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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values | methods listlengths 2 6 | n_methods int64 2 6 | original_id stringlengths 38 40 ⌀ | prompt stringlengths 160 3.93k | prompted_full_text stringlengths 681 10.7k | revision_id stringlengths 40 40 | skeleton stringlengths 162 4.09k | snapshot_name stringclasses 1
value | snapshot_source_dir stringclasses 1
value | solution stringlengths 331 8.3k | source stringclasses 1
value | source_path stringlengths 5 177 | source_repo stringlengths 6 88 | split stringclasses 1
value | star_events_count int64 0 209k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
2c5b3255f2bc9fa3d96f5af3b5885f817ee45e34 | [
"self._padding = padding\nself._padding_mode = padding_mode\nsuper(Pad1D, self).__init__(**kwargs)",
"if self._padding_mode == 'zero':\n paddings = ((0, 0), self._padding, (0, 0))\n outputs = tf.pad(inputs, paddings)\nelif self._padding_mode == 'wrap':\n outputs = tf.concat([inputs[:, -self._padding[0]:,... | <|body_start_0|>
self._padding = padding
self._padding_mode = padding_mode
super(Pad1D, self).__init__(**kwargs)
<|end_body_0|>
<|body_start_1|>
if self._padding_mode == 'zero':
paddings = ((0, 0), self._padding, (0, 0))
outputs = tf.pad(inputs, paddings)
... | Pads a (batch, size, channels) tensor. | Pad1D | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Pad1D:
"""Pads a (batch, size, channels) tensor."""
def __init__(self, padding, padding_mode, **kwargs):
"""Creates the padding layer. Args: padding: (pad_left, pad_right) pair. How many elements to add to both sides of the second dimension. If this is used for the very first layer o... | stack_v2_sparse_classes_10k_train_000900 | 14,886 | permissive | [
{
"docstring": "Creates the padding layer. Args: padding: (pad_left, pad_right) pair. How many elements to add to both sides of the second dimension. If this is used for the very first layer of the feelers CNN, this can be thought as the number of feeler entries to add before the first feeler entry and after th... | 2 | stack_v2_sparse_classes_30k_train_000552 | Implement the Python class `Pad1D` described below.
Class description:
Pads a (batch, size, channels) tensor.
Method signatures and docstrings:
- def __init__(self, padding, padding_mode, **kwargs): Creates the padding layer. Args: padding: (pad_left, pad_right) pair. How many elements to add to both sides of the sec... | Implement the Python class `Pad1D` described below.
Class description:
Pads a (batch, size, channels) tensor.
Method signatures and docstrings:
- def __init__(self, padding, padding_mode, **kwargs): Creates the padding layer. Args: padding: (pad_left, pad_right) pair. How many elements to add to both sides of the sec... | 26ab377a6853463b2efce40970e54d44b91e79ca | <|skeleton|>
class Pad1D:
"""Pads a (batch, size, channels) tensor."""
def __init__(self, padding, padding_mode, **kwargs):
"""Creates the padding layer. Args: padding: (pad_left, pad_right) pair. How many elements to add to both sides of the second dimension. If this is used for the very first layer o... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Pad1D:
"""Pads a (batch, size, channels) tensor."""
def __init__(self, padding, padding_mode, **kwargs):
"""Creates the padding layer. Args: padding: (pad_left, pad_right) pair. How many elements to add to both sides of the second dimension. If this is used for the very first layer of the feelers... | the_stack_v2_python_sparse | service/learner/brains/layers.py | stewartmiles/falken | train | 1 |
2b750661653a1e7d68e28546e0072acf8668062e | [
"if not maze or not maze[0]:\n return False\nm, n = (len(maze), len(maze[0]))\nk = len(self.DOORS)\nkeys = [0] * k\nhas_gold = False\nqueue = []\ndoors = [None] * k\nholds = [0] * k\nvisited = set()\nfor x in range(m):\n for y in range(n):\n if maze[x][y] == self.START:\n queue.append((x, y)... | <|body_start_0|>
if not maze or not maze[0]:
return False
m, n = (len(maze), len(maze[0]))
k = len(self.DOORS)
keys = [0] * k
has_gold = False
queue = []
doors = [None] * k
holds = [0] * k
visited = set()
for x in range(m):
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def find_treasure_in_maze(self, maze):
""":type maze: list[str] :rtype: bool"""
<|body_0|>
def bfs(self, maze, queue, keys, holds, doors, visited):
"""return True if got gold, otherwise False :type maze: list[str] :type queue: list[tuple[int]] :type keys: l... | stack_v2_sparse_classes_10k_train_000901 | 4,626 | no_license | [
{
"docstring": ":type maze: list[str] :rtype: bool",
"name": "find_treasure_in_maze",
"signature": "def find_treasure_in_maze(self, maze)"
},
{
"docstring": "return True if got gold, otherwise False :type maze: list[str] :type queue: list[tuple[int]] :type keys: list[int] :type holds: list[int] ... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def find_treasure_in_maze(self, maze): :type maze: list[str] :rtype: bool
- def bfs(self, maze, queue, keys, holds, doors, visited): return True if got gold, otherwise False :typ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def find_treasure_in_maze(self, maze): :type maze: list[str] :rtype: bool
- def bfs(self, maze, queue, keys, holds, doors, visited): return True if got gold, otherwise False :typ... | 91892fd64281d96b8a9d5c0d57b938c314ae71be | <|skeleton|>
class Solution:
def find_treasure_in_maze(self, maze):
""":type maze: list[str] :rtype: bool"""
<|body_0|>
def bfs(self, maze, queue, keys, holds, doors, visited):
"""return True if got gold, otherwise False :type maze: list[str] :type queue: list[tuple[int]] :type keys: l... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def find_treasure_in_maze(self, maze):
""":type maze: list[str] :rtype: bool"""
if not maze or not maze[0]:
return False
m, n = (len(maze), len(maze[0]))
k = len(self.DOORS)
keys = [0] * k
has_gold = False
queue = []
doors =... | the_stack_v2_python_sparse | other/find_treasure_in_maze.py | jaychsu/algorithm | train | 143 | |
4e9878922a1df080980f6ce06c1a1fb939c05562 | [
"def from_left(nums):\n \"\"\"increase the smaller number to the previous highest\"\"\"\n found = False\n p = nums[0]\n for i in range(1, len(nums)):\n if p > nums[i]:\n if found:\n return False\n found = True\n else:\n p = nums[i]\n retur... | <|body_start_0|>
def from_left(nums):
"""increase the smaller number to the previous highest"""
found = False
p = nums[0]
for i in range(1, len(nums)):
if p > nums[i]:
if found:
return False
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def checkPossibility(self, nums: List[int]) -> bool:
"""02/03/2021 18:41 Two passes from left and from right Time complexity: O(n) Space complexity: O(1)"""
<|body_0|>
def checkPossibility(self, nums: List[int]) -> bool:
"""One pass, inplace Time complexity... | stack_v2_sparse_classes_10k_train_000902 | 3,325 | no_license | [
{
"docstring": "02/03/2021 18:41 Two passes from left and from right Time complexity: O(n) Space complexity: O(1)",
"name": "checkPossibility",
"signature": "def checkPossibility(self, nums: List[int]) -> bool"
},
{
"docstring": "One pass, inplace Time complexity: O(n) Space complexity: O(1)",
... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def checkPossibility(self, nums: List[int]) -> bool: 02/03/2021 18:41 Two passes from left and from right Time complexity: O(n) Space complexity: O(1)
- def checkPossibility(self... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def checkPossibility(self, nums: List[int]) -> bool: 02/03/2021 18:41 Two passes from left and from right Time complexity: O(n) Space complexity: O(1)
- def checkPossibility(self... | 1389a009a02e90e8700a7a00e0b7f797c129cdf4 | <|skeleton|>
class Solution:
def checkPossibility(self, nums: List[int]) -> bool:
"""02/03/2021 18:41 Two passes from left and from right Time complexity: O(n) Space complexity: O(1)"""
<|body_0|>
def checkPossibility(self, nums: List[int]) -> bool:
"""One pass, inplace Time complexity... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def checkPossibility(self, nums: List[int]) -> bool:
"""02/03/2021 18:41 Two passes from left and from right Time complexity: O(n) Space complexity: O(1)"""
def from_left(nums):
"""increase the smaller number to the previous highest"""
found = False
... | the_stack_v2_python_sparse | leetcode/solved/665_Non-decreasing_Array/solution.py | sungminoh/algorithms | train | 0 | |
f41d9aa5ce5dcd04cc01b1109a73dcee668ac3df | [
"super(BahandauAttention, self).__init__()\nself.W1 = tf.keras.layers.Dense(units=units)\nself.W2 = tf.keras.layers.Dense(units=units)\nself.V = tf.keras.layers.Dense(units=1)",
"hidden_state_with_time_axis = tf.expand_dims(hidden_state, 1)\nscore = self.V(tf.nn.tanh(self.W1(hidden_state_with_time_axis) + self.W2... | <|body_start_0|>
super(BahandauAttention, self).__init__()
self.W1 = tf.keras.layers.Dense(units=units)
self.W2 = tf.keras.layers.Dense(units=units)
self.V = tf.keras.layers.Dense(units=1)
<|end_body_0|>
<|body_start_1|>
hidden_state_with_time_axis = tf.expand_dims(hidden_state,... | The attention layer with bahandau score. | BahandauAttention | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BahandauAttention:
"""The attention layer with bahandau score."""
def __init__(self, units):
"""The structure function. Args: units: The units number of attention hidden layer."""
<|body_0|>
def call(self, inputs, hidden_state):
"""The Args: inputs: The inputs. h... | stack_v2_sparse_classes_10k_train_000903 | 20,417 | no_license | [
{
"docstring": "The structure function. Args: units: The units number of attention hidden layer.",
"name": "__init__",
"signature": "def __init__(self, units)"
},
{
"docstring": "The Args: inputs: The inputs. hidden_state: The rnn hidden layer state. Returns: The context vectors and attention we... | 2 | stack_v2_sparse_classes_30k_train_001495 | Implement the Python class `BahandauAttention` described below.
Class description:
The attention layer with bahandau score.
Method signatures and docstrings:
- def __init__(self, units): The structure function. Args: units: The units number of attention hidden layer.
- def call(self, inputs, hidden_state): The Args: ... | Implement the Python class `BahandauAttention` described below.
Class description:
The attention layer with bahandau score.
Method signatures and docstrings:
- def __init__(self, units): The structure function. Args: units: The units number of attention hidden layer.
- def call(self, inputs, hidden_state): The Args: ... | d1b70b2a954f4665b628ba252b03c1a74b95559f | <|skeleton|>
class BahandauAttention:
"""The attention layer with bahandau score."""
def __init__(self, units):
"""The structure function. Args: units: The units number of attention hidden layer."""
<|body_0|>
def call(self, inputs, hidden_state):
"""The Args: inputs: The inputs. h... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class BahandauAttention:
"""The attention layer with bahandau score."""
def __init__(self, units):
"""The structure function. Args: units: The units number of attention hidden layer."""
super(BahandauAttention, self).__init__()
self.W1 = tf.keras.layers.Dense(units=units)
self.W... | the_stack_v2_python_sparse | NeuralNetworks-tensorflow/RNN/nmt_with_attention/nmt.py | zhaocc1106/machine_learn | train | 15 |
5533738cfe772ea3bb4f6f84500b97841a7e4725 | [
"if self.field:\n return 'Date field summary aggregations for \"{0:s}\"'.format(self.field)\nreturn 'Date field summary aggregations for an unknown field.'",
"self.field = field\nself.field_query_string = field_query_string\nformatted_field_name = self.format_field_by_type(field)\nif field_query_string == '*':... | <|body_start_0|>
if self.field:
return 'Date field summary aggregations for "{0:s}"'.format(self.field)
return 'Date field summary aggregations for an unknown field.'
<|end_body_0|>
<|body_start_1|>
self.field = field
self.field_query_string = field_query_string
form... | Date-based Summary Aggregations. | DateSummaryAggregator | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DateSummaryAggregator:
"""Date-based Summary Aggregations."""
def chart_title(self):
"""Returns a title for the chart."""
<|body_0|>
def run(self, field, field_query_string='*', start_time='', end_time='', date_interval='year'):
"""Runs the SummaryAggregation agg... | stack_v2_sparse_classes_10k_train_000904 | 13,136 | permissive | [
{
"docstring": "Returns a title for the chart.",
"name": "chart_title",
"signature": "def chart_title(self)"
},
{
"docstring": "Runs the SummaryAggregation aggregator. Args: field: What field to aggregate on. field_query_string: The field value(s) to aggregate on. supported_charts: The chart typ... | 2 | null | Implement the Python class `DateSummaryAggregator` described below.
Class description:
Date-based Summary Aggregations.
Method signatures and docstrings:
- def chart_title(self): Returns a title for the chart.
- def run(self, field, field_query_string='*', start_time='', end_time='', date_interval='year'): Runs the S... | Implement the Python class `DateSummaryAggregator` described below.
Class description:
Date-based Summary Aggregations.
Method signatures and docstrings:
- def chart_title(self): Returns a title for the chart.
- def run(self, field, field_query_string='*', start_time='', end_time='', date_interval='year'): Runs the S... | 24f471b58ca4a87cb053961b5f05c07a544ca7b8 | <|skeleton|>
class DateSummaryAggregator:
"""Date-based Summary Aggregations."""
def chart_title(self):
"""Returns a title for the chart."""
<|body_0|>
def run(self, field, field_query_string='*', start_time='', end_time='', date_interval='year'):
"""Runs the SummaryAggregation agg... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class DateSummaryAggregator:
"""Date-based Summary Aggregations."""
def chart_title(self):
"""Returns a title for the chart."""
if self.field:
return 'Date field summary aggregations for "{0:s}"'.format(self.field)
return 'Date field summary aggregations for an unknown field... | the_stack_v2_python_sparse | timesketch/lib/aggregators/summary.py | google/timesketch | train | 2,263 |
27804157bd4866469b89c0294fee607aa4b4d174 | [
"gt = cv2.imread(TestImageFeature.sample)\ngt = cv2.cvtColor(gt, cv2.COLOR_BGR2RGB)\nif image.shape != gt.shape:\n gt = cv2.resize(gt, (255, 255))\ngt = tf.convert_to_tensor(gt, dtype=tf.float32)\nssim = tf.image.ssim(image, gt, max_val=255)\nassert ssim.numpy() > criteria",
"if resize:\n feat = ImageFeatur... | <|body_start_0|>
gt = cv2.imread(TestImageFeature.sample)
gt = cv2.cvtColor(gt, cv2.COLOR_BGR2RGB)
if image.shape != gt.shape:
gt = cv2.resize(gt, (255, 255))
gt = tf.convert_to_tensor(gt, dtype=tf.float32)
ssim = tf.image.ssim(image, gt, max_val=255)
assert s... | TestImageFeature | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestImageFeature:
def check_ssim(image: tf.Tensor, criteria: float=0.99):
"""Check ssim with groud-truth sample"""
<|body_0|>
def test_encode_decode_in_eager_execution(self, resize):
"""Test encode-decode within eager execution mode Use ssim to check the decoded imag... | stack_v2_sparse_classes_10k_train_000905 | 8,391 | no_license | [
{
"docstring": "Check ssim with groud-truth sample",
"name": "check_ssim",
"signature": "def check_ssim(image: tf.Tensor, criteria: float=0.99)"
},
{
"docstring": "Test encode-decode within eager execution mode Use ssim to check the decoded image",
"name": "test_encode_decode_in_eager_execut... | 3 | stack_v2_sparse_classes_30k_train_002598 | Implement the Python class `TestImageFeature` described below.
Class description:
Implement the TestImageFeature class.
Method signatures and docstrings:
- def check_ssim(image: tf.Tensor, criteria: float=0.99): Check ssim with groud-truth sample
- def test_encode_decode_in_eager_execution(self, resize): Test encode-... | Implement the Python class `TestImageFeature` described below.
Class description:
Implement the TestImageFeature class.
Method signatures and docstrings:
- def check_ssim(image: tf.Tensor, criteria: float=0.99): Check ssim with groud-truth sample
- def test_encode_decode_in_eager_execution(self, resize): Test encode-... | 5da5317cedd380c244f20a96213e883d6ef29de2 | <|skeleton|>
class TestImageFeature:
def check_ssim(image: tf.Tensor, criteria: float=0.99):
"""Check ssim with groud-truth sample"""
<|body_0|>
def test_encode_decode_in_eager_execution(self, resize):
"""Test encode-decode within eager execution mode Use ssim to check the decoded imag... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TestImageFeature:
def check_ssim(image: tf.Tensor, criteria: float=0.99):
"""Check ssim with groud-truth sample"""
gt = cv2.imread(TestImageFeature.sample)
gt = cv2.cvtColor(gt, cv2.COLOR_BGR2RGB)
if image.shape != gt.shape:
gt = cv2.resize(gt, (255, 255))
g... | the_stack_v2_python_sparse | Database/_unittests/test_features.py | MingRuey/mlbox | train | 2 | |
97c48ebc01c91ca0db786bc0fd5d132d3b63ecc4 | [
"Search.__init__(self)\nself.token = token\nself.serviceName = 'YouTube'",
"self.logger.info('Running YouTube search for query %s...', query)\nurl = 'https://www.googleapis.com/youtube/v3/search?q=%s&maxResults=%i&part=snippet&key=%s&relevanceLanguage=%s&type=video' % (query.replace(' ', '+'), maxresults, self.to... | <|body_start_0|>
Search.__init__(self)
self.token = token
self.serviceName = 'YouTube'
<|end_body_0|>
<|body_start_1|>
self.logger.info('Running YouTube search for query %s...', query)
url = 'https://www.googleapis.com/youtube/v3/search?q=%s&maxResults=%i&part=snippet&key=%s&rel... | YouTubeSearch | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class YouTubeSearch:
def __init__(self, token):
"""Create a new YouTubeSearch instance. token should be a valid YouTube Data API key."""
<|body_0|>
def search(self, query, maxresults=10, lang='en', **opt):
"""Searches YouTube for videos using the given query. Returns a dic... | stack_v2_sparse_classes_10k_train_000906 | 5,488 | no_license | [
{
"docstring": "Create a new YouTubeSearch instance. token should be a valid YouTube Data API key.",
"name": "__init__",
"signature": "def __init__(self, token)"
},
{
"docstring": "Searches YouTube for videos using the given query. Returns a dict of url: title pairs pointing to videos. If maxres... | 2 | stack_v2_sparse_classes_30k_train_005953 | Implement the Python class `YouTubeSearch` described below.
Class description:
Implement the YouTubeSearch class.
Method signatures and docstrings:
- def __init__(self, token): Create a new YouTubeSearch instance. token should be a valid YouTube Data API key.
- def search(self, query, maxresults=10, lang='en', **opt)... | Implement the Python class `YouTubeSearch` described below.
Class description:
Implement the YouTubeSearch class.
Method signatures and docstrings:
- def __init__(self, token): Create a new YouTubeSearch instance. token should be a valid YouTube Data API key.
- def search(self, query, maxresults=10, lang='en', **opt)... | 5fbff4606d50a114613edbb1f360aca070be9226 | <|skeleton|>
class YouTubeSearch:
def __init__(self, token):
"""Create a new YouTubeSearch instance. token should be a valid YouTube Data API key."""
<|body_0|>
def search(self, query, maxresults=10, lang='en', **opt):
"""Searches YouTube for videos using the given query. Returns a dic... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class YouTubeSearch:
def __init__(self, token):
"""Create a new YouTubeSearch instance. token should be a valid YouTube Data API key."""
Search.__init__(self)
self.token = token
self.serviceName = 'YouTube'
def search(self, query, maxresults=10, lang='en', **opt):
"""Sea... | the_stack_v2_python_sparse | ytsearch.py | fredi-68/Ram | train | 0 | |
c8049094844995027357513c2e867c03987995f7 | [
"\"\"\" Take parameters, and Sprite Constants \"\"\"\nsuper(BeesSprite, self).__init__(world_map, BeesSprite.IMAGE, GRID_LOCK, BeesSprite.HEALTH_BAR, BeesSprite.AVG_SPEED, BeesSprite.VISION, coordinates)\nself.type = 'bees'\nself.prey = ['plant']",
"visible_tiles = vision.vision(15, self.world_map, self.tile)\nvi... | <|body_start_0|>
""" Take parameters, and Sprite Constants """
super(BeesSprite, self).__init__(world_map, BeesSprite.IMAGE, GRID_LOCK, BeesSprite.HEALTH_BAR, BeesSprite.AVG_SPEED, BeesSprite.VISION, coordinates)
self.type = 'bees'
self.prey = ['plant']
<|end_body_0|>
<|body_start_1|>
... | BeesSprite | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BeesSprite:
def __init__(self, world_map, GRID_LOCK, coordinates=None):
"""Create a BeesSprite object :param world_map: WorldMap Object :param coordinates: Array of coordinates [x,y] :param GRID_LOCK: Lock for screen (for threading)"""
<|body_0|>
def move(self, target=None):... | stack_v2_sparse_classes_10k_train_000907 | 3,276 | no_license | [
{
"docstring": "Create a BeesSprite object :param world_map: WorldMap Object :param coordinates: Array of coordinates [x,y] :param GRID_LOCK: Lock for screen (for threading)",
"name": "__init__",
"signature": "def __init__(self, world_map, GRID_LOCK, coordinates=None)"
},
{
"docstring": "@Overri... | 3 | stack_v2_sparse_classes_30k_train_003393 | Implement the Python class `BeesSprite` described below.
Class description:
Implement the BeesSprite class.
Method signatures and docstrings:
- def __init__(self, world_map, GRID_LOCK, coordinates=None): Create a BeesSprite object :param world_map: WorldMap Object :param coordinates: Array of coordinates [x,y] :param... | Implement the Python class `BeesSprite` described below.
Class description:
Implement the BeesSprite class.
Method signatures and docstrings:
- def __init__(self, world_map, GRID_LOCK, coordinates=None): Create a BeesSprite object :param world_map: WorldMap Object :param coordinates: Array of coordinates [x,y] :param... | 8995bd57ae0faaf7420c74e1a7b2c091c64d6942 | <|skeleton|>
class BeesSprite:
def __init__(self, world_map, GRID_LOCK, coordinates=None):
"""Create a BeesSprite object :param world_map: WorldMap Object :param coordinates: Array of coordinates [x,y] :param GRID_LOCK: Lock for screen (for threading)"""
<|body_0|>
def move(self, target=None):... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class BeesSprite:
def __init__(self, world_map, GRID_LOCK, coordinates=None):
"""Create a BeesSprite object :param world_map: WorldMap Object :param coordinates: Array of coordinates [x,y] :param GRID_LOCK: Lock for screen (for threading)"""
""" Take parameters, and Sprite Constants """
supe... | the_stack_v2_python_sparse | sprites/sprite___bees.py | EcoSimulator/EcoSim2.0 | train | 0 | |
2590c26528939dd5be2ef405a001557d30688d9e | [
"super(QCustomActionGroup, self).__init__(*args, **kwargs)\nself.triggered.connect(self.onTriggered)\nself._last_checked = None",
"if action.isCheckable() and action.isChecked():\n if self.isExclusive():\n last = self._last_checked\n if last is not None and last is not action:\n last.s... | <|body_start_0|>
super(QCustomActionGroup, self).__init__(*args, **kwargs)
self.triggered.connect(self.onTriggered)
self._last_checked = None
<|end_body_0|>
<|body_start_1|>
if action.isCheckable() and action.isChecked():
if self.isExclusive():
last = self._l... | A QActionGroup subclass which fixes some toggling issues. When a QActionGroup is set from non-exclusive to exclusive, it doesn't uncheck the non-current actions. It also does not keep track of the most recently checked widget when in non-exclusive mode, so that state is lost. This subclass corrects these issues. | QCustomActionGroup | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class QCustomActionGroup:
"""A QActionGroup subclass which fixes some toggling issues. When a QActionGroup is set from non-exclusive to exclusive, it doesn't uncheck the non-current actions. It also does not keep track of the most recently checked widget when in non-exclusive mode, so that state is los... | stack_v2_sparse_classes_10k_train_000908 | 6,993 | permissive | [
{
"docstring": "Initialize a QCustomActionGroup. Parameters ---------- *args, **kwargs The positional and keyword arguments needed to initialize a QActionGroup.",
"name": "__init__",
"signature": "def __init__(self, *args, **kwargs)"
},
{
"docstring": "The signal handler for the 'triggered' sign... | 3 | stack_v2_sparse_classes_30k_train_005867 | Implement the Python class `QCustomActionGroup` described below.
Class description:
A QActionGroup subclass which fixes some toggling issues. When a QActionGroup is set from non-exclusive to exclusive, it doesn't uncheck the non-current actions. It also does not keep track of the most recently checked widget when in n... | Implement the Python class `QCustomActionGroup` described below.
Class description:
A QActionGroup subclass which fixes some toggling issues. When a QActionGroup is set from non-exclusive to exclusive, it doesn't uncheck the non-current actions. It also does not keep track of the most recently checked widget when in n... | 1544e7fb371b8f941cfa2fde682795e479380284 | <|skeleton|>
class QCustomActionGroup:
"""A QActionGroup subclass which fixes some toggling issues. When a QActionGroup is set from non-exclusive to exclusive, it doesn't uncheck the non-current actions. It also does not keep track of the most recently checked widget when in non-exclusive mode, so that state is los... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class QCustomActionGroup:
"""A QActionGroup subclass which fixes some toggling issues. When a QActionGroup is set from non-exclusive to exclusive, it doesn't uncheck the non-current actions. It also does not keep track of the most recently checked widget when in non-exclusive mode, so that state is lost. This subcl... | the_stack_v2_python_sparse | enaml/qt/qt_action_group.py | MatthieuDartiailh/enaml | train | 26 |
2cf209d8ac3496f4a6ca3746e216ccf9a4b0e24f | [
"head = ListNode(0)\np = head\nwhile phead and qhead:\n if phead.val < qhead.val:\n p.next = phead\n phead = phead.next\n else:\n p.next = qhead\n qhead = qhead.next\n p = p.next\nif phead:\n p.next = phead\nif qhead:\n p.next = qhead\nreturn head.next",
"if not lists:\n... | <|body_start_0|>
head = ListNode(0)
p = head
while phead and qhead:
if phead.val < qhead.val:
p.next = phead
phead = phead.next
else:
p.next = qhead
qhead = qhead.next
p = p.next
if phead:... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def merge2Lists(self, phead, qhead):
"""合并2个有序链表"""
<|body_0|>
def mergeKLists(self, lists):
""":type lists: List[ListNode] :rtype: ListNode"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
head = ListNode(0)
p = head
while ... | stack_v2_sparse_classes_10k_train_000909 | 1,467 | no_license | [
{
"docstring": "合并2个有序链表",
"name": "merge2Lists",
"signature": "def merge2Lists(self, phead, qhead)"
},
{
"docstring": ":type lists: List[ListNode] :rtype: ListNode",
"name": "mergeKLists",
"signature": "def mergeKLists(self, lists)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def merge2Lists(self, phead, qhead): 合并2个有序链表
- def mergeKLists(self, lists): :type lists: List[ListNode] :rtype: ListNode | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def merge2Lists(self, phead, qhead): 合并2个有序链表
- def mergeKLists(self, lists): :type lists: List[ListNode] :rtype: ListNode
<|skeleton|>
class Solution:
def merge2Lists(self... | 5d3574ccd282d0146c83c286ae28d8baaabd4910 | <|skeleton|>
class Solution:
def merge2Lists(self, phead, qhead):
"""合并2个有序链表"""
<|body_0|>
def mergeKLists(self, lists):
""":type lists: List[ListNode] :rtype: ListNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def merge2Lists(self, phead, qhead):
"""合并2个有序链表"""
head = ListNode(0)
p = head
while phead and qhead:
if phead.val < qhead.val:
p.next = phead
phead = phead.next
else:
p.next = qhead
... | the_stack_v2_python_sparse | 23_合并K个排序链表.py | lovehhf/LeetCode | train | 0 | |
3801ed79f7c258e89672eb21a2c6c1d76b473ee8 | [
"subv = SimpleMachineVertex(None, '')\npl = Placement(subv, 0, 0, 1)\nPlacements([pl])",
"pls = Placements()\nself.assertEqual(pls._placements, dict())\nself.assertEqual(pls._machine_vertices, dict())",
"subv = list()\nfor i in range(5):\n subv.append(SimpleMachineVertex(None, ''))\npl = list()\nfor i in ran... | <|body_start_0|>
subv = SimpleMachineVertex(None, '')
pl = Placement(subv, 0, 0, 1)
Placements([pl])
<|end_body_0|>
<|body_start_1|>
pls = Placements()
self.assertEqual(pls._placements, dict())
self.assertEqual(pls._machine_vertices, dict())
<|end_body_1|>
<|body_start_... | tester for placements object in pacman.model.placements.placements | TestPlacements | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestPlacements:
"""tester for placements object in pacman.model.placements.placements"""
def test_create_new_placements(self):
"""test creating a placements object :return:"""
<|body_0|>
def test_create_new_empty_placements(self):
"""checks that creating an empty... | stack_v2_sparse_classes_10k_train_000910 | 2,548 | no_license | [
{
"docstring": "test creating a placements object :return:",
"name": "test_create_new_placements",
"signature": "def test_create_new_placements(self)"
},
{
"docstring": "checks that creating an empty placements object is valid :return:",
"name": "test_create_new_empty_placements",
"signa... | 5 | stack_v2_sparse_classes_30k_train_001750 | Implement the Python class `TestPlacements` described below.
Class description:
tester for placements object in pacman.model.placements.placements
Method signatures and docstrings:
- def test_create_new_placements(self): test creating a placements object :return:
- def test_create_new_empty_placements(self): checks t... | Implement the Python class `TestPlacements` described below.
Class description:
tester for placements object in pacman.model.placements.placements
Method signatures and docstrings:
- def test_create_new_placements(self): test creating a placements object :return:
- def test_create_new_empty_placements(self): checks t... | 5c2faba4d823e9341e5c18f61ea9bf8c6e15b687 | <|skeleton|>
class TestPlacements:
"""tester for placements object in pacman.model.placements.placements"""
def test_create_new_placements(self):
"""test creating a placements object :return:"""
<|body_0|>
def test_create_new_empty_placements(self):
"""checks that creating an empty... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TestPlacements:
"""tester for placements object in pacman.model.placements.placements"""
def test_create_new_placements(self):
"""test creating a placements object :return:"""
subv = SimpleMachineVertex(None, '')
pl = Placement(subv, 0, 0, 1)
Placements([pl])
def test... | the_stack_v2_python_sparse | unittests/model_tests/placement_tests/test_placements_model.py | kfriesth/PACMAN | train | 0 |
fd1eb433a667e93f061cffd39a8bbd32f2ebbb39 | [
"self.maxDiff = None\nentry = dedent('\\n Main topic text\\n # subtopics\\n ## foo\\n Foo sub-category\\n ### moo\\n Foo/Moo subsub-category\\n #### dum\\n Foo/Moo/Dum subsubsub-category\\n ## bar\\n Bar su... | <|body_start_0|>
self.maxDiff = None
entry = dedent('\n Main topic text\n # subtopics\n ## foo\n Foo sub-category\n ### moo\n Foo/Moo subsub-category\n #### dum\n Foo/Moo/Dum subsubsub-category\n ## bar\n ... | Test the subtopic parser. | TestParseSubtopics | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestParseSubtopics:
"""Test the subtopic parser."""
def test_parse_entry(self):
"""Test for subcategories"""
<|body_0|>
def test_parse_single_entry(self):
"""Test parsing single subcategory"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.ma... | stack_v2_sparse_classes_10k_train_000911 | 3,736 | permissive | [
{
"docstring": "Test for subcategories",
"name": "test_parse_entry",
"signature": "def test_parse_entry(self)"
},
{
"docstring": "Test parsing single subcategory",
"name": "test_parse_single_entry",
"signature": "def test_parse_single_entry(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_004258 | Implement the Python class `TestParseSubtopics` described below.
Class description:
Test the subtopic parser.
Method signatures and docstrings:
- def test_parse_entry(self): Test for subcategories
- def test_parse_single_entry(self): Test parsing single subcategory | Implement the Python class `TestParseSubtopics` described below.
Class description:
Test the subtopic parser.
