93025acdad6111732e52243ac54f1 | <|skeleton|>
class MyDist:
"""A generic class to provide common features to my distributions."""
def __init__(self, mean=0, scale=1, upper=None, lower=None):
"""Wraps the important parameters we want to vary to the initialization function."""
<|body_0|>
def getSample(self, n):
"""G... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MyDist:
"""A generic class to provide common features to my distributions."""
def __init__(self, mean=0, scale=1, upper=None, lower=None):
"""Wraps the important parameters we want to vary to the initialization function."""
self.mean = mean
self.scale = scale
self.upper = ... | the_stack_v2_python_sparse | generate_electrons/distributions.py | billyziege/tem_scripts | train | 0 |
8353ae1289096f301e0dd287b965a69eff127320 | [
"auctioneer = Auctioneer()\n[auctioneer.register_bidder(x) for x in bidders]\nself._auctioneer = auctioneer",
"print('Auctioning ' + item + ' starting at ' + str(start_price))\nself._auctioneer.accept_bid(start_price, None)\nwinner = self._auctioneer.get_highest_bidder()\nfinal_price = self._auctioneer.get_highes... | <|body_start_0|>
auctioneer = Auctioneer()
[auctioneer.register_bidder(x) for x in bidders]
self._auctioneer = auctioneer
<|end_body_0|>
<|body_start_1|>
print('Auctioning ' + item + ' starting at ' + str(start_price))
self._auctioneer.accept_bid(start_price, None)
winne... | Simulates an auction. Is responsible for driving the auctioneer and the bidders. | Auction | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Auction:
"""Simulates an auction. Is responsible for driving the auctioneer and the bidders."""
def __init__(self, bidders):
"""Initialize an auction. Requires a list of bidders that are attending the auction and can bid. :param bidders: sequence type of objects of type Bidder"""
... | stack_v2_sparse_classes_75kplus_train_074581 | 5,374 | no_license | [
{
"docstring": "Initialize an auction. Requires a list of bidders that are attending the auction and can bid. :param bidders: sequence type of objects of type Bidder",
"name": "__init__",
"signature": "def __init__(self, bidders)"
},
{
"docstring": "Starts the auction for the given item at the g... | 2 | stack_v2_sparse_classes_30k_train_053845 | Implement the Python class `Auction` described below.
Class description:
Simulates an auction. Is responsible for driving the auctioneer and the bidders.
Method signatures and docstrings:
- def __init__(self, bidders): Initialize an auction. Requires a list of bidders that are attending the auction and can bid. :para... | Implement the Python class `Auction` described below.
Class description:
Simulates an auction. Is responsible for driving the auctioneer and the bidders.
Method signatures and docstrings:
- def __init__(self, bidders): Initialize an auction. Requires a list of bidders that are attending the auction and can bid. :para... | 46441744be7773075f5f91c09c1032e9fc0a54e8 | <|skeleton|>
class Auction:
"""Simulates an auction. Is responsible for driving the auctioneer and the bidders."""
def __init__(self, bidders):
"""Initialize an auction. Requires a list of bidders that are attending the auction and can bid. :param bidders: sequence type of objects of type Bidder"""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Auction:
"""Simulates an auction. Is responsible for driving the auctioneer and the bidders."""
def __init__(self, bidders):
"""Initialize an auction. Requires a list of bidders that are attending the auction and can bid. :param bidders: sequence type of objects of type Bidder"""
auctione... | the_stack_v2_python_sparse | Labs/Lab6/auction_simulator.py | Xaitin/3522_A01053901 | train | 0 |
86a9a44e6fd9bce0bef0e38d3ac3871984b89cdb | [
"tokens = os.path.splitext(os.path.basename(limitfile))[0].split('_')\nif tokens[3] in ['point', 'dmap', 'dradial']:\n return True\nreturn tokens[2] in ['point', 'dmap', 'dradial']",
"tokens = os.path.splitext(os.path.basename(limitfile))[0].split('_')\nif tokens[3] in ['point', 'map', 'radial']:\n return T... | <|body_start_0|>
tokens = os.path.splitext(os.path.basename(limitfile))[0].split('_')
if tokens[3] in ['point', 'dmap', 'dradial']:
return True
return tokens[2] in ['point', 'dmap', 'dradial']
<|end_body_0|>
<|body_start_1|>
tokens = os.path.splitext(os.path.basename(limitfi... | Small class to collect limit results from a series of simulations. | CollectLimits | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CollectLimits:
"""Small class to collect limit results from a series of simulations."""
def is_decay_limits(limitfile):
"""Return true if a file has limits for decay"""
<|body_0|>
def is_ann_limits(limitfile):
"""Return true if a file has limits for annhilation""... | stack_v2_sparse_classes_75kplus_train_074582 | 11,467 | permissive | [
{
"docstring": "Return true if a file has limits for decay",
"name": "is_decay_limits",
"signature": "def is_decay_limits(limitfile)"
},
{
"docstring": "Return true if a file has limits for annhilation",
"name": "is_ann_limits",
"signature": "def is_ann_limits(limitfile)"
},
{
"d... | 4 | stack_v2_sparse_classes_30k_train_016021 | Implement the Python class `CollectLimits` described below.
Class description:
Small class to collect limit results from a series of simulations.
Method signatures and docstrings:
- def is_decay_limits(limitfile): Return true if a file has limits for decay
- def is_ann_limits(limitfile): Return true if a file has lim... | Implement the Python class `CollectLimits` described below.
Class description:
Small class to collect limit results from a series of simulations.
Method signatures and docstrings:
- def is_decay_limits(limitfile): Return true if a file has limits for decay
- def is_ann_limits(limitfile): Return true if a file has lim... | e5b3f950d18d5077f7abf46f53fcf59e97bb3301 | <|skeleton|>
class CollectLimits:
"""Small class to collect limit results from a series of simulations."""
def is_decay_limits(limitfile):
"""Return true if a file has limits for decay"""
<|body_0|>
def is_ann_limits(limitfile):
"""Return true if a file has limits for annhilation""... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CollectLimits:
"""Small class to collect limit results from a series of simulations."""
def is_decay_limits(limitfile):
"""Return true if a file has limits for decay"""
tokens = os.path.splitext(os.path.basename(limitfile))[0].split('_')
if tokens[3] in ['point', 'dmap', 'dradial'... | the_stack_v2_python_sparse | dmpipe/dm_collect.py | fermiPy/dmpipe | train | 1 |
240dfe17f8091c20f806de1d17dcb81569eaaff6 | [
"self.probability = p\nself.min_factor = min_factor\nself.max_factor = max_factor",
"if np.random.random() < self.probability:\n factor = np.random.uniform(self.min_factor, self.max_factor)\n image_enhancer_contrast = ImageEnhance.Contrast(image)\n image = image_enhancer_contrast.enhance(factor)\nreturn ... | <|body_start_0|>
self.probability = p
self.min_factor = min_factor
self.max_factor = max_factor
<|end_body_0|>
<|body_start_1|>
if np.random.random() < self.probability:
factor = np.random.uniform(self.min_factor, self.max_factor)
image_enhancer_contrast = ImageE... | This class is used to random change contrast of an image. | RandomContrast | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RandomContrast:
"""This class is used to random change contrast of an image."""