Method signatures and docstrings:
- def test_parse_entry(self): Test for subcategories
- def test_parse_single_entry(self): Test parsing single subcategory
<|skeleton|>
class TestParseSubtopics:
"""Test ... | b3ca58b5c1325a3bf57051dfe23560a08d2947b7 | <|skeleton|>
class TestParseSubtopics:
"""Test the subtopic parser."""
def test_parse_entry(self):
"""Test for subcategories"""
<|body_0|>
def test_parse_single_entry(self):
"""Test parsing single subcategory"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TestParseSubtopics:
"""Test the subtopic parser."""
def test_parse_entry(self):
"""Test for subcategories"""
self.maxDiff = None
entry = dedent('\n Main topic text\n # subtopics\n ## foo\n Foo sub-category\n ### moo\n ... | the_stack_v2_python_sparse | evennia/help/tests.py | evennia/evennia | train | 1,781 |
cf0c5e3ddaecb2f9fd25dcafc1c660631e65a42d | [
"if self.has_permission('RightTPI') is False:\n self.no_access()\nwith Database() as db:\n if id_survey is None:\n data = db.query(Table).all()\n else:\n data = db.query(Table).get(id_survey)\nreturn {'data': data}",
"if self.has_permission('RightTPI') is False:\n self.no_access()\nid_su... | <|body_start_0|>
if self.has_permission('RightTPI') is False:
self.no_access()
with Database() as db:
if id_survey is None:
data = db.query(Table).all()
else:
data = db.query(Table).get(id_survey)
return {'data': data}
<|end_bod... | Survey | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Survey:
def get(self, id_survey=None):
"""Return the survey information :param id_survey: UUID"""
<|body_0|>
def create(self, body):
"""Create a new survey :param body: { name: JSON, survey_type: ENUM('test'), questions: JSON }"""
<|body_1|>
def modify(s... | stack_v2_sparse_classes_10k_train_000912 | 2,534 | no_license | [
{
"docstring": "Return the survey information :param id_survey: UUID",
"name": "get",
"signature": "def get(self, id_survey=None)"
},
{
"docstring": "Create a new survey :param body: { name: JSON, survey_type: ENUM('test'), questions: JSON }",
"name": "create",
"signature": "def create(s... | 4 | stack_v2_sparse_classes_30k_train_006719 | Implement the Python class `Survey` described below.
Class description:
Implement the Survey class.
Method signatures and docstrings:
- def get(self, id_survey=None): Return the survey information :param id_survey: UUID
- def create(self, body): Create a new survey :param body: { name: JSON, survey_type: ENUM('test')... | Implement the Python class `Survey` described below.
Class description:
Implement the Survey class.
Method signatures and docstrings:
- def get(self, id_survey=None): Return the survey information :param id_survey: UUID
- def create(self, body): Create a new survey :param body: { name: JSON, survey_type: ENUM('test')... | 43bd57c466a5cd3b133ddc437cb4a6b9f007d267 | <|skeleton|>
class Survey:
def get(self, id_survey=None):
"""Return the survey information :param id_survey: UUID"""
<|body_0|>
def create(self, body):
"""Create a new survey :param body: { name: JSON, survey_type: ENUM('test'), questions: JSON }"""
<|body_1|>
def modify(s... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Survey:
def get(self, id_survey=None):
"""Return the survey information :param id_survey: UUID"""
if self.has_permission('RightTPI') is False:
self.no_access()
with Database() as db:
if id_survey is None:
data = db.query(Table).all()
... | the_stack_v2_python_sparse | resturls/survey.py | CAUCA-9-1-1/survip-api | train | 1 | |
64a2dabeebcda17f2e421b0e05e9b6c1928665f6 | [
"if not root:\n return -1\nret = 1 + max((self.findLeavesHelper(child, results) for child in (root.left, root.right)))\nif ret >= len(results):\n results.append([])\nresults[ret].append(root.val)\nreturn ret",
"ret = []\nself.findLeavesHelper(root, ret)\nreturn ret"
] | <|body_start_0|>
if not root:
return -1
ret = 1 + max((self.findLeavesHelper(child, results) for child in (root.left, root.right)))
if ret >= len(results):
results.append([])
results[ret].append(root.val)
return ret
<|end_body_0|>
<|body_start_1|>
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findLeavesHelper(self, root, results):
"""push root and all descendants to results return the distance from root to farthest leaf"""
<|body_0|>
def findLeaves(self, root):
""":type root: TreeNode :rtype: List[List[int]]"""
<|body_1|>
<|end_skel... | stack_v2_sparse_classes_10k_train_000913 | 830 | no_license | [
{
"docstring": "push root and all descendants to results return the distance from root to farthest leaf",
"name": "findLeavesHelper",
"signature": "def findLeavesHelper(self, root, results)"
},
{
"docstring": ":type root: TreeNode :rtype: List[List[int]]",
"name": "findLeaves",
"signatur... | 2 | stack_v2_sparse_classes_30k_train_005672 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findLeavesHelper(self, root, results): push root and all descendants to results return the distance from root to farthest leaf
- def findLeaves(self, root): :type root: TreeN... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findLeavesHelper(self, root, results): push root and all descendants to results return the distance from root to farthest leaf
- def findLeaves(self, root): :type root: TreeN... | 6e051eb554d9cf6f424f1e0a77f3072adf7f64c4 | <|skeleton|>
class Solution:
def findLeavesHelper(self, root, results):
"""push root and all descendants to results return the distance from root to farthest leaf"""
<|body_0|>
def findLeaves(self, root):
""":type root: TreeNode :rtype: List[List[int]]"""
<|body_1|>
<|end_skel... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def findLeavesHelper(self, root, results):
"""push root and all descendants to results return the distance from root to farthest leaf"""
if not root:
return -1
ret = 1 + max((self.findLeavesHelper(child, results) for child in (root.left, root.right)))
if r... | the_stack_v2_python_sparse | 366. Find Leaves of Binary Tree.py | vincent-kangzhou/LeetCode-Python | train | 0 | |
3206706f2940b7954780b39e562687db186a8120 | [
"def postorder(root):\n return postorder(root.left) + postorder(root.right) + [root.val] if root else []\nreturn ' '.join(map(str, postorder(root)))",
"def helper(lower, upper):\n if not data or data[-1] < lower or data[-1] > upper:\n return None\n cur = data.pop()\n root = TreeNode(cur)\n r... | <|body_start_0|>
def postorder(root):
return postorder(root.left) + postorder(root.right) + [root.val] if root else []
return ' '.join(map(str, postorder(root)))
<|end_body_0|>
<|body_start_1|>
def helper(lower, upper):
if not data or data[-1] < lower or data[-1] > upper... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root: TreeNode) -> str:
"""Encodes a tree to a single string."""
<|body_0|>
def deserialize(self, data: str) -> TreeNode:
"""Decodes your encoded data to tree."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
def postorder(... | stack_v2_sparse_classes_10k_train_000914 | 1,111 | no_license | [
{
"docstring": "Encodes a tree to a single string.",
"name": "serialize",
"signature": "def serialize(self, root: TreeNode) -> str"
},
{
"docstring": "Decodes your encoded data to tree.",
"name": "deserialize",
"signature": "def deserialize(self, data: str) -> TreeNode"
}
] | 2 | null | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root: TreeNode) -> str: Encodes a tree to a single string.
- def deserialize(self, data: str) -> TreeNode: Decodes your encoded data to tree. | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root: TreeNode) -> str: Encodes a tree to a single string.
- def deserialize(self, data: str) -> TreeNode: Decodes your encoded data to tree.
<|skeleton|>
class Co... | 034efcefe9940267abcf4c9cab655b2344e3e901 | <|skeleton|>
class Codec:
def serialize(self, root: TreeNode) -> str:
"""Encodes a tree to a single string."""
<|body_0|>
def deserialize(self, data: str) -> TreeNode:
"""Decodes your encoded data to tree."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Codec:
def serialize(self, root: TreeNode) -> str:
"""Encodes a tree to a single string."""
def postorder(root):
return postorder(root.left) + postorder(root.right) + [root.val] if root else []
return ' '.join(map(str, postorder(root)))
def deserialize(self, data: str)... | the_stack_v2_python_sparse | 449_serialize_and_deserialize_bst.py | HongsenHe/algo2018 | train | 0 | |
80099bde77aa0a5ad3fce51183e75843a7d7bf11 | [
"if not chars:\n return 0\ni, j, count, last = (1, 1, 1, chars[0])\nfor j in range(1, len(chars)):\n if chars[j] != last:\n if count > 1:\n for digit in str(count):\n chars[i] = digit\n i += 1\n chars[i] = chars[j]\n i += 1\n last = chars[j]... | <|body_start_0|>
if not chars:
return 0
i, j, count, last = (1, 1, 1, chars[0])
for j in range(1, len(chars)):
if chars[j] != last:
if count > 1:
for digit in str(count):
chars[i] = digit
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def compress(self, chars):
""":type chars: List[str] :rtype: int"""
<|body_0|>
def compress2(self, chars):
""":type chars: List[str] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not chars:
return 0
i, ... | stack_v2_sparse_classes_10k_train_000915 | 2,800 | no_license | [
{
"docstring": ":type chars: List[str] :rtype: int",
"name": "compress",
"signature": "def compress(self, chars)"
},
{
"docstring": ":type chars: List[str] :rtype: int",
"name": "compress2",
"signature": "def compress2(self, chars)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def compress(self, chars): :type chars: List[str] :rtype: int
- def compress2(self, chars): :type chars: List[str] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def compress(self, chars): :type chars: List[str] :rtype: int
- def compress2(self, chars): :type chars: List[str] :rtype: int
<|skeleton|>
class Solution:
def compress(sel... | 635af6e22aa8eef8e7920a585d43a45a891a8157 | <|skeleton|>
class Solution:
def compress(self, chars):
""":type chars: List[str] :rtype: int"""
<|body_0|>
def compress2(self, chars):
""":type chars: List[str] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def compress(self, chars):
""":type chars: List[str] :rtype: int"""
if not chars:
return 0
i, j, count, last = (1, 1, 1, chars[0])
for j in range(1, len(chars)):
if chars[j] != last:
if count > 1:
for digit i... | the_stack_v2_python_sparse | code443StringCompression.py | cybelewang/leetcode-python | train | 0 | |
9514aac7959d4683866f58f39e280b93e6a5eba7 | [
"m = len(dungeon)\nif m <= 0:\n return 1\nn = len(dungeon[0])\ndp = [[0] * n for _ in range(m)]\ndp[-1][-1] = -min(0, dungeon[-1][-1]) + 1\nfor i in range(m - 2, -1, -1):\n dp[i][-1] = max(dp[i + 1][-1] - dungeon[i][-1], 1)\nfor j in range(n - 2, -1, -1):\n dp[-1][j] = max(dp[-1][j + 1] - dungeon[-1][j], 1... | <|body_start_0|>
m = len(dungeon)
if m <= 0:
return 1
n = len(dungeon[0])
dp = [[0] * n for _ in range(m)]
dp[-1][-1] = -min(0, dungeon[-1][-1]) + 1
for i in range(m - 2, -1, -1):
dp[i][-1] = max(dp[i + 1][-1] - dungeon[i][-1], 1)
for j in ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def calculateMinimumHP(self, dungeon):
""":type dungeon: List[List[int]] :rtype: int 55ms"""
<|body_0|>
def calculateMinimumHP1(self, dungeon):
""":type dungeon: List[List[int]] :rtype: int"""
<|body_1|>
def calculateMinimumHP_1(self, dungeon):... | stack_v2_sparse_classes_10k_train_000916 | 3,275 | no_license | [
{
"docstring": ":type dungeon: List[List[int]] :rtype: int 55ms",
"name": "calculateMinimumHP",
"signature": "def calculateMinimumHP(self, dungeon)"
},
{
"docstring": ":type dungeon: List[List[int]] :rtype: int",
"name": "calculateMinimumHP1",
"signature": "def calculateMinimumHP1(self, ... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def calculateMinimumHP(self, dungeon): :type dungeon: List[List[int]] :rtype: int 55ms
- def calculateMinimumHP1(self, dungeon): :type dungeon: List[List[int]] :rtype: int
- def ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def calculateMinimumHP(self, dungeon): :type dungeon: List[List[int]] :rtype: int 55ms
- def calculateMinimumHP1(self, dungeon): :type dungeon: List[List[int]] :rtype: int
- def ... | 679a2b246b8b6bb7fc55ed1c8096d3047d6d4461 | <|skeleton|>
class Solution:
def calculateMinimumHP(self, dungeon):
""":type dungeon: List[List[int]] :rtype: int 55ms"""
<|body_0|>
def calculateMinimumHP1(self, dungeon):
""":type dungeon: List[List[int]] :rtype: int"""
<|body_1|>
def calculateMinimumHP_1(self, dungeon):... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def calculateMinimumHP(self, dungeon):
""":type dungeon: List[List[int]] :rtype: int 55ms"""
m = len(dungeon)
if m <= 0:
return 1
n = len(dungeon[0])
dp = [[0] * n for _ in range(m)]
dp[-1][-1] = -min(0, dungeon[-1][-1]) + 1
for i i... | the_stack_v2_python_sparse | DungeonGame_HARD_174.py | 953250587/leetcode-python | train | 2 | |
0dede8582813858998aafa1921f7aa86ed0d54e4 | [
"expected = '{SSHA}xkDIIx1I7A4gC98Vt/+UelIkTDYxMjM0NQ=='\nresult = user.encodePassword('MoinMoin', salt='12345')\nassert result == expected\nresult = user.encodePassword(u'MoinMoin', salt='12345')\nassert result == expected",
"result = user.encodePassword(u'סיסמה סודית בהחלט', salt='12345')\nexpected = '{SSHA}Yiw... | <|body_start_0|>
expected = '{SSHA}xkDIIx1I7A4gC98Vt/+UelIkTDYxMjM0NQ=='
result = user.encodePassword('MoinMoin', salt='12345')
assert result == expected
result = user.encodePassword(u'MoinMoin', salt='12345')
assert result == expected
<|end_body_0|>
<|body_start_1|>
res... | user: encode passwords tests | TestEncodePassword | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestEncodePassword:
"""user: encode passwords tests"""
def testAscii(self):
"""user: encode ascii password"""
<|body_0|>
def testUnicode(self):
"""user: encode unicode password"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
expected = '{SSHA}xk... | stack_v2_sparse_classes_10k_train_000917 | 11,347 | no_license | [
{
"docstring": "user: encode ascii password",
"name": "testAscii",
"signature": "def testAscii(self)"
},
{
"docstring": "user: encode unicode password",
"name": "testUnicode",
"signature": "def testUnicode(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_006715 | Implement the Python class `TestEncodePassword` described below.
Class description:
user: encode passwords tests
Method signatures and docstrings:
- def testAscii(self): user: encode ascii password
- def testUnicode(self): user: encode unicode password | Implement the Python class `TestEncodePassword` described below.
Class description:
user: encode passwords tests
Method signatures and docstrings:
- def testAscii(self): user: encode ascii password
- def testUnicode(self): user: encode unicode password
<|skeleton|>
class TestEncodePassword:
"""user: encode passw... | d6e801402c4538bdfb34a97cf07153101167c1ec | <|skeleton|>
class TestEncodePassword:
"""user: encode passwords tests"""
def testAscii(self):
"""user: encode ascii password"""
<|body_0|>
def testUnicode(self):
"""user: encode unicode password"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TestEncodePassword:
"""user: encode passwords tests"""
def testAscii(self):
"""user: encode ascii password"""
expected = '{SSHA}xkDIIx1I7A4gC98Vt/+UelIkTDYxMjM0NQ=='
result = user.encodePassword('MoinMoin', salt='12345')
assert result == expected
result = user.enco... | the_stack_v2_python_sparse | MoinMoin/_tests/test_user.py | happytk/jardin | train | 0 |
61eb98f72306a5956921d213ffe3f60528d29617 | [
"if isinstance(distrib, dict):\n total_prob = sum(distrib.values())\n if total_prob <= 0.0:\n InferenceUtils.log.warning('all assignments in the distribution have a zero probability, cannot be normalised')\n return distrib\n for key, value in distrib.items():\n distrib[key] = distrib[k... | <|body_start_0|>
if isinstance(distrib, dict):
total_prob = sum(distrib.values())
if total_prob <= 0.0:
InferenceUtils.log.warning('all assignments in the distribution have a zero probability, cannot be normalised')
return distrib
for key, valu... | Utility functions for inference operations. | InferenceUtils | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InferenceUtils:
"""Utility functions for inference operations."""
def normalize(distrib):
"""Normalise the given probability distribution (assuming no conditional variables). :param distrib: the distribution to normalise :return: the normalised distribution"""
<|body_0|>
... | stack_v2_sparse_classes_10k_train_000918 | 5,313 | permissive | [
{
"docstring": "Normalise the given probability distribution (assuming no conditional variables). :param distrib: the distribution to normalise :return: the normalised distribution",
"name": "normalize",
"signature": "def normalize(distrib)"
},
{
"docstring": "Normalises the double array (ensuri... | 5 | stack_v2_sparse_classes_30k_train_001459 | Implement the Python class `InferenceUtils` described below.
Class description:
Utility functions for inference operations.
Method signatures and docstrings:
- def normalize(distrib): Normalise the given probability distribution (assuming no conditional variables). :param distrib: the distribution to normalise :retur... | Implement the Python class `InferenceUtils` described below.
Class description:
Utility functions for inference operations.
Method signatures and docstrings:
- def normalize(distrib): Normalise the given probability distribution (assuming no conditional variables). :param distrib: the distribution to normalise :retur... | c9bca653c18ccc082dc8b86b4a8feee9ed00a75b | <|skeleton|>
class InferenceUtils:
"""Utility functions for inference operations."""
def normalize(distrib):
"""Normalise the given probability distribution (assuming no conditional variables). :param distrib: the distribution to normalise :return: the normalised distribution"""
<|body_0|>
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class InferenceUtils:
"""Utility functions for inference operations."""
def normalize(distrib):
"""Normalise the given probability distribution (assuming no conditional variables). :param distrib: the distribution to normalise :return: the normalised distribution"""
if isinstance(distrib, dict)... | the_stack_v2_python_sparse | utils/inference_utils.py | ppijbb/PyOpenDial | train | 0 |
1b3538cb8b6ddc9180fb62f925ab213932bb6415 | [
"self.__rootFile = ROOT.TFile(rootPath)\nself.__rootTree = self.__rootFile.Get('Config')\nself.__rootTree.GetEntry(0)",
"leaf = self.__rootTree.GetLeaf(registerName)\nimport array\nregInfo = PRECINCT_INFO[precinctName][registerName]\nregData = array.array(ROOT_TYPECODE_2_ARRAY_TYPECODE[regInfo.typeCode], [0] * re... | <|body_start_0|>
self.__rootFile = ROOT.TFile(rootPath)
self.__rootTree = self.__rootFile.Get('Config')
self.__rootTree.GetEntry(0)
<|end_body_0|>
<|body_start_1|>
leaf = self.__rootTree.GetLeaf(registerName)
import array
regInfo = PRECINCT_INFO[precinctName][registerNam... | Provide LATC ROOT file data in form of python arrays | LATCRootFile | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LATCRootFile:
"""Provide LATC ROOT file data in form of python arrays"""
def __init__(self, rootPath):
"""open ROOT File args: rootPath - path to input LATC ROOT file"""
<|body_0|>
def getRegisterData(self, precinctName, registerName):
"""retrieve single dimensio... | stack_v2_sparse_classes_10k_train_000919 | 9,121 | permissive | [
{
"docstring": "open ROOT File args: rootPath - path to input LATC ROOT file",
"name": "__init__",
"signature": "def __init__(self, rootPath)"
},
{
"docstring": "retrieve single dimensional python array with data for specified register",
"name": "getRegisterData",
"signature": "def getRe... | 2 | stack_v2_sparse_classes_30k_train_007236 | Implement the Python class `LATCRootFile` described below.
Class description:
Provide LATC ROOT file data in form of python arrays
Method signatures and docstrings:
- def __init__(self, rootPath): open ROOT File args: rootPath - path to input LATC ROOT file
- def getRegisterData(self, precinctName, registerName): ret... | Implement the Python class `LATCRootFile` described below.
Class description:
Provide LATC ROOT file data in form of python arrays
Method signatures and docstrings:
- def __init__(self, rootPath): open ROOT File args: rootPath - path to input LATC ROOT file
- def getRegisterData(self, precinctName, registerName): ret... | 3b824540d8173a24be12316a3821304e4ea20a1f | <|skeleton|>
class LATCRootFile:
"""Provide LATC ROOT file data in form of python arrays"""
def __init__(self, rootPath):
"""open ROOT File args: rootPath - path to input LATC ROOT file"""
<|body_0|>
def getRegisterData(self, precinctName, registerName):
"""retrieve single dimensio... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class LATCRootFile:
"""Provide LATC ROOT file data in form of python arrays"""
def __init__(self, rootPath):
"""open ROOT File args: rootPath - path to input LATC ROOT file"""
self.__rootFile = ROOT.TFile(rootPath)
self.__rootTree = self.__rootFile.Get('Config')
self.__rootTree.... | the_stack_v2_python_sparse | python/LATCRootData.py | fermi-lat/configData | train | 0 |
5e872aaf50142500d7a3573769ca37b9a7cc7d65 | [
"super(ResNetBase, self).__init__()\nself.output_channel_block = [int(output_channel / 4), int(output_channel / 2), output_channel, output_channel]\nself.inplanes = int(output_channel / 8)\nself.conv0_1 = nn.Conv2d(input_channel, int(output_channel / 16), kernel_size=3, stride=1, padding=1, bias=False)\nself.bn0_1 ... | <|body_start_0|>
super(ResNetBase, self).__init__()
self.output_channel_block = [int(output_channel / 4), int(output_channel / 2), output_channel, output_channel]
self.inplanes = int(output_channel / 8)
self.conv0_1 = nn.Conv2d(input_channel, int(output_channel / 16), kernel_size=3, stri... | Base share backbone network | ResNetBase | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ResNetBase:
"""Base share backbone network"""
def __init__(self, input_channel, output_channel, block, layers):
"""Args: input_channel (int): input channel output_channel (int): output channel block (BasicBlock): convolution block layers (list): layers of the block"""
<|body_... | stack_v2_sparse_classes_10k_train_000920 | 11,483 | permissive | [
{
"docstring": "Args: input_channel (int): input channel output_channel (int): output channel block (BasicBlock): convolution block layers (list): layers of the block",
"name": "__init__",
"signature": "def __init__(self, input_channel, output_channel, block, layers)"
},
{
"docstring": "Args: bl... | 3 | stack_v2_sparse_classes_30k_test_000094 | Implement the Python class `ResNetBase` described below.
Class description:
Base share backbone network
Method signatures and docstrings:
- def __init__(self, input_channel, output_channel, block, layers): Args: input_channel (int): input channel output_channel (int): output channel block (BasicBlock): convolution bl... | Implement the Python class `ResNetBase` described below.
Class description:
Base share backbone network
Method signatures and docstrings:
- def __init__(self, input_channel, output_channel, block, layers): Args: input_channel (int): input channel output_channel (int): output channel block (BasicBlock): convolution bl... | fb47a96d1a38f5ce634c6f12d710ed5300cc89fc | <|skeleton|>
class ResNetBase:
"""Base share backbone network"""
def __init__(self, input_channel, output_channel, block, layers):
"""Args: input_channel (int): input channel output_channel (int): output channel block (BasicBlock): convolution block layers (list): layers of the block"""
<|body_... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ResNetBase:
"""Base share backbone network"""
def __init__(self, input_channel, output_channel, block, layers):
"""Args: input_channel (int): input channel output_channel (int): output channel block (BasicBlock): convolution block layers (list): layers of the block"""
super(ResNetBase, se... | the_stack_v2_python_sparse | davarocr/davarocr/davar_rcg/models/backbones/ResNetRFL.py | OCRWorld/DAVAR-Lab-OCR | train | 0 |
032349d03afa0b99286113274e73f38e7f31b83c | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn DeviceLogCollectionResponse()",
"from .app_log_upload_state import AppLogUploadState\nfrom .entity import Entity\nfrom .app_log_upload_state import AppLogUploadState\nfrom .entity import Entity\nfields: Dict[str, Callable[[Any], None]]... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return DeviceLogCollectionResponse()
<|end_body_0|>
<|body_start_1|>
from .app_log_upload_state import AppLogUploadState
from .entity import Entity
from .app_log_upload_state import App... | Windows Log Collection request entity. | DeviceLogCollectionResponse | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DeviceLogCollectionResponse:
"""Windows Log Collection request entity."""
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> DeviceLogCollectionResponse:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The pa... | stack_v2_sparse_classes_10k_train_000921 | 4,403 | permissive | [
{
"docstring": "Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Returns: DeviceLogCollectionResponse",
"name": "create_from_discriminator_value",
"signature": "def create_from_discr... | 3 | null | Implement the Python class `DeviceLogCollectionResponse` described below.
Class description:
Windows Log Collection request entity.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> DeviceLogCollectionResponse: Creates a new instance of the appropriate cl... | Implement the Python class `DeviceLogCollectionResponse` described below.
Class description:
Windows Log Collection request entity.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> DeviceLogCollectionResponse: Creates a new instance of the appropriate cl... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class DeviceLogCollectionResponse:
"""Windows Log Collection request entity."""
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> DeviceLogCollectionResponse:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The pa... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class DeviceLogCollectionResponse:
"""Windows Log Collection request entity."""
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> DeviceLogCollectionResponse:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to u... | the_stack_v2_python_sparse | msgraph/generated/models/device_log_collection_response.py | microsoftgraph/msgraph-sdk-python | train | 135 |
9193651aa9e4d16d33f0b7b4bdc8307099a537b2 | [
"cmd_output = self._run_command([self.EXECUTABLE, '--version'])\nmatch = re.search('^Poetry version (?P<version>\\\\S*)', cmd_output)\nif not match:\n LOGGER.warning('unable to parse poetry version from output:\\n%s', cmd_output)\n return Version('0.0.0')\nreturn Version(match.group('version'))",
"pyproject... | <|body_start_0|>
cmd_output = self._run_command([self.EXECUTABLE, '--version'])
match = re.search('^Poetry version (?P<version>\\S*)', cmd_output)
if not match:
LOGGER.warning('unable to parse poetry version from output:\n%s', cmd_output)
return Version('0.0.0')
r... | Poetry dependency manager. | Poetry | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Poetry:
"""Poetry dependency manager."""
def version(self) -> Version:
"""poetry version."""
<|body_0|>
def dir_is_project(cls, directory: StrPath, **__kwargs: Any) -> bool:
"""Determine if the directory contains a project for this dependency manager. Args: direc... | stack_v2_sparse_classes_10k_train_000922 | 4,732 | permissive | [
{
"docstring": "poetry version.",
"name": "version",
"signature": "def version(self) -> Version"
},
{
"docstring": "Determine if the directory contains a project for this dependency manager. Args: directory: Directory to check.",
"name": "dir_is_project",
"signature": "def dir_is_project... | 3 | stack_v2_sparse_classes_30k_train_003959 | Implement the Python class `Poetry` described below.
Class description:
Poetry dependency manager.
Method signatures and docstrings:
- def version(self) -> Version: poetry version.
- def dir_is_project(cls, directory: StrPath, **__kwargs: Any) -> bool: Determine if the directory contains a project for this dependency... | Implement the Python class `Poetry` described below.
Class description:
Poetry dependency manager.
Method signatures and docstrings:
- def version(self) -> Version: poetry version.
- def dir_is_project(cls, directory: StrPath, **__kwargs: Any) -> bool: Determine if the directory contains a project for this dependency... | 0763b06aee07d2cf3f037a49ca0cb81a048c5deb | <|skeleton|>
class Poetry:
"""Poetry dependency manager."""
def version(self) -> Version:
"""poetry version."""
<|body_0|>
def dir_is_project(cls, directory: StrPath, **__kwargs: Any) -> bool:
"""Determine if the directory contains a project for this dependency manager. Args: direc... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Poetry:
"""Poetry dependency manager."""
def version(self) -> Version:
"""poetry version."""
cmd_output = self._run_command([self.EXECUTABLE, '--version'])
match = re.search('^Poetry version (?P<version>\\S*)', cmd_output)
if not match:
LOGGER.warning('unable t... | the_stack_v2_python_sparse | runway/dependency_managers/_poetry.py | onicagroup/runway | train | 156 |
3e33a8ffefc16aa193800135bf66d0a940abcefb | [
"startTime = datetime.datetime.now()\nclient = dml.pymongo.MongoClient()\nrepo = client.repo\nrepo.authenticate('xcao19', 'xcao19')\nurl = 'http://data.insideairbnb.com/united-states/ma/boston/2019-01-17/visualisations/neighbourhoods.csv'\ndf = pd.read_csv(url, encoding='ISO-8859-1')\njson_df = df.to_json(orient='r... | <|body_start_0|>
startTime = datetime.datetime.now()
client = dml.pymongo.MongoClient()
repo = client.repo
repo.authenticate('xcao19', 'xcao19')
url = 'http://data.insideairbnb.com/united-states/ma/boston/2019-01-17/visualisations/neighbourhoods.csv'
df = pd.read_csv(url,... | AirBNB_neighborhoods | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AirBNB_neighborhoods:
def execute(trial=False):
"""Retrieve some data sets (not using the API here for the sake of simplicity)."""
<|body_0|>
def provenance(doc=prov.model.ProvDocument(), startTime=None, endTime=None):
"""Create the provenance document describing eve... | stack_v2_sparse_classes_10k_train_000923 | 3,316 | no_license | [
{
"docstring": "Retrieve some data sets (not using the API here for the sake of simplicity).",
"name": "execute",
"signature": "def execute(trial=False)"
},
{
"docstring": "Create the provenance document describing everything happening in this script. Each run of the script will generate a new d... | 2 | null | Implement the Python class `AirBNB_neighborhoods` described below.
Class description:
Implement the AirBNB_neighborhoods class.
Method signatures and docstrings:
- def execute(trial=False): Retrieve some data sets (not using the API here for the sake of simplicity).
- def provenance(doc=prov.model.ProvDocument(), sta... | Implement the Python class `AirBNB_neighborhoods` described below.
Class description:
Implement the AirBNB_neighborhoods class.
Method signatures and docstrings:
- def execute(trial=False): Retrieve some data sets (not using the API here for the sake of simplicity).
- def provenance(doc=prov.model.ProvDocument(), sta... | 90284cf3debbac36eead07b8d2339cdd191b86cf | <|skeleton|>
class AirBNB_neighborhoods:
def execute(trial=False):
"""Retrieve some data sets (not using the API here for the sake of simplicity)."""
<|body_0|>
def provenance(doc=prov.model.ProvDocument(), startTime=None, endTime=None):
"""Create the provenance document describing eve... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class AirBNB_neighborhoods:
def execute(trial=False):
"""Retrieve some data sets (not using the API here for the sake of simplicity)."""
startTime = datetime.datetime.now()
client = dml.pymongo.MongoClient()
repo = client.repo
repo.authenticate('xcao19', 'xcao19')
url... | the_stack_v2_python_sparse | xcao19/AirBNB_neighborhoods.py | maximega/course-2019-spr-proj | train | 2 | |
3e676a0487467960ba477b169e3e028a22a28896 | [
"line = line.rstrip('\\n')\ntry:\n super(DataSamplerTaskHadoop, self).__init__(line)\nexcept ValueError as e:\n raise DataSamplerTaskInitError('%s' % e)\ntry:\n self._ratio = self.get_attribute('ratio', self._json, 'ratio')\n self._encode = self.get_attribute('encode', self._json, 'code')\n self._dec... | <|body_start_0|>
line = line.rstrip('\n')
try:
super(DataSamplerTaskHadoop, self).__init__(line)
except ValueError as e:
raise DataSamplerTaskInitError('%s' % e)
try:
self._ratio = self.get_attribute('ratio', self._json, 'ratio')
self._enco... | hadoop data sampler task | DataSamplerTaskHadoop | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DataSamplerTaskHadoop:
"""hadoop data sampler task"""
def __init__(self, line):
"""Change line to taskconf object Args: line: str Exception: DataSamplerTaskInitError"""
<|body_0|>
def excute(self):
"""begin to sample Args: None Return: 0"""
<|body_1|>
<|... | stack_v2_sparse_classes_10k_train_000924 | 6,255 | no_license | [
{
"docstring": "Change line to taskconf object Args: line: str Exception: DataSamplerTaskInitError",
"name": "__init__",
"signature": "def __init__(self, line)"
},
{
"docstring": "begin to sample Args: None Return: 0",
"name": "excute",
"signature": "def excute(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_006199 | Implement the Python class `DataSamplerTaskHadoop` described below.
Class description:
hadoop data sampler task
Method signatures and docstrings:
- def __init__(self, line): Change line to taskconf object Args: line: str Exception: DataSamplerTaskInitError
- def excute(self): begin to sample Args: None Return: 0 | Implement the Python class `DataSamplerTaskHadoop` described below.