def __init__(self, p=0.9, min_factor=0.4, max_factor=1.8):
"""required :attr:`probability` parameter :func:`~Augmentor.Pipeline.Pipeline.random_contrast` function. :param probability: Controls the probabi... | stack_v2_sparse_classes_75kplus_train_074583 | 40,740 | no_license | [
{
"docstring": "required :attr:`probability` parameter :func:`~Augmentor.Pipeline.Pipeline.random_contrast` function. :param probability: Controls the probability that the operation is performed when it is invoked in the pipeline. :param min_factor: The value between 0.0 and max_factor that define the minimum a... | 2 | stack_v2_sparse_classes_30k_train_043207 | Implement the Python class `RandomContrast` described below.
Class description:
This class is used to random change contrast of an image.
Method signatures and docstrings:
- def __init__(self, p=0.9, min_factor=0.4, max_factor=1.8): required :attr:`probability` parameter :func:`~Augmentor.Pipeline.Pipeline.random_con... | Implement the Python class `RandomContrast` described below.
Class description:
This class is used to random change contrast of an image.
Method signatures and docstrings:
- def __init__(self, p=0.9, min_factor=0.4, max_factor=1.8): required :attr:`probability` parameter :func:`~Augmentor.Pipeline.Pipeline.random_con... | a9c19225733b1a61eb0b006e6afc1bd2826bba2b | <|skeleton|>
class RandomContrast:
"""This class is used to random change contrast of an image."""
def __init__(self, p=0.9, min_factor=0.4, max_factor=1.8):
"""required :attr:`probability` parameter :func:`~Augmentor.Pipeline.Pipeline.random_contrast` function. :param probability: Controls the probabi... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class RandomContrast:
"""This class is used to random change contrast of an image."""
def __init__(self, p=0.9, min_factor=0.4, max_factor=1.8):
"""required :attr:`probability` parameter :func:`~Augmentor.Pipeline.Pipeline.random_contrast` function. :param probability: Controls the probability that the... | the_stack_v2_python_sparse | imcls/data/transforms/operations.py | iYuqinL/imcls | train | 0 |
3c5f1b946f42a8c8ff4c62996aa14672581ebb78 | [
"ip = UserLogic.visitor_ip_address(request)\ndata = request.data\npassword = data.pop('password', None)\nif not password:\n return ParseError(ErrorMsg.UserPassword.value)\nlogging.warning(LoggingMsg.LoggingMsg_user_1.value.format(ip, data))\nuser_data = self.get_serializer(data=data)\nuser_data.is_valid(raise_ex... | <|body_start_0|>
ip = UserLogic.visitor_ip_address(request)
data = request.data
password = data.pop('password', None)
if not password:
return ParseError(ErrorMsg.UserPassword.value)
logging.warning(LoggingMsg.LoggingMsg_user_1.value.format(ip, data))
user_data... | To registration user and activate account | UsersViewSet | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UsersViewSet:
"""To registration user and activate account"""
def create(self, request, *args, **kwargs):
"""{"username":"name", "password":"password", "email":"test@e.e"}"""
<|body_0|>
def activate(self, request, **kwargs):
"""Example: after registration you get... | stack_v2_sparse_classes_75kplus_train_074584 | 3,844 | no_license | [
{
"docstring": "{\"username\":\"name\", \"password\":\"password\", \"email\":\"test@e.e\"}",
"name": "create",
"signature": "def create(self, request, *args, **kwargs)"
},
{
"docstring": "Example: after registration you get email with link to activate account link : http://localhost:8000/api/v1/... | 2 | null | Implement the Python class `UsersViewSet` described below.
Class description:
To registration user and activate account
Method signatures and docstrings:
- def create(self, request, *args, **kwargs): {"username":"name", "password":"password", "email":"test@e.e"}
- def activate(self, request, **kwargs): Example: after... | Implement the Python class `UsersViewSet` described below.
Class description:
To registration user and activate account
Method signatures and docstrings:
- def create(self, request, *args, **kwargs): {"username":"name", "password":"password", "email":"test@e.e"}
- def activate(self, request, **kwargs): Example: after... | 59cea18c9f5d6ad899ba25c272793aeae8eaf4a9 | <|skeleton|>
class UsersViewSet:
"""To registration user and activate account"""
def create(self, request, *args, **kwargs):
"""{"username":"name", "password":"password", "email":"test@e.e"}"""
<|body_0|>
def activate(self, request, **kwargs):
"""Example: after registration you get... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class UsersViewSet:
"""To registration user and activate account"""
def create(self, request, *args, **kwargs):
"""{"username":"name", "password":"password", "email":"test@e.e"}"""
ip = UserLogic.visitor_ip_address(request)
data = request.data
password = data.pop('password', Non... | the_stack_v2_python_sparse | apps/users/views.py | kaday506s/TestPlaneks | train | 0 |
899c6af62cb0ab3a8e8c3cb4a4def6f3b5149334 | [
"self.filename = logname\nlogging.getLogger().setLevel(logging.DEBUG)\nlogfile = logging.handlers.RotatingFileHandler(self.filename, maxBytes=10 * 1024 * 1024, backupCount=30)\nlogfile.setLevel(logging.DEBUG)\nformatter = logging.Formatter('[%(asctime)s] [%(levelname)-5s] [%(process)d] %(message)s', '%Y-%m-%d %H:%M... | <|body_start_0|>
self.filename = logname
logging.getLogger().setLevel(logging.DEBUG)
logfile = logging.handlers.RotatingFileHandler(self.filename, maxBytes=10 * 1024 * 1024, backupCount=30)
logfile.setLevel(logging.DEBUG)
formatter = logging.Formatter('[%(asctime)s] [%(levelname)... | mini logging's class | mini_logging | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class mini_logging:
"""mini logging's class"""
def __init__(self, logname):
"""logging"""
<|body_0|>
def GenLog(self, logType, logContent):
"""set the basiconfig for the log. It's a file log."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.filena... | stack_v2_sparse_classes_75kplus_train_074585 | 3,429 | no_license | [
{
"docstring": "logging",
"name": "__init__",
"signature": "def __init__(self, logname)"
},
{
"docstring": "set the basiconfig for the log. It's a file log.",
"name": "GenLog",
"signature": "def GenLog(self, logType, logContent)"
}
] | 2 | null | Implement the Python class `mini_logging` described below.