Class description:
hadoop data sampler task
Method signatures and docstrings:
- def __init__(self, line): Change line to taskconf object Args: line: str Exception: DataSamplerTaskInitError
- def excute(self): begin to sample Args: None Return: 0
<|s... | 913fb4af29f4395f4a300d35c00236065075960e | <|skeleton|>
class DataSamplerTaskHadoop:
"""hadoop data sampler task"""
def __init__(self, line):
"""Change line to taskconf object Args: line: str Exception: DataSamplerTaskInitError"""
<|body_0|>
def excute(self):
"""begin to sample Args: None Return: 0"""
<|body_1|>
<|... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class DataSamplerTaskHadoop:
"""hadoop data sampler task"""
def __init__(self, line):
"""Change line to taskconf object Args: line: str Exception: DataSamplerTaskInitError"""
line = line.rstrip('\n')
try:
super(DataSamplerTaskHadoop, self).__init__(line)
except Value... | the_stack_v2_python_sparse | script/data_sampler_task.py | jhuangpku/data_checker | train | 0 |
d7c841a1c0bc2e9f925ed9e277e34e965d845761 | [
"self.scenario = scenario\nself.actions = load_action_list(scenario)\nnvec = [len(self.action_types), len(self.scenario.subnets) - 1, max(self.scenario.subnets), self.scenario.num_os + 1, self.scenario.num_services, self.scenario.num_processes]\nsuper().__init__(nvec)",
"assert isinstance(action_vec, (list, tuple... | <|body_start_0|>
self.scenario = scenario
self.actions = load_action_list(scenario)
nvec = [len(self.action_types), len(self.scenario.subnets) - 1, max(self.scenario.subnets), self.scenario.num_os + 1, self.scenario.num_services, self.scenario.num_processes]
super().__init__(nvec)
<|end_... | A parameterised action space for NASim environment. Inherits and implements the gym.spaces.MultiDiscrete action space, where each dimension corresponds to a different action parameter. The action parameters (in order) are: 0. Action Type = [0, 5] Where: 0=Exploit, 1=PrivilegeEscalation, 2=ServiceScan, 3=OSScan, 4=Subne... | ParameterisedActionSpace | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ParameterisedActionSpace:
"""A parameterised action space for NASim environment. Inherits and implements the gym.spaces.MultiDiscrete action space, where each dimension corresponds to a different action parameter. The action parameters (in order) are: 0. Action Type = [0, 5] Where: 0=Exploit, 1=P... | stack_v2_sparse_classes_10k_train_000925 | 25,856 | permissive | [
{
"docstring": "Parameters ---------- scenario : Scenario scenario description",
"name": "__init__",
"signature": "def __init__(self, scenario)"
},
{
"docstring": "Get Action object corresponding to action vector. Parameters ---------- action_vector : list of ints or tuple of ints or Numpy.Array... | 5 | stack_v2_sparse_classes_30k_train_004203 | Implement the Python class `ParameterisedActionSpace` described below.
Class description:
A parameterised action space for NASim environment. Inherits and implements the gym.spaces.MultiDiscrete action space, where each dimension corresponds to a different action parameter. The action parameters (in order) are: 0. Act... | Implement the Python class `ParameterisedActionSpace` described below.
Class description:
A parameterised action space for NASim environment. Inherits and implements the gym.spaces.MultiDiscrete action space, where each dimension corresponds to a different action parameter. The action parameters (in order) are: 0. Act... | 4f26de37cfdc3e4553ed8b7484c4db8e2924bdea | <|skeleton|>
class ParameterisedActionSpace:
"""A parameterised action space for NASim environment. Inherits and implements the gym.spaces.MultiDiscrete action space, where each dimension corresponds to a different action parameter. The action parameters (in order) are: 0. Action Type = [0, 5] Where: 0=Exploit, 1=P... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ParameterisedActionSpace:
"""A parameterised action space for NASim environment. Inherits and implements the gym.spaces.MultiDiscrete action space, where each dimension corresponds to a different action parameter. The action parameters (in order) are: 0. Action Type = [0, 5] Where: 0=Exploit, 1=PrivilegeEscal... | the_stack_v2_python_sparse | nasim/envs/action.py | Jjschwartz/NetworkAttackSimulator | train | 101 |
682254421905ea22ba187f9b2c48f2f88701294a | [
"while sx < tx and sy < ty:\n tx, ty = (tx % ty, ty % tx)\nreturn sx == tx and sy <= ty and ((ty - sy) % sx == 0) or (sy == ty and sx <= tx and ((tx - sx) % sy == 0))",
"while sx < tx and sy < ty:\n tx, ty = (tx % ty, ty % tx)\nreturn sx == tx and sy <= ty and ((ty - sy) % sx == 0) or (sy == ty and sx <= tx... | <|body_start_0|>
while sx < tx and sy < ty:
tx, ty = (tx % ty, ty % tx)
return sx == tx and sy <= ty and ((ty - sy) % sx == 0) or (sy == ty and sx <= tx and ((tx - sx) % sy == 0))
<|end_body_0|>
<|body_start_1|>
while sx < tx and sy < ty:
tx, ty = (tx % ty, ty % tx)
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def reachingPoints(self, sx, sy, tx, ty):
""":type sx: int :type sy: int :type tx: int :type ty: int :rtype: bool"""
<|body_0|>
def rewrite(self, sx, sy, tx, ty):
""":type sx: int :type sy: int :type tx: int :type ty: int :rtype: bool A move consists of tak... | stack_v2_sparse_classes_10k_train_000926 | 2,133 | no_license | [
{
"docstring": ":type sx: int :type sy: int :type tx: int :type ty: int :rtype: bool",
"name": "reachingPoints",
"signature": "def reachingPoints(self, sx, sy, tx, ty)"
},
{
"docstring": ":type sx: int :type sy: int :type tx: int :type ty: int :rtype: bool A move consists of taking a point (x, y... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def reachingPoints(self, sx, sy, tx, ty): :type sx: int :type sy: int :type tx: int :type ty: int :rtype: bool
- def rewrite(self, sx, sy, tx, ty): :type sx: int :type sy: int :t... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def reachingPoints(self, sx, sy, tx, ty): :type sx: int :type sy: int :type tx: int :type ty: int :rtype: bool
- def rewrite(self, sx, sy, tx, ty): :type sx: int :type sy: int :t... | 6350568d16b0f8c49a020f055bb6d72e2705ea56 | <|skeleton|>
class Solution:
def reachingPoints(self, sx, sy, tx, ty):
""":type sx: int :type sy: int :type tx: int :type ty: int :rtype: bool"""
<|body_0|>
def rewrite(self, sx, sy, tx, ty):
""":type sx: int :type sy: int :type tx: int :type ty: int :rtype: bool A move consists of tak... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def reachingPoints(self, sx, sy, tx, ty):
""":type sx: int :type sy: int :type tx: int :type ty: int :rtype: bool"""
while sx < tx and sy < ty:
tx, ty = (tx % ty, ty % tx)
return sx == tx and sy <= ty and ((ty - sy) % sx == 0) or (sy == ty and sx <= tx and ((tx - ... | the_stack_v2_python_sparse | math/780_Reaching_Points.py | vsdrun/lc_public | train | 6 | |
1bf31946657b271b7a836bb0e7a1312e0febc74b | [
"n = len(s)\nif n == 0:\n return '^$'\nres = '^'\nfor i in range(n):\n res += '#' + s[i]\nres += '#$'\nreturn res",
"T = self.preProcess(s)\nn = len(T)\np = [0] * n\nC, R = (0, 0)\nfor i in range(1, n - 1):\n i_mirror = 2 * C - i\n if R > i:\n p[i] = min(R - i, p[i_mirror])\n while T[i + 1 +... | <|body_start_0|>
n = len(s)
if n == 0:
return '^$'
res = '^'
for i in range(n):
res += '#' + s[i]
res += '#$'
return res
<|end_body_0|>
<|body_start_1|>
T = self.preProcess(s)
n = len(T)
p = [0] * n
C, R = (0, 0)
... | Solution3 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution3:
def preProcess(self, s):
"""Transform S into T. For example, S = "abba", T = "^#a#b#b#a#$". ^ and $ signs are sentinels appended to each end to avoid bounds checking"""
<|body_0|>
def longestPalindrome(self, s):
""":type s: str :rtype: str"""
<|bod... | stack_v2_sparse_classes_10k_train_000927 | 2,734 | no_license | [
{
"docstring": "Transform S into T. For example, S = \"abba\", T = \"^#a#b#b#a#$\". ^ and $ signs are sentinels appended to each end to avoid bounds checking",
"name": "preProcess",
"signature": "def preProcess(self, s)"
},
{
"docstring": ":type s: str :rtype: str",
"name": "longestPalindrom... | 2 | stack_v2_sparse_classes_30k_train_000612 | Implement the Python class `Solution3` described below.
Class description:
Implement the Solution3 class.
Method signatures and docstrings:
- def preProcess(self, s): Transform S into T. For example, S = "abba", T = "^#a#b#b#a#$". ^ and $ signs are sentinels appended to each end to avoid bounds checking
- def longest... | Implement the Python class `Solution3` described below.
Class description:
Implement the Solution3 class.
Method signatures and docstrings:
- def preProcess(self, s): Transform S into T. For example, S = "abba", T = "^#a#b#b#a#$". ^ and $ signs are sentinels appended to each end to avoid bounds checking
- def longest... | 08e791733824ddf82ba07d1666b1e5e07fb8189d | <|skeleton|>
class Solution3:
def preProcess(self, s):
"""Transform S into T. For example, S = "abba", T = "^#a#b#b#a#$". ^ and $ signs are sentinels appended to each end to avoid bounds checking"""
<|body_0|>
def longestPalindrome(self, s):
""":type s: str :rtype: str"""
<|bod... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution3:
def preProcess(self, s):
"""Transform S into T. For example, S = "abba", T = "^#a#b#b#a#$". ^ and $ signs are sentinels appended to each end to avoid bounds checking"""
n = len(s)
if n == 0:
return '^$'
res = '^'
for i in range(n):
res... | the_stack_v2_python_sparse | longest_palindromic_substring.py | mihaanali/coding_practice | train | 0 | |
71d305bfd850dbee94b3f4b3c6a359dc403a8af3 | [
"mongo = database.MongoDBConnection()\nwith mongo:\n db = mongo.connection.HPNortonDatabase\n products = db['products']\n customers = db['customers']\n rentals = db['rentals']\nproducts.drop()\ncustomers.drop()\nrentals.drop()",
"directory_path = 'data'\ntuple1, tuple2 = database.import_data(directory... | <|body_start_0|>
mongo = database.MongoDBConnection()
with mongo:
db = mongo.connection.HPNortonDatabase
products = db['products']
customers = db['customers']
rentals = db['rentals']
products.drop()
customers.drop()
rentals.drop()
<... | Tests for the database module | DatabaseTests | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DatabaseTests:
"""Tests for the database module"""
def setUp(self):
"""Sets up database for each test"""
<|body_0|>
def test_import_data(self):
"""Tests the import_data function"""
<|body_1|>
def test_show_available_products(self):
"""Tests t... | stack_v2_sparse_classes_10k_train_000928 | 3,519 | no_license | [
{
"docstring": "Sets up database for each test",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "Tests the import_data function",
"name": "test_import_data",
"signature": "def test_import_data(self)"
},
{
"docstring": "Tests the show_available_products module",... | 4 | null | Implement the Python class `DatabaseTests` described below.
Class description:
Tests for the database module
Method signatures and docstrings:
- def setUp(self): Sets up database for each test
- def test_import_data(self): Tests the import_data function
- def test_show_available_products(self): Tests the show_availab... | Implement the Python class `DatabaseTests` described below.
Class description:
Tests for the database module
Method signatures and docstrings:
- def setUp(self): Sets up database for each test
- def test_import_data(self): Tests the import_data function
- def test_show_available_products(self): Tests the show_availab... | 5dac60f39e3909ff05b26721d602ed20f14d6be3 | <|skeleton|>
class DatabaseTests:
"""Tests for the database module"""
def setUp(self):
"""Sets up database for each test"""
<|body_0|>
def test_import_data(self):
"""Tests the import_data function"""
<|body_1|>
def test_show_available_products(self):
"""Tests t... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class DatabaseTests:
"""Tests for the database module"""
def setUp(self):
"""Sets up database for each test"""
mongo = database.MongoDBConnection()
with mongo:
db = mongo.connection.HPNortonDatabase
products = db['products']
customers = db['customers'... | the_stack_v2_python_sparse | students/amirg/lesson09/assignment/test_database.py | JavaRod/SP_Python220B_2019 | train | 1 |
f382f24c18c81e7fca39440e5fa55080e1c486a0 | [
"from fractions import gcd\nvals = collections.Counter(deck).values()\nreturn reduce(gcd, vals) >= 2",
"def gcd(a, b):\n if b == 0:\n return a\n return gcd(b, a % b)\nvals = collections.Counter(deck).values()\nreturn reduce(gcd, vals) > 1",
"n = len(deck)\nvals = collections.Counter(deck).values()\... | <|body_start_0|>
from fractions import gcd
vals = collections.Counter(deck).values()
return reduce(gcd, vals) >= 2
<|end_body_0|>
<|body_start_1|>
def gcd(a, b):
if b == 0:
return a
return gcd(b, a % b)
vals = collections.Counter(deck).val... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def hasGroupsSizeX(self, deck):
""":type deck: List[int] :rtype: bool"""
<|body_0|>
def hasGroupsSizeX(self, deck):
""":type deck: List[int] :rtype: bool"""
<|body_1|>
def hasGroupsSizeX(self, deck):
""":type deck: List[int] :rtype: boo... | stack_v2_sparse_classes_10k_train_000929 | 1,001 | no_license | [
{
"docstring": ":type deck: List[int] :rtype: bool",
"name": "hasGroupsSizeX",
"signature": "def hasGroupsSizeX(self, deck)"
},
{
"docstring": ":type deck: List[int] :rtype: bool",
"name": "hasGroupsSizeX",
"signature": "def hasGroupsSizeX(self, deck)"
},
{
"docstring": ":type de... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def hasGroupsSizeX(self, deck): :type deck: List[int] :rtype: bool
- def hasGroupsSizeX(self, deck): :type deck: List[int] :rtype: bool
- def hasGroupsSizeX(self, deck): :type de... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def hasGroupsSizeX(self, deck): :type deck: List[int] :rtype: bool
- def hasGroupsSizeX(self, deck): :type deck: List[int] :rtype: bool
- def hasGroupsSizeX(self, deck): :type de... | a509b383a42f54313970168d9faa11f088f18708 | <|skeleton|>
class Solution:
def hasGroupsSizeX(self, deck):
""":type deck: List[int] :rtype: bool"""
<|body_0|>
def hasGroupsSizeX(self, deck):
""":type deck: List[int] :rtype: bool"""
<|body_1|>
def hasGroupsSizeX(self, deck):
""":type deck: List[int] :rtype: boo... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def hasGroupsSizeX(self, deck):
""":type deck: List[int] :rtype: bool"""
from fractions import gcd
vals = collections.Counter(deck).values()
return reduce(gcd, vals) >= 2
def hasGroupsSizeX(self, deck):
""":type deck: List[int] :rtype: bool"""
def... | the_stack_v2_python_sparse | 0914_X_of_a_Kind_in_a_Deck_of_Cards.py | bingli8802/leetcode | train | 0 | |
e2671ef3ec11f82e4070e8f740b54abe4796c0fb | [
"scripts = ['core_parser_app/js/builtin/autocomplete.js'] + scripts\nAbstractModule.__init__(self, scripts=scripts, styles=styles)\nself.label = label",
"params = {}\nif self.data != '':\n params['value'] = self.data\nif self.label is not None:\n params.update({'label': self.label})\nreturn AbstractModule.r... | <|body_start_0|>
scripts = ['core_parser_app/js/builtin/autocomplete.js'] + scripts
AbstractModule.__init__(self, scripts=scripts, styles=styles)
self.label = label
<|end_body_0|>
<|body_start_1|>
params = {}
if self.data != '':
params['value'] = self.data
if... | AutoCompleteModule class | AbstractAutoCompleteModule | [
"NIST-Software",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AbstractAutoCompleteModule:
"""AutoCompleteModule class"""
def __init__(self, scripts=list(), styles=list(), label=None):
"""Initialize the module Args: scripts: styles: label:"""
<|body_0|>
def _render_module(self, request):
"""Return the module Args: request: R... | stack_v2_sparse_classes_10k_train_000930 | 1,022 | permissive | [
{
"docstring": "Initialize the module Args: scripts: styles: label:",
"name": "__init__",
"signature": "def __init__(self, scripts=list(), styles=list(), label=None)"
},
{
"docstring": "Return the module Args: request: Returns:",
"name": "_render_module",
"signature": "def _render_module... | 2 | stack_v2_sparse_classes_30k_train_004491 | Implement the Python class `AbstractAutoCompleteModule` described below.
Class description:
AutoCompleteModule class
Method signatures and docstrings:
- def __init__(self, scripts=list(), styles=list(), label=None): Initialize the module Args: scripts: styles: label:
- def _render_module(self, request): Return the mo... | Implement the Python class `AbstractAutoCompleteModule` described below.
Class description:
AutoCompleteModule class
Method signatures and docstrings:
- def __init__(self, scripts=list(), styles=list(), label=None): Initialize the module Args: scripts: styles: label:
- def _render_module(self, request): Return the mo... | cef5e0f040c87e5fb224c59f90c314a6944e4d6b | <|skeleton|>
class AbstractAutoCompleteModule:
"""AutoCompleteModule class"""
def __init__(self, scripts=list(), styles=list(), label=None):
"""Initialize the module Args: scripts: styles: label:"""
<|body_0|>
def _render_module(self, request):
"""Return the module Args: request: R... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class AbstractAutoCompleteModule:
"""AutoCompleteModule class"""
def __init__(self, scripts=list(), styles=list(), label=None):
"""Initialize the module Args: scripts: styles: label:"""
scripts = ['core_parser_app/js/builtin/autocomplete.js'] + scripts
AbstractModule.__init__(self, scri... | the_stack_v2_python_sparse | core_parser_app/tools/modules/views/builtin/autocomplete_module.py | usnistgov/core_parser_app | train | 0 |
8614f6c3c28f4f35ae86fd6b151814cd353ae817 | [
"def get(root, items):\n if root is None:\n items.append('null')\n return\n items.append(str(root.val))\n get(root.left, items)\n get(root.right, items)\nitems = []\nget(root, items)\nreturn ','.join(items)",
"def get_root(data):\n if not data:\n return\n curr = data.popleft... | <|body_start_0|>
def get(root, items):
if root is None:
items.append('null')
return
items.append(str(root.val))
get(root.left, items)
get(root.right, items)
items = []
get(root, items)
return ','.join(items)
... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|>
<|body_... | stack_v2_sparse_classes_10k_train_000931 | 1,352 | no_license | [
{
"docstring": "Encodes a tree to a single string. :type root: TreeNode :rtype: str",
"name": "serialize",
"signature": "def serialize(self, root)"
},
{
"docstring": "Decodes your encoded data to tree. :type data: str :rtype: TreeNode",
"name": "deserialize",
"signature": "def deserializ... | 2 | stack_v2_sparse_classes_30k_train_005665 | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | 8e87b10bd77289b891591b770a6f7adc2c00fdf0 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
def get(root, items):
if root is None:
items.append('null')
return
items.append(str(root.val))
get(root.left, items)
... | the_stack_v2_python_sparse | Temp/serialize_and_deserialize_bst.py | karthik4636/practice_problems | train | 0 | |
fe699ee0cbe2831fdfd71707a98ae51fba00b641 | [
"logging.info('## SETUP METHOD ##')\nlogging.info('# Initializing the webdriver.')\nself.chprofile = self.create_chprofile()\nself.driver = webdriver.Chrome(self.chprofile)\nself.driver.maximize_window()\nself.driver.implicitly_wait(5)\nself.driver.get('http://the-internet.herokuapp.com/')",
"logging.info('## TEA... | <|body_start_0|>
logging.info('## SETUP METHOD ##')
logging.info('# Initializing the webdriver.')
self.chprofile = self.create_chprofile()
self.driver = webdriver.Chrome(self.chprofile)
self.driver.maximize_window()
self.driver.implicitly_wait(5)
self.driver.get('... | This class is for instantiating web driver instances. | DriverManagerChrome | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DriverManagerChrome:
"""This class is for instantiating web driver instances."""
def setUp(self):
"""This method is to instantiate the web driver instance."""
<|body_0|>
def tearDown(self):
"""This is teardown method. It is to capture the screenshots for failed t... | stack_v2_sparse_classes_10k_train_000932 | 3,946 | permissive | [
{
"docstring": "This method is to instantiate the web driver instance.",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "This is teardown method. It is to capture the screenshots for failed test cases, & to remove web driver object.",
"name": "tearDown",
"signature": "... | 3 | stack_v2_sparse_classes_30k_train_000209 | Implement the Python class `DriverManagerChrome` described below.
Class description:
This class is for instantiating web driver instances.
Method signatures and docstrings:
- def setUp(self): This method is to instantiate the web driver instance.
- def tearDown(self): This is teardown method. It is to capture the scr... | Implement the Python class `DriverManagerChrome` described below.
Class description:
This class is for instantiating web driver instances.
Method signatures and docstrings:
- def setUp(self): This method is to instantiate the web driver instance.
- def tearDown(self): This is teardown method. It is to capture the scr... | 65513cb85eccb1ae3fae4ac3625d0e6878720ec8 | <|skeleton|>
class DriverManagerChrome:
"""This class is for instantiating web driver instances."""
def setUp(self):
"""This method is to instantiate the web driver instance."""
<|body_0|>
def tearDown(self):
"""This is teardown method. It is to capture the screenshots for failed t... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class DriverManagerChrome:
"""This class is for instantiating web driver instances."""
def setUp(self):
"""This method is to instantiate the web driver instance."""
logging.info('## SETUP METHOD ##')
logging.info('# Initializing the webdriver.')
self.chprofile = self.create_chpr... | the_stack_v2_python_sparse | attic/2019/contributions-2019/open/mudaliar-yptu/PWAF/utility/drivermanager.py | Agriad/devops-course | train | 0 |
4d9839bde36fff5c4027e394a82c5f4b1e52fdba | [
"def backTrack(res, nums, tmp, start):\n if len(tmp) > 0:\n t = tmp.copy()\n res.append(t)\n for i in range(start, len(nums)):\n tmp.append(nums[i])\n backTrack(res, nums, tmp, i + 1)\n tmp.pop()\nt = [[]]\nres = [[]]\ntmp = []\ndic = {}\nnums.sort()\nbackTrack(t, nums, tmp,... | <|body_start_0|>
def backTrack(res, nums, tmp, start):
if len(tmp) > 0:
t = tmp.copy()
res.append(t)
for i in range(start, len(nums)):
tmp.append(nums[i])
backTrack(res, nums, tmp, i + 1)
tmp.pop()
t ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def subsetsWithDup(self, nums):
""":type nums: List[int] :rtype: List[List[int]]"""
<|body_0|>
def subsetsWithDup0(self, nums):
""":type nums: List[int] :rtype: List[List[int]]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
def backTrack(... | stack_v2_sparse_classes_10k_train_000933 | 1,933 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: List[List[int]]",
"name": "subsetsWithDup",
"signature": "def subsetsWithDup(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: List[List[int]]",
"name": "subsetsWithDup0",
"signature": "def subsetsWithDup0(self, nums)"
}
] | 2 | stack_v2_sparse_classes_30k_train_006014 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def subsetsWithDup(self, nums): :type nums: List[int] :rtype: List[List[int]]
- def subsetsWithDup0(self, nums): :type nums: List[int] :rtype: List[List[int]] | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def subsetsWithDup(self, nums): :type nums: List[int] :rtype: List[List[int]]
- def subsetsWithDup0(self, nums): :type nums: List[int] :rtype: List[List[int]]
<|skeleton|>
class... | 9e49b2c6003b957276737005d4aaac276b44d251 | <|skeleton|>
class Solution:
def subsetsWithDup(self, nums):
""":type nums: List[int] :rtype: List[List[int]]"""
<|body_0|>
def subsetsWithDup0(self, nums):
""":type nums: List[int] :rtype: List[List[int]]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def subsetsWithDup(self, nums):
""":type nums: List[int] :rtype: List[List[int]]"""
def backTrack(res, nums, tmp, start):
if len(tmp) > 0:
t = tmp.copy()
res.append(t)
for i in range(start, len(nums)):
tmp.append... | the_stack_v2_python_sparse | PythonCode/src/0090_Subsets_II.py | oneyuan/CodeforFun | train | 0 | |
1941dca737d2baaef65cf0b403cb3cb0fb67b085 | [
"self.cumhelper = CUMHelper(commu_ip, commu_port)\nself.cumhelper.chvolume(commu_volume)\nself.debug_handler = debug_handler\nrospy.loginfo('CommUWrapper instance created.')",
"rospy.loginfo(\"Saying '%s' in %s..\", utterance, 'English' if english else 'Japanese')\nif self.debug_handler is not None:\n self.deb... | <|body_start_0|>
self.cumhelper = CUMHelper(commu_ip, commu_port)
self.cumhelper.chvolume(commu_volume)
self.debug_handler = debug_handler
rospy.loginfo('CommUWrapper instance created.')
<|end_body_0|>
<|body_start_1|>
rospy.loginfo("Saying '%s' in %s..", utterance, 'English' if... | CommUWrapper | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CommUWrapper:
def __init__(self, commu_ip='127.0.0.1', commu_port=6019, commu_volume=10, debug_handler=None):
"""Instantiates a new CommUWrapper instance. This wraps all the functions of the CommU Helper python library, found under ./helper/. :param commu_ip: The ip address of the CommU ... | stack_v2_sparse_classes_10k_train_000934 | 3,119 | no_license | [
{
"docstring": "Instantiates a new CommUWrapper instance. This wraps all the functions of the CommU Helper python library, found under ./helper/. :param commu_ip: The ip address of the CommU to control. :param commu_port: The port of the CommUManager on the CommU. :param commu_volume: The volume of the CommU. P... | 3 | stack_v2_sparse_classes_30k_train_003530 | Implement the Python class `CommUWrapper` described below.
Class description:
Implement the CommUWrapper class.
Method signatures and docstrings:
- def __init__(self, commu_ip='127.0.0.1', commu_port=6019, commu_volume=10, debug_handler=None): Instantiates a new CommUWrapper instance. This wraps all the functions of ... | Implement the Python class `CommUWrapper` described below.
Class description:
Implement the CommUWrapper class.
Method signatures and docstrings:
- def __init__(self, commu_ip='127.0.0.1', commu_port=6019, commu_volume=10, debug_handler=None): Instantiates a new CommUWrapper instance. This wraps all the functions of ... | 53aedca77d1f61437a22d0c52093555fb815d79b | <|skeleton|>
class CommUWrapper:
def __init__(self, commu_ip='127.0.0.1', commu_port=6019, commu_volume=10, debug_handler=None):
"""Instantiates a new CommUWrapper instance. This wraps all the functions of the CommU Helper python library, found under ./helper/. :param commu_ip: The ip address of the CommU ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class CommUWrapper:
def __init__(self, commu_ip='127.0.0.1', commu_port=6019, commu_volume=10, debug_handler=None):
"""Instantiates a new CommUWrapper instance. This wraps all the functions of the CommU Helper python library, found under ./helper/. :param commu_ip: The ip address of the CommU to control. :p... | the_stack_v2_python_sparse | src/commu_wrapper/src/wrapper.py | mgmeedendorp/ros-commu | train | 2 | |
54c9cfcfd170d0c69bc33d4df3ea4fed5e7d8245 | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\ntry:\n mapping_value = parse_node.get_child_node('@odata.type').get_str_value()\nexcept AttributeError:\n mapping_value = None\nif mapping_value and mapping_value.casefold() == '#microsoft.graph.iosVppEBook'.casefold():\n from .ios_vpp... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
try:
mapping_value = parse_node.get_child_node('@odata.type').get_str_value()
except AttributeError:
mapping_value = None
if mapping_value and mapping_value.casefold() ==... | An abstract class containing the base properties for Managed eBook. | ManagedEBook | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ManagedEBook:
"""An abstract class containing the base properties for Managed eBook."""
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> ManagedEBook:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The par... | stack_v2_sparse_classes_10k_train_000935 | 6,821 | permissive | [
{
"docstring": "Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Returns: ManagedEBook",
"name": "create_from_discriminator_value",
"signature": "def create_from_discriminator_value(... | 3 | stack_v2_sparse_classes_30k_test_000273 | Implement the Python class `ManagedEBook` described below.
Class description:
An abstract class containing the base properties for Managed eBook.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> ManagedEBook: Creates a new instance of the appropriate cla... | Implement the Python class `ManagedEBook` described below.
Class description:
An abstract class containing the base properties for Managed eBook.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> ManagedEBook: Creates a new instance of the appropriate cla... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class ManagedEBook:
"""An abstract class containing the base properties for Managed eBook."""
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> ManagedEBook:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The par... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ManagedEBook:
"""An abstract class containing the base properties for Managed eBook."""
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> ManagedEBook:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to us... | the_stack_v2_python_sparse | msgraph/generated/models/managed_e_book.py | microsoftgraph/msgraph-sdk-python | train | 135 |
74ba213d4fab33b0a7cfabe35671d93818512ca4 | [
"self.s_g = s_g\nself.s_s = s_s\nself.h = h\nself.alpha = alpha\nself.ratio_s_g = ratio_s_g",
"assert len(f1.shape) == 1, 'input must be 1d ndarray'\nassert len(f2.shape) == 1, 'input must be 1d ndarray'\nassert f1.shape == f2.shape\nn_trial = len(f1)\nf1_ = np.tile(f1, (n_samp, 1)) + self.s_s * np.random.randn(n... | <|body_start_0|>
self.s_g = s_g
self.s_s = s_s
self.h = h
self.alpha = alpha
self.ratio_s_g = ratio_s_g
<|end_body_0|>
<|body_start_1|>
assert len(f1.shape) == 1, 'input must be 1d ndarray'
assert len(f2.shape) == 1, 'input must be 1d ndarray'
assert f1.s... | RecencyModel | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RecencyModel:
def __init__(self, s_g, s_s, alpha=0.0, h=0.0, ratio_s_g=1):
"""Constructor :param s_g: std of gaussian part of unigauss :param h: weight of flat prior in unigauss mixture assuming unnormalized gaussians sharing the same variance :param s_s: std of likelihood :param alpha: ... | stack_v2_sparse_classes_10k_train_000936 | 11,426 | no_license | [
{
"docstring": "Constructor :param s_g: std of gaussian part of unigauss :param h: weight of flat prior in unigauss mixture assuming unnormalized gaussians sharing the same variance :param s_s: std of likelihood :param alpha: ratio between gaussians",
"name": "__init__",
"signature": "def __init__(self,... | 2 | stack_v2_sparse_classes_30k_train_004208 | Implement the Python class `RecencyModel` described below.
Class description:
Implement the RecencyModel class.
Method signatures and docstrings:
- def __init__(self, s_g, s_s, alpha=0.0, h=0.0, ratio_s_g=1): Constructor :param s_g: std of gaussian part of unigauss :param h: weight of flat prior in unigauss mixture a... | Implement the Python class `RecencyModel` described below.
Class description:
Implement the RecencyModel class.
Method signatures and docstrings:
- def __init__(self, s_g, s_s, alpha=0.0, h=0.0, ratio_s_g=1): Constructor :param s_g: std of gaussian part of unigauss :param h: weight of flat prior in unigauss mixture a... | 2a05aa98b501c8633e1fe2baf611d137740709de | <|skeleton|>
class RecencyModel:
def __init__(self, s_g, s_s, alpha=0.0, h=0.0, ratio_s_g=1):
"""Constructor :param s_g: std of gaussian part of unigauss :param h: weight of flat prior in unigauss mixture assuming unnormalized gaussians sharing the same variance :param s_s: std of likelihood :param alpha: ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class RecencyModel:
def __init__(self, s_g, s_s, alpha=0.0, h=0.0, ratio_s_g=1):
"""Constructor :param s_g: std of gaussian part of unigauss :param h: weight of flat prior in unigauss mixture assuming unnormalized gaussians sharing the same variance :param s_s: std of likelihood :param alpha: ratio between ... | the_stack_v2_python_sparse | model/simple_model.py | ItayLieder/GMM_simulations | train | 0 | |
ae53ce51b67ccea4836c1ec7ad4421123c9336ed | [
"if not root:\n return '# '\nans = str(root.val) + ' '\nans += self.serialize(root.left)\nans += self.serialize(root.right)\nreturn ans",
"def helper(data):\n if not data:\n return None\n cur = data.pop(0)\n if cur == '#':\n return None\n root = TreeNode(int(cur))\n root.left = hel... | <|body_start_0|>
if not root:
return '# '
ans = str(root.val) + ' '
ans += self.serialize(root.left)
ans += self.serialize(root.right)
return ans
<|end_body_0|>
<|body_start_1|>
def helper(data):
if not data:
return None
... | Codec | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root: TreeNode) -> str:
"""Encodes a tree to a single string."""
<|body_0|>
def deserialize(self, data: str) -> TreeNode:
"""Decodes your encoded data to tree."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not root:
... | stack_v2_sparse_classes_10k_train_000937 | 834 | permissive | [
{
"docstring": "Encodes a tree to a single string.",
"name": "serialize",
"signature": "def serialize(self, root: TreeNode) -> str"
},
{
"docstring": "Decodes your encoded data to tree.",
"name": "deserialize",
"signature": "def deserialize(self, data: str) -> TreeNode"
}
] | 2 | stack_v2_sparse_classes_30k_train_001252 | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root: TreeNode) -> str: Encodes a tree to a single string.
- def deserialize(self, data: str) -> TreeNode: Decodes your encoded data to tree. | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root: TreeNode) -> str: Encodes a tree to a single string.
- def deserialize(self, data: str) -> TreeNode: Decodes your encoded data to tree.
<|skeleton|>
class Co... | 64018a9ead8731ef98d48ab3bbd9d1dd6410c6e7 | <|skeleton|>
class Codec:
def serialize(self, root: TreeNode) -> str:
"""Encodes a tree to a single string."""
<|body_0|>
def deserialize(self, data: str) -> TreeNode:
"""Decodes your encoded data to tree."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Codec:
def serialize(self, root: TreeNode) -> str:
"""Encodes a tree to a single string."""
if not root:
return '# '
ans = str(root.val) + ' '
ans += self.serialize(root.left)
ans += self.serialize(root.right)
return ans
def deserialize(self, da... | the_stack_v2_python_sparse | 449_SerializeandDeserializeBST/Codec.py | excaliburnan/SolutionsOnLeetcodeForZZW | train | 0 | |
59a6aad641515f42b8350b73d9551abc80647b6d | [
"def dfs(root, value):\n if root:\n value = dfs(root.left, value)\n value.append(root.val)\n value = dfs(root.right, value)\n return value\nvalue = dfs(root, [])\nhead = TreeNode(0)\ncopy_head = head\nfor i in value:\n root = TreeNode(i)\n head.right = root\n head = head.right\nr... | <|body_start_0|>
def dfs(root, value):
if root:
value = dfs(root.left, value)
value.append(root.val)
value = dfs(root.right, value)
return value
value = dfs(root, [])
head = TreeNode(0)
copy_head = head
for i... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def increasingBST(self, root):
""":type root: TreeNode :rtype: TreeNode 100 ms"""
<|body_0|>
def increasingBST_1(self, root, tail=None):
"""112ms 增加一个参数 :param root: :param tail: :return:"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
def... | stack_v2_sparse_classes_10k_train_000938 | 1,827 | no_license | [
{
"docstring": ":type root: TreeNode :rtype: TreeNode 100 ms",
"name": "increasingBST",
"signature": "def increasingBST(self, root)"
},
{
"docstring": "112ms 增加一个参数 :param root: :param tail: :return:",
"name": "increasingBST_1",
"signature": "def increasingBST_1(self, root, tail=None)"
... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def increasingBST(self, root): :type root: TreeNode :rtype: TreeNode 100 ms
- def increasingBST_1(self, root, tail=None): 112ms 增加一个参数 :param root: :param tail: :return: | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def increasingBST(self, root): :type root: TreeNode :rtype: TreeNode 100 ms
- def increasingBST_1(self, root, tail=None): 112ms 增加一个参数 :param root: :param tail: :return:
<|skele... | 679a2b246b8b6bb7fc55ed1c8096d3047d6d4461 | <|skeleton|>
class Solution:
def increasingBST(self, root):
""":type root: TreeNode :rtype: TreeNode 100 ms"""
<|body_0|>
def increasingBST_1(self, root, tail=None):
"""112ms 增加一个参数 :param root: :param tail: :return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def increasingBST(self, root):
""":type root: TreeNode :rtype: TreeNode 100 ms"""
def dfs(root, value):
if root:
value = dfs(root.left, value)
value.append(root.val)
value = dfs(root.right, value)
return value
... | the_stack_v2_python_sparse | IncreasingOrderSearchTree_897.py | 953250587/leetcode-python | train | 2 | |
3be51894584c440b2b70367639511c9fc0fd5062 | [
"self.vals = deque()\nself.size = size\nself.curr_size = 0\nself.sum = 0",
"if self.size == 0:\n return None\nself.curr_size += 1\nself.sum += val\nself.vals.append(val)\nif self.curr_size > self.size:\n self.sum -= self.vals.popleft()\n self.curr_size -= 1\nreturn self.sum / self.curr_size"
] | <|body_start_0|>
self.vals = deque()
self.size = size
self.curr_size = 0
self.sum = 0
<|end_body_0|>
<|body_start_1|>
if self.size == 0:
return None
self.curr_size += 1
self.sum += val
self.vals.append(val)
if self.curr_size > self.siz... | MovingAverage | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MovingAverage:
def __init__(self, size):
"""Initialize your data structure here. :type size: int"""
<|body_0|>
def next(self, val):
""":type val: int :rtype: float"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.vals = deque()
self.size... | stack_v2_sparse_classes_10k_train_000939 | 806 | no_license | [
{
"docstring": "Initialize your data structure here. :type size: int",
"name": "__init__",
"signature": "def __init__(self, size)"
},
{
"docstring": ":type val: int :rtype: float",
"name": "next",
"signature": "def next(self, val)"
}
] | 2 | stack_v2_sparse_classes_30k_train_003507 | Implement the Python class `MovingAverage` described below.
Class description:
Implement the MovingAverage class.
Method signatures and docstrings:
- def __init__(self, size): Initialize your data structure here. :type size: int
- def next(self, val): :type val: int :rtype: float | Implement the Python class `MovingAverage` described below.
Class description:
Implement the MovingAverage class.
Method signatures and docstrings:
- def __init__(self, size): Initialize your data structure here. :type size: int
- def next(self, val): :type val: int :rtype: float
<|skeleton|>
class MovingAverage:
... | 692bf0e5aab402d55463274e99ab4d0ed56ce64c | <|skeleton|>
class MovingAverage:
def __init__(self, size):
"""Initialize your data structure here. :type size: int"""
<|body_0|>
def next(self, val):
""":type val: int :rtype: float"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class MovingAverage:
def __init__(self, size):
"""Initialize your data structure here. :type size: int"""
self.vals = deque()
self.size = size
self.curr_size = 0
self.sum = 0
def next(self, val):
""":type val: int :rtype: float"""
if self.size == 0:
... | the_stack_v2_python_sparse | 346-moving_avg_from_data_stream.py | WweiL/LeetCode | train | 0 | |
0e14fee914d0539960df826146901b0dda61af07 | [
"root = setUp()\nself.assertEqual(root.left.value, 2)\nself.assertEqual(root.right.value, 10)\nself.assertEqual(root.left.right.value, 3)\nself.assertEqual(root.value, 5)",
"root = setUp()\nroot.remove(2)\nself.assertEqual(root.left.value, 3)\nself.assertEqual(root.right.value, 10)\nself.assertEqual(root.left.rig... | <|body_start_0|>
root = setUp()
self.assertEqual(root.left.value, 2)
self.assertEqual(root.right.value, 10)
self.assertEqual(root.left.right.value, 3)
self.assertEqual(root.value, 5)
<|end_body_0|>
<|body_start_1|>
root = setUp()
root.remove(2)
self.asser... | Class with unittests for BST_Construction.py | test_BST_Construction | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class test_BST_Construction:
"""Class with unittests for BST_Construction.py"""
def test_Insert(self):
"""Checks insertion method"""
<|body_0|>
def test_Delete(self):
"""Checks deletion method"""
<|body_1|>
def test_Contains(self):
"""Checks conati... | stack_v2_sparse_classes_10k_train_000940 | 1,353 | no_license | [
{
"docstring": "Checks insertion method",
"name": "test_Insert",
"signature": "def test_Insert(self)"
},
{
"docstring": "Checks deletion method",
"name": "test_Delete",
"signature": "def test_Delete(self)"
},
{
"docstring": "Checks conatins method",
"name": "test_Contains",
... | 3 | null | Implement the Python class `test_BST_Construction` described below.
Class description:
Class with unittests for BST_Construction.py
Method signatures and docstrings:
- def test_Insert(self): Checks insertion method
- def test_Delete(self): Checks deletion method
- def test_Contains(self): Checks conatins method | Implement the Python class `test_BST_Construction` described below.
Class description:
Class with unittests for BST_Construction.py
Method signatures and docstrings:
- def test_Insert(self): Checks insertion method
- def test_Delete(self): Checks deletion method
- def test_Contains(self): Checks conatins method
<|sk... | 3aa62ad36c3b06b2a3b05f1f8e2a9e21d68b371f | <|skeleton|>
class test_BST_Construction:
"""Class with unittests for BST_Construction.py"""
def test_Insert(self):
"""Checks insertion method"""
<|body_0|>
def test_Delete(self):
"""Checks deletion method"""
<|body_1|>
def test_Contains(self):
"""Checks conati... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class test_BST_Construction:
"""Class with unittests for BST_Construction.py"""
def test_Insert(self):
"""Checks insertion method"""
root = setUp()
self.assertEqual(root.left.value, 2)
self.assertEqual(root.right.value, 10)
self.assertEqual(root.left.right.value, 3)
... | the_stack_v2_python_sparse | DataStructures/BST_Construction/test_BST_Construction.py | JakubKazimierski/PythonPortfolio | train | 9 |
67e5670b3e365348f8797cfe2df8113397c3eee7 | [
"invalid = u'! @ # $ % ^ & * ( ) - = + , : ; \" | ~ / \\\\ \\x00 \\u202a'.split()\nbase = u'User%sName'\nexpected = False\nfor c in invalid:\n name = base % c\n result = user.isValidName(request, name)\nself.assertEqual(result, expected, 'Expected \"%(expected)s\" but got \"%(result)s\"' % locals())",
"case... | <|body_start_0|>
invalid = u'! @ # $ % ^ & * ( ) - = + , : ; " | ~ / \\ \x00 \u202a'.split()
base = u'User%sName'
expected = False
for c in invalid:
name = base % c
result = user.isValidName(request, name)
self.assertEqual(result, expected, 'Expected "%(ex... | IsValidNameTestCase | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IsValidNameTestCase:
def testNonAlnumCharacters(self):
"""user: isValidName: reject unicode non alpha numeric characters : and , used in acl rules, we might add more characters to the syntax."""
<|body_0|>
def testWhitespace(self):
"""user: isValidName: reject leadin... | stack_v2_sparse_classes_10k_train_000941 | 8,790 | no_license | [
{
"docstring": "user: isValidName: reject unicode non alpha numeric characters : and , used in acl rules, we might add more characters to the syntax.",
"name": "testNonAlnumCharacters",
"signature": "def testNonAlnumCharacters(self)"
},
{
"docstring": "user: isValidName: reject leading, trailing... | 3 | stack_v2_sparse_classes_30k_train_006258 | Implement the Python class `IsValidNameTestCase` described below.
Class description:
Implement the IsValidNameTestCase class.
Method signatures and docstrings:
- def testNonAlnumCharacters(self): user: isValidName: reject unicode non alpha numeric characters : and , used in acl rules, we might add more characters to ... | Implement the Python class `IsValidNameTestCase` described below.
Class description:
Implement the IsValidNameTestCase class.
Method signatures and docstrings:
- def testNonAlnumCharacters(self): user: isValidName: reject unicode non alpha numeric characters : and , used in acl rules, we might add more characters to ... | a2c30c3b742c65fb2c5bfbab1267d643823882a5 | <|skeleton|>
class IsValidNameTestCase:
def testNonAlnumCharacters(self):
"""user: isValidName: reject unicode non alpha numeric characters : and , used in acl rules, we might add more characters to the syntax."""
<|body_0|>
def testWhitespace(self):
"""user: isValidName: reject leadin... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class IsValidNameTestCase:
def testNonAlnumCharacters(self):
"""user: isValidName: reject unicode non alpha numeric characters : and , used in acl rules, we might add more characters to the syntax."""
invalid = u'! @ # $ % ^ & * ( ) - = + , : ; " | ~ / \\ \x00 \u202a'.split()
base = u'User%s... | the_stack_v2_python_sparse | mysocietyorg/moin/lib/python2.4/site-packages/MoinMoin/_tests/test_user.py | MyfanwyNixon/orgsites | train | 0 | |
0ea8ac8090ae397b5cfaaab7595b0d30ec78d823 | [
"super().__init__(metadata, **kwargs)\nself.col = col\nbasic_meta = backend_key_to_query(key).copy()\nself.col.delete_many(basic_meta)\nbasic_meta['write_time'] = datetime.now(py_utc)\nbasic_meta['run_start_time'] = datetime.now(py_utc)\nbasic_meta['provides_meta'] = True\nself.run_start = None\nself.basic_md = bas... | <|body_start_0|>
super().__init__(metadata, **kwargs)
self.col = col
basic_meta = backend_key_to_query(key).copy()
self.col.delete_many(basic_meta)
basic_meta['write_time'] = datetime.now(py_utc)
basic_meta['run_start_time'] = datetime.now(py_utc)
basic_meta['prov... | MongoSaver | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MongoSaver:
def __init__(self, key: str, metadata: dict, col: collection.Collection, **kwargs):
"""Mongo saver :param key: string of strax.Datakey :param metadata: metadata to save belonging to data :param col: collection (NB! pymongo collection object) of mongo instance to write to"""
... | stack_v2_sparse_classes_10k_train_000942 | 14,056 | permissive | [
{
"docstring": "Mongo saver :param key: string of strax.Datakey :param metadata: metadata to save belonging to data :param col: collection (NB! pymongo collection object) of mongo instance to write to",
"name": "__init__",
"signature": "def __init__(self, key: str, metadata: dict, col: collection.Collec... | 4 | stack_v2_sparse_classes_30k_train_004948 | Implement the Python class `MongoSaver` described below.
Class description:
Implement the MongoSaver class.
Method signatures and docstrings:
- def __init__(self, key: str, metadata: dict, col: collection.Collection, **kwargs): Mongo saver :param key: string of strax.Datakey :param metadata: metadata to save belongin... | Implement the Python class `MongoSaver` described below.
Class description:
Implement the MongoSaver class.
Method signatures and docstrings:
- def __init__(self, key: str, metadata: dict, col: collection.Collection, **kwargs): Mongo saver :param key: string of strax.Datakey :param metadata: metadata to save belongin... | a466a94b5dd576cf7eda12ace8760fd60dc3df11 | <|skeleton|>
class MongoSaver:
def __init__(self, key: str, metadata: dict, col: collection.Collection, **kwargs):
"""Mongo saver :param key: string of strax.Datakey :param metadata: metadata to save belonging to data :param col: collection (NB! pymongo collection object) of mongo instance to write to"""
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class MongoSaver:
def __init__(self, key: str, metadata: dict, col: collection.Collection, **kwargs):
"""Mongo saver :param key: string of strax.Datakey :param metadata: metadata to save belonging to data :param col: collection (NB! pymongo collection object) of mongo instance to write to"""
super()... | the_stack_v2_python_sparse | strax/storage/mongo.py | AxFoundation/strax | train | 21 | |
2b9a9ee0b49fb000be15190543892ac2ed410413 | [
"super(TrajLoss, self).__init__()\nself.use_variance = use_variance\nself.cls_loss_weight = cls_loss_weight\nself.nll_loss_weight = nll_loss_weight\nself.loss_weight_minade = loss_weight_minade\nself.loss_weight_minfde = loss_weight_minfde",
"traj = traj_preds\nlog_probs = traj_prob\ntraj_gt = gt_future_traj\nbat... | <|body_start_0|>
super(TrajLoss, self).__init__()
self.use_variance = use_variance
self.cls_loss_weight = cls_loss_weight
self.nll_loss_weight = nll_loss_weight
self.loss_weight_minade = loss_weight_minade
self.loss_weight_minfde = loss_weight_minfde
<|end_body_0|>
<|bod... | MTP loss modified to include variances. Uses MSE for mode selection. Can also be used with Multipath outputs, with residuals added to anchors. | TrajLoss | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TrajLoss:
"""MTP loss modified to include variances. Uses MSE for mode selection. Can also be used with Multipath outputs, with residuals added to anchors."""
def __init__(self, use_variance=False, cls_loss_weight=1.0, nll_loss_weight=1.0, loss_weight_minade=0.0, loss_weight_minfde=1.0, loss... | stack_v2_sparse_classes_10k_train_000943 | 8,891 | permissive | [
{
"docstring": "Initialize MTP loss :param args: Dictionary with the following (optional) keys use_variance: bool, whether or not to use variances for computing regression component of loss, default: False alpha: float, relative weight assigned to classification component, compared to regression component of lo... | 2 | stack_v2_sparse_classes_30k_train_006097 | Implement the Python class `TrajLoss` described below.
Class description:
MTP loss modified to include variances. Uses MSE for mode selection. Can also be used with Multipath outputs, with residuals added to anchors.
Method signatures and docstrings:
- def __init__(self, use_variance=False, cls_loss_weight=1.0, nll_l... | Implement the Python class `TrajLoss` described below.
Class description:
MTP loss modified to include variances. Uses MSE for mode selection. Can also be used with Multipath outputs, with residuals added to anchors.
Method signatures and docstrings:
- def __init__(self, use_variance=False, cls_loss_weight=1.0, nll_l... | 2f38ff1357d3956af11c5609d5275db56c559c20 | <|skeleton|>
class TrajLoss:
"""MTP loss modified to include variances. Uses MSE for mode selection. Can also be used with Multipath outputs, with residuals added to anchors."""
def __init__(self, use_variance=False, cls_loss_weight=1.0, nll_loss_weight=1.0, loss_weight_minade=0.0, loss_weight_minfde=1.0, loss... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TrajLoss:
"""MTP loss modified to include variances. Uses MSE for mode selection. Can also be used with Multipath outputs, with residuals added to anchors."""
def __init__(self, use_variance=False, cls_loss_weight=1.0, nll_loss_weight=1.0, loss_weight_minade=0.0, loss_weight_minfde=1.0, loss_weight_mr=1.... | the_stack_v2_python_sparse | projects/mmdet3d_plugin/losses/traj_loss.py | OpenDriveLab/UniAD | train | 2,156 |
00f3b73a17f249a6cb3ac196ce9111290f2d5d1a | [
"try:\n igdb = request.GET['igdb']\n game = Game.objects.get(igdb=igdb)\n user = CustomUser.objects.get(id=request.user.id)\n r = Ratings.objects.get(game=game, user=user)\nexcept ObjectDoesNotExist:\n return Response({})\nserializer = RatingSerializer(r)\nreturn Response(serializer.data)",
"rating... | <|body_start_0|>
try:
igdb = request.GET['igdb']
game = Game.objects.get(igdb=igdb)
user = CustomUser.objects.get(id=request.user.id)
r = Ratings.objects.get(game=game, user=user)
except ObjectDoesNotExist:
return Response({})
serialize... | Endpoint related to rating a game. Users can rate a game in a scale of 1 to 10. This value is saved in the Ratigs model, which takes the IDs of a user and a game as foreign keys. This endpoint accepts both GET and POST methods. Users must be authenticated to interact with this endpoint. | Rate | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Rate:
"""Endpoint related to rating a game. Users can rate a game in a scale of 1 to 10. This value is saved in the Ratigs model, which takes the IDs of a user and a game as foreign keys. This endpoint accepts both GET and POST methods. Users must be authenticated to interact with this endpoint."... | stack_v2_sparse_classes_10k_train_000944 | 15,728 | no_license | [
{
"docstring": "Get rating for a specific game by the logged-in user. If the game or rating don't exist in the database, no rating exists, so we return nothing. Args: game: the game ID. Returns: response: a RatingSerializer indicating the user, game and rating.",
"name": "get",
"signature": "def get(sel... | 2 | stack_v2_sparse_classes_30k_train_006406 | Implement the Python class `Rate` described below.
Class description:
Endpoint related to rating a game. Users can rate a game in a scale of 1 to 10. This value is saved in the Ratigs model, which takes the IDs of a user and a game as foreign keys. This endpoint accepts both GET and POST methods. Users must be authent... | Implement the Python class `Rate` described below.
Class description:
Endpoint related to rating a game. Users can rate a game in a scale of 1 to 10. This value is saved in the Ratigs model, which takes the IDs of a user and a game as foreign keys. This endpoint accepts both GET and POST methods. Users must be authent... | 7f7e44ca0dae3525394458c16b7093f90612524b | <|skeleton|>
class Rate:
"""Endpoint related to rating a game. Users can rate a game in a scale of 1 to 10. This value is saved in the Ratigs model, which takes the IDs of a user and a game as foreign keys. This endpoint accepts both GET and POST methods. Users must be authenticated to interact with this endpoint."... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Rate:
"""Endpoint related to rating a game. Users can rate a game in a scale of 1 to 10. This value is saved in the Ratigs model, which takes the IDs of a user and a game as foreign keys. This endpoint accepts both GET and POST methods. Users must be authenticated to interact with this endpoint."""
def g... | the_stack_v2_python_sparse | backend/actions/views.py | RMalmberg/overworld | train | 3 |
13ca2ab3f3c99398ff018f03bb09bbded209500a | [
"startTime = datetime.datetime.now()\nclient = dml.pymongo.MongoClient()\nrepo = client.repo\nrepo.authenticate('medinad', 'medinad')\napp1 = repo.medinad.app\ntickets = repo.medinad.tickets\n\ndef product(R, S):\n return [(t, u) for t in R for u in S]\n\ndef project(R, p):\n return [p(t) for t in R]\napp1_li... | <|body_start_0|>
startTime = datetime.datetime.now()
client = dml.pymongo.MongoClient()
repo = client.repo
repo.authenticate('medinad', 'medinad')
app1 = repo.medinad.app
tickets = repo.medinad.tickets
def product(R, S):
return [(t, u) for t in R for ... | apptickets | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class apptickets:
def execute(trial=False):
"""Retrieve some data sets (not using the API here for the sake of simplicity)."""
<|body_0|>
def provenance(doc=prov.model.ProvDocument(), startTime=None, endTime=None):
"""Create the provenance document describing everything ha... | stack_v2_sparse_classes_10k_train_000945 | 5,306 | no_license | [
{
"docstring": "Retrieve some data sets (not using the API here for the sake of simplicity).",
"name": "execute",
"signature": "def execute(trial=False)"
},
{
"docstring": "Create the provenance document describing everything happening in this script. Each run of the script will generate a new d... | 2 | stack_v2_sparse_classes_30k_test_000044 | Implement the Python class `apptickets` described below.
Class description:
Implement the apptickets class.
Method signatures and docstrings:
- def execute(trial=False): Retrieve some data sets (not using the API here for the sake of simplicity).
- def provenance(doc=prov.model.ProvDocument(), startTime=None, endTime... | Implement the Python class `apptickets` described below.
Class description:
Implement the apptickets class.
Method signatures and docstrings:
- def execute(trial=False): Retrieve some data sets (not using the API here for the sake of simplicity).
- def provenance(doc=prov.model.ProvDocument(), startTime=None, endTime... | 97e72731ffadbeae57d7a332decd58706e7c08de | <|skeleton|>
class apptickets:
def execute(trial=False):
"""Retrieve some data sets (not using the API here for the sake of simplicity)."""
<|body_0|>
def provenance(doc=prov.model.ProvDocument(), startTime=None, endTime=None):
"""Create the provenance document describing everything ha... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class apptickets:
def execute(trial=False):
"""Retrieve some data sets (not using the API here for the sake of simplicity)."""
startTime = datetime.datetime.now()
client = dml.pymongo.MongoClient()
repo = client.repo
repo.authenticate('medinad', 'medinad')
app1 = repo... | the_stack_v2_python_sparse | jtbloom_rfballes_medinad/medinad/apptickets.py | ROODAY/course-2017-fal-proj | train | 3 | |
857837e58561133e353303b45d72312fd1f9a497 | [
"if os.name == 'nt':\n pass\nelse:\n self.fd = sys.stdin.fileno()\n self.new_term = termios.tcgetattr(self.fd)\n self.old_term = termios.tcgetattr(self.fd)\n self.new_term[3] = self.new_term[3] & ~termios.ICANON & ~termios.ECHO\n termios.tcsetattr(self.fd, termios.TCSAFLUSH, self.new_term)\n at... | <|body_start_0|>
if os.name == 'nt':
pass
else:
self.fd = sys.stdin.fileno()
self.new_term = termios.tcgetattr(self.fd)
self.old_term = termios.tcgetattr(self.fd)
self.new_term[3] = self.new_term[3] & ~termios.ICANON & ~termios.ECHO
... | KBHit | [
"CC-BY-4.0",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class KBHit:
def __init__(self):
"""Creates a KBHit object that you can call to do various keyboard things."""
<|body_0|>
def set_normal_term(self):
"""Resets to normal terminal. On Windows this is a no-op."""
<|body_1|>
def getch(self):
"""Returns a k... | stack_v2_sparse_classes_10k_train_000946 | 4,095 | permissive | [
{
"docstring": "Creates a KBHit object that you can call to do various keyboard things.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Resets to normal terminal. On Windows this is a no-op.",
"name": "set_normal_term",
"signature": "def set_normal_term(self)"
... | 5 | null | Implement the Python class `KBHit` described below.
Class description:
Implement the KBHit class.
Method signatures and docstrings:
- def __init__(self): Creates a KBHit object that you can call to do various keyboard things.
- def set_normal_term(self): Resets to normal terminal. On Windows this is a no-op.
- def ge... | Implement the Python class `KBHit` described below.
Class description:
Implement the KBHit class.
Method signatures and docstrings:
- def __init__(self): Creates a KBHit object that you can call to do various keyboard things.
- def set_normal_term(self): Resets to normal terminal. On Windows this is a no-op.
- def ge... | 9253740baf46ebf4eacbce6bf3369150c5fb8ee0 | <|skeleton|>
class KBHit:
def __init__(self):
"""Creates a KBHit object that you can call to do various keyboard things."""
<|body_0|>
def set_normal_term(self):
"""Resets to normal terminal. On Windows this is a no-op."""
<|body_1|>
def getch(self):
"""Returns a k... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class KBHit:
def __init__(self):
"""Creates a KBHit object that you can call to do various keyboard things."""
if os.name == 'nt':
pass
else:
self.fd = sys.stdin.fileno()
self.new_term = termios.tcgetattr(self.fd)
self.old_term = termios.tcgeta... | the_stack_v2_python_sparse | pyocd/utility/kbhit.py | pyocd/pyOCD | train | 507 | |
1594477157a934f635f1b286347b458cc4e5d0df | [
"self.quit = False\nself.add = False\nself.delete = False\nself.item = None",
"print('[command] [item] (command: a to add, d to delete, q to quit).')\nline = input()\ncommand = line[:1]\nself.item = line[2:]\nif command == 'a':\n self.add = True\nelif command == 'q':\n self.quit = True\nelif command == 'd':... | <|body_start_0|>
self.quit = False
self.add = False
self.delete = False
self.item = None
<|end_body_0|>
<|body_start_1|>
print('[command] [item] (command: a to add, d to delete, q to quit).')
line = input()
command = line[:1]
self.item = line[2:]
... | Order class. | Order | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Order:
"""Order class."""
def __init__(self):
"""Initializing the order."""
<|body_0|>
def get_input(self):
"""Retrieve the order."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.quit = False
self.add = False
self.delete = F... | stack_v2_sparse_classes_10k_train_000947 | 630 | permissive | [
{
"docstring": "Initializing the order.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Retrieve the order.",
"name": "get_input",
"signature": "def get_input(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_007284 | Implement the Python class `Order` described below.
Class description:
Order class.
Method signatures and docstrings:
- def __init__(self): Initializing the order.
- def get_input(self): Retrieve the order. | Implement the Python class `Order` described below.
Class description:
Order class.
Method signatures and docstrings:
- def __init__(self): Initializing the order.
- def get_input(self): Retrieve the order.
<|skeleton|>
class Order:
"""Order class."""
def __init__(self):
"""Initializing the order.""... | fa58835d532126c4cfb0baf4cb8d9d8a0e2703d2 | <|skeleton|>
class Order:
"""Order class."""
def __init__(self):
"""Initializing the order."""
<|body_0|>
def get_input(self):
"""Retrieve the order."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Order:
"""Order class."""
def __init__(self):
"""Initializing the order."""
self.quit = False
self.add = False
self.delete = False
self.item = None
def get_input(self):
"""Retrieve the order."""
print('[command] [item] (command: a to add, d to ... | the_stack_v2_python_sparse | sales/shopping_order.py | carlb15/Python | train | 2 |
bcdbebfa4d8693a33adb23b2d37d47237b4ba330 | [
"data = first_line(filename)\ndata = json.loads(data)\nreturn total_nums(data)",
"data = first_line(filename)\ndata = json.loads(data)\nreturn total_nums_no_red(data)"
] | <|body_start_0|>
data = first_line(filename)
data = json.loads(data)
return total_nums(data)
<|end_body_0|>
<|body_start_1|>
data = first_line(filename)
data = json.loads(data)
return total_nums_no_red(data)
<|end_body_1|>
| AoC 2015 Day 12 | Day12 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Day12:
"""AoC 2015 Day 12"""
def part1(filename: str) -> int:
"""Given a filename, solve 2015 day 12 part 1"""
<|body_0|>
def part2(filename: str) -> int:
"""Given a filename, solve 2015 day 12 part 2"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_10k_train_000948 | 1,440 | no_license | [
{
"docstring": "Given a filename, solve 2015 day 12 part 1",
"name": "part1",
"signature": "def part1(filename: str) -> int"
},
{
"docstring": "Given a filename, solve 2015 day 12 part 2",
"name": "part2",
"signature": "def part2(filename: str) -> int"
}
] | 2 | stack_v2_sparse_classes_30k_train_000316 | Implement the Python class `Day12` described below.
Class description:
AoC 2015 Day 12
Method signatures and docstrings:
- def part1(filename: str) -> int: Given a filename, solve 2015 day 12 part 1
- def part2(filename: str) -> int: Given a filename, solve 2015 day 12 part 2 | Implement the Python class `Day12` described below.
Class description:
AoC 2015 Day 12
Method signatures and docstrings:
- def part1(filename: str) -> int: Given a filename, solve 2015 day 12 part 1
- def part2(filename: str) -> int: Given a filename, solve 2015 day 12 part 2
<|skeleton|>
class Day12:
"""AoC 201... | e89db235837d2d05848210a18c9c2a4456085570 | <|skeleton|>
class Day12:
"""AoC 2015 Day 12"""
def part1(filename: str) -> int:
"""Given a filename, solve 2015 day 12 part 1"""
<|body_0|>
def part2(filename: str) -> int:
"""Given a filename, solve 2015 day 12 part 2"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Day12:
"""AoC 2015 Day 12"""
def part1(filename: str) -> int:
"""Given a filename, solve 2015 day 12 part 1"""
data = first_line(filename)
data = json.loads(data)
return total_nums(data)
def part2(filename: str) -> int:
"""Given a filename, solve 2015 day 12 p... | the_stack_v2_python_sparse | 2015/python2015/aoc/day12.py | mreishus/aoc | train | 16 |
aae448fa8cba82d39ec70b39f682f36f28a5824b | [
"self.ip = ip\nif interface not in netifaces.interfaces():\n logger.error('Error: No valid interface detected for external %s : %s.', ip, interface)\n sys.exit(1)\nself.interface = interface",
"ip_packet = ethernet_packet.child()\ndelta_ttl = ip_packet.get_ip_ttl() - path\nip_packet.set_ip_ttl(delta_ttl)\ni... | <|body_start_0|>
self.ip = ip
if interface not in netifaces.interfaces():
logger.error('Error: No valid interface detected for external %s : %s.', ip, interface)
sys.exit(1)
self.interface = interface
<|end_body_0|>
<|body_start_1|>
ip_packet = ethernet_packet.ch... | Defines bindings of external machine interfaces to virtual ips in the network | External | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class External:
"""Defines bindings of external machine interfaces to virtual ips in the network"""
def __init__(self, ip, interface):
"""Function initialized an external machine in the network Args: ip : ip address of the machine in the network interface : network interface the machine is... | stack_v2_sparse_classes_10k_train_000949 | 28,024 | permissive | [
{
"docstring": "Function initialized an external machine in the network Args: ip : ip address of the machine in the network interface : network interface the machine is connected to",
"name": "__init__",
"signature": "def __init__(self, ip, interface)"
},
{
"docstring": "Function conveys traffic... | 2 | stack_v2_sparse_classes_30k_train_000127 | Implement the Python class `External` described below.
Class description:
Defines bindings of external machine interfaces to virtual ips in the network
Method signatures and docstrings:
- def __init__(self, ip, interface): Function initialized an external machine in the network Args: ip : ip address of the machine in... | Implement the Python class `External` described below.
Class description:
Defines bindings of external machine interfaces to virtual ips in the network
Method signatures and docstrings:
- def __init__(self, ip, interface): Function initialized an external machine in the network Args: ip : ip address of the machine in... | a2812eddff632eceb68b6d00872617f536132788 | <|skeleton|>
class External:
"""Defines bindings of external machine interfaces to virtual ips in the network"""
def __init__(self, ip, interface):
"""Function initialized an external machine in the network Args: ip : ip address of the machine in the network interface : network interface the machine is... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class External:
"""Defines bindings of external machine interfaces to virtual ips in the network"""
def __init__(self, ip, interface):
"""Function initialized an external machine in the network Args: ip : ip address of the machine in the network interface : network interface the machine is connected to... | the_stack_v2_python_sparse | honeyd/core/element.py | kevindar/honeyd-python | train | 0 |
8b57c5dc657fee3490a9dae1ab9e5a154da9fb4f | [
"self.mapping = {}\nfor i in xrange(len(words)):\n self.mapping[words[i]] = self.mapping.get(words[i], []) + [i]",
"wl1 = self.mapping[word1]\nwl2 = self.mapping[word2]\ni = j = 0\nminlen = 1 << 31\nwhile i < len(wl1) and j < len(wl2):\n minlen = min(abs(wl1[i] - wl2[j]), minlen)\n if wl1[i] < wl2[j]:\n ... | <|body_start_0|>
self.mapping = {}
for i in xrange(len(words)):
self.mapping[words[i]] = self.mapping.get(words[i], []) + [i]
<|end_body_0|>
<|body_start_1|>
wl1 = self.mapping[word1]
wl2 = self.mapping[word2]
i = j = 0
minlen = 1 << 31
while i < len(... | WordDistance | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WordDistance:
def __init__(self, words):
"""initialize your data structure here. :type words: List[str]"""
<|body_0|>
def shortest(self, word1, word2):
"""Adds a word into the data structure. :type word1: str :type word2: str :rtype: int"""
<|body_1|>
<|end_... | stack_v2_sparse_classes_10k_train_000950 | 982 | permissive | [
{
"docstring": "initialize your data structure here. :type words: List[str]",
"name": "__init__",
"signature": "def __init__(self, words)"
},
{
"docstring": "Adds a word into the data structure. :type word1: str :type word2: str :rtype: int",
"name": "shortest",
"signature": "def shortes... | 2 | null | Implement the Python class `WordDistance` described below.