Class description:
mini logging's class
Method signatures and docstrings:
- def __init__(self, logname): logging
- def GenLog(self, logType, logContent): set the basiconfig for the log. It's a file log. | Implement the Python class `mini_logging` described below.
Class description:
mini logging's class
Method signatures and docstrings:
- def __init__(self, logname): logging
- def GenLog(self, logType, logContent): set the basiconfig for the log. It's a file log.
<|skeleton|>
class mini_logging:
"""mini logging's ... | 6505830e909e98464e7fb13f50c712a414b1f508 | <|skeleton|>
class mini_logging:
"""mini logging's class"""
def __init__(self, logname):
"""logging"""
<|body_0|>
def GenLog(self, logType, logContent):
"""set the basiconfig for the log. It's a file log."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class mini_logging:
"""mini logging's class"""
def __init__(self, logname):
"""logging"""
self.filename = logname
logging.getLogger().setLevel(logging.DEBUG)
logfile = logging.handlers.RotatingFileHandler(self.filename, maxBytes=10 * 1024 * 1024, backupCount=30)
logfile.... | the_stack_v2_python_sparse | agent/libs/td_logging.py | jsonkey/neo | train | 1 |
b60711affb032386a1ed5342de0057d817705862 | [
"pygame.sprite.Sprite.__init__(self)\nself.image = pygame.Surface([70, 50])\nself.image.fill((255, 255, 255))\nself.rect = self.image.get_rect()\nself.rect.y = 40\nself.set_pos(pos)",
"if pos == 0:\n self.rect.x = -15\nelif pos == 1:\n self.rect.x = 148\nelif pos == 2:\n self.rect.x = 310\nelif pos == 3:... | <|body_start_0|>
pygame.sprite.Sprite.__init__(self)
self.image = pygame.Surface([70, 50])
self.image.fill((255, 255, 255))
self.rect = self.image.get_rect()
self.rect.y = 40
self.set_pos(pos)
<|end_body_0|>
<|body_start_1|>
if pos == 0:
self.rect.x =... | Pygame sprite class for riverbank sprites used for killing the player | Riverbank | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Riverbank:
"""Pygame sprite class for riverbank sprites used for killing the player"""
def __init__(self, pos):
"""- :param pos: An int representing the "index" of the riverbank. Should be 0-5, with 0 representing the left-most riverbank and 5 representing the right-most bank."""
... | stack_v2_sparse_classes_75kplus_train_074586 | 1,472 | permissive | [
{
"docstring": "- :param pos: An int representing the \"index\" of the riverbank. Should be 0-5, with 0 representing the left-most riverbank and 5 representing the right-most bank.",
"name": "__init__",
"signature": "def __init__(self, pos)"
},
{
"docstring": "Helper function called by construct... | 2 | stack_v2_sparse_classes_30k_train_007861 | Implement the Python class `Riverbank` described below.
Class description:
Pygame sprite class for riverbank sprites used for killing the player
Method signatures and docstrings:
- def __init__(self, pos): - :param pos: An int representing the "index" of the riverbank. Should be 0-5, with 0 representing the left-most... | Implement the Python class `Riverbank` described below.
Class description:
Pygame sprite class for riverbank sprites used for killing the player
Method signatures and docstrings:
- def __init__(self, pos): - :param pos: An int representing the "index" of the riverbank. Should be 0-5, with 0 representing the left-most... | d8c6bad99ccaf10d3cca05b6fc44799e2f46ad2a | <|skeleton|>
class Riverbank:
"""Pygame sprite class for riverbank sprites used for killing the player"""
def __init__(self, pos):
"""- :param pos: An int representing the "index" of the riverbank. Should be 0-5, with 0 representing the left-most riverbank and 5 representing the right-most bank."""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Riverbank:
"""Pygame sprite class for riverbank sprites used for killing the player"""
def __init__(self, pos):
"""- :param pos: An int representing the "index" of the riverbank. Should be 0-5, with 0 representing the left-most riverbank and 5 representing the right-most bank."""
pygame.s... | the_stack_v2_python_sparse | src/Sprites/riverbank.py | johnpcooke94/project-scrumger-games | train | 0 |
d7dc2de967278bd3f5f0b3f17414d0ba3f4e1454 | [
"try:\n proband_id, relation_to_proband = self.original.split(self.delim)\n self.proband_id = proband_id\n self.relation_to_proband = [relation_to_proband]\nexcept ValueError as exc:\n if 'not enough values to unpack' in exc.args[0]:\n self.proband_id = self.original\n self.relation_to_pro... | <|body_start_0|>
try:
proband_id, relation_to_proband = self.original.split(self.delim)
self.proband_id = proband_id
self.relation_to_proband = [relation_to_proband]
except ValueError as exc:
if 'not enough values to unpack' in exc.args[0]:
... | Represent the original and digested information encoded in a biorepidnumber. | BiorepIDNumber | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BiorepIDNumber:
"""Represent the original and digested information encoded in a biorepidnumber."""
def __attrs_post_init__(self):
"""Perform custom __init__ actions after the attrs init func."""
<|body_0|>
def __relations_not_in(self, attribute, value):
"""Valida... | stack_v2_sparse_classes_75kplus_train_074587 | 2,212 | permissive | [
{
"docstring": "Perform custom __init__ actions after the attrs init func.",
"name": "__attrs_post_init__",
"signature": "def __attrs_post_init__(self)"
},
{
"docstring": "Validate that ``relation_to_proband`` is not in ``value``.",
"name": "__relations_not_in",
"signature": "def __relat... | 2 | null | Implement the Python class `BiorepIDNumber` described below.
Class description:
Represent the original and digested information encoded in a biorepidnumber.
Method signatures and docstrings:
- def __attrs_post_init__(self): Perform custom __init__ actions after the attrs init func.
- def __relations_not_in(self, attr... | Implement the Python class `BiorepIDNumber` described below.
Class description:
Represent the original and digested information encoded in a biorepidnumber.
Method signatures and docstrings:
- def __attrs_post_init__(self): Perform custom __init__ actions after the attrs init func.
- def __relations_not_in(self, attr... | 50396e5ffdff5473098556d18635daecb47b60d9 | <|skeleton|>
class BiorepIDNumber:
"""Represent the original and digested information encoded in a biorepidnumber."""
def __attrs_post_init__(self):
"""Perform custom __init__ actions after the attrs init func."""
<|body_0|>
def __relations_not_in(self, attribute, value):
"""Valida... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class BiorepIDNumber:
"""Represent the original and digested information encoded in a biorepidnumber."""
def __attrs_post_init__(self):
"""Perform custom __init__ actions after the attrs init func."""
try:
proband_id, relation_to_proband = self.original.split(self.delim)
... | the_stack_v2_python_sparse | src/biorep_etl/data/parsers/bch/biorepository.py | ScottSnapperLab/biorep-etl | train | 0 |
406e66a7dbdee8a5ac1b6aafa6a3a0fcc4ad9750 | [
"feature_id = kwargs['feature_id']\ngate_id = kwargs.get('gate_id', None)\nvotes = Vote.get_votes(feature_id=feature_id, gate_id=gate_id)\ndicts = [converters.vote_value_to_json_dict(v) for v in votes]\nreturn {'votes': dicts}",
"feature_id = kwargs['feature_id']\ngate_id = kwargs['gate_id']\nfeature = self.get_s... | <|body_start_0|>
feature_id = kwargs['feature_id']
gate_id = kwargs.get('gate_id', None)
votes = Vote.get_votes(feature_id=feature_id, gate_id=gate_id)
dicts = [converters.vote_value_to_json_dict(v) for v in votes]
return {'votes': dicts}
<|end_body_0|>
<|body_start_1|>
... | Users may see the set of votes on a feature, and add their own, if allowed. | VotesAPI | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VotesAPI:
"""Users may see the set of votes on a feature, and add their own, if allowed."""
def do_get(self, **kwargs) -> dict[str, list[dict[str, Any]]]:
"""Return a list of all vote values for a given feature."""
<|body_0|>
def do_post(self, **kwargs) -> dict[str, str]... | stack_v2_sparse_classes_75kplus_train_074588 | 4,047 | permissive | [
{
"docstring": "Return a list of all vote values for a given feature.",
"name": "do_get",
"signature": "def do_get(self, **kwargs) -> dict[str, list[dict[str, Any]]]"
},
{
"docstring": "Set a user's vote value for the specified feature and gate.",
"name": "do_post",
"signature": "def do_... | 3 | stack_v2_sparse_classes_30k_train_017054 | Implement the Python class `VotesAPI` described below.
Class description:
Users may see the set of votes on a feature, and add their own, if allowed.
Method signatures and docstrings:
- def do_get(self, **kwargs) -> dict[str, list[dict[str, Any]]]: Return a list of all vote values for a given feature.
- def do_post(s... | Implement the Python class `VotesAPI` described below.
Class description:
Users may see the set of votes on a feature, and add their own, if allowed.
Method signatures and docstrings:
- def do_get(self, **kwargs) -> dict[str, list[dict[str, Any]]]: Return a list of all vote values for a given feature.
- def do_post(s... | 17f9886d064da5bda84006d5866077727646fff2 | <|skeleton|>
class VotesAPI:
"""Users may see the set of votes on a feature, and add their own, if allowed."""
def do_get(self, **kwargs) -> dict[str, list[dict[str, Any]]]:
"""Return a list of all vote values for a given feature."""
<|body_0|>
def do_post(self, **kwargs) -> dict[str, str]... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class VotesAPI:
"""Users may see the set of votes on a feature, and add their own, if allowed."""
def do_get(self, **kwargs) -> dict[str, list[dict[str, Any]]]:
"""Return a list of all vote values for a given feature."""
feature_id = kwargs['feature_id']
gate_id = kwargs.get('gate_id', ... | the_stack_v2_python_sparse | api/reviews_api.py | GoogleChrome/chromium-dashboard | train | 574 |
8fec4c9193b5ae8636ce2e79b962fb6be2cf4ca5 | [
"self.active = active\nself.order_size_limit = int(order_size_limit)\nself.order_price_upper_limit = float(order_price_upper_limit)\nself.balance_use_limit = float(balance_use_limit)\nself.trade_count = trade_count\nself.trade_limit = int(trade_limit)",
"msg = ''\nif not self.active:\n msg = u'风控: 风控引擎未开启'\n ... | <|body_start_0|>
self.active = active
self.order_size_limit = int(order_size_limit)
self.order_price_upper_limit = float(order_price_upper_limit)
self.balance_use_limit = float(balance_use_limit)
self.trade_count = trade_count
self.trade_limit = int(trade_limit)
<|end_bod... | 风控引擎 | RiskManager | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RiskManager:
"""风控引擎"""
def __init__(self, active, order_size_limit, order_price_upper_limit, balance_use_limit, trade_limit, trade_count):
"""Constructor"""
<|body_0|>
def checkRisk(self, orderReq, tick, account):
"""检查风险"""
<|body_1|>
<|end_skeleton|>
... | stack_v2_sparse_classes_75kplus_train_074589 | 3,904 | no_license | [
{
"docstring": "Constructor",
"name": "__init__",
"signature": "def __init__(self, active, order_size_limit, order_price_upper_limit, balance_use_limit, trade_limit, trade_count)"
},
{
"docstring": "检查风险",
"name": "checkRisk",
"signature": "def checkRisk(self, orderReq, tick, account)"
... | 2 | stack_v2_sparse_classes_30k_train_048843 | Implement the Python class `RiskManager` described below.
Class description:
风控引擎
Method signatures and docstrings:
- def __init__(self, active, order_size_limit, order_price_upper_limit, balance_use_limit, trade_limit, trade_count): Constructor
- def checkRisk(self, orderReq, tick, account): 检查风险 | Implement the Python class `RiskManager` described below.
Class description:
风控引擎
Method signatures and docstrings:
- def __init__(self, active, order_size_limit, order_price_upper_limit, balance_use_limit, trade_limit, trade_count): Constructor
- def checkRisk(self, orderReq, tick, account): 检查风险
<|skeleton|>
class... | 1390db7bba9c2a3408b09a863b03f7802cbe2fff | <|skeleton|>
class RiskManager:
"""风控引擎"""
def __init__(self, active, order_size_limit, order_price_upper_limit, balance_use_limit, trade_limit, trade_count):
"""Constructor"""
<|body_0|>
def checkRisk(self, orderReq, tick, account):
"""检查风险"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class RiskManager:
"""风控引擎"""
def __init__(self, active, order_size_limit, order_price_upper_limit, balance_use_limit, trade_limit, trade_count):
"""Constructor"""
self.active = active
self.order_size_limit = int(order_size_limit)
self.order_price_upper_limit = float(order_price... | the_stack_v2_python_sparse | 基线库/源码/SQuant/trader/trade/riskManager.py | SQuantTeam/SQuant | train | 4 |
81b36b15f0205e2e8ed31653241e68ec27f153e1 | [
"activity = self.object\nid_list_schema = IdListSchema()\ntag_id_list = id_list_schema.deserialize(self.request_data)\nsession = activity.current_session\nquery = Tag.query(session=session)\nquery = query.filter(Tag.id.in_(tag_id_list))\ntag_list = query.all()\nfor tag in tag_list:\n activity.tags.append(tag)\nr... | <|body_start_0|>
activity = self.object
id_list_schema = IdListSchema()
tag_id_list = id_list_schema.deserialize(self.request_data)
session = activity.current_session
query = Tag.query(session=session)
query = query.filter(Tag.id.in_(tag_id_list))
tag_list = query... | REST API resource for Activity model. | ActivityResource | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ActivityResource:
"""REST API resource for Activity model."""
def add_tags(self):
"""Add tags to current activity. Return a List of Tags that were added."""