Class description:
Implement the WordDistance class.
Method signatures and docstrings:
- def __init__(self, words): initialize your data structure here. :type words: List[str]
- def shortest(self, word1, word2): Adds a word into the data structure. :type word... | Implement the Python class `WordDistance` described below.
Class description:
Implement the WordDistance class.
Method signatures and docstrings:
- def __init__(self, words): initialize your data structure here. :type words: List[str]
- def shortest(self, word1, word2): Adds a word into the data structure. :type word... | 86f1cb98de801f58c39d9a48ce9de12df7303d20 | <|skeleton|>
class WordDistance:
def __init__(self, words):
"""initialize your data structure here. :type words: List[str]"""
<|body_0|>
def shortest(self, word1, word2):
"""Adds a word into the data structure. :type word1: str :type word2: str :rtype: int"""
<|body_1|>
<|end_... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class WordDistance:
def __init__(self, words):
"""initialize your data structure here. :type words: List[str]"""
self.mapping = {}
for i in xrange(len(words)):
self.mapping[words[i]] = self.mapping.get(words[i], []) + [i]
def shortest(self, word1, word2):
"""Adds a w... | the_stack_v2_python_sparse | 244-Shortest-Word-Distance-II/solution.py | Tanych/CodeTracking | train | 0 | |
79b88cfb0013cfe3ff89046b6315c677f120f59b | [
"if not root:\n return ''\nres = [self.serialize(root.left), root.val, self.serialize(root.right)]\nreturn str(res)",
"if not data:\n return\nleft, cur, right = eval(data)\nroot = TreeNode(cur)\nroot.left = self.deserialize(left)\nroot.right = self.deserialize(right)\nreturn root"
] | <|body_start_0|>
if not root:
return ''
res = [self.serialize(root.left), root.val, self.serialize(root.right)]
return str(res)
<|end_body_0|>
<|body_start_1|>
if not data:
return
left, cur, right = eval(data)
root = TreeNode(cur)
root.lef... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root: TreeNode) -> str:
"""Encodes a tree to a single string."""
<|body_0|>
def deserialize(self, data: str) -> TreeNode:
"""Decodes your encoded data to tree."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not root:
... | stack_v2_sparse_classes_10k_train_000951 | 3,000 | no_license | [
{
"docstring": "Encodes a tree to a single string.",
"name": "serialize",
"signature": "def serialize(self, root: TreeNode) -> str"
},
{
"docstring": "Decodes your encoded data to tree.",
"name": "deserialize",
"signature": "def deserialize(self, data: str) -> TreeNode"
}
] | 2 | stack_v2_sparse_classes_30k_train_000777 | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root: TreeNode) -> str: Encodes a tree to a single string.
- def deserialize(self, data: str) -> TreeNode: Decodes your encoded data to tree. | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root: TreeNode) -> str: Encodes a tree to a single string.
- def deserialize(self, data: str) -> TreeNode: Decodes your encoded data to tree.
<|skeleton|>
class Co... | 6dc5b8968b6bef0186d3806e4aa35ee7b5d75ff2 | <|skeleton|>
class Codec:
def serialize(self, root: TreeNode) -> str:
"""Encodes a tree to a single string."""
<|body_0|>
def deserialize(self, data: str) -> TreeNode:
"""Decodes your encoded data to tree."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Codec:
def serialize(self, root: TreeNode) -> str:
"""Encodes a tree to a single string."""
if not root:
return ''
res = [self.serialize(root.left), root.val, self.serialize(root.right)]
return str(res)
def deserialize(self, data: str) -> TreeNode:
"""D... | the_stack_v2_python_sparse | letecode/361-480/441-460/449.py | hshrimp/letecode_for_me | train | 1 | |
3db8ffa1807be8ab32bd9f959a9469b5a5e2e493 | [
"self.continuous = continuous\nstate_observations = [numpy.asarray(so) for so in state_observations]\nif continuous:\n self.state_distributions = [kde.gaussian_kde(so) for so in state_observations]\nelse:\n max_val = max((so.max() for so in state_observations))\n state_counts = [numpy.bincount(so, minlengt... | <|body_start_0|>
self.continuous = continuous
state_observations = [numpy.asarray(so) for so in state_observations]
if continuous:
self.state_distributions = [kde.gaussian_kde(so) for so in state_observations]
else:
max_val = max((so.max() for so in state_observat... | ObservationProbabilityEstimator | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ObservationProbabilityEstimator:
def __init__(self, state_observations, continuous=True, pseudocount=1):
"""Given a set of observations known to belong to different states, construct an object that will estimate the probability that new observations belong to each state (i.e. the p_obser... | stack_v2_sparse_classes_10k_train_000952 | 9,590 | permissive | [
{
"docstring": "Given a set of observations known to belong to different states, construct an object that will estimate the probability that new observations belong to each state (i.e. the p_observations_given_state matrix) Parameters: state_observations: list of length S containing an array of observation data... | 2 | stack_v2_sparse_classes_30k_test_000255 | Implement the Python class `ObservationProbabilityEstimator` described below.
Class description:
Implement the ObservationProbabilityEstimator class.
Method signatures and docstrings:
- def __init__(self, state_observations, continuous=True, pseudocount=1): Given a set of observations known to belong to different sta... | Implement the Python class `ObservationProbabilityEstimator` described below.
Class description:
Implement the ObservationProbabilityEstimator class.
Method signatures and docstrings:
- def __init__(self, state_observations, continuous=True, pseudocount=1): Given a set of observations known to belong to different sta... | dc789acd481df86e0bc99e137ceb05c196425d03 | <|skeleton|>
class ObservationProbabilityEstimator:
def __init__(self, state_observations, continuous=True, pseudocount=1):
"""Given a set of observations known to belong to different states, construct an object that will estimate the probability that new observations belong to each state (i.e. the p_obser... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ObservationProbabilityEstimator:
def __init__(self, state_observations, continuous=True, pseudocount=1):
"""Given a set of observations known to belong to different states, construct an object that will estimate the probability that new observations belong to each state (i.e. the p_observations_given_... | the_stack_v2_python_sparse | zplib/scalar_stats/hmm.py | zplab/zplib | train | 1 | |
1d56f70baf8e9185b69afd77dcd7fac15b19595c | [
"doc = xml.dom.minidom.Document()\narticleData = MetaXml.createGoobiMetadata(doc, article_metadata)\nmodsExtTag = doc.createElement('mods:extension')\nmodsExtTag.appendChild(articleData)\nmodsTag = doc.createElement('mods:mods')\nmodsTag.setAttributeNS('mods', 'xmlns:mods', 'http://www.loc.gov/mods/v3')\nmodsTag.ap... | <|body_start_0|>
doc = xml.dom.minidom.Document()
articleData = MetaXml.createGoobiMetadata(doc, article_metadata)
modsExtTag = doc.createElement('mods:extension')
modsExtTag.appendChild(articleData)
modsTag = doc.createElement('mods:mods')
modsTag.setAttributeNS('mods', ... | This class contains functions used for working with Goobi's meta.xml file | MetaXml | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MetaXml:
"""This class contains functions used for working with Goobi's meta.xml file"""
def generateArticleXml(article_id, article_metadata):
"""Given an id and a dictionary of data, create an XML node in the article format Metadata should follow this format: [ {'name': 'Abstract', ... | stack_v2_sparse_classes_10k_train_000953 | 3,630 | no_license | [
{
"docstring": "Given an id and a dictionary of data, create an XML node in the article format Metadata should follow this format: [ {'name': 'Abstract', 'data' : 'From the Roman Empire...' }, {'name' : 'TitleDocMain', 'data' : 'Return of the oppressed'}, {'name' : 'Author', 'type' : 'person', 'fields' : [ {'ta... | 3 | stack_v2_sparse_classes_30k_train_005066 | Implement the Python class `MetaXml` described below.
Class description:
This class contains functions used for working with Goobi's meta.xml file
Method signatures and docstrings:
- def generateArticleXml(article_id, article_metadata): Given an id and a dictionary of data, create an XML node in the article format Me... | Implement the Python class `MetaXml` described below.
Class description:
This class contains functions used for working with Goobi's meta.xml file
Method signatures and docstrings:
- def generateArticleXml(article_id, article_metadata): Given an id and a dictionary of data, create an XML node in the article format Me... | 1891071f6c5445cb9470b3d6a896fd6077466a37 | <|skeleton|>
class MetaXml:
"""This class contains functions used for working with Goobi's meta.xml file"""
def generateArticleXml(article_id, article_metadata):
"""Given an id and a dictionary of data, create an XML node in the article format Metadata should follow this format: [ {'name': 'Abstract', ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class MetaXml:
"""This class contains functions used for working with Goobi's meta.xml file"""
def generateArticleXml(article_id, article_metadata):
"""Given an id and a dictionary of data, create an XML node in the article format Metadata should follow this format: [ {'name': 'Abstract', 'data' : 'Fro... | the_stack_v2_python_sparse | kb/tools/goobi/meta_xml.py | kb-dk/goobi-scripts | train | 0 |
720d2a07ca675ad86e8903581955833b08d1330f | [
"edgeList.sort(key=lambda x: x[2])\nself.__uf = VersionedUnionFind(n)\nself.__weights = []\nfor index, (i, j, weight) in enumerate(edgeList):\n if not self.__uf.union_set(i, j):\n continue\n self.__uf.snap()\n self.__weights.append(weight)",
"snap_id = bisect.bisect_left(self.__weights, limit) - 1... | <|body_start_0|>
edgeList.sort(key=lambda x: x[2])
self.__uf = VersionedUnionFind(n)
self.__weights = []
for index, (i, j, weight) in enumerate(edgeList):
if not self.__uf.union_set(i, j):
continue
self.__uf.snap()
self.__weights.append... | DistanceLimitedPathsExist2 | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DistanceLimitedPathsExist2:
def __init__(self, n, edgeList):
""":type n: int :type edgeList: List[List[int]]"""
<|body_0|>
def query(self, p, q, limit):
""":type p: int :type q: int :type limit: int :rtype: bool"""
<|body_1|>
<|end_skeleton|>
<|body_start_0... | stack_v2_sparse_classes_10k_train_000954 | 7,205 | permissive | [
{
"docstring": ":type n: int :type edgeList: List[List[int]]",
"name": "__init__",
"signature": "def __init__(self, n, edgeList)"
},
{
"docstring": ":type p: int :type q: int :type limit: int :rtype: bool",
"name": "query",
"signature": "def query(self, p, q, limit)"
}
] | 2 | null | Implement the Python class `DistanceLimitedPathsExist2` described below.
Class description:
Implement the DistanceLimitedPathsExist2 class.
Method signatures and docstrings:
- def __init__(self, n, edgeList): :type n: int :type edgeList: List[List[int]]
- def query(self, p, q, limit): :type p: int :type q: int :type ... | Implement the Python class `DistanceLimitedPathsExist2` described below.
Class description:
Implement the DistanceLimitedPathsExist2 class.
Method signatures and docstrings:
- def __init__(self, n, edgeList): :type n: int :type edgeList: List[List[int]]
- def query(self, p, q, limit): :type p: int :type q: int :type ... | 4dc4e6642dc92f1983c13564cc0fd99917cab358 | <|skeleton|>
class DistanceLimitedPathsExist2:
def __init__(self, n, edgeList):
""":type n: int :type edgeList: List[List[int]]"""
<|body_0|>
def query(self, p, q, limit):
""":type p: int :type q: int :type limit: int :rtype: bool"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class DistanceLimitedPathsExist2:
def __init__(self, n, edgeList):
""":type n: int :type edgeList: List[List[int]]"""
edgeList.sort(key=lambda x: x[2])
self.__uf = VersionedUnionFind(n)
self.__weights = []
for index, (i, j, weight) in enumerate(edgeList):
if not s... | the_stack_v2_python_sparse | Python/checking-existence-of-edge-length-limited-paths-ii.py | kamyu104/LeetCode-Solutions | train | 4,549 | |
fa1427fa9a6d84ce1a50449404e9fe79792ff85a | [
"def gcd(a, b):\n while b != 0:\n tmp = b\n b = a % b\n a = tmp\n return a\nif x + y < z:\n return False\nif x == z or y == z or x + y == z:\n return True\nreturn z % gcd(x, y) == 0",
"import collections\nvisited = collections.defaultdict(dict)\nq = collections.deque([(0, 0)])\nwh... | <|body_start_0|>
def gcd(a, b):
while b != 0:
tmp = b
b = a % b
a = tmp
return a
if x + y < z:
return False
if x == z or y == z or x + y == z:
return True
return z % gcd(x, y) == 0
<|end_body_... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def canMeasureWater(self, x, y, z):
""":type x: int :type y: int :type z: int :rtype: bool"""
<|body_0|>
def canMeasureWater_BFS(self, x, y, z):
""":type x: int :type y: int :type z: int :rtype: bool"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>... | stack_v2_sparse_classes_10k_train_000955 | 2,358 | no_license | [
{
"docstring": ":type x: int :type y: int :type z: int :rtype: bool",
"name": "canMeasureWater",
"signature": "def canMeasureWater(self, x, y, z)"
},
{
"docstring": ":type x: int :type y: int :type z: int :rtype: bool",
"name": "canMeasureWater_BFS",
"signature": "def canMeasureWater_BFS... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def canMeasureWater(self, x, y, z): :type x: int :type y: int :type z: int :rtype: bool
- def canMeasureWater_BFS(self, x, y, z): :type x: int :type y: int :type z: int :rtype: b... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def canMeasureWater(self, x, y, z): :type x: int :type y: int :type z: int :rtype: bool
- def canMeasureWater_BFS(self, x, y, z): :type x: int :type y: int :type z: int :rtype: b... | 0a7aa09a2b95e4caca5b5123fb735ceb5c01e992 | <|skeleton|>
class Solution:
def canMeasureWater(self, x, y, z):
""":type x: int :type y: int :type z: int :rtype: bool"""
<|body_0|>
def canMeasureWater_BFS(self, x, y, z):
""":type x: int :type y: int :type z: int :rtype: bool"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def canMeasureWater(self, x, y, z):
""":type x: int :type y: int :type z: int :rtype: bool"""
def gcd(a, b):
while b != 0:
tmp = b
b = a % b
a = tmp
return a
if x + y < z:
return False
... | the_stack_v2_python_sparse | water-and-jug-problem.py | onestarshang/leetcode | train | 0 | |
cd546587a5335ddbe39bbdd1a8a7bb914f85dea8 | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn AccessPackage()",
"from .access_package_assignment_policy import AccessPackageAssignmentPolicy\nfrom .access_package_catalog import AccessPackageCatalog\nfrom .access_package_resource_role_scope import AccessPackageResourceRoleScope\nf... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return AccessPackage()
<|end_body_0|>
<|body_start_1|>
from .access_package_assignment_policy import AccessPackageAssignmentPolicy
from .access_package_catalog import AccessPackageCatalog
... | AccessPackage | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AccessPackage:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> AccessPackage:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Returns... | stack_v2_sparse_classes_10k_train_000956 | 6,428 | permissive | [
{
"docstring": "Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Returns: AccessPackage",
"name": "create_from_discriminator_value",
"signature": "def create_from_discriminator_value... | 3 | null | Implement the Python class `AccessPackage` described below.
Class description:
Implement the AccessPackage class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> AccessPackage: Creates a new instance of the appropriate class based on discriminator value... | Implement the Python class `AccessPackage` described below.
Class description:
Implement the AccessPackage class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> AccessPackage: Creates a new instance of the appropriate class based on discriminator value... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class AccessPackage:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> AccessPackage:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Returns... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class AccessPackage:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> AccessPackage:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Returns: AccessPackag... | the_stack_v2_python_sparse | msgraph/generated/models/access_package.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
f9cadcded151c9b6a9f402cd63432e1804b87ac7 | [
"idx = 0\nwhile idx < len(intervals):\n cur = intervals[idx]\n if newInterval[0] <= cur[0]:\n intervals.insert(idx, newInterval)\n break\n else:\n idx += 1\nelse:\n intervals.append(newInterval)\nreturn self.merge(intervals)",
"if len(intervals) < 2:\n return intervals\nidx = 0... | <|body_start_0|>
idx = 0
while idx < len(intervals):
cur = intervals[idx]
if newInterval[0] <= cur[0]:
intervals.insert(idx, newInterval)
break
else:
idx += 1
else:
intervals.append(newInterval)
... | Solution_B | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution_B:
def insert(self, intervals: List[List[int]], newInterval: List[int]) -> List[List[int]]:
"""Insert the intervals only according to the first element, so that intervals is still sorted Then merge like LC056"""
<|body_0|>
def merge(self, intervals):
"""Help... | stack_v2_sparse_classes_10k_train_000957 | 4,614 | permissive | [
{
"docstring": "Insert the intervals only according to the first element, so that intervals is still sorted Then merge like LC056",
"name": "insert",
"signature": "def insert(self, intervals: List[List[int]], newInterval: List[int]) -> List[List[int]]"
},
{
"docstring": "Helper B modified from l... | 2 | null | Implement the Python class `Solution_B` described below.
Class description:
Implement the Solution_B class.
Method signatures and docstrings:
- def insert(self, intervals: List[List[int]], newInterval: List[int]) -> List[List[int]]: Insert the intervals only according to the first element, so that intervals is still ... | Implement the Python class `Solution_B` described below.
Class description:
Implement the Solution_B class.
Method signatures and docstrings:
- def insert(self, intervals: List[List[int]], newInterval: List[int]) -> List[List[int]]: Insert the intervals only according to the first element, so that intervals is still ... | 143422321cbc3715ca08f6c3af8f960a55887ced | <|skeleton|>
class Solution_B:
def insert(self, intervals: List[List[int]], newInterval: List[int]) -> List[List[int]]:
"""Insert the intervals only according to the first element, so that intervals is still sorted Then merge like LC056"""
<|body_0|>
def merge(self, intervals):
"""Help... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution_B:
def insert(self, intervals: List[List[int]], newInterval: List[int]) -> List[List[int]]:
"""Insert the intervals only according to the first element, so that intervals is still sorted Then merge like LC056"""
idx = 0
while idx < len(intervals):
cur = intervals[i... | the_stack_v2_python_sparse | LeetCode/LC057_insert_interval.py | jxie0755/Learning_Python | train | 0 | |
e74e64c7c73e5d81d8a59b53586a8cf9d678921e | [
"for i in range(num_consumer_types):\n if self.DiscFac == DiscFac_list[i]:\n self.solution_terminal.cFunc = deepcopy(consumers_ss[i].solution[0].cFunc)\n self.solution_terminal.vFunc = deepcopy(consumers_ss[i].solution[0].vFunc)\n self.solution_terminal.vPfunc = deepcopy(consumers_ss[i].solu... | <|body_start_0|>
for i in range(num_consumer_types):
if self.DiscFac == DiscFac_list[i]:
self.solution_terminal.cFunc = deepcopy(consumers_ss[i].solution[0].cFunc)
self.solution_terminal.vFunc = deepcopy(consumers_ss[i].solution[0].vFunc)
self.solution... | FBSNK2 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FBSNK2:
def update_solution_terminal(self):
"""Update the terminal period solution. This method should be run when a new AgentType is created or when CRRA changes. Parameters ---------- none Returns ------- none"""
<|body_0|>
def sim_birth(self, which_agents):
"""Mak... | stack_v2_sparse_classes_10k_train_000958 | 31,380 | no_license | [
{
"docstring": "Update the terminal period solution. This method should be run when a new AgentType is created or when CRRA changes. Parameters ---------- none Returns ------- none",
"name": "update_solution_terminal",
"signature": "def update_solution_terminal(self)"
},
{
"docstring": "Makes ne... | 2 | stack_v2_sparse_classes_30k_train_000515 | Implement the Python class `FBSNK2` described below.
Class description:
Implement the FBSNK2 class.
Method signatures and docstrings:
- def update_solution_terminal(self): Update the terminal period solution. This method should be run when a new AgentType is created or when CRRA changes. Parameters ---------- none Re... | Implement the Python class `FBSNK2` described below.
Class description:
Implement the FBSNK2 class.
Method signatures and docstrings:
- def update_solution_terminal(self): Update the terminal period solution. This method should be run when a new AgentType is created or when CRRA changes. Parameters ---------- none Re... | a7bc0bba0734ed6d16c0fe26f650118507e6c115 | <|skeleton|>
class FBSNK2:
def update_solution_terminal(self):
"""Update the terminal period solution. This method should be run when a new AgentType is created or when CRRA changes. Parameters ---------- none Returns ------- none"""
<|body_0|>
def sim_birth(self, which_agents):
"""Mak... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class FBSNK2:
def update_solution_terminal(self):
"""Update the terminal period solution. This method should be run when a new AgentType is created or when CRRA changes. Parameters ---------- none Returns ------- none"""
for i in range(num_consumer_types):
if self.DiscFac == DiscFac_list... | the_stack_v2_python_sparse | Jacobians/ConsumptionJacobians/Jacobian-SS.py | wdu9/FBS-NK | train | 1 | |
fdb9af6308e60b7f913135329713a002b28acc66 | [
"elem = deepcopy(elem)\nyld = elem.find('./YIELD')\nif yld is not None:\n yld.tag = 'YLD'\nreturn super(MFINFO, MFINFO).groom(elem)",
"elem = deepcopy(elem)\nyld = elem.find('./YLD')\nif yld is not None:\n yld.tag = 'YIELD'\nreturn super(MFINFO, MFINFO).ungroom(elem)"
] | <|body_start_0|>
elem = deepcopy(elem)
yld = elem.find('./YIELD')
if yld is not None:
yld.tag = 'YLD'
return super(MFINFO, MFINFO).groom(elem)
<|end_body_0|>
<|body_start_1|>
elem = deepcopy(elem)
yld = elem.find('./YLD')
if yld is not None:
... | OFX section 13.8.5.3 | MFINFO | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MFINFO:
"""OFX section 13.8.5.3"""
def groom(elem):
"""Rename all Elements tagged YIELD (reserved Python keyword) to YLD"""
<|body_0|>
def ungroom(elem):
"""Rename YLD back to YIELD"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
elem = deepcopy... | stack_v2_sparse_classes_10k_train_000959 | 6,031 | no_license | [
{
"docstring": "Rename all Elements tagged YIELD (reserved Python keyword) to YLD",
"name": "groom",
"signature": "def groom(elem)"
},
{
"docstring": "Rename YLD back to YIELD",
"name": "ungroom",
"signature": "def ungroom(elem)"
}
] | 2 | stack_v2_sparse_classes_30k_train_004761 | Implement the Python class `MFINFO` described below.
Class description:
OFX section 13.8.5.3
Method signatures and docstrings:
- def groom(elem): Rename all Elements tagged YIELD (reserved Python keyword) to YLD
- def ungroom(elem): Rename YLD back to YIELD | Implement the Python class `MFINFO` described below.
Class description:
OFX section 13.8.5.3
Method signatures and docstrings:
- def groom(elem): Rename all Elements tagged YIELD (reserved Python keyword) to YLD
- def ungroom(elem): Rename YLD back to YIELD
<|skeleton|>
class MFINFO:
"""OFX section 13.8.5.3"""
... | 67e688ea6510853657736c3804969d029c672c5c | <|skeleton|>
class MFINFO:
"""OFX section 13.8.5.3"""
def groom(elem):
"""Rename all Elements tagged YIELD (reserved Python keyword) to YLD"""
<|body_0|>
def ungroom(elem):
"""Rename YLD back to YIELD"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class MFINFO:
"""OFX section 13.8.5.3"""
def groom(elem):
"""Rename all Elements tagged YIELD (reserved Python keyword) to YLD"""
elem = deepcopy(elem)
yld = elem.find('./YIELD')
if yld is not None:
yld.tag = 'YLD'
return super(MFINFO, MFINFO).groom(elem)
... | the_stack_v2_python_sparse | env/lib/python3.6/site-packages/ofxtools/models/invest/securities.py | yetaai/batchaccounting | train | 0 |
5884c9d06bb9947a11e2247472b18c5c2f5c5815 | [
"global op\nop = 0\nnext = pcs.Field('next_header', 8)\nlen = pcs.Field('length', 8)\ntype = pcs.Field('type', 8)\npcs.Packet.__init__(self, [next, len, type], bytes)",
"global op\nop += 1\notype = pcs.Field('otype' + str(op), 8)\nolen = pcs.Field('olength' + str(op), 8, default=len / 8)\nif len != 0:\n odata ... | <|body_start_0|>
global op
op = 0
next = pcs.Field('next_header', 8)
len = pcs.Field('length', 8)
type = pcs.Field('type', 8)
pcs.Packet.__init__(self, [next, len, type], bytes)
<|end_body_0|>
<|body_start_1|>
global op
op += 1
otype = pcs.Field('... | A class that contains the IPv6 hop-by-hop options extension-headers. | hopopts | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class hopopts:
"""A class that contains the IPv6 hop-by-hop options extension-headers."""
def __init__(self, bytes=None):
"""IPv6 hopbyhop options extension header from RFC 2460"""
<|body_0|>
def option(self, len=0):
"""add option header to the hop-by-hop extension hea... | stack_v2_sparse_classes_10k_train_000960 | 7,919 | no_license | [
{
"docstring": "IPv6 hopbyhop options extension header from RFC 2460",
"name": "__init__",
"signature": "def __init__(self, bytes=None)"
},
{
"docstring": "add option header to the hop-by-hop extension header",
"name": "option",
"signature": "def option(self, len=0)"
}
] | 2 | stack_v2_sparse_classes_30k_train_000759 | Implement the Python class `hopopts` described below.
Class description:
A class that contains the IPv6 hop-by-hop options extension-headers.
Method signatures and docstrings:
- def __init__(self, bytes=None): IPv6 hopbyhop options extension header from RFC 2460
- def option(self, len=0): add option header to the hop... | Implement the Python class `hopopts` described below.
Class description:
A class that contains the IPv6 hop-by-hop options extension-headers.
Method signatures and docstrings:
- def __init__(self, bytes=None): IPv6 hopbyhop options extension header from RFC 2460
- def option(self, len=0): add option header to the hop... | a070a39586b582fbeea72abf12bbfd812955ad81 | <|skeleton|>
class hopopts:
"""A class that contains the IPv6 hop-by-hop options extension-headers."""
def __init__(self, bytes=None):
"""IPv6 hopbyhop options extension header from RFC 2460"""
<|body_0|>
def option(self, len=0):
"""add option header to the hop-by-hop extension hea... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class hopopts:
"""A class that contains the IPv6 hop-by-hop options extension-headers."""
def __init__(self, bytes=None):
"""IPv6 hopbyhop options extension header from RFC 2460"""
global op
op = 0
next = pcs.Field('next_header', 8)
len = pcs.Field('length', 8)
t... | the_stack_v2_python_sparse | src/pcs/packets/ipv6.py | bilouro/tcptest | train | 0 |
a4646da9f864ad16d92c13259e4cba52041ca990 | [
"folder_path = os.path.abspath(raw_folder)\ndata = dict()\nfiles = os.listdir(folder_path)\nfor file in files:\n if is_ignored(file):\n continue\n try:\n file = os.path.join(raw_folder, file)\n datum = cls.process_file(file)\n except FileNotCompatible:\n continue\n _, kwrd = ... | <|body_start_0|>
folder_path = os.path.abspath(raw_folder)
data = dict()
files = os.listdir(folder_path)
for file in files:
if is_ignored(file):
continue
try:
file = os.path.join(raw_folder, file)
datum = cls.process... | SpectreParser | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SpectreParser:
def parse(cls, raw_folder: str) -> Dict[str, Any]:
"""parses the spectre data in the raw folder :param raw_folder: absolute path to the spectre raw data :return: dictionary representing all the simulation data that has been saved."""
<|body_0|>
def process_fil... | stack_v2_sparse_classes_10k_train_000961 | 2,408 | permissive | [
{
"docstring": "parses the spectre data in the raw folder :param raw_folder: absolute path to the spectre raw data :return: dictionary representing all the simulation data that has been saved.",
"name": "parse",
"signature": "def parse(cls, raw_folder: str) -> Dict[str, Any]"
},
{
"docstring": "... | 2 | stack_v2_sparse_classes_30k_train_001952 | Implement the Python class `SpectreParser` described below.
Class description:
Implement the SpectreParser class.
Method signatures and docstrings:
- def parse(cls, raw_folder: str) -> Dict[str, Any]: parses the spectre data in the raw folder :param raw_folder: absolute path to the spectre raw data :return: dictionar... | Implement the Python class `SpectreParser` described below.
Class description:
Implement the SpectreParser class.
Method signatures and docstrings:
- def parse(cls, raw_folder: str) -> Dict[str, Any]: parses the spectre data in the raw folder :param raw_folder: absolute path to the spectre raw data :return: dictionar... | 2ce6da8665d944bab8508a83bc4d3d07fd5afb35 | <|skeleton|>
class SpectreParser:
def parse(cls, raw_folder: str) -> Dict[str, Any]:
"""parses the spectre data in the raw folder :param raw_folder: absolute path to the spectre raw data :return: dictionary representing all the simulation data that has been saved."""
<|body_0|>
def process_fil... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SpectreParser:
def parse(cls, raw_folder: str) -> Dict[str, Any]:
"""parses the spectre data in the raw folder :param raw_folder: absolute path to the spectre raw data :return: dictionary representing all the simulation data that has been saved."""
folder_path = os.path.abspath(raw_folder)
... | the_stack_v2_python_sparse | eval_engines/spectre/parser.py | kouroshHakha/bag_deep_ckt | train | 19 | |
f0c842f71926f58aad3f2622f4b321d0548122d2 | [
"super().__init__(name=name)\nself._embed = embed\nself._reward_prediction = RewardPrediction(hidden_size=hidden_size, activation=activation)",
"embeddings = snt.BatchApply(self._embed)(inputs)\nembeddings = snt.flatten(embeddings)\nlogits = self._reward_prediction(embeddings)\nreturn logits"
] | <|body_start_0|>
super().__init__(name=name)
self._embed = embed
self._reward_prediction = RewardPrediction(hidden_size=hidden_size, activation=activation)
<|end_body_0|>
<|body_start_1|>
embeddings = snt.BatchApply(self._embed)(inputs)
embeddings = snt.flatten(embeddings)
... | Module that produces a reward prediction output from an observations input. This module implements the Reward prediction module from the FTW paper and wraps it together with a (possibly shared) embedding module (= embed). Thus, its output is a logits tensor, representing the log-probabilities for the 3 categories to pr... | RewardPredictionNetwork | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RewardPredictionNetwork:
"""Module that produces a reward prediction output from an observations input. This module implements the Reward prediction module from the FTW paper and wraps it together with a (possibly shared) embedding module (= embed). Thus, its output is a logits tensor, representi... | stack_v2_sparse_classes_10k_train_000962 | 10,989 | no_license | [
{
"docstring": "Initializes the RewardPredictionNetwork module. Args: embed: Embedding module (of type sonnet.Module) to transform observations into an embedding, e.g. FtwTorso. hidden_size: size of hidden linear layer activation: activation function to be used in RewardPrediction module (between linear and log... | 2 | stack_v2_sparse_classes_30k_train_005309 | Implement the Python class `RewardPredictionNetwork` described below.
Class description:
Module that produces a reward prediction output from an observations input. This module implements the Reward prediction module from the FTW paper and wraps it together with a (possibly shared) embedding module (= embed). Thus, it... | Implement the Python class `RewardPredictionNetwork` described below.
Class description:
Module that produces a reward prediction output from an observations input. This module implements the Reward prediction module from the FTW paper and wraps it together with a (possibly shared) embedding module (= embed). Thus, it... | 1c2b2768f2c5996c8cc998d0271f3857949bdaeb | <|skeleton|>
class RewardPredictionNetwork:
"""Module that produces a reward prediction output from an observations input. This module implements the Reward prediction module from the FTW paper and wraps it together with a (possibly shared) embedding module (= embed). Thus, its output is a logits tensor, representi... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class RewardPredictionNetwork:
"""Module that produces a reward prediction output from an observations input. This module implements the Reward prediction module from the FTW paper and wraps it together with a (possibly shared) embedding module (= embed). Thus, its output is a logits tensor, representing the log-pr... | the_stack_v2_python_sparse | ftw/tf/networks/auxiliary.py | RaoulDrake/ftw | train | 3 |
b587cb668f5e1e3ba09761e1bea04d15bcbd72a9 | [
"super().__init__(entry, account, zone, entity_description)\nself._attr_state: StateType = None\nself._old_state: StateType = None",
"if last_state is not None:\n self._attr_state = last_state.state\nif self.state == STATE_UNAVAILABLE:\n self._attr_available = False",
"new_state = None\nif sia_event.code:... | <|body_start_0|>
super().__init__(entry, account, zone, entity_description)
self._attr_state: StateType = None
self._old_state: StateType = None
<|end_body_0|>
<|body_start_1|>
if last_state is not None:
self._attr_state = last_state.state
if self.state == STATE_UNAV... | Class for SIA Alarm Control Panels. | SIAAlarmControlPanel | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SIAAlarmControlPanel:
"""Class for SIA Alarm Control Panels."""
def __init__(self, entry: ConfigEntry, account: str, zone: int, entity_description: SIAAlarmControlPanelEntityDescription) -> None:
"""Create SIAAlarmControlPanel object."""