<|body_0|>
def remove_tags(self):
"""Remove tags from current activity. JSON request body is a list of int... | stack_v2_sparse_classes_75kplus_train_074590 | 2,050 | permissive | [
{
"docstring": "Add tags to current activity. Return a List of Tags that were added.",
"name": "add_tags",
"signature": "def add_tags(self)"
},
{
"docstring": "Remove tags from current activity. JSON request body is a list of integer values with Tag IDs to remove. Returns a list with the Tags th... | 2 | stack_v2_sparse_classes_30k_train_012656 | Implement the Python class `ActivityResource` described below.
Class description:
REST API resource for Activity model.
Method signatures and docstrings:
- def add_tags(self): Add tags to current activity. Return a List of Tags that were added.
- def remove_tags(self): Remove tags from current activity. JSON request ... | Implement the Python class `ActivityResource` described below.
Class description:
REST API resource for Activity model.
Method signatures and docstrings:
- def add_tags(self): Add tags to current activity. Return a List of Tags that were added.
- def remove_tags(self): Remove tags from current activity. JSON request ... | 2cbd9c0cc8f265eb1ddcb23c29c23e18e25bd421 | <|skeleton|>
class ActivityResource:
"""REST API resource for Activity model."""
def add_tags(self):
"""Add tags to current activity. Return a List of Tags that were added."""
<|body_0|>
def remove_tags(self):
"""Remove tags from current activity. JSON request body is a list of int... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ActivityResource:
"""REST API resource for Activity model."""
def add_tags(self):
"""Add tags to current activity. Return a List of Tags that were added."""
activity = self.object
id_list_schema = IdListSchema()
tag_id_list = id_list_schema.deserialize(self.request_data)
... | the_stack_v2_python_sparse | sandglass/time/api/v1/activity.py | jeronimoalbi/sandglass.time | train | 0 |
0afd4d6d8b8c52b30b8fe331a2ff48e628a88e87 | [
"bsscs = BSSCS_CLASSIFIER(l2_reg=tf.contrib.layers.l2_regularizer(scale=0.001), learning_rate=0.001, steps=250, batch=250)\nself.assertTrue(bsscs != None)\nsingle_layer = bsscs.create_layer(512, activation=tf.nn.relu)\nself.assertTrue(single_layer != None)",
"bsscs = BSSCS_CLASSIFIER(l2_reg=tf.contrib.layers.l2_r... | <|body_start_0|>
bsscs = BSSCS_CLASSIFIER(l2_reg=tf.contrib.layers.l2_regularizer(scale=0.001), learning_rate=0.001, steps=250, batch=250)
self.assertTrue(bsscs != None)
single_layer = bsscs.create_layer(512, activation=tf.nn.relu)
self.assertTrue(single_layer != None)
<|end_body_0|>
<|... | ClassifierNetworkTests | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ClassifierNetworkTests:
def test_layer_creation(self):
"""Tests the creation of a default layer preconditions: No layer has been created postconditions: layer with default placeholder has been created"""
<|body_0|>
def test_loss_creation(self):
"""Tests the creation ... | stack_v2_sparse_classes_75kplus_train_074591 | 3,035 | no_license | [
{
"docstring": "Tests the creation of a default layer preconditions: No layer has been created postconditions: layer with default placeholder has been created",
"name": "test_layer_creation",
"signature": "def test_layer_creation(self)"
},
{
"docstring": "Tests the creation of a loss function pr... | 4 | stack_v2_sparse_classes_30k_val_001842 | Implement the Python class `ClassifierNetworkTests` described below.
Class description:
Implement the ClassifierNetworkTests class.
Method signatures and docstrings:
- def test_layer_creation(self): Tests the creation of a default layer preconditions: No layer has been created postconditions: layer with default place... | Implement the Python class `ClassifierNetworkTests` described below.
Class description:
Implement the ClassifierNetworkTests class.
Method signatures and docstrings:
- def test_layer_creation(self): Tests the creation of a default layer preconditions: No layer has been created postconditions: layer with default place... | d665ca405bdf35fdb57f8149a10b90be82d8de22 | <|skeleton|>
class ClassifierNetworkTests:
def test_layer_creation(self):
"""Tests the creation of a default layer preconditions: No layer has been created postconditions: layer with default placeholder has been created"""
<|body_0|>
def test_loss_creation(self):
"""Tests the creation ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ClassifierNetworkTests:
def test_layer_creation(self):
"""Tests the creation of a default layer preconditions: No layer has been created postconditions: layer with default placeholder has been created"""
bsscs = BSSCS_CLASSIFIER(l2_reg=tf.contrib.layers.l2_regularizer(scale=0.001), learning_ra... | the_stack_v2_python_sparse | BSSCSFramework/classifier_tests.py | wezleysherman/TBI-NN-421 | train | 3 | |
eb83f960720951e9eea5a9c8b3c5fe1b9d71275d | [
"t1 = BinaryTree(3, BinaryTree(5, right=BinaryTree(2)))\nt2 = BinaryTree(4, BinaryTree(6), BinaryTree(7))\nt = BinaryTree(1, t1, t2)\nself.assertEqual(get_largest_height_difference(None), 0)\nself.assertEqual(get_largest_height_difference(t1), 2)\nself.assertEqual(get_largest_height_difference(t2), 0)\nself.assertE... | <|body_start_0|>
t1 = BinaryTree(3, BinaryTree(5, right=BinaryTree(2)))
t2 = BinaryTree(4, BinaryTree(6), BinaryTree(7))
t = BinaryTree(1, t1, t2)
self.assertEqual(get_largest_height_difference(None), 0)
self.assertEqual(get_largest_height_difference(t1), 2)
self.assertEq... | ExerciseTests | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ExerciseTests:
def test_client_code(self):
"""Tests the client code to make sure the exercise passes it."""