<|body_0|>
def handle_last_state(... | stack_v2_sparse_classes_10k_train_000963 | 4,240 | permissive | [
{
"docstring": "Create SIAAlarmControlPanel object.",
"name": "__init__",
"signature": "def __init__(self, entry: ConfigEntry, account: str, zone: int, entity_description: SIAAlarmControlPanelEntityDescription) -> None"
},
{
"docstring": "Handle the last state.",
"name": "handle_last_state",... | 3 | null | Implement the Python class `SIAAlarmControlPanel` described below.
Class description:
Class for SIA Alarm Control Panels.
Method signatures and docstrings:
- def __init__(self, entry: ConfigEntry, account: str, zone: int, entity_description: SIAAlarmControlPanelEntityDescription) -> None: Create SIAAlarmControlPanel ... | Implement the Python class `SIAAlarmControlPanel` described below.
Class description:
Class for SIA Alarm Control Panels.
Method signatures and docstrings:
- def __init__(self, entry: ConfigEntry, account: str, zone: int, entity_description: SIAAlarmControlPanelEntityDescription) -> None: Create SIAAlarmControlPanel ... | 80caeafcb5b6e2f9da192d0ea6dd1a5b8244b743 | <|skeleton|>
class SIAAlarmControlPanel:
"""Class for SIA Alarm Control Panels."""
def __init__(self, entry: ConfigEntry, account: str, zone: int, entity_description: SIAAlarmControlPanelEntityDescription) -> None:
"""Create SIAAlarmControlPanel object."""
<|body_0|>
def handle_last_state(... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SIAAlarmControlPanel:
"""Class for SIA Alarm Control Panels."""
def __init__(self, entry: ConfigEntry, account: str, zone: int, entity_description: SIAAlarmControlPanelEntityDescription) -> None:
"""Create SIAAlarmControlPanel object."""
super().__init__(entry, account, zone, entity_descr... | the_stack_v2_python_sparse | homeassistant/components/sia/alarm_control_panel.py | home-assistant/core | train | 35,501 |
a7a935e17e4a551c4986fc4106fac8b74e866e63 | [
"create_hm_flow = linear_flow.Flow(constants.CREATE_HEALTH_MONITOR_FLOW)\ncreate_hm_flow.add(lifecycle_tasks.HealthMonitorToErrorOnRevertTask(requires=[constants.HEALTH_MON, constants.LISTENERS, constants.LOADBALANCER]))\ncreate_hm_flow.add(database_tasks.MarkHealthMonitorPendingCreateInDB(requires=constants.HEALTH... | <|body_start_0|>
create_hm_flow = linear_flow.Flow(constants.CREATE_HEALTH_MONITOR_FLOW)
create_hm_flow.add(lifecycle_tasks.HealthMonitorToErrorOnRevertTask(requires=[constants.HEALTH_MON, constants.LISTENERS, constants.LOADBALANCER]))
create_hm_flow.add(database_tasks.MarkHealthMonitorPendingCr... | HealthMonitorFlows | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HealthMonitorFlows:
def get_create_health_monitor_flow(self):
"""Create a flow to create a health monitor :returns: The flow for creating a health monitor"""
<|body_0|>
def get_delete_health_monitor_flow(self):
"""Create a flow to delete a health monitor :returns: Th... | stack_v2_sparse_classes_10k_train_000964 | 4,639 | permissive | [
{
"docstring": "Create a flow to create a health monitor :returns: The flow for creating a health monitor",
"name": "get_create_health_monitor_flow",
"signature": "def get_create_health_monitor_flow(self)"
},
{
"docstring": "Create a flow to delete a health monitor :returns: The flow for deletin... | 3 | null | Implement the Python class `HealthMonitorFlows` described below.
Class description:
Implement the HealthMonitorFlows class.
Method signatures and docstrings:
- def get_create_health_monitor_flow(self): Create a flow to create a health monitor :returns: The flow for creating a health monitor
- def get_delete_health_mo... | Implement the Python class `HealthMonitorFlows` described below.
Class description:
Implement the HealthMonitorFlows class.
Method signatures and docstrings:
- def get_create_health_monitor_flow(self): Create a flow to create a health monitor :returns: The flow for creating a health monitor
- def get_delete_health_mo... | 0426285a41464a5015494584f109eed35a0d44db | <|skeleton|>
class HealthMonitorFlows:
def get_create_health_monitor_flow(self):
"""Create a flow to create a health monitor :returns: The flow for creating a health monitor"""
<|body_0|>
def get_delete_health_monitor_flow(self):
"""Create a flow to delete a health monitor :returns: Th... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class HealthMonitorFlows:
def get_create_health_monitor_flow(self):
"""Create a flow to create a health monitor :returns: The flow for creating a health monitor"""
create_hm_flow = linear_flow.Flow(constants.CREATE_HEALTH_MONITOR_FLOW)
create_hm_flow.add(lifecycle_tasks.HealthMonitorToErrorO... | the_stack_v2_python_sparse | octavia/controller/worker/v2/flows/health_monitor_flows.py | openstack/octavia | train | 147 | |
f71dbbae927fe13ef250bde6a7d167083652e69f | [
"self.check_parameters(params)\nexp = np.exp(1j * params[0])\nreturn UnitaryMatrix([[1, 0], [0, exp]])",
"self.check_parameters(params)\ndexp = 1j * np.exp(1j * params[0])\nreturn np.array([[[0, 0], [0, dexp]]], dtype=np.complex128)",
"self.check_env_matrix(env_matrix)\na = np.real(env_matrix[1, 1])\nb = np.ima... | <|body_start_0|>
self.check_parameters(params)
exp = np.exp(1j * params[0])
return UnitaryMatrix([[1, 0], [0, exp]])
<|end_body_0|>
<|body_start_1|>
self.check_parameters(params)
dexp = 1j * np.exp(1j * params[0])
return np.array([[[0, 0], [0, dexp]]], dtype=np.complex12... | The U1 single qubit gate. | U1Gate | [
"LicenseRef-scancode-unknown-license-reference",
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class U1Gate:
"""The U1 single qubit gate."""
def get_unitary(self, params: Sequence[float]=[]) -> UnitaryMatrix:
"""Returns the unitary for this gate, see Unitary for more info."""
<|body_0|>
def get_grad(self, params: Sequence[float]=[]) -> np.ndarray:
"""Returns the... | stack_v2_sparse_classes_10k_train_000965 | 1,728 | permissive | [
{
"docstring": "Returns the unitary for this gate, see Unitary for more info.",
"name": "get_unitary",
"signature": "def get_unitary(self, params: Sequence[float]=[]) -> UnitaryMatrix"
},
{
"docstring": "Returns the gradient for this gate, see Gate for more info.",
"name": "get_grad",
"s... | 3 | stack_v2_sparse_classes_30k_train_006430 | Implement the Python class `U1Gate` described below.
Class description:
The U1 single qubit gate.
Method signatures and docstrings:
- def get_unitary(self, params: Sequence[float]=[]) -> UnitaryMatrix: Returns the unitary for this gate, see Unitary for more info.
- def get_grad(self, params: Sequence[float]=[]) -> np... | Implement the Python class `U1Gate` described below.
Class description:
The U1 single qubit gate.
Method signatures and docstrings:
- def get_unitary(self, params: Sequence[float]=[]) -> UnitaryMatrix: Returns the unitary for this gate, see Unitary for more info.
- def get_grad(self, params: Sequence[float]=[]) -> np... | 3083218c2f4e3c3ce4ba027d12caa30c384d7665 | <|skeleton|>
class U1Gate:
"""The U1 single qubit gate."""
def get_unitary(self, params: Sequence[float]=[]) -> UnitaryMatrix:
"""Returns the unitary for this gate, see Unitary for more info."""
<|body_0|>
def get_grad(self, params: Sequence[float]=[]) -> np.ndarray:
"""Returns the... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class U1Gate:
"""The U1 single qubit gate."""
def get_unitary(self, params: Sequence[float]=[]) -> UnitaryMatrix:
"""Returns the unitary for this gate, see Unitary for more info."""
self.check_parameters(params)
exp = np.exp(1j * params[0])
return UnitaryMatrix([[1, 0], [0, exp]... | the_stack_v2_python_sparse | bqskit/ir/gates/parameterized/u1.py | mtreinish/bqskit | train | 0 |
a6bae47c9c4a941bbf4612836085308b298e6ee1 | [
"if os.path.exists(settings.GOVERNOR_INTERFACE):\n interface = settings.GOVERNOR_INTERFACE\n path = '/snapd/' + '/'.join(request.postpath)\nelse:\n interface = settings.SNAPD_INTERFACE\n path = '/' + '/'.join(request.postpath)\nbody = None\nheaders = {}\nctype = request.requestHeaders.getRawHeaders('Con... | <|body_start_0|>
if os.path.exists(settings.GOVERNOR_INTERFACE):
interface = settings.GOVERNOR_INTERFACE
path = '/snapd/' + '/'.join(request.postpath)
else:
interface = settings.SNAPD_INTERFACE
path = '/' + '/'.join(request.postpath)
body = None
... | Expose the snapd API by forwarding requests. Changed in 0.13: we try to send the request through the governor service so that paradrop can be installed in strict mode. https://github.com/snapcore/snapd/wiki/REST-API | SnapdResource | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SnapdResource:
"""Expose the snapd API by forwarding requests. Changed in 0.13: we try to send the request through the governor service so that paradrop can be installed in strict mode. https://github.com/snapcore/snapd/wiki/REST-API"""
def do_snapd_request(self, request):
"""Forward... | stack_v2_sparse_classes_10k_train_000966 | 2,158 | permissive | [
{
"docstring": "Forward the API request to snapd.",
"name": "do_snapd_request",
"signature": "def do_snapd_request(self, request)"
},
{
"docstring": "Fulfill requests by forwarding them to snapd. We use a synchronous implementation of HTTP over Unix sockets, so we do the request in a worker thre... | 2 | stack_v2_sparse_classes_30k_train_007145 | Implement the Python class `SnapdResource` described below.
Class description:
Expose the snapd API by forwarding requests. Changed in 0.13: we try to send the request through the governor service so that paradrop can be installed in strict mode. https://github.com/snapcore/snapd/wiki/REST-API
Method signatures and d... | Implement the Python class `SnapdResource` described below.
Class description:
Expose the snapd API by forwarding requests. Changed in 0.13: we try to send the request through the governor service so that paradrop can be installed in strict mode. https://github.com/snapcore/snapd/wiki/REST-API
Method signatures and d... | c910fd5ac1d1b5e234f40f9f5592cc981e9bb5db | <|skeleton|>
class SnapdResource:
"""Expose the snapd API by forwarding requests. Changed in 0.13: we try to send the request through the governor service so that paradrop can be installed in strict mode. https://github.com/snapcore/snapd/wiki/REST-API"""
def do_snapd_request(self, request):
"""Forward... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SnapdResource:
"""Expose the snapd API by forwarding requests. Changed in 0.13: we try to send the request through the governor service so that paradrop can be installed in strict mode. https://github.com/snapcore/snapd/wiki/REST-API"""
def do_snapd_request(self, request):
"""Forward the API requ... | the_stack_v2_python_sparse | paradrop/daemon/paradrop/backend/snapd_resource.py | ParadropLabs/Paradrop | train | 88 |
c4d309a75020ab6eeafd6255881ba5197980b08b | [
"import revitron\ntry:\n return revitron.Document(self.element.GetLinkDocument()).getPath()\nexcept:\n pass",
"import revitron\ntry:\n return revitron.DOC.GetElement(self.get('Type'))\nexcept:\n pass"
] | <|body_start_0|>
import revitron
try:
return revitron.Document(self.element.GetLinkDocument()).getPath()
except:
pass
<|end_body_0|>
<|body_start_1|>
import revitron
try:
return revitron.DOC.GetElement(self.get('Type'))
except:
... | A wrapper class for Revit links. | LinkRvt | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LinkRvt:
"""A wrapper class for Revit links."""
def getPath(self):
"""Gets the path of the linked document. Returns: string: The path on disk"""
<|body_0|>
def getType(self):
"""Gets the type object of the link. Returns: object: The Link type"""
<|body_1|... | stack_v2_sparse_classes_10k_train_000967 | 621 | permissive | [
{
"docstring": "Gets the path of the linked document. Returns: string: The path on disk",
"name": "getPath",
"signature": "def getPath(self)"
},
{
"docstring": "Gets the type object of the link. Returns: object: The Link type",
"name": "getType",
"signature": "def getType(self)"
}
] | 2 | stack_v2_sparse_classes_30k_test_000131 | Implement the Python class `LinkRvt` described below.
Class description:
A wrapper class for Revit links.
Method signatures and docstrings:
- def getPath(self): Gets the path of the linked document. Returns: string: The path on disk
- def getType(self): Gets the type object of the link. Returns: object: The Link type | Implement the Python class `LinkRvt` described below.
Class description:
A wrapper class for Revit links.
Method signatures and docstrings:
- def getPath(self): Gets the path of the linked document. Returns: string: The path on disk
- def getType(self): Gets the type object of the link. Returns: object: The Link type... | f373a0388c8b45f14f93510c9e8870190dba3b78 | <|skeleton|>
class LinkRvt:
"""A wrapper class for Revit links."""
def getPath(self):
"""Gets the path of the linked document. Returns: string: The path on disk"""
<|body_0|>
def getType(self):
"""Gets the type object of the link. Returns: object: The Link type"""
<|body_1|... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class LinkRvt:
"""A wrapper class for Revit links."""
def getPath(self):
"""Gets the path of the linked document. Returns: string: The path on disk"""
import revitron
try:
return revitron.Document(self.element.GetLinkDocument()).getPath()
except:
pass
... | the_stack_v2_python_sparse | revitron/link.py | Thomas84/revitron | train | 0 |
2993c58fb7b33bf4320ed9f245d41597339e7e9b | [
"if user_config_directory is CredentialsStore._DEFAULT_CONFIG_DIRECTORY:\n user_config_directory = util.get_user_config_directory()\n if user_config_directory is None:\n logger.warning('Credentials caching disabled - no private config directory found')\nif user_config_directory is None:\n self._cred... | <|body_start_0|>
if user_config_directory is CredentialsStore._DEFAULT_CONFIG_DIRECTORY:
user_config_directory = util.get_user_config_directory()
if user_config_directory is None:
logger.warning('Credentials caching disabled - no private config directory found')
i... | Private file store for a `google.oauth2.credentials.Credentials`. | CredentialsStore | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CredentialsStore:
"""Private file store for a `google.oauth2.credentials.Credentials`."""
def __init__(self, user_config_directory=_DEFAULT_CONFIG_DIRECTORY):
"""Creates a CredentialsStore. Args: user_config_directory: Optional absolute path to the root directory for storing user con... | stack_v2_sparse_classes_10k_train_000968 | 16,711 | permissive | [
{
"docstring": "Creates a CredentialsStore. Args: user_config_directory: Optional absolute path to the root directory for storing user configs, under which to store the credentials file. If not set, defaults to a platform-specific location. If set to None, the store is disabled (reads return None; write and cle... | 4 | null | Implement the Python class `CredentialsStore` described below.
Class description:
Private file store for a `google.oauth2.credentials.Credentials`.
Method signatures and docstrings:
- def __init__(self, user_config_directory=_DEFAULT_CONFIG_DIRECTORY): Creates a CredentialsStore. Args: user_config_directory: Optional... | Implement the Python class `CredentialsStore` described below.
Class description:
Private file store for a `google.oauth2.credentials.Credentials`.
Method signatures and docstrings:
- def __init__(self, user_config_directory=_DEFAULT_CONFIG_DIRECTORY): Creates a CredentialsStore. Args: user_config_directory: Optional... | 5961c76dca0fb9bb40d146f5ce13834ac29d8ddb | <|skeleton|>
class CredentialsStore:
"""Private file store for a `google.oauth2.credentials.Credentials`."""
def __init__(self, user_config_directory=_DEFAULT_CONFIG_DIRECTORY):
"""Creates a CredentialsStore. Args: user_config_directory: Optional absolute path to the root directory for storing user con... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class CredentialsStore:
"""Private file store for a `google.oauth2.credentials.Credentials`."""
def __init__(self, user_config_directory=_DEFAULT_CONFIG_DIRECTORY):
"""Creates a CredentialsStore. Args: user_config_directory: Optional absolute path to the root directory for storing user configs, under w... | the_stack_v2_python_sparse | tensorboard/uploader/auth.py | tensorflow/tensorboard | train | 6,766 |
118b13c4003ef41be67e7cf52bdc626f68c07633 | [
"xy = numpy.insert(x, 0, values=y, axis=1)\ndf = pandas.DataFrame.from_records(xy)\ncolumns = ['y']\ncolumns_x = ['x' + str(i) for i in range(x.shape[1])]\ncolumns.extend(columns_x)\ndf.columns = columns\ndf.to_excel(path)",
"columns = ['x' + str(i) for i in range(x.shape[1])]\ndf = pandas.DataFrame.from_records(... | <|body_start_0|>
xy = numpy.insert(x, 0, values=y, axis=1)
df = pandas.DataFrame.from_records(xy)
columns = ['y']
columns_x = ['x' + str(i) for i in range(x.shape[1])]
columns.extend(columns_x)
df.columns = columns
df.to_excel(path)
<|end_body_0|>
<|body_start_1|... | ExcelTool | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ExcelTool:
def saveXY2Excel(x, y, path='SALP_TRAIN_DATA.xlsx'):
""":param self: :param x: :param y: :param path: 输出excel路径 :return:"""
<|body_0|>
def saveX2Excel(x, path='SALP_PREDICT_DATA.xlsx'):
"""存储预测数据集 :param x: :param path: :return:"""
<|body_1|>
... | stack_v2_sparse_classes_10k_train_000969 | 1,144 | no_license | [
{
"docstring": ":param self: :param x: :param y: :param path: 输出excel路径 :return:",
"name": "saveXY2Excel",
"signature": "def saveXY2Excel(x, y, path='SALP_TRAIN_DATA.xlsx')"
},
{
"docstring": "存储预测数据集 :param x: :param path: :return:",
"name": "saveX2Excel",
"signature": "def saveX2Excel(... | 3 | stack_v2_sparse_classes_30k_train_005664 | Implement the Python class `ExcelTool` described below.
Class description:
Implement the ExcelTool class.
Method signatures and docstrings:
- def saveXY2Excel(x, y, path='SALP_TRAIN_DATA.xlsx'): :param self: :param x: :param y: :param path: 输出excel路径 :return:
- def saveX2Excel(x, path='SALP_PREDICT_DATA.xlsx'): 存储预测数... | Implement the Python class `ExcelTool` described below.
Class description:
Implement the ExcelTool class.
Method signatures and docstrings:
- def saveXY2Excel(x, y, path='SALP_TRAIN_DATA.xlsx'): :param self: :param x: :param y: :param path: 输出excel路径 :return:
- def saveX2Excel(x, path='SALP_PREDICT_DATA.xlsx'): 存储预测数... | 69b740332eaaecac553a4cc74c3e25f2af6889ac | <|skeleton|>
class ExcelTool:
def saveXY2Excel(x, y, path='SALP_TRAIN_DATA.xlsx'):
""":param self: :param x: :param y: :param path: 输出excel路径 :return:"""
<|body_0|>
def saveX2Excel(x, path='SALP_PREDICT_DATA.xlsx'):
"""存储预测数据集 :param x: :param path: :return:"""
<|body_1|>
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ExcelTool:
def saveXY2Excel(x, y, path='SALP_TRAIN_DATA.xlsx'):
""":param self: :param x: :param y: :param path: 输出excel路径 :return:"""
xy = numpy.insert(x, 0, values=y, axis=1)
df = pandas.DataFrame.from_records(xy)
columns = ['y']
columns_x = ['x' + str(i) for i in ran... | the_stack_v2_python_sparse | data/excelTools.py | 9DemonFox/simpleLearning | train | 9 | |
3935a5406927ee70fe9136c685cba75f7cfb571e | [
"if self.request_token is None:\n redirect_url = build_absolute_uri(self.request, self.callback_url)\n headers = {'X-Accept': 'application/json'}\n data = {'consumer_key': self.consumer_key, 'redirect_uri': redirect_url}\n response = requests.post(url=self.request_token_url, json=data, headers=headers)\... | <|body_start_0|>
if self.request_token is None:
redirect_url = build_absolute_uri(self.request, self.callback_url)
headers = {'X-Accept': 'application/json'}
data = {'consumer_key': self.consumer_key, 'redirect_uri': redirect_url}
response = requests.post(url=self... | PocketOAuthClient | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PocketOAuthClient:
def _get_request_token(self):
"""Obtain a temporary request token to authorize an access token and to sign the request to obtain the access token"""
<|body_0|>
def get_redirect(self, authorization_url, extra_params):
"""Returns a ``HttpResponseRedi... | stack_v2_sparse_classes_10k_train_000970 | 3,273 | permissive | [
{
"docstring": "Obtain a temporary request token to authorize an access token and to sign the request to obtain the access token",
"name": "_get_request_token",
"signature": "def _get_request_token(self)"
},
{
"docstring": "Returns a ``HttpResponseRedirect`` object to redirect the user to the Po... | 3 | null | Implement the Python class `PocketOAuthClient` described below.
Class description:
Implement the PocketOAuthClient class.
Method signatures and docstrings:
- def _get_request_token(self): Obtain a temporary request token to authorize an access token and to sign the request to obtain the access token
- def get_redirec... | Implement the Python class `PocketOAuthClient` described below.
Class description:
Implement the PocketOAuthClient class.
Method signatures and docstrings:
- def _get_request_token(self): Obtain a temporary request token to authorize an access token and to sign the request to obtain the access token
- def get_redirec... | 6b8911a5ebbabda0d446f2743bd4d00d250ed500 | <|skeleton|>
class PocketOAuthClient:
def _get_request_token(self):
"""Obtain a temporary request token to authorize an access token and to sign the request to obtain the access token"""
<|body_0|>
def get_redirect(self, authorization_url, extra_params):
"""Returns a ``HttpResponseRedi... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class PocketOAuthClient:
def _get_request_token(self):
"""Obtain a temporary request token to authorize an access token and to sign the request to obtain the access token"""
if self.request_token is None:
redirect_url = build_absolute_uri(self.request, self.callback_url)
head... | the_stack_v2_python_sparse | allauth/socialaccount/providers/pocket/client.py | pennersr/django-allauth | train | 7,719 | |
39ee4a5fced47b3a3d474d763697c2d5249f784d | [
"if app:\n self.app = app\n self.init_app(app)",
"self.init_config(app)\napp.extensions['invenio-app-ils'] = _InvenioAppIlsState(app)\napp.register_blueprint(Blueprint('invenio_app_ils_mail', __name__, template_folder='templates'))\nlogging.getLogger('py.warnings').propagate = False",
"for k in dir(config... | <|body_start_0|>
if app:
self.app = app
self.init_app(app)
<|end_body_0|>
<|body_start_1|>
self.init_config(app)
app.extensions['invenio-app-ils'] = _InvenioAppIlsState(app)
app.register_blueprint(Blueprint('invenio_app_ils_mail', __name__, template_folder='templ... | Invenio App ILS UI app. | InvenioAppIls | [
"LicenseRef-scancode-unknown-license-reference",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InvenioAppIls:
"""Invenio App ILS UI app."""
def __init__(self, app=None):
"""Extension initialization."""
<|body_0|>
def init_app(self, app):
"""Flask application initialization."""
<|body_1|>
def init_config(self, app):
"""Initialize config... | stack_v2_sparse_classes_10k_train_000971 | 3,362 | permissive | [
{
"docstring": "Extension initialization.",
"name": "__init__",
"signature": "def __init__(self, app=None)"
},
{
"docstring": "Flask application initialization.",
"name": "init_app",
"signature": "def init_app(self, app)"
},
{
"docstring": "Initialize configuration.",
"name":... | 3 | stack_v2_sparse_classes_30k_train_002511 | Implement the Python class `InvenioAppIls` described below.
Class description:
Invenio App ILS UI app.
Method signatures and docstrings:
- def __init__(self, app=None): Extension initialization.
- def init_app(self, app): Flask application initialization.
- def init_config(self, app): Initialize configuration. | Implement the Python class `InvenioAppIls` described below.
Class description:
Invenio App ILS UI app.
Method signatures and docstrings:
- def __init__(self, app=None): Extension initialization.
- def init_app(self, app): Flask application initialization.
- def init_config(self, app): Initialize configuration.
<|ske... | 961e88ba144b1371b629dfbc0baaf388e46e667f | <|skeleton|>
class InvenioAppIls:
"""Invenio App ILS UI app."""
def __init__(self, app=None):
"""Extension initialization."""
<|body_0|>
def init_app(self, app):
"""Flask application initialization."""
<|body_1|>
def init_config(self, app):
"""Initialize config... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class InvenioAppIls:
"""Invenio App ILS UI app."""
def __init__(self, app=None):
"""Extension initialization."""
if app:
self.app = app
self.init_app(app)
def init_app(self, app):
"""Flask application initialization."""
self.init_config(app)
... | the_stack_v2_python_sparse | invenio_app_ils/ext.py | lauren-d/invenio-app-ils | train | 0 |
a39273827da5a139d0ae4b1b1a2ee992980b92b8 | [
"assert in_channels % 2 == 0, 'in_channels should be divisible by 2'\nsuper().__init__()\nself.half_channels = in_channels // 2\nself.use_only_mean = use_only_mean\nself.input_conv = torch.nn.Conv1d(self.half_channels, hidden_channels, 1)\nself.encoder = WaveNet(in_channels=-1, out_channels=-1, kernel_size=kernel_s... | <|body_start_0|>
assert in_channels % 2 == 0, 'in_channels should be divisible by 2'
super().__init__()
self.half_channels = in_channels // 2
self.use_only_mean = use_only_mean
self.input_conv = torch.nn.Conv1d(self.half_channels, hidden_channels, 1)
self.encoder = WaveNe... | Residual affine coupling layer. | ResidualAffineCouplingLayer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ResidualAffineCouplingLayer:
"""Residual affine coupling layer."""
def __init__(self, in_channels: int=192, hidden_channels: int=192, kernel_size: int=5, base_dilation: int=1, layers: int=5, stacks: int=1, global_channels: int=-1, dropout_rate: float=0.0, use_weight_norm: bool=True, bias: bo... | stack_v2_sparse_classes_10k_train_000972 | 7,596 | permissive | [
{
"docstring": "Initialzie ResidualAffineCouplingLayer module. Args: in_channels (int): Number of input channels. hidden_channels (int): Number of hidden channels. kernel_size (int): Kernel size for WaveNet. base_dilation (int): Base dilation factor for WaveNet. layers (int): Number of layers of WaveNet. stacks... | 2 | null | Implement the Python class `ResidualAffineCouplingLayer` described below.
Class description:
Residual affine coupling layer.
Method signatures and docstrings:
- def __init__(self, in_channels: int=192, hidden_channels: int=192, kernel_size: int=5, base_dilation: int=1, layers: int=5, stacks: int=1, global_channels: i... | Implement the Python class `ResidualAffineCouplingLayer` described below.
Class description:
Residual affine coupling layer.
Method signatures and docstrings:
- def __init__(self, in_channels: int=192, hidden_channels: int=192, kernel_size: int=5, base_dilation: int=1, layers: int=5, stacks: int=1, global_channels: i... | bcd20948db7846ee523443ef9fd78c7a1248c95e | <|skeleton|>
class ResidualAffineCouplingLayer:
"""Residual affine coupling layer."""
def __init__(self, in_channels: int=192, hidden_channels: int=192, kernel_size: int=5, base_dilation: int=1, layers: int=5, stacks: int=1, global_channels: int=-1, dropout_rate: float=0.0, use_weight_norm: bool=True, bias: bo... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ResidualAffineCouplingLayer:
"""Residual affine coupling layer."""
def __init__(self, in_channels: int=192, hidden_channels: int=192, kernel_size: int=5, base_dilation: int=1, layers: int=5, stacks: int=1, global_channels: int=-1, dropout_rate: float=0.0, use_weight_norm: bool=True, bias: bool=True, use_... | the_stack_v2_python_sparse | espnet2/gan_tts/vits/residual_coupling.py | espnet/espnet | train | 7,242 |
f734bfadb0561e90e1e3d50d833e2f8cfcbb1715 | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn AccessReviewSet()",
"from .access_review_history_definition import AccessReviewHistoryDefinition\nfrom .access_review_schedule_definition import AccessReviewScheduleDefinition\nfrom .entity import Entity\nfrom .access_review_history_de... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return AccessReviewSet()
<|end_body_0|>
<|body_start_1|>
from .access_review_history_definition import AccessReviewHistoryDefinition
from .access_review_schedule_definition import AccessReviewS... | AccessReviewSet | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AccessReviewSet:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> AccessReviewSet:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Ret... | stack_v2_sparse_classes_10k_train_000973 | 3,028 | permissive | [
{
"docstring": "Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Returns: AccessReviewSet",
"name": "create_from_discriminator_value",
"signature": "def create_from_discriminator_val... | 3 | stack_v2_sparse_classes_30k_train_007300 | Implement the Python class `AccessReviewSet` described below.
Class description:
Implement the AccessReviewSet class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> AccessReviewSet: Creates a new instance of the appropriate class based on discriminator... | Implement the Python class `AccessReviewSet` described below.
Class description:
Implement the AccessReviewSet class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> AccessReviewSet: Creates a new instance of the appropriate class based on discriminator... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class AccessReviewSet:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> AccessReviewSet:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Ret... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class AccessReviewSet:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> AccessReviewSet:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Returns: AccessRe... | the_stack_v2_python_sparse | msgraph/generated/models/access_review_set.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
631de2942d6f0b78ea75799a7cdf87ae27958f39 | [
"super().__init__()\nif not callable(raysampler):\n raise ValueError('\"raysampler\" has to be a \"Callable\" object.')\nif not callable(raymarcher):\n raise ValueError('\"raymarcher\" has to be a \"Callable\" object.')\nself.raysampler = raysampler\nself.raymarcher = raymarcher",
"if not callable(volumetri... | <|body_start_0|>
super().__init__()
if not callable(raysampler):
raise ValueError('"raysampler" has to be a "Callable" object.')
if not callable(raymarcher):
raise ValueError('"raymarcher" has to be a "Callable" object.')
self.raysampler = raysampler
self.... | A class for rendering a batch of implicit surfaces. The class should be initialized with a raysampler and raymarcher class which both have to be a `Callable`. VOLUMETRIC_FUNCTION The `forward` function of the renderer accepts as input the rendering cameras as well as the `volumetric_function` `Callable`, which defines ... | ImplicitRenderer | [
"MIT",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ImplicitRenderer:
"""A class for rendering a batch of implicit surfaces. The class should be initialized with a raysampler and raymarcher class which both have to be a `Callable`. VOLUMETRIC_FUNCTION The `forward` function of the renderer accepts as input the rendering cameras as well as the `vol... | stack_v2_sparse_classes_10k_train_000974 | 17,111 | permissive | [
{
"docstring": "Args: raysampler: A `Callable` that takes as input scene cameras (an instance of `CamerasBase`) and returns a RayBundle or HeterogeneousRayBundle, that describes the rays emitted from the cameras. raymarcher: A `Callable` that receives the response of the `volumetric_function` (an input to `self... | 2 | stack_v2_sparse_classes_30k_train_001345 | Implement the Python class `ImplicitRenderer` described below.
Class description:
A class for rendering a batch of implicit surfaces. The class should be initialized with a raysampler and raymarcher class which both have to be a `Callable`. VOLUMETRIC_FUNCTION The `forward` function of the renderer accepts as input th... | Implement the Python class `ImplicitRenderer` described below.
Class description:
A class for rendering a batch of implicit surfaces. The class should be initialized with a raysampler and raymarcher class which both have to be a `Callable`. VOLUMETRIC_FUNCTION The `forward` function of the renderer accepts as input th... | a3d99cab6bf5eb69be8d5eb48895da6edd859565 | <|skeleton|>
class ImplicitRenderer:
"""A class for rendering a batch of implicit surfaces. The class should be initialized with a raysampler and raymarcher class which both have to be a `Callable`. VOLUMETRIC_FUNCTION The `forward` function of the renderer accepts as input the rendering cameras as well as the `vol... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ImplicitRenderer:
"""A class for rendering a batch of implicit surfaces. The class should be initialized with a raysampler and raymarcher class which both have to be a `Callable`. VOLUMETRIC_FUNCTION The `forward` function of the renderer accepts as input the rendering cameras as well as the `volumetric_funct... | the_stack_v2_python_sparse | pytorch3d/renderer/implicit/renderer.py | facebookresearch/pytorch3d | train | 7,964 |
a7565767aba273b63778460edc7e99085fe1bbd6 | [
"self.x = int(x)\nself.y = int(y)\nself.p = int(p)\nself.ip_address = ip_address",
"if self.p > 0:\n return self.p\nelse:\n return TYPICAL_PHYSICAL_VIRTUAL_MAP[0 - self.p]",
"result = CORE_RANGE.fullmatch(core_string)\nif result is not None:\n return range(int(result.group(1)), int(result.group(2)) + 1... | <|body_start_0|>
self.x = int(x)
self.y = int(y)
self.p = int(p)
self.ip_address = ip_address
<|end_body_0|>
<|body_start_1|>
if self.p > 0:
return self.p
else:
return TYPICAL_PHYSICAL_VIRTUAL_MAP[0 - self.p]
<|end_body_1|>
<|body_start_2|>
... | Represents a core to be ignored when building a machine. | IgnoreCore | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IgnoreCore:
"""Represents a core to be ignored when building a machine."""
def __init__(self, x, y, p, ip_address=None):
""":param x: X coordinate of a core to ignore :type x: int or str :param y: Y coordinate of a core to ignore :type y: int or str :param p: The virtual core ID of a... | stack_v2_sparse_classes_10k_train_000975 | 5,810 | permissive | [
{
"docstring": ":param x: X coordinate of a core to ignore :type x: int or str :param y: Y coordinate of a core to ignore :type y: int or str :param p: The virtual core ID of a core if > 0, or the physical core if <= 0 (actual value will be negated) :type p: int or str :param ip_address: Optional IP address whi... | 5 | stack_v2_sparse_classes_30k_train_006361 | Implement the Python class `IgnoreCore` described below.
Class description:
Represents a core to be ignored when building a machine.
Method signatures and docstrings:
- def __init__(self, x, y, p, ip_address=None): :param x: X coordinate of a core to ignore :type x: int or str :param y: Y coordinate of a core to igno... | Implement the Python class `IgnoreCore` described below.
Class description:
Represents a core to be ignored when building a machine.
Method signatures and docstrings:
- def __init__(self, x, y, p, ip_address=None): :param x: X coordinate of a core to ignore :type x: int or str :param y: Y coordinate of a core to igno... | 7ec4276879249d53ed8153a62b0b344c5f0b99e3 | <|skeleton|>
class IgnoreCore:
"""Represents a core to be ignored when building a machine."""
def __init__(self, x, y, p, ip_address=None):
""":param x: X coordinate of a core to ignore :type x: int or str :param y: Y coordinate of a core to ignore :type y: int or str :param p: The virtual core ID of a... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class IgnoreCore:
"""Represents a core to be ignored when building a machine."""
def __init__(self, x, y, p, ip_address=None):
""":param x: X coordinate of a core to ignore :type x: int or str :param y: Y coordinate of a core to ignore :type y: int or str :param p: The virtual core ID of a core if > 0,... | the_stack_v2_python_sparse | spinn_machine/ignores/ignore_core.py | SpiNNakerManchester/SpiNNMachine | train | 6 |
763050d8f94b9409bd29b0aa821787ab0c1e103c | [
"result = []\nif not root:\n return 0\nstackOfNode = [root]\nstackOfString = [root.val]\nwhile stackOfNode:\n currNode = stackOfNode.pop()\n currString = stackOfString.pop()\n if currNode.left:\n stackOfNode.append(currNode.left)\n stackOfString.append(currString * 10 + currNode.left.val)\... | <|body_start_0|>
result = []
if not root:
return 0
stackOfNode = [root]
stackOfString = [root.val]
while stackOfNode:
currNode = stackOfNode.pop()
currString = stackOfString.pop()
if currNode.left:
stackOfNode.append... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def sumNumbers(self, root):
""":type root: TreeNode :rtype: int"""
<|body_0|>
def sumNumbers_self(self, root):
""":type root: TreeNode :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
result = []
if not root:
... | stack_v2_sparse_classes_10k_train_000976 | 1,662 | no_license | [
{
"docstring": ":type root: TreeNode :rtype: int",
"name": "sumNumbers",
"signature": "def sumNumbers(self, root)"
},
{
"docstring": ":type root: TreeNode :rtype: int",
"name": "sumNumbers_self",
"signature": "def sumNumbers_self(self, root)"
}
] | 2 | stack_v2_sparse_classes_30k_train_002025 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def sumNumbers(self, root): :type root: TreeNode :rtype: int
- def sumNumbers_self(self, root): :type root: TreeNode :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def sumNumbers(self, root): :type root: TreeNode :rtype: int
- def sumNumbers_self(self, root): :type root: TreeNode :rtype: int
<|skeleton|>
class Solution:
def sumNumbers... | ea492ec864b50547214ecbbb2cdeeac21e70229b | <|skeleton|>
class Solution:
def sumNumbers(self, root):
""":type root: TreeNode :rtype: int"""
<|body_0|>
def sumNumbers_self(self, root):
""":type root: TreeNode :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def sumNumbers(self, root):
""":type root: TreeNode :rtype: int"""
result = []
if not root:
return 0
stackOfNode = [root]
stackOfString = [root.val]
while stackOfNode:
currNode = stackOfNode.pop()
currString = stackO... | the_stack_v2_python_sparse | 129_sum_root_to_leaf_numbers/sol.py | lianke123321/leetcode_sol | train | 0 | |
0ad62148204938c5ab7c9f3f836c6f7bc2f50b2e | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn IosUpdateConfiguration()",
"from .day_of_week import DayOfWeek\nfrom .device_configuration import DeviceConfiguration\nfrom .day_of_week import DayOfWeek\nfrom .device_configuration import DeviceConfiguration\nfields: Dict[str, Callabl... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return IosUpdateConfiguration()
<|end_body_0|>
<|body_start_1|>
from .day_of_week import DayOfWeek
from .device_configuration import DeviceConfiguration
from .day_of_week import DayOfWe... | IOS Update Configuration, allows you to configure time window within week to install iOS updates | IosUpdateConfiguration | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IosUpdateConfiguration:
"""IOS Update Configuration, allows you to configure time window within week to install iOS updates"""
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> IosUpdateConfiguration:
"""Creates a new instance of the appropriate class based... | stack_v2_sparse_classes_10k_train_000977 | 3,544 | permissive | [
{
"docstring": "Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Returns: IosUpdateConfiguration",
"name": "create_from_discriminator_value",
"signature": "def create_from_discrimina... | 3 | stack_v2_sparse_classes_30k_train_000779 | Implement the Python class `IosUpdateConfiguration` described below.
Class description:
IOS Update Configuration, allows you to configure time window within week to install iOS updates
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> IosUpdateConfigurati... | Implement the Python class `IosUpdateConfiguration` described below.
Class description:
IOS Update Configuration, allows you to configure time window within week to install iOS updates
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> IosUpdateConfigurati... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class IosUpdateConfiguration:
"""IOS Update Configuration, allows you to configure time window within week to install iOS updates"""
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> IosUpdateConfiguration:
"""Creates a new instance of the appropriate class based... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class IosUpdateConfiguration:
"""IOS Update Configuration, allows you to configure time window within week to install iOS updates"""
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> IosUpdateConfiguration:
"""Creates a new instance of the appropriate class based on discrimin... | the_stack_v2_python_sparse | msgraph/generated/models/ios_update_configuration.py | microsoftgraph/msgraph-sdk-python | train | 135 |
3d723c4c908b2393b1cd891282bd5e4aa7c20fb5 | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn X509CertificateAuthenticationMethodConfiguration()",
"from .authentication_method_configuration import AuthenticationMethodConfiguration\nfrom .authentication_method_target import AuthenticationMethodTarget\nfrom .x509_certificate_auth... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return X509CertificateAuthenticationMethodConfiguration()
<|end_body_0|>
<|body_start_1|>
from .authentication_method_configuration import AuthenticationMethodConfiguration
from .authentication... | X509CertificateAuthenticationMethodConfiguration | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class X509CertificateAuthenticationMethodConfiguration:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> X509CertificateAuthenticationMethodConfiguration:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse nod... | stack_v2_sparse_classes_10k_train_000978 | 4,581 | permissive | [
{
"docstring": "Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Returns: X509CertificateAuthenticationMethodConfiguration",
"name": "create_from_discriminator_value",
"signature": "... | 3 | null | Implement the Python class `X509CertificateAuthenticationMethodConfiguration` described below.
Class description:
Implement the X509CertificateAuthenticationMethodConfiguration class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> X509CertificateAuthen... | Implement the Python class `X509CertificateAuthenticationMethodConfiguration` described below.
Class description:
Implement the X509CertificateAuthenticationMethodConfiguration class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> X509CertificateAuthen... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class X509CertificateAuthenticationMethodConfiguration:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> X509CertificateAuthenticationMethodConfiguration:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse nod... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class X509CertificateAuthenticationMethodConfiguration:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> X509CertificateAuthenticationMethodConfiguration:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to re... | the_stack_v2_python_sparse | msgraph/generated/models/x509_certificate_authentication_method_configuration.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
401905174d6908ff175b93dd35435d6dd19d1f6a | [
"self.fname = fname\nif not fname:\n self.fname = sys.stdin",
"line = self.fname.readline()\nwhile not line.startswith('>'):\n line = self.fname.readline()\nheader = line[1:].rstrip()\nsequence = ''\nfor line in self.fname:\n if line.startswith('>'):\n yield [header, sequence]\n header = li... | <|body_start_0|>
self.fname = fname
if not fname:
self.fname = sys.stdin
<|end_body_0|>
<|body_start_1|>
line = self.fname.readline()
while not line.startswith('>'):
line = self.fname.readline()
header = line[1:].rstrip()
sequence = ''
for... | This class taken from BME 160 Lab 4 starter code. Provides reading of a FastA file. object attribute fname: standard input methods readFasta(): returns header and sequence as strings. Author: David Bernick, Modifications: me Date: April 19, 2013 | FastAreader | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FastAreader:
"""This class taken from BME 160 Lab 4 starter code. Provides reading of a FastA file. object attribute fname: standard input methods readFasta(): returns header and sequence as strings. Author: David Bernick, Modifications: me Date: April 19, 2013"""
def __init__(self, fname=''... | stack_v2_sparse_classes_10k_train_000979 | 1,405 | no_license | [
{
"docstring": "contructor: saves attribute fname",
"name": "__init__",
"signature": "def __init__(self, fname='')"
},
{
"docstring": "returns each FastA record as 2 strings - header and sequence. whitespace is removed, no adjustment is made to sequence contents. The initial '>' is removed from ... | 2 | stack_v2_sparse_classes_30k_train_002539 | Implement the Python class `FastAreader` described below.
Class description:
This class taken from BME 160 Lab 4 starter code. Provides reading of a FastA file. object attribute fname: standard input methods readFasta(): returns header and sequence as strings. Author: David Bernick, Modifications: me Date: April 19, 2... | Implement the Python class `FastAreader` described below.
Class description:
This class taken from BME 160 Lab 4 starter code. Provides reading of a FastA file. object attribute fname: standard input methods readFasta(): returns header and sequence as strings. Author: David Bernick, Modifications: me Date: April 19, 2... | 7236f20f52810195af397a07a797003c5c45b1e9 | <|skeleton|>
class FastAreader:
"""This class taken from BME 160 Lab 4 starter code. Provides reading of a FastA file. object attribute fname: standard input methods readFasta(): returns header and sequence as strings. Author: David Bernick, Modifications: me Date: April 19, 2013"""
def __init__(self, fname=''... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class FastAreader:
"""This class taken from BME 160 Lab 4 starter code. Provides reading of a FastA file. object attribute fname: standard input methods readFasta(): returns header and sequence as strings. Author: David Bernick, Modifications: me Date: April 19, 2013"""
def __init__(self, fname=''):
""... | the_stack_v2_python_sparse | generate_read_size_distribution.py | belgravia/stacker-scripts | train | 0 |
deec239cac777d1686d93df93e23797d6e50395c | [
"super(MenuPointer, self).__init__(image=MenuPointer.image, x=x, y=y, dx=0, dy=0)\nself.game = game\nself.selection = 0\nself.num_options = len(self.game.options) - 1\nself.menu = menu\nself.counter = 15",
"if self.counter > 0:\n self.counter -= 1\nif self.counter == 0:\n if self.num_options > 0:\n i... | <|body_start_0|>
super(MenuPointer, self).__init__(image=MenuPointer.image, x=x, y=y, dx=0, dy=0)
self.game = game
self.selection = 0
self.num_options = len(self.game.options) - 1
self.menu = menu
self.counter = 15
<|end_body_0|>
<|body_start_1|>
if self.counter ... | Pointer for highlighting and making selections on the game menus | MenuPointer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MenuPointer:
"""Pointer for highlighting and making selections on the game menus"""
def __init__(self, game, x, y, menu):
"""Initialize the sprite."""
<|body_0|>
def update(self):
"""Move the pointer up and down through the options list If the user hits enter pro... | stack_v2_sparse_classes_10k_train_000980 | 3,711 | no_license | [
{
"docstring": "Initialize the sprite.",
"name": "__init__",
"signature": "def __init__(self, game, x, y, menu)"
},
{
"docstring": "Move the pointer up and down through the options list If the user hits enter proceed with the selected option",
"name": "update",
"signature": "def update(s... | 4 | stack_v2_sparse_classes_30k_val_000057 | Implement the Python class `MenuPointer` described below.
Class description:
Pointer for highlighting and making selections on the game menus
Method signatures and docstrings:
- def __init__(self, game, x, y, menu): Initialize the sprite.
- def update(self): Move the pointer up and down through the options list If th... | Implement the Python class `MenuPointer` described below.
Class description:
Pointer for highlighting and making selections on the game menus
Method signatures and docstrings:
- def __init__(self, game, x, y, menu): Initialize the sprite.
- def update(self): Move the pointer up and down through the options list If th... | aab3e28ef659b9a62060940e752b22679b344fdf | <|skeleton|>
class MenuPointer:
"""Pointer for highlighting and making selections on the game menus"""
def __init__(self, game, x, y, menu):
"""Initialize the sprite."""
<|body_0|>
def update(self):
"""Move the pointer up and down through the options list If the user hits enter pro... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class MenuPointer:
"""Pointer for highlighting and making selections on the game menus"""
def __init__(self, game, x, y, menu):
"""Initialize the sprite."""
super(MenuPointer, self).__init__(image=MenuPointer.image, x=x, y=y, dx=0, dy=0)
self.game = game
self.selection = 0
... | the_stack_v2_python_sparse | bin/menuPointer.py | noelano/Portal | train | 0 |
60f20bb4d7b7964ceca30bd694f06e3681d15528 | [
"neighbors = {}\nencoder = _IntegerEncoder()\nn_entries = len(table)\nfor n, (sequence, value) in enumerate(table.items()):\n if n % 1000000 == 0 or (n < 1000000 and n % 100000 == 0):\n logging.info('loading ScaM results %r/%r', n, n_entries)\n neighbor_sequences = [neighbor.docid for neighbor in value... | <|body_start_0|>
neighbors = {}
encoder = _IntegerEncoder()
n_entries = len(table)
for n, (sequence, value) in enumerate(table.items()):
if n % 1000000 == 0 or (n < 1000000 and n % 100000 == 0):
logging.info('loading ScaM results %r/%r', n, n_entries)
... | Matcher that uses pre-computed lookup tables generated by ScaM. | ScaMMatcher | [
"Apache-2.0",
"CC-BY-4.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ScaMMatcher:
"""Matcher that uses pre-computed lookup tables generated by ScaM."""
def __init__(self, table, dtype='u4'):
"""Initialize as ScaMMatcher. Args: table: Mapping[str, result_pb2.NearestNeighbor] mapping each sequence to all of its (approximate) neighbors within some fixed ... | stack_v2_sparse_classes_10k_train_000981 | 19,209 | permissive | [
{
"docstring": "Initialize as ScaMMatcher. Args: table: Mapping[str, result_pb2.NearestNeighbor] mapping each sequence to all of its (approximate) neighbors within some fixed edit distance. dtype: optional object convertable to numpy.dtype to use for storing positive integer IDs. Raises: ValueError: if dtype wa... | 3 | null | Implement the Python class `ScaMMatcher` described below.
Class description:
Matcher that uses pre-computed lookup tables generated by ScaM.
Method signatures and docstrings:
- def __init__(self, table, dtype='u4'): Initialize as ScaMMatcher. Args: table: Mapping[str, result_pb2.NearestNeighbor] mapping each sequence... | Implement the Python class `ScaMMatcher` described below.
Class description:
Matcher that uses pre-computed lookup tables generated by ScaM.
Method signatures and docstrings:
- def __init__(self, table, dtype='u4'): Initialize as ScaMMatcher. Args: table: Mapping[str, result_pb2.NearestNeighbor] mapping each sequence... | 5573d9c5822f4e866b6692769963ae819cb3f10d | <|skeleton|>
class ScaMMatcher:
"""Matcher that uses pre-computed lookup tables generated by ScaM."""
def __init__(self, table, dtype='u4'):
"""Initialize as ScaMMatcher. Args: table: Mapping[str, result_pb2.NearestNeighbor] mapping each sequence to all of its (approximate) neighbors within some fixed ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ScaMMatcher:
"""Matcher that uses pre-computed lookup tables generated by ScaM."""
def __init__(self, table, dtype='u4'):
"""Initialize as ScaMMatcher. Args: table: Mapping[str, result_pb2.NearestNeighbor] mapping each sequence to all of its (approximate) neighbors within some fixed edit distance... | the_stack_v2_python_sparse | aptamers_mlpd/preprocess/clustering.py | Jimmy-INL/google-research | train | 1 |
2ce0900a1f9d3913db3dbd2041d6ae3060a6fc69 | [
"assert len(self.buff_dict) == 10\nassert self.buff_dict.popitem() == (9, 9)\nassert len(self.buff_dict) == 9\nassert (9, 9) not in self.buff_dict.items()",
"try:\n assert self.buff_dict.get(i) == i\nexcept AssertionError:\n assert self.buff_dict.get(i) is None"
] | <|body_start_0|>
assert len(self.buff_dict) == 10
assert self.buff_dict.popitem() == (9, 9)
assert len(self.buff_dict) == 9
assert (9, 9) not in self.buff_dict.items()
<|end_body_0|>
<|body_start_1|>
try:
assert self.buff_dict.get(i) == i
except AssertionErro... | тесты для dict | TestDict2 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestDict2:
"""тесты для dict"""
def test_dict_2_1(self):
"""тест метода popitem"""
<|body_0|>
def test_dict_2_2(self, i):
"""тест метода get"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
assert len(self.buff_dict) == 10
assert self.buf... | stack_v2_sparse_classes_10k_train_000982 | 1,316 | no_license | [
{
"docstring": "тест метода popitem",
"name": "test_dict_2_1",
"signature": "def test_dict_2_1(self)"
},
{
"docstring": "тест метода get",
"name": "test_dict_2_2",
"signature": "def test_dict_2_2(self, i)"
}
] | 2 | stack_v2_sparse_classes_30k_train_001148 | Implement the Python class `TestDict2` described below.
Class description:
тесты для dict
Method signatures and docstrings:
- def test_dict_2_1(self): тест метода popitem
- def test_dict_2_2(self, i): тест метода get | Implement the Python class `TestDict2` described below.
Class description:
тесты для dict
Method signatures and docstrings:
- def test_dict_2_1(self): тест метода popitem
- def test_dict_2_2(self, i): тест метода get
<|skeleton|>
class TestDict2:
"""тесты для dict"""
def test_dict_2_1(self):
"""тест... | 9c468bc73dc4e326f423cb7932090f59b50a4371 | <|skeleton|>
class TestDict2:
"""тесты для dict"""
def test_dict_2_1(self):
"""тест метода popitem"""
<|body_0|>
def test_dict_2_2(self, i):
"""тест метода get"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TestDict2:
"""тесты для dict"""
def test_dict_2_1(self):
"""тест метода popitem"""
assert len(self.buff_dict) == 10
assert self.buff_dict.popitem() == (9, 9)
assert len(self.buff_dict) == 9
assert (9, 9) not in self.buff_dict.items()
def test_dict_2_2(self, i)... | the_stack_v2_python_sparse | hw1/test_dict.py | ikramanop/2020-1-Atom-QA-Python-L-Marder | train | 1 |
78bc9fcbed87191634711c7cfcefbb6f977882f5 | [
"super(ICM, self).__init__(state_size, action_size, eta)\nself.hidden_dim = hidden_dim\nself.state_rep_size = state_rep_size\nself.learning_rate = learning_rate\nself.discrete_actions = discrete_actions\nself.model_dev = 'cpu'\nself.model = ICMNetwork(state_size, action_size, hidden_dim, state_rep_size, discrete_ac... | <|body_start_0|>
super(ICM, self).__init__(state_size, action_size, eta)
self.hidden_dim = hidden_dim
self.state_rep_size = state_rep_size
self.learning_rate = learning_rate
self.discrete_actions = discrete_actions
self.model_dev = 'cpu'
self.model = ICMNetwork(st... | Intrinsic curiosity module (ICM) class Paper: Pathak, D., Agrawal, P., Efros, A. A., & Darrell, T. (2017). Curiosity-driven exploration by self-supervised prediction. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops (pp. 16-17). Link: http://openaccess.thecvf.com/content_cvpr_2... | ICM | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ICM:
"""Intrinsic curiosity module (ICM) class Paper: Pathak, D., Agrawal, P., Efros, A. A., & Darrell, T. (2017). Curiosity-driven exploration by self-supervised prediction. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops (pp. 16-17). Link: http://opena... | stack_v2_sparse_classes_10k_train_000983 | 4,445 | no_license | [
{
"docstring": "Initialise parameters for MARL training :param state_size: dimension of state input :param action_size: dimension of action input :param hidden_dim: hidden dimension of networks :param state_rep_size: dimension of state representation in network :param learning_rate: learning rate for ICM parame... | 4 | stack_v2_sparse_classes_30k_train_000789 | Implement the Python class `ICM` described below.
Class description:
Intrinsic curiosity module (ICM) class Paper: Pathak, D., Agrawal, P., Efros, A. A., & Darrell, T. (2017). Curiosity-driven exploration by self-supervised prediction. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Wo... | Implement the Python class `ICM` described below.
Class description:
Intrinsic curiosity module (ICM) class Paper: Pathak, D., Agrawal, P., Efros, A. A., & Darrell, T. (2017). Curiosity-driven exploration by self-supervised prediction. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Wo... | 2afa0a9d83bd66a151c1a19242c5ef22cf4eb1f6 | <|skeleton|>
class ICM:
"""Intrinsic curiosity module (ICM) class Paper: Pathak, D., Agrawal, P., Efros, A. A., & Darrell, T. (2017). Curiosity-driven exploration by self-supervised prediction. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops (pp. 16-17). Link: http://opena... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ICM:
"""Intrinsic curiosity module (ICM) class Paper: Pathak, D., Agrawal, P., Efros, A. A., & Darrell, T. (2017). Curiosity-driven exploration by self-supervised prediction. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops (pp. 16-17). Link: http://openaccess.thecvf.... | the_stack_v2_python_sparse | intrinsic_rewards/icm/icm.py | Jarvis-K/MSc_Curiosity_MARL | train | 0 |
88b2439cbb6400403b7c3a34451b6355e3358996 | [
"try:\n version = get_openflow_header(this_packet, 0)\n if version['version'] == 1:\n self.ofp = unpack10(this_packet)\n elif version['version'] == 4:\n self.ofp = unpack13(this_packet)\n else:\n self.ofp = 0\nexcept:\n self.ofp = 0",
"if not libs.core.filters.filter_msg(self):... | <|body_start_0|>
try:
version = get_openflow_header(this_packet, 0)
if version['version'] == 1:
self.ofp = unpack10(this_packet)
elif version['version'] == 4:
self.ofp = unpack13(this_packet)
else:
self.ofp = 0
... | Used to process all data regarding this OpenFlow message. With the python-openflow (pyof) lib, only one variable became necessary. | OFMessage | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OFMessage:
"""Used to process all data regarding this OpenFlow message. With the python-openflow (pyof) lib, only one variable became necessary."""
def __init__(self, this_packet):
"""Instantiate OFMessage class Args: self: this class this_packet: OpenFlow msg in binary format"""
... | stack_v2_sparse_classes_10k_train_000984 | 2,331 | permissive | [
{
"docstring": "Instantiate OFMessage class Args: self: this class this_packet: OpenFlow msg in binary format",
"name": "__init__",
"signature": "def __init__(self, this_packet)"
},
{
"docstring": "Generic printing function Args: pkt: Packet class",
"name": "print_packet",
"signature": "... | 2 | stack_v2_sparse_classes_30k_train_002432 | Implement the Python class `OFMessage` described below.
Class description:
Used to process all data regarding this OpenFlow message. With the python-openflow (pyof) lib, only one variable became necessary.
Method signatures and docstrings:
- def __init__(self, this_packet): Instantiate OFMessage class Args: self: thi... | Implement the Python class `OFMessage` described below.
Class description:
Used to process all data regarding this OpenFlow message. With the python-openflow (pyof) lib, only one variable became necessary.
Method signatures and docstrings:
- def __init__(self, this_packet): Instantiate OFMessage class Args: self: thi... | 4b79b6c9ebb8f237ed189c38eefc9e98226606f6 | <|skeleton|>
class OFMessage:
"""Used to process all data regarding this OpenFlow message. With the python-openflow (pyof) lib, only one variable became necessary."""
def __init__(self, this_packet):
"""Instantiate OFMessage class Args: self: this class this_packet: OpenFlow msg in binary format"""
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class OFMessage:
"""Used to process all data regarding this OpenFlow message. With the python-openflow (pyof) lib, only one variable became necessary."""
def __init__(self, this_packet):
"""Instantiate OFMessage class Args: self: this class this_packet: OpenFlow msg in binary format"""
try:
... | the_stack_v2_python_sparse | libs/gen/ofmessage.py | amlight/ofp_sniffer | train | 16 |
f82ae254c765166c3de130b28f3f1a59a127d1c0 | [
"deltap = field_data.compute_dFrdQ(ptcl_data.r, ptcl_data.z, ptcl_data.qOc)\nfield_data.delta_P_dc -= deltap[0]\nfield_data.delta_P_omega -= deltap[1]",
"deltap = field_data.compute_dFrdQ(ptcl_data.r, ptcl_data.z, ptcl_data.qOc)\nfield_data.delta_P_dc += deltap[0]\nfield_data.delta_P_omega += deltap[1]",
"delta... | <|body_start_0|>
deltap = field_data.compute_dFrdQ(ptcl_data.r, ptcl_data.z, ptcl_data.qOc)
field_data.delta_P_dc -= deltap[0]
field_data.delta_P_omega -= deltap[1]
<|end_body_0|>
<|body_start_1|>
deltap = field_data.compute_dFrdQ(ptcl_data.r, ptcl_data.z, ptcl_data.qOc)
field_d... | similarity_drift_maps | [
"Apache-2.0",
"LicenseRef-scancode-warranty-disclaimer",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class similarity_drift_maps:
def S_r(self, field_data, ptcl_data):
"""Compute the effects of the r similarity map on the fields and particles :param field_data: :param ptcl_data: :return: nothing"""
<|body_0|>
def S_r_inverse(self, field_data, ptcl_data):
"""Compute the ef... | stack_v2_sparse_classes_10k_train_000985 | 1,804 | permissive | [
{
"docstring": "Compute the effects of the r similarity map on the fields and particles :param field_data: :param ptcl_data: :return: nothing",
"name": "S_r",
"signature": "def S_r(self, field_data, ptcl_data)"
},
{
"docstring": "Compute the effects of the r-inverse similarity map on the fields ... | 4 | stack_v2_sparse_classes_30k_train_000694 | Implement the Python class `similarity_drift_maps` described below.
Class description:
Implement the similarity_drift_maps class.
Method signatures and docstrings:
- def S_r(self, field_data, ptcl_data): Compute the effects of the r similarity map on the fields and particles :param field_data: :param ptcl_data: :retu... | Implement the Python class `similarity_drift_maps` described below.
Class description:
Implement the similarity_drift_maps class.
Method signatures and docstrings:
- def S_r(self, field_data, ptcl_data): Compute the effects of the r similarity map on the fields and particles :param field_data: :param ptcl_data: :retu... | 14b119267686c64e2d0fcd3be19c365b8d486e22 | <|skeleton|>
class similarity_drift_maps:
def S_r(self, field_data, ptcl_data):
"""Compute the effects of the r similarity map on the fields and particles :param field_data: :param ptcl_data: :return: nothing"""
<|body_0|>
def S_r_inverse(self, field_data, ptcl_data):
"""Compute the ef... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class similarity_drift_maps:
def S_r(self, field_data, ptcl_data):
"""Compute the effects of the r similarity map on the fields and particles :param field_data: :param ptcl_data: :return: nothing"""
deltap = field_data.compute_dFrdQ(ptcl_data.r, ptcl_data.z, ptcl_data.qOc)
field_data.delta_P... | the_stack_v2_python_sparse | rssympim/sympim_rz/maps/similarity_drift_maps.py | radiasoft/rssympim | train | 2 | |
3e9af28a4872dd2a0eb5fafb9a1795c385c75977 | [
"if not matrix:\n self.dp = None\n return\nm = len(matrix)\nn = len(matrix[0])\ndp = self.dp = [[0 for _ in range(n + 1)] for _ in range(m + 1)]\nfor x in range(1, m + 1):\n for y in range(1, n + 1):\n dp[x][y] = dp[x - 1][y] + dp[x][y - 1] - dp[x - 1][y - 1] + matrix[x - 1][y - 1]",
"if not self.... | <|body_start_0|>
if not matrix:
self.dp = None
return
m = len(matrix)
n = len(matrix[0])
dp = self.dp = [[0 for _ in range(n + 1)] for _ in range(m + 1)]
for x in range(1, m + 1):
for y in range(1, n + 1):
dp[x][y] = dp[x - 1][y... | NumMatrix | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NumMatrix:
def __init__(self, matrix):
"""initialize your data structure here. :type matrix: List[List[int]]"""
<|body_0|>
def sumRegion(self, row1, col1, row2, col2):
"""sum of elements matrix[(row1,col1)..(row2,col2)], inclusive. :type row1: int :type col1: int :ty... | stack_v2_sparse_classes_10k_train_000986 | 1,287 | no_license | [
{
"docstring": "initialize your data structure here. :type matrix: List[List[int]]",
"name": "__init__",
"signature": "def __init__(self, matrix)"
},
{
"docstring": "sum of elements matrix[(row1,col1)..(row2,col2)], inclusive. :type row1: int :type col1: int :type row2: int :type col2: int :rtyp... | 2 | stack_v2_sparse_classes_30k_train_006840 | Implement the Python class `NumMatrix` described below.
Class description:
Implement the NumMatrix class.
Method signatures and docstrings:
- def __init__(self, matrix): initialize your data structure here. :type matrix: List[List[int]]
- def sumRegion(self, row1, col1, row2, col2): sum of elements matrix[(row1,col1)... | Implement the Python class `NumMatrix` described below.
Class description:
Implement the NumMatrix class.
Method signatures and docstrings:
- def __init__(self, matrix): initialize your data structure here. :type matrix: List[List[int]]
- def sumRegion(self, row1, col1, row2, col2): sum of elements matrix[(row1,col1)... | a041962eeab9192799ad7f74b4bbd3e4f74933d0 | <|skeleton|>
class NumMatrix:
def __init__(self, matrix):
"""initialize your data structure here. :type matrix: List[List[int]]"""
<|body_0|>
def sumRegion(self, row1, col1, row2, col2):
"""sum of elements matrix[(row1,col1)..(row2,col2)], inclusive. :type row1: int :type col1: int :ty... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class NumMatrix:
def __init__(self, matrix):
"""initialize your data structure here. :type matrix: List[List[int]]"""
if not matrix:
self.dp = None
return
m = len(matrix)
n = len(matrix[0])
dp = self.dp = [[0 for _ in range(n + 1)] for _ in range(m + 1... | the_stack_v2_python_sparse | codes/304. Range Sum Query 2D - Immutable.py | zcgu/leetcode | train | 1 | |
da93e0746aaedfb7d36cd653f0e250c0b86fe8cd | [
"Instrument.__init__(self, cle)\nself.emplacement = 'mains'\nself.positions = (1, 2)\nself.precision = 10\nself.calcul = 60\nself.etendre_editeur('r', 'précision', Uniligne, self, 'precision')\nself.etendre_editeur('ca', 'temps de calcul', Uniligne, self, 'calcul')",
"precision = enveloppes['r']\nprecision.apercu... | <|body_start_0|>
Instrument.__init__(self, cle)
self.emplacement = 'mains'
self.positions = (1, 2)
self.precision = 10
self.calcul = 60
self.etendre_editeur('r', 'précision', Uniligne, self, 'precision')
self.etendre_editeur('ca', 'temps de calcul', Uniligne, self... | Type d'objet: sextant. | Sextant | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Sextant:
"""Type d'objet: sextant."""
def __init__(self, cle=''):
"""Constructeur de l'objet"""
<|body_0|>
def travailler_enveloppes(self, enveloppes):
"""Travail sur les enveloppes"""
<|body_1|>
def regarder(self, personnage):
"""Quand on re... | stack_v2_sparse_classes_10k_train_000987 | 3,821 | permissive | [
{
"docstring": "Constructeur de l'objet",
"name": "__init__",
"signature": "def __init__(self, cle='')"
},
{
"docstring": "Travail sur les enveloppes",
"name": "travailler_enveloppes",
"signature": "def travailler_enveloppes(self, enveloppes)"
},
{
"docstring": "Quand on regarde ... | 3 | null | Implement the Python class `Sextant` described below.