<|body_0|>
def test_hidden(self):
"""The hidden test for students."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
t1 = BinaryTree(3, BinaryT... | stack_v2_sparse_classes_75kplus_train_074592 | 2,301 | no_license | [
{
"docstring": "Tests the client code to make sure the exercise passes it.",
"name": "test_client_code",
"signature": "def test_client_code(self)"
},
{
"docstring": "The hidden test for students.",
"name": "test_hidden",
"signature": "def test_hidden(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_012219 | Implement the Python class `ExerciseTests` described below.
Class description:
Implement the ExerciseTests class.
Method signatures and docstrings:
- def test_client_code(self): Tests the client code to make sure the exercise passes it.
- def test_hidden(self): The hidden test for students. | Implement the Python class `ExerciseTests` described below.
Class description:
Implement the ExerciseTests class.
Method signatures and docstrings:
- def test_client_code(self): Tests the client code to make sure the exercise passes it.
- def test_hidden(self): The hidden test for students.
<|skeleton|>
class Exerci... | 556c5485e38ad81dae7bb14e312f2b081100245d | <|skeleton|>
class ExerciseTests:
def test_client_code(self):
"""Tests the client code to make sure the exercise passes it."""
<|body_0|>
def test_hidden(self):
"""The hidden test for students."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ExerciseTests:
def test_client_code(self):
"""Tests the client code to make sure the exercise passes it."""
t1 = BinaryTree(3, BinaryTree(5, right=BinaryTree(2)))
t2 = BinaryTree(4, BinaryTree(6), BinaryTree(7))
t = BinaryTree(1, t1, t2)
self.assertEqual(get_largest_hei... | the_stack_v2_python_sparse | pyta/Week10_summer/test_ex7.py | Kevintjy/Python-Beginner | train | 1 | |
4d5e8f7bce16534835cb54723402c0442eb632d7 | [
"self.mean = float(mean)\nself.stddev = float(stddev)\nif stddev < 1:\n raise ValueError('stddev must be a positive value')\nif data is not None and (not isinstance(data, list)):\n raise TypeError('data must be a list')\nif isinstance(data, list) and len(data) < 2:\n raise ValueError('data must contain mul... | <|body_start_0|>
self.mean = float(mean)
self.stddev = float(stddev)
if stddev < 1:
raise ValueError('stddev must be a positive value')
if data is not None and (not isinstance(data, list)):
raise TypeError('data must be a list')
if isinstance(data, list) a... | class Normal | Normal | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Normal:
"""class Normal"""
def __init__(self, data=None, mean=0.0, stddev=1.0):
"""data is a list of the data to be used to estimate the distribution mean is the mean of the distribution stddev is the standard deviation of the distribution Sets the instance attributes mean and stddev... | stack_v2_sparse_classes_75kplus_train_074593 | 2,397 | no_license | [
{
"docstring": "data is a list of the data to be used to estimate the distribution mean is the mean of the distribution stddev is the standard deviation of the distribution Sets the instance attributes mean and stddev",
"name": "__init__",
"signature": "def __init__(self, data=None, mean=0.0, stddev=1.0... | 5 | stack_v2_sparse_classes_30k_train_011188 | Implement the Python class `Normal` described below.
Class description:
class Normal
Method signatures and docstrings:
- def __init__(self, data=None, mean=0.0, stddev=1.0): data is a list of the data to be used to estimate the distribution mean is the mean of the distribution stddev is the standard deviation of the ... | Implement the Python class `Normal` described below.
Class description:
class Normal
Method signatures and docstrings:
- def __init__(self, data=None, mean=0.0, stddev=1.0): data is a list of the data to be used to estimate the distribution mean is the mean of the distribution stddev is the standard deviation of the ... | 4a7a8ff0c4f785656a395d0abf4f182ce1fef5bc | <|skeleton|>
class Normal:
"""class Normal"""
def __init__(self, data=None, mean=0.0, stddev=1.0):
"""data is a list of the data to be used to estimate the distribution mean is the mean of the distribution stddev is the standard deviation of the distribution Sets the instance attributes mean and stddev... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Normal:
"""class Normal"""
def __init__(self, data=None, mean=0.0, stddev=1.0):
"""data is a list of the data to be used to estimate the distribution mean is the mean of the distribution stddev is the standard deviation of the distribution Sets the instance attributes mean and stddev"""
s... | the_stack_v2_python_sparse | math/0x03-probability/normal.py | xica369/holbertonschool-machine_learning | train | 0 |
3b1eb63c7c5b22c4c784c696ff03a3b0f8430efc | [
"number = ''.join((c for c in number if c.isnumeric()))\nif len(number) == number_length:\n return number\nreturn None",
"number = number.replace(' ', '')\nresult = re.match('^[0-9]+$', number)\nif not result:\n return True\nreturn False",
"ni_nuber = re.match('^\\\\s*[a-zA-Z]{2}(?:\\\\s*\\\\d\\\\s*){6}[a... | <|body_start_0|>
number = ''.join((c for c in number if c.isnumeric()))
if len(number) == number_length:
return number
return None
<|end_body_0|>
<|body_start_1|>
number = number.replace(' ', '')
result = re.match('^[0-9]+$', number)
if not result:
... | NumberLengthValidator | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NumberLengthValidator:
def normalise_number(number, number_length):
"""Return a normalised NHS number if valid, or None if not,"""
<|body_0|>
def number_only(number):
"""Return a normalised NHS number if valid, or None if not,"""
<|body_1|>
def ni_number... | stack_v2_sparse_classes_75kplus_train_074594 | 1,349 | permissive | [
{
"docstring": "Return a normalised NHS number if valid, or None if not,",
"name": "normalise_number",
"signature": "def normalise_number(number, number_length)"
},
{
"docstring": "Return a normalised NHS number if valid, or None if not,",
"name": "number_only",
"signature": "def number_... | 3 | stack_v2_sparse_classes_30k_train_011957 | Implement the Python class `NumberLengthValidator` described below.
Class description:
Implement the NumberLengthValidator class.
Method signatures and docstrings:
- def normalise_number(number, number_length): Return a normalised NHS number if valid, or None if not,
- def number_only(number): Return a normalised NHS... | Implement the Python class `NumberLengthValidator` described below.
Class description:
Implement the NumberLengthValidator class.
Method signatures and docstrings:
- def normalise_number(number, number_length): Return a normalised NHS number if valid, or None if not,
- def number_only(number): Return a normalised NHS... | ad049db27650e850742a3bd466f96d36a3420589 | <|skeleton|>
class NumberLengthValidator:
def normalise_number(number, number_length):
"""Return a normalised NHS number if valid, or None if not,"""
<|body_0|>
def number_only(number):
"""Return a normalised NHS number if valid, or None if not,"""
<|body_1|>
def ni_number... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class NumberLengthValidator:
def normalise_number(number, number_length):
"""Return a normalised NHS number if valid, or None if not,"""
number = ''.join((c for c in number if c.isnumeric()))
if len(number) == number_length:
return number
return None
def number_only(... | the_stack_v2_python_sparse | ndopapp/main/ndop_validator.py | uk-gov-mirror/nhsconnect.ndop-nojs | train | 0 | |
4b025007c7c14e0c5a64a7cfb01d3ba79d1b27ab | [
"self.mirror = mirror\nself.codename = codename\nself.architecture = architecture\nself.repositories = repositories\nself.updates = updates",
"mirror_url = self.mirror.url()\nurls = []\nfor repository in self.repositories:\n urls.append(f'{mirror_url}dists/{self.codename}/{repository}/binary-{self.architecture... | <|body_start_0|>
self.mirror = mirror
self.codename = codename
self.architecture = architecture
self.repositories = repositories
self.updates = updates
<|end_body_0|>
<|body_start_1|>
mirror_url = self.mirror.url()
urls = []
for repository in self.reposit... | DebianBasedSource | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DebianBasedSource:
def __init__(self, mirror, codename, architecture, repositories, updates):
"""A Debian Based Source object that can be used to navigate debian based package archives. Parameters ---------- mirror : the mirror to use to download the source packages codename : the codena... | stack_v2_sparse_classes_75kplus_train_074595 | 4,691 | permissive | [
{
"docstring": "A Debian Based Source object that can be used to navigate debian based package archives. Parameters ---------- mirror : the mirror to use to download the source packages codename : the codename of the version of the distribution to use architecture : the target architecture of the packages repos... | 2 | stack_v2_sparse_classes_30k_train_008799 | Implement the Python class `DebianBasedSource` described below.
Class description:
Implement the DebianBasedSource class.
Method signatures and docstrings:
- def __init__(self, mirror, codename, architecture, repositories, updates): A Debian Based Source object that can be used to navigate debian based package archiv... | Implement the Python class `DebianBasedSource` described below.
Class description:
Implement the DebianBasedSource class.
Method signatures and docstrings:
- def __init__(self, mirror, codename, architecture, repositories, updates): A Debian Based Source object that can be used to navigate debian based package archiv... | dfe1a73aa72cad4338445bec370be064707bff0c | <|skeleton|>
class DebianBasedSource:
def __init__(self, mirror, codename, architecture, repositories, updates):
"""A Debian Based Source object that can be used to navigate debian based package archives. Parameters ---------- mirror : the mirror to use to download the source packages codename : the codena... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DebianBasedSource:
def __init__(self, mirror, codename, architecture, repositories, updates):
"""A Debian Based Source object that can be used to navigate debian based package archives. Parameters ---------- mirror : the mirror to use to download the source packages codename : the codename of the vers... | the_stack_v2_python_sparse | fetchy/plugins/packages/source.py | gridl/fetchy | train | 0 | |
1546e03a56a9d1d59ea5bdd4bb59dd13c408bab8 | [
"cache.clear()\npart = Part.objects.create(name='Test Part', description='I am but a humble test part', IPN='IPN-123')\nreturn part",
"cache.clear()\nself.assertTrue(part.settings.part_component_default())\nself.assertTrue(part.settings.part_purchaseable_default())\nself.assertFalse(part.settings.part_salable_def... | <|body_start_0|>
cache.clear()
part = Part.objects.create(name='Test Part', description='I am but a humble test part', IPN='IPN-123')
return part
<|end_body_0|>
<|body_start_1|>
cache.clear()
self.assertTrue(part.settings.part_component_default())
self.assertTrue(part.se... | Tests to ensure that the user-configurable default values work as expected. Some fields for the Part model can have default values specified by the user. | PartSettingsTest | [
"MIT",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PartSettingsTest:
"""Tests to ensure that the user-configurable default values work as expected. Some fields for the Part model can have default values specified by the user."""
def make_part(self):
"""Helper function to create a simple part."""
<|body_0|>
def test_defau... | stack_v2_sparse_classes_75kplus_train_074596 | 24,967 | permissive | [
{
"docstring": "Helper function to create a simple part.",
"name": "make_part",
"signature": "def make_part(self)"
},
{
"docstring": "Test that the default values for the part settings are correct.",
"name": "test_defaults",
"signature": "def test_defaults(self)"
},
{
"docstring"... | 5 | null | Implement the Python class `PartSettingsTest` described below.
Class description:
Tests to ensure that the user-configurable default values work as expected. Some fields for the Part model can have default values specified by the user.
Method signatures and docstrings:
- def make_part(self): Helper function to create... | Implement the Python class `PartSettingsTest` described below.
Class description:
Tests to ensure that the user-configurable default values work as expected. Some fields for the Part model can have default values specified by the user.
Method signatures and docstrings:
- def make_part(self): Helper function to create... | e88a8e99a5f0b201c67a95cba097c729f090d5e2 | <|skeleton|>
class PartSettingsTest:
"""Tests to ensure that the user-configurable default values work as expected. Some fields for the Part model can have default values specified by the user."""
def make_part(self):
"""Helper function to create a simple part."""
<|body_0|>
def test_defau... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PartSettingsTest:
"""Tests to ensure that the user-configurable default values work as expected. Some fields for the Part model can have default values specified by the user."""
def make_part(self):
"""Helper function to create a simple part."""
cache.clear()
part = Part.objects.c... | the_stack_v2_python_sparse | InvenTree/part/test_part.py | inventree/InvenTree | train | 3,077 |
e4cc7f263d1e2a103b065e68de700f19b2e0eb2c | [
"num = sum([n * pow(10, len(num) - i - 1) for i, n in enumerate(num)]) + k\nres = []\nwhile num:\n res = [num % 10] + res\n num = num // 10\nreturn res",
"res = []\ni = len(num) - 1\ncarry = 0\nwhile k or i >= 0 or carry:\n n1 = num[i] if i >= 0 else 0\n n2 = k % 10 if k else 0\n n = n1 + n2 + carr... | <|body_start_0|>
num = sum([n * pow(10, len(num) - i - 1) for i, n in enumerate(num)]) + k
res = []
while num:
res = [num % 10] + res
num = num // 10
return res
<|end_body_0|>
<|body_start_1|>
res = []
i = len(num) - 1
carry = 0
wh... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def addToArrayForm(self, num, k):
""":type num: List[int] :type k: int :rtype: List[int]"""
<|body_0|>
def addToArrayForm(self, num, k):
""":type num: List[int] :type k: int :rtype: List[int]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_75kplus_train_074597 | 2,023 | no_license | [
{
"docstring": ":type num: List[int] :type k: int :rtype: List[int]",
"name": "addToArrayForm",
"signature": "def addToArrayForm(self, num, k)"
},
{
"docstring": ":type num: List[int] :type k: int :rtype: List[int]",
"name": "addToArrayForm",
"signature": "def addToArrayForm(self, num, k... | 2 | stack_v2_sparse_classes_30k_train_020006 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def addToArrayForm(self, num, k): :type num: List[int] :type k: int :rtype: List[int]
- def addToArrayForm(self, num, k): :type num: List[int] :type k: int :rtype: List[int] | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def addToArrayForm(self, num, k): :type num: List[int] :type k: int :rtype: List[int]
- def addToArrayForm(self, num, k): :type num: List[int] :type k: int :rtype: List[int]
<|s... | 860590239da0618c52967a55eda8d6bbe00bfa96 | <|skeleton|>
class Solution:
def addToArrayForm(self, num, k):
""":type num: List[int] :type k: int :rtype: List[int]"""
<|body_0|>
def addToArrayForm(self, num, k):
""":type num: List[int] :type k: int :rtype: List[int]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def addToArrayForm(self, num, k):
""":type num: List[int] :type k: int :rtype: List[int]"""
num = sum([n * pow(10, len(num) - i - 1) for i, n in enumerate(num)]) + k
res = []
while num:
res = [num % 10] + res
num = num // 10
return res
... | the_stack_v2_python_sparse | LeetCode/p0989/I/add-to-array-form-of-integer.py | Ynjxsjmh/PracticeMakesPerfect | train | 0 | |
3aa2285efd246c67c64029f79686255970282379 | [
"if len(num) <= k:\n return '0'\nelif k <= 0:\n return num\ncount = 0\nindex = 0\nnew_num = ''\nwhile index < len(num):\n if index + 1 < len(num) and int(num[index]) > int(num[index + 1]):\n index += 1\n count += 1\n while new_num and count < k and (num[index] == '0'):\n new... | <|body_start_0|>
if len(num) <= k:
return '0'
elif k <= 0:
return num
count = 0
index = 0
new_num = ''
while index < len(num):
if index + 1 < len(num) and int(num[index]) > int(num[index + 1]):
index += 1
... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def _removeKdigits(self, num, k):
""":type num: str :type k: int :rtype: str"""
<|body_0|>
def __removeKdigits(self, num, k):
""":type num: str :type k: int :rtype: str"""
<|body_1|>
def removeKdigits(self, num, k):
""":type num: str :t... | stack_v2_sparse_classes_75kplus_train_074598 | 14,768 | permissive | [
{
"docstring": ":type num: str :type k: int :rtype: str",
"name": "_removeKdigits",
"signature": "def _removeKdigits(self, num, k)"
},
{
"docstring": ":type num: str :type k: int :rtype: str",
"name": "__removeKdigits",
"signature": "def __removeKdigits(self, num, k)"
},
{
"docst... | 3 | stack_v2_sparse_classes_30k_train_049060 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def _removeKdigits(self, num, k): :type num: str :type k: int :rtype: str
- def __removeKdigits(self, num, k): :type num: str :type k: int :rtype: str
- def removeKdigits(self, n... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def _removeKdigits(self, num, k): :type num: str :type k: int :rtype: str
- def __removeKdigits(self, num, k): :type num: str :type k: int :rtype: str
- def removeKdigits(self, n... | 0dd67edca4e0b0323cb5a7239f02ea46383cd15a | <|skeleton|>
class Solution:
def _removeKdigits(self, num, k):
""":type num: str :type k: int :rtype: str"""
<|body_0|>
def __removeKdigits(self, num, k):
""":type num: str :type k: int :rtype: str"""
<|body_1|>
def removeKdigits(self, num, k):
""":type num: str :t... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def _removeKdigits(self, num, k):
""":type num: str :type k: int :rtype: str"""
if len(num) <= k:
return '0'
elif k <= 0:
return num
count = 0
index = 0
new_num = ''
while index < len(num):
if index + 1 < len... | the_stack_v2_python_sparse | 402.remove-k-digits.py | windard/leeeeee | train | 0 | |
94d722f388d674c4b4bb8fdf9a1434a2c73d061e | [
"super(AgeFilter, self).__init__(order)\nself.age = age\nself.ageField = ageField\nself.ageTolerance = ageTolerance\nif self.ageTolerance < 0:\n self.ageTolerance = 0\nself.minAgeField = minAgeField\nself.maxAgeField = maxAgeField\nself.rejectUnclassified = rejectUnclassified",
"for result in results:\n if ... | <|body_start_0|>
super(AgeFilter, self).__init__(order)
self.age = age
self.ageField = ageField
self.ageTolerance = ageTolerance
if self.ageTolerance < 0:
self.ageTolerance = 0
self.minAgeField = minAgeField
self.maxAgeField = maxAgeField
self.... | Filters search results based on either a specific age or if the age is within an age range defined by the result. Note: there is no default value for 'age' it must be passed to this filter so that it can be customised for the application using it. Options: * order (int): filter precedence * age (integer) : the age of t... | AgeFilter | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AgeFilter:
"""Filters search results based on either a specific age or if the age is within an age range defined by the result. Note: there is no default value for 'age' it must be passed to this filter so that it can be customised for the application using it. Options: * order (int): filter prec... | stack_v2_sparse_classes_75kplus_train_074599 | 2,776 | permissive | [
{
"docstring": "Constructor for AgeFilter",
"name": "__init__",
"signature": "def __init__(self, age, ageField=None, ageTolerance=3, minAgeField='minAge', maxAgeField='maxAge', order=0, rejectUnclassified=False)"
},
{
"docstring": "Filters the results according to a given range in which the resu... | 2 | stack_v2_sparse_classes_30k_train_033408 | Implement the Python class `AgeFilter` described below.
Class description:
Filters search results based on either a specific age or if the age is within an age range defined by the result. Note: there is no default value for 'age' it must be passed to this filter so that it can be customised for the application using ... | Implement the Python class `AgeFilter` described below.
Class description:
Filters search results based on either a specific age or if the age is within an age range defined by the result. Note: there is no default value for 'age' it must be passed to this filter so that it can be customised for the application using ... | ed72aee466649bd834d5b4459eb6e0173df6e2ec | <|skeleton|>
class AgeFilter:
"""Filters search results based on either a specific age or if the age is within an age range defined by the result. Note: there is no default value for 'age' it must be passed to this filter so that it can be customised for the application using it. Options: * order (int): filter prec... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AgeFilter:
"""Filters search results based on either a specific age or if the age is within an age range defined by the result. Note: there is no default value for 'age' it must be passed to this filter so that it can be customised for the application using it. Options: * order (int): filter precedence * age ... | the_stack_v2_python_sparse | reference-code/puppy/result/filter/ageFilter.py | Granvanoeli/ifind | train | 0 |
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