Class description:
Type d'objet: sextant.
Method signatures and docstrings:
- def __init__(self, cle=''): Constructeur de l'objet
- def travailler_enveloppes(self, enveloppes): Travail sur les enveloppes
- def regarder(self, personnage): Quand on regarde la sextan... | Implement the Python class `Sextant` described below.
Class description:
Type d'objet: sextant.
Method signatures and docstrings:
- def __init__(self, cle=''): Constructeur de l'objet
- def travailler_enveloppes(self, enveloppes): Travail sur les enveloppes
- def regarder(self, personnage): Quand on regarde la sextan... | 7e93bff08cdf891352efba587e89c40f3b4a2301 | <|skeleton|>
class Sextant:
"""Type d'objet: sextant."""
def __init__(self, cle=''):
"""Constructeur de l'objet"""
<|body_0|>
def travailler_enveloppes(self, enveloppes):
"""Travail sur les enveloppes"""
<|body_1|>
def regarder(self, personnage):
"""Quand on re... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Sextant:
"""Type d'objet: sextant."""
def __init__(self, cle=''):
"""Constructeur de l'objet"""
Instrument.__init__(self, cle)
self.emplacement = 'mains'
self.positions = (1, 2)
self.precision = 10
self.calcul = 60
self.etendre_editeur('r', 'précisi... | the_stack_v2_python_sparse | src/secondaires/navigation/types/sextant.py | vincent-lg/tsunami | train | 5 |
71ac6e9debfe67d31456d98c384332719e0bc816 | [
"parser = subparsers.add_parser('set', help=textwrap.fill('Set contents of pattoo DB.', width=width))\nself.subparsers = parser.add_subparsers(dest='qualifier')\nfor name in dir(self):\n attribute = getattr(self, name)\n if ismethod(attribute):\n if name.startswith('_'):\n continue\n ... | <|body_start_0|>
parser = subparsers.add_parser('set', help=textwrap.fill('Set contents of pattoo DB.', width=width))
self.subparsers = parser.add_subparsers(dest='qualifier')
for name in dir(self):
attribute = getattr(self, name)
if ismethod(attribute):
i... | Class gathers all CLI 'set' information. | _Set | [
"GPL-3.0-only"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class _Set:
"""Class gathers all CLI 'set' information."""
def __init__(self, subparsers, width=80):
"""Intialize the class."""
<|body_0|>
def language(self, width=80):
"""Process set language CLI commands. Args: width: Width of the help text string to STDIO before wra... | stack_v2_sparse_classes_10k_train_000988 | 14,703 | permissive | [
{
"docstring": "Intialize the class.",
"name": "__init__",
"signature": "def __init__(self, subparsers, width=80)"
},
{
"docstring": "Process set language CLI commands. Args: width: Width of the help text string to STDIO before wrapping Returns: None",
"name": "language",
"signature": "d... | 3 | stack_v2_sparse_classes_30k_val_000402 | Implement the Python class `_Set` described below.
Class description:
Class gathers all CLI 'set' information.
Method signatures and docstrings:
- def __init__(self, subparsers, width=80): Intialize the class.
- def language(self, width=80): Process set language CLI commands. Args: width: Width of the help text strin... | Implement the Python class `_Set` described below.
Class description:
Class gathers all CLI 'set' information.
Method signatures and docstrings:
- def __init__(self, subparsers, width=80): Intialize the class.
- def language(self, width=80): Process set language CLI commands. Args: width: Width of the help text strin... | 57bd3e82e49d51e3426b13ad53ed8326a735ce29 | <|skeleton|>
class _Set:
"""Class gathers all CLI 'set' information."""
def __init__(self, subparsers, width=80):
"""Intialize the class."""
<|body_0|>
def language(self, width=80):
"""Process set language CLI commands. Args: width: Width of the help text string to STDIO before wra... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class _Set:
"""Class gathers all CLI 'set' information."""
def __init__(self, subparsers, width=80):
"""Intialize the class."""
parser = subparsers.add_parser('set', help=textwrap.fill('Set contents of pattoo DB.', width=width))
self.subparsers = parser.add_subparsers(dest='qualifier')
... | the_stack_v2_python_sparse | pattoo/cli/cli.py | palisadoes/pattoo | train | 0 |
f218a16813a9351c677fdbc7a6ebe9d0242e2284 | [
"QuestionTextFormRecord._init_map(self)\nQuestionFilesFormRecord._init_map(self)\nsuper(QuestionTextAndFilesMixin, self)._init_map()",
"QuestionTextFormRecord._init_metadata(self)\nQuestionFilesFormRecord._init_metadata(self)\nsuper(QuestionTextAndFilesMixin, self)._init_metadata()"
] | <|body_start_0|>
QuestionTextFormRecord._init_map(self)
QuestionFilesFormRecord._init_map(self)
super(QuestionTextAndFilesMixin, self)._init_map()
<|end_body_0|>
<|body_start_1|>
QuestionTextFormRecord._init_metadata(self)
QuestionFilesFormRecord._init_metadata(self)
sup... | Mixin class to make the two classes compatible with super() for _init_map and _init_metadata | QuestionTextAndFilesMixin | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class QuestionTextAndFilesMixin:
"""Mixin class to make the two classes compatible with super() for _init_map and _init_metadata"""
def _init_map(self):
"""stub"""
<|body_0|>
def _init_metadata(self):
"""stub"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_10k_train_000989 | 22,562 | permissive | [
{
"docstring": "stub",
"name": "_init_map",
"signature": "def _init_map(self)"
},
{
"docstring": "stub",
"name": "_init_metadata",
"signature": "def _init_metadata(self)"
}
] | 2 | null | Implement the Python class `QuestionTextAndFilesMixin` described below.
Class description:
Mixin class to make the two classes compatible with super() for _init_map and _init_metadata
Method signatures and docstrings:
- def _init_map(self): stub
- def _init_metadata(self): stub | Implement the Python class `QuestionTextAndFilesMixin` described below.
Class description:
Mixin class to make the two classes compatible with super() for _init_map and _init_metadata
Method signatures and docstrings:
- def _init_map(self): stub
- def _init_metadata(self): stub
<|skeleton|>
class QuestionTextAndFile... | 445f968a175d61c8d92c0f617a3c17dc1dc7c584 | <|skeleton|>
class QuestionTextAndFilesMixin:
"""Mixin class to make the two classes compatible with super() for _init_map and _init_metadata"""
def _init_map(self):
"""stub"""
<|body_0|>
def _init_metadata(self):
"""stub"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class QuestionTextAndFilesMixin:
"""Mixin class to make the two classes compatible with super() for _init_map and _init_metadata"""
def _init_map(self):
"""stub"""
QuestionTextFormRecord._init_map(self)
QuestionFilesFormRecord._init_map(self)
super(QuestionTextAndFilesMixin, sel... | the_stack_v2_python_sparse | dlkit/records/assessment/basic/simple_records.py | mitsei/dlkit | train | 2 |
669d87757f3be036c1f9421489221e332c9a2d63 | [
"try:\n inst = Tenant.objects.get(pk=inst_id)\nexcept Tenant.DoesNotExist:\n return api_error(code=404, msg=_('Tenant not existed.'))\ninst_admins = [x.user for x in TenantAdmin.objects.filter(tenant=inst)]\nusernames = [x.user for x in Profile.objects.filter(tenant=inst.name)]\nusers = [User.objects.get(x) f... | <|body_start_0|>
try:
inst = Tenant.objects.get(pk=inst_id)
except Tenant.DoesNotExist:
return api_error(code=404, msg=_('Tenant not existed.'))
inst_admins = [x.user for x in TenantAdmin.objects.filter(tenant=inst)]
usernames = [x.user for x in Profile.objects.fi... | AdminTenant | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AdminTenant:
def get(self, request, inst_id):
"""Get tenant details"""
<|body_0|>
def put(self, request, inst_id):
"""Update tenant quota"""
<|body_1|>
def delete(self, request, inst_id):
"""Delete a tenant"""
<|body_2|>
<|end_skeleton|>... | stack_v2_sparse_classes_10k_train_000990 | 34,523 | permissive | [
{
"docstring": "Get tenant details",
"name": "get",
"signature": "def get(self, request, inst_id)"
},
{
"docstring": "Update tenant quota",
"name": "put",
"signature": "def put(self, request, inst_id)"
},
{
"docstring": "Delete a tenant",
"name": "delete",
"signature": "d... | 3 | null | Implement the Python class `AdminTenant` described below.
Class description:
Implement the AdminTenant class.
Method signatures and docstrings:
- def get(self, request, inst_id): Get tenant details
- def put(self, request, inst_id): Update tenant quota
- def delete(self, request, inst_id): Delete a tenant | Implement the Python class `AdminTenant` described below.
Class description:
Implement the AdminTenant class.
Method signatures and docstrings:
- def get(self, request, inst_id): Get tenant details
- def put(self, request, inst_id): Update tenant quota
- def delete(self, request, inst_id): Delete a tenant
<|skeleton... | 13b3ed26a04248211ef91ca70dccc617be27a3c3 | <|skeleton|>
class AdminTenant:
def get(self, request, inst_id):
"""Get tenant details"""
<|body_0|>
def put(self, request, inst_id):
"""Update tenant quota"""
<|body_1|>
def delete(self, request, inst_id):
"""Delete a tenant"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class AdminTenant:
def get(self, request, inst_id):
"""Get tenant details"""
try:
inst = Tenant.objects.get(pk=inst_id)
except Tenant.DoesNotExist:
return api_error(code=404, msg=_('Tenant not existed.'))
inst_admins = [x.user for x in TenantAdmin.objects.filt... | the_stack_v2_python_sparse | fhs/usr/share/python/syncwerk/restapi/restapi/api3/custom/admin/tenants.py | syncwerk/syncwerk-server-restapi | train | 0 | |
95f8d5cdb04db131eec782075bf3a3abf601f4e7 | [
"self.beta1 = beta1\nself.beta2 = beta2\nself.eps = eps\nmomentums = dict()\nvelocitys = dict()\nfor k, v in model.params.items():\n momentums[k] = np.zeros_like(v)\n velocitys[k] = np.zeros_like(v)\nself.momentums = momentums\nself.velocitys = velocitys\nself.t = 0",
"beta1 = self.beta1\nbeta2 = self.beta2... | <|body_start_0|>
self.beta1 = beta1
self.beta2 = beta2
self.eps = eps
momentums = dict()
velocitys = dict()
for k, v in model.params.items():
momentums[k] = np.zeros_like(v)
velocitys[k] = np.zeros_like(v)
self.momentums = momentums
... | AdamOptim | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AdamOptim:
def __init__(self, model, beta1=0.9, beta2=0.999, eps=1e-08):
"""Inputs: :param model: a neural network class object :param beta1: (float) should be close to 1 :param beta2: (float) similar to beta1 :param eps: (float) in different case, the good value for eps will be differen... | stack_v2_sparse_classes_10k_train_000991 | 9,004 | no_license | [
{
"docstring": "Inputs: :param model: a neural network class object :param beta1: (float) should be close to 1 :param beta2: (float) similar to beta1 :param eps: (float) in different case, the good value for eps will be different",
"name": "__init__",
"signature": "def __init__(self, model, beta1=0.9, b... | 2 | stack_v2_sparse_classes_30k_train_003320 | Implement the Python class `AdamOptim` described below.
Class description:
Implement the AdamOptim class.
Method signatures and docstrings:
- def __init__(self, model, beta1=0.9, beta2=0.999, eps=1e-08): Inputs: :param model: a neural network class object :param beta1: (float) should be close to 1 :param beta2: (floa... | Implement the Python class `AdamOptim` described below.
Class description:
Implement the AdamOptim class.
Method signatures and docstrings:
- def __init__(self, model, beta1=0.9, beta2=0.999, eps=1e-08): Inputs: :param model: a neural network class object :param beta1: (float) should be close to 1 :param beta2: (floa... | a401d09c28432109e9ced10e5011bff97dda05b9 | <|skeleton|>
class AdamOptim:
def __init__(self, model, beta1=0.9, beta2=0.999, eps=1e-08):
"""Inputs: :param model: a neural network class object :param beta1: (float) should be close to 1 :param beta2: (float) similar to beta1 :param eps: (float) in different case, the good value for eps will be differen... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class AdamOptim:
def __init__(self, model, beta1=0.9, beta2=0.999, eps=1e-08):
"""Inputs: :param model: a neural network class object :param beta1: (float) should be close to 1 :param beta2: (float) similar to beta1 :param eps: (float) in different case, the good value for eps will be different"""
s... | the_stack_v2_python_sparse | assignment2/E4040.2017.Assign2.xw2501/E4040.2017.Assign2.xw2501/ecbm4040/optimizers.py | xw2501/Deep_Learning_study | train | 7 | |
9b90606d3456f8603f6db3ae0aea5585b0173077 | [
"picking_obj = self.pool.get('stock.picking')\nseq_obj_name = self._name\nvals['name'] = self.pool.get('ir.sequence').get(cr, user, seq_obj_name)\nnew_id = picking_obj.create(cr, user, vals, context)\nreturn new_id",
"picking_obj = self.pool.get('stock.picking')\nwrite_boolean = picking_obj.write(cr, uid, ids, va... | <|body_start_0|>
picking_obj = self.pool.get('stock.picking')
seq_obj_name = self._name
vals['name'] = self.pool.get('ir.sequence').get(cr, user, seq_obj_name)
new_id = picking_obj.create(cr, user, vals, context)
return new_id
<|end_body_0|>
<|body_start_1|>
picking_obj ... | stock_picking_out | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class stock_picking_out:
def create(self, cr, user, vals, context=None):
"""Override create to call create of stock.picking"""
<|body_0|>
def write(self, cr, uid, ids, vals, context=None):
"""Override write to call write of stock.picking"""
<|body_1|>
<|end_skelet... | stack_v2_sparse_classes_10k_train_000992 | 17,898 | no_license | [
{
"docstring": "Override create to call create of stock.picking",
"name": "create",
"signature": "def create(self, cr, user, vals, context=None)"
},
{
"docstring": "Override write to call write of stock.picking",
"name": "write",
"signature": "def write(self, cr, uid, ids, vals, context=... | 2 | stack_v2_sparse_classes_30k_train_007001 | Implement the Python class `stock_picking_out` described below.
Class description:
Implement the stock_picking_out class.
Method signatures and docstrings:
- def create(self, cr, user, vals, context=None): Override create to call create of stock.picking
- def write(self, cr, uid, ids, vals, context=None): Override wr... | Implement the Python class `stock_picking_out` described below.
Class description:
Implement the stock_picking_out class.
Method signatures and docstrings:
- def create(self, cr, user, vals, context=None): Override create to call create of stock.picking
- def write(self, cr, uid, ids, vals, context=None): Override wr... | 0b997095c260d58b026440967fea3a202bef7efb | <|skeleton|>
class stock_picking_out:
def create(self, cr, user, vals, context=None):
"""Override create to call create of stock.picking"""
<|body_0|>
def write(self, cr, uid, ids, vals, context=None):
"""Override write to call write of stock.picking"""
<|body_1|>
<|end_skelet... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class stock_picking_out:
def create(self, cr, user, vals, context=None):
"""Override create to call create of stock.picking"""
picking_obj = self.pool.get('stock.picking')
seq_obj_name = self._name
vals['name'] = self.pool.get('ir.sequence').get(cr, user, seq_obj_name)
new_id... | the_stack_v2_python_sparse | v_7/NISS/shamil_v3/stock_oc/model/stock.py | musabahmed/baba | train | 0 | |
d5b807a3a7122fb54658b4a180be703ef8b52f96 | [
"self._feature_columns = feature_columns\nself._optimizer_fn = optimizer_fn\nself._checkpoint_dir = checkpoint_dir\nself._hparams = hparams\nself._aux_head_weight = hparams.aux_head_weight\nself._learn_mixture_weights = hparams.learn_mixture_weights\nself._initial_learning_rate = hparams.initial_learning_rate\nself... | <|body_start_0|>
self._feature_columns = feature_columns
self._optimizer_fn = optimizer_fn
self._checkpoint_dir = checkpoint_dir
self._hparams = hparams
self._aux_head_weight = hparams.aux_head_weight
self._learn_mixture_weights = hparams.learn_mixture_weights
sel... | Builds a NASNet subnetwork for AdaNet. | Builder | [
"Apache-2.0",
"LicenseRef-scancode-generic-cla"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Builder:
"""Builds a NASNet subnetwork for AdaNet."""
def __init__(self, feature_columns, optimizer_fn, checkpoint_dir, hparams, seed):
"""Initializes a `Builder`. Args: feature_columns: The input feature columns of the problem. optimizer_fn: Function that accepts a float 'learning_r... | stack_v2_sparse_classes_10k_train_000993 | 11,982 | permissive | [
{
"docstring": "Initializes a `Builder`. Args: feature_columns: The input feature columns of the problem. optimizer_fn: Function that accepts a float 'learning_rate' argument and returns an `Optimizer` instance and learning rate `Tensor` which may have a custom learning rate schedule applied. checkpoint_dir: Ch... | 5 | stack_v2_sparse_classes_30k_train_003933 | Implement the Python class `Builder` described below.
Class description:
Builds a NASNet subnetwork for AdaNet.
Method signatures and docstrings:
- def __init__(self, feature_columns, optimizer_fn, checkpoint_dir, hparams, seed): Initializes a `Builder`. Args: feature_columns: The input feature columns of the problem... | Implement the Python class `Builder` described below.
Class description:
Builds a NASNet subnetwork for AdaNet.
Method signatures and docstrings:
- def __init__(self, feature_columns, optimizer_fn, checkpoint_dir, hparams, seed): Initializes a `Builder`. Args: feature_columns: The input feature columns of the problem... | 74106c51e0602bdd62b643f4d6c42a00142947bc | <|skeleton|>
class Builder:
"""Builds a NASNet subnetwork for AdaNet."""
def __init__(self, feature_columns, optimizer_fn, checkpoint_dir, hparams, seed):
"""Initializes a `Builder`. Args: feature_columns: The input feature columns of the problem. optimizer_fn: Function that accepts a float 'learning_r... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Builder:
"""Builds a NASNet subnetwork for AdaNet."""
def __init__(self, feature_columns, optimizer_fn, checkpoint_dir, hparams, seed):
"""Initializes a `Builder`. Args: feature_columns: The input feature columns of the problem. optimizer_fn: Function that accepts a float 'learning_rate' argument... | the_stack_v2_python_sparse | research/improve_nas/trainer/improve_nas.py | todun/adanet | train | 1 |
70f9553d80bd7ebd981f9f855e99f0ce93ffd8b1 | [
"if len(nums) < 2:\n return True\none_chance = False\nfor i in range(len(nums) - 1):\n if nums[i] > nums[i + 1]:\n if not one_chance:\n one_chance = True\n else:\n return False\nreturn True",
"if len(nums) < 2:\n return True\nlast = nums[0]\nindex = 1\none_chance = Fal... | <|body_start_0|>
if len(nums) < 2:
return True
one_chance = False
for i in range(len(nums) - 1):
if nums[i] > nums[i + 1]:
if not one_chance:
one_chance = True
else:
return False
return True
<... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def _checkPossibility(self, nums):
""":type nums: List[int] :rtype: bool"""
<|body_0|>
def __checkPossibility(self, nums):
""":type nums: List[int] :rtype: bool"""
<|body_1|>
def checkPossibility(self, nums):
""":type nums: List[int] :r... | stack_v2_sparse_classes_10k_train_000994 | 3,075 | permissive | [
{
"docstring": ":type nums: List[int] :rtype: bool",
"name": "_checkPossibility",
"signature": "def _checkPossibility(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: bool",
"name": "__checkPossibility",
"signature": "def __checkPossibility(self, nums)"
},
{
"docstri... | 3 | stack_v2_sparse_classes_30k_train_005470 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def _checkPossibility(self, nums): :type nums: List[int] :rtype: bool
- def __checkPossibility(self, nums): :type nums: List[int] :rtype: bool
- def checkPossibility(self, nums):... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def _checkPossibility(self, nums): :type nums: List[int] :rtype: bool
- def __checkPossibility(self, nums): :type nums: List[int] :rtype: bool
- def checkPossibility(self, nums):... | 0dd67edca4e0b0323cb5a7239f02ea46383cd15a | <|skeleton|>
class Solution:
def _checkPossibility(self, nums):
""":type nums: List[int] :rtype: bool"""
<|body_0|>
def __checkPossibility(self, nums):
""":type nums: List[int] :rtype: bool"""
<|body_1|>
def checkPossibility(self, nums):
""":type nums: List[int] :r... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def _checkPossibility(self, nums):
""":type nums: List[int] :rtype: bool"""
if len(nums) < 2:
return True
one_chance = False
for i in range(len(nums) - 1):
if nums[i] > nums[i + 1]:
if not one_chance:
one_cha... | the_stack_v2_python_sparse | 665.non-decreasing-array.py | windard/leeeeee | train | 0 | |
7b65e94561f3e63be754cbcfd733623c3f4aaed0 | [
"if model._meta.app_label in self.auth_apps:\n return 'default'\nreturn None",
"if model._meta.app_label in self.auth_apps:\n return 'default'\nreturn None",
"if obj1._meta.app_label in self.auth_apps or obj2._meta.app_label in self.auth_apps:\n return True\nreturn None",
"if app_label == 'auth':\n ... | <|body_start_0|>
if model._meta.app_label in self.auth_apps:
return 'default'
return None
<|end_body_0|>
<|body_start_1|>
if model._meta.app_label in self.auth_apps:
return 'default'
return None
<|end_body_1|>
<|body_start_2|>
if obj1._meta.app_label in ... | A router to control all database operations on models in the auth application. | AuthRouter | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AuthRouter:
"""A router to control all database operations on models in the auth application."""
def db_for_read(self, model, **hints):
"""Attempts to read auth models go to auth_db."""
<|body_0|>
def db_for_write(self, model, **hints):
"""Attempts to write auth ... | stack_v2_sparse_classes_10k_train_000995 | 3,782 | no_license | [
{
"docstring": "Attempts to read auth models go to auth_db.",
"name": "db_for_read",
"signature": "def db_for_read(self, model, **hints)"
},
{
"docstring": "Attempts to write auth models go to auth_db.",
"name": "db_for_write",
"signature": "def db_for_write(self, model, **hints)"
},
... | 4 | stack_v2_sparse_classes_30k_train_006544 | Implement the Python class `AuthRouter` described below.
Class description:
A router to control all database operations on models in the auth application.
Method signatures and docstrings:
- def db_for_read(self, model, **hints): Attempts to read auth models go to auth_db.
- def db_for_write(self, model, **hints): At... | Implement the Python class `AuthRouter` described below.
Class description:
A router to control all database operations on models in the auth application.
Method signatures and docstrings:
- def db_for_read(self, model, **hints): Attempts to read auth models go to auth_db.
- def db_for_write(self, model, **hints): At... | 9858638344366fd60e9b75a299326f951e7e66d0 | <|skeleton|>
class AuthRouter:
"""A router to control all database operations on models in the auth application."""
def db_for_read(self, model, **hints):
"""Attempts to read auth models go to auth_db."""
<|body_0|>
def db_for_write(self, model, **hints):
"""Attempts to write auth ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class AuthRouter:
"""A router to control all database operations on models in the auth application."""
def db_for_read(self, model, **hints):
"""Attempts to read auth models go to auth_db."""
if model._meta.app_label in self.auth_apps:
return 'default'
return None
def d... | the_stack_v2_python_sparse | aqi_backend/common/database_routers.py | dschurholz/myaqi-backend | train | 0 |
0ecf8cdd2d74a740da3fa2ca28fd824a00d415ec | [
"self._watcher = watcher\nself._default_value = default_value\nself._flag = threading.Event()\nself.watch()",
"if self._default_value:\n return not self._flag.is_set()\nelse:\n return self._flag.is_set()",
"if self._watcher.watch():\n self._flag.set()\nelse:\n self._flag.clear()"
] | <|body_start_0|>
self._watcher = watcher
self._default_value = default_value
self._flag = threading.Event()
self.watch()
<|end_body_0|>
<|body_start_1|>
if self._default_value:
return not self._flag.is_set()
else:
return self._flag.is_set()
<|end_... | FeatureSwitch checks if a feature is enabled or not. | FeatureSwitch | [
"LicenseRef-scancode-warranty-disclaimer",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FeatureSwitch:
"""FeatureSwitch checks if a feature is enabled or not."""
def __init__(self, watcher, default_value):
"""Constructor for FeatureSwitch. Args: watcher: the watcher object used to determine if the feature is enabled or not default_value: bool, value when the watcher obj... | stack_v2_sparse_classes_10k_train_000996 | 4,327 | permissive | [
{
"docstring": "Constructor for FeatureSwitch. Args: watcher: the watcher object used to determine if the feature is enabled or not default_value: bool, value when the watcher object returns False",
"name": "__init__",
"signature": "def __init__(self, watcher, default_value)"
},
{
"docstring": "... | 3 | stack_v2_sparse_classes_30k_train_001347 | Implement the Python class `FeatureSwitch` described below.
Class description:
FeatureSwitch checks if a feature is enabled or not.
Method signatures and docstrings:
- def __init__(self, watcher, default_value): Constructor for FeatureSwitch. Args: watcher: the watcher object used to determine if the feature is enabl... | Implement the Python class `FeatureSwitch` described below.
Class description:
FeatureSwitch checks if a feature is enabled or not.
Method signatures and docstrings:
- def __init__(self, watcher, default_value): Constructor for FeatureSwitch. Args: watcher: the watcher object used to determine if the feature is enabl... | 1f647ada6b3f2b2f3fb4e59d326f73a2c891fc30 | <|skeleton|>
class FeatureSwitch:
"""FeatureSwitch checks if a feature is enabled or not."""
def __init__(self, watcher, default_value):
"""Constructor for FeatureSwitch. Args: watcher: the watcher object used to determine if the feature is enabled or not default_value: bool, value when the watcher obj... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class FeatureSwitch:
"""FeatureSwitch checks if a feature is enabled or not."""
def __init__(self, watcher, default_value):
"""Constructor for FeatureSwitch. Args: watcher: the watcher object used to determine if the feature is enabled or not default_value: bool, value when the watcher object returns F... | the_stack_v2_python_sparse | biggraphite/utils.py | criteo/biggraphite | train | 129 |
971732a3eb9197bc8edc5506f5308d2615bd7cea | [
"max_count = 0\ninvalid_index = -1\nstack = []\nfor i in range(len(s)):\n if s[i] == '(':\n stack.append(i)\n elif stack:\n stack.pop()\n start_index = stack[-1] if stack else invalid_index\n max_count = max(max_count, i - start_index)\n else:\n invalid_index = i\nreturn ... | <|body_start_0|>
max_count = 0
invalid_index = -1
stack = []
for i in range(len(s)):
if s[i] == '(':
stack.append(i)
elif stack:
stack.pop()
start_index = stack[-1] if stack else invalid_index
max_cou... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def longestValidParentheses(self, s):
""":type s: str :rtype: int"""
<|body_0|>
def longestValidParentheses_failed(self, s):
""":type s: str :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
max_count = 0
invalid_index = ... | stack_v2_sparse_classes_10k_train_000997 | 2,271 | no_license | [
{
"docstring": ":type s: str :rtype: int",
"name": "longestValidParentheses",
"signature": "def longestValidParentheses(self, s)"
},
{
"docstring": ":type s: str :rtype: int",
"name": "longestValidParentheses_failed",
"signature": "def longestValidParentheses_failed(self, s)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longestValidParentheses(self, s): :type s: str :rtype: int
- def longestValidParentheses_failed(self, s): :type s: str :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longestValidParentheses(self, s): :type s: str :rtype: int
- def longestValidParentheses_failed(self, s): :type s: str :rtype: int
<|skeleton|>
class Solution:
def long... | e60ba45fe2f2e5e3b3abfecec3db76f5ce1fde59 | <|skeleton|>
class Solution:
def longestValidParentheses(self, s):
""":type s: str :rtype: int"""
<|body_0|>
def longestValidParentheses_failed(self, s):
""":type s: str :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def longestValidParentheses(self, s):
""":type s: str :rtype: int"""
max_count = 0
invalid_index = -1
stack = []
for i in range(len(s)):
if s[i] == '(':
stack.append(i)
elif stack:
stack.pop()
... | the_stack_v2_python_sparse | src/lt_32.py | oxhead/CodingYourWay | train | 0 | |
5a9daab4114da3539b8233b71115e085b5a9a4fe | [
"ignored = request.GET.get('ignored', False)\nsort = request.GET.get('sort')\nsort_fields = ['created_date', 'invite__times_used', 'invite__invitees__created_date', 'answer']\nif not sort in sort_fields + ['-{:s}'.format(f) for f in sort_fields]:\n sort = '-created_date'\nrequests = models.InviteRequest.objects.... | <|body_start_0|>
ignored = request.GET.get('ignored', False)
sort = request.GET.get('sort')
sort_fields = ['created_date', 'invite__times_used', 'invite__invitees__created_date', 'answer']
if not sort in sort_fields + ['-{:s}'.format(f) for f in sort_fields]:
sort = '-created... | grant invites like the benevolent lord you are | ManageInviteRequests | [
"LicenseRef-scancode-warranty-disclaimer"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ManageInviteRequests:
"""grant invites like the benevolent lord you are"""
def get(self, request):
"""view a list of requests"""
<|body_0|>
def post(self, request):
"""send out an invite"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
ignored = ... | stack_v2_sparse_classes_10k_train_000998 | 6,414 | no_license | [
{
"docstring": "view a list of requests",
"name": "get",
"signature": "def get(self, request)"
},
{
"docstring": "send out an invite",
"name": "post",
"signature": "def post(self, request)"
}
] | 2 | null | Implement the Python class `ManageInviteRequests` described below.
Class description:
grant invites like the benevolent lord you are
Method signatures and docstrings:
- def get(self, request): view a list of requests
- def post(self, request): send out an invite | Implement the Python class `ManageInviteRequests` described below.
Class description:
grant invites like the benevolent lord you are
Method signatures and docstrings:
- def get(self, request): view a list of requests
- def post(self, request): send out an invite
<|skeleton|>
class ManageInviteRequests:
"""grant ... | 0f8da5b738047f3c34d60d93f59bdedd8f797224 | <|skeleton|>
class ManageInviteRequests:
"""grant invites like the benevolent lord you are"""
def get(self, request):
"""view a list of requests"""
<|body_0|>
def post(self, request):
"""send out an invite"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ManageInviteRequests:
"""grant invites like the benevolent lord you are"""
def get(self, request):
"""view a list of requests"""
ignored = request.GET.get('ignored', False)
sort = request.GET.get('sort')
sort_fields = ['created_date', 'invite__times_used', 'invite__invitee... | the_stack_v2_python_sparse | bookwyrm/views/admin/invite.py | bookwyrm-social/bookwyrm | train | 1,398 |
d8c7887bedc466479f5584538c0f694ef4f5e612 | [
"n = len(nums)\nL = [1] * n\nR = [1] * n\nfor i in range(1, n):\n L[i] = L[i - 1] * nums[i - 1]\nfor i in range(n - 2, -1, -1):\n R[i] = R[i + 1] * nums[i + 1]\nres = []\nfor i in range(n):\n res.append(L[i] * R[i])\nreturn res",
"n = len(nums)\nL = [1] * n\nfor i in range(1, n):\n L[i] = L[i - 1] * n... | <|body_start_0|>
n = len(nums)
L = [1] * n
R = [1] * n
for i in range(1, n):
L[i] = L[i - 1] * nums[i - 1]
for i in range(n - 2, -1, -1):
R[i] = R[i + 1] * nums[i + 1]
res = []
for i in range(n):
res.append(L[i] * R[i])
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def productExceptSelf(self, nums):
""":type nums: List[int] :rtype: List[int]"""
<|body_0|>
def productExceptSelf(self, nums):
""":type nums: List[int] :rtype: List[int]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
n = len(nums)
... | stack_v2_sparse_classes_10k_train_000999 | 945 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: List[int]",
"name": "productExceptSelf",
"signature": "def productExceptSelf(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: List[int]",
"name": "productExceptSelf",
"signature": "def productExceptSelf(self, nums)"
}
] | 2 | stack_v2_sparse_classes_30k_train_002788 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def productExceptSelf(self, nums): :type nums: List[int] :rtype: List[int]
- def productExceptSelf(self, nums): :type nums: List[int] :rtype: List[int] | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def productExceptSelf(self, nums): :type nums: List[int] :rtype: List[int]
- def productExceptSelf(self, nums): :type nums: List[int] :rtype: List[int]
<|skeleton|>
class Soluti... | a509b383a42f54313970168d9faa11f088f18708 | <|skeleton|>
class Solution:
def productExceptSelf(self, nums):
""":type nums: List[int] :rtype: List[int]"""
<|body_0|>
def productExceptSelf(self, nums):
""":type nums: List[int] :rtype: List[int]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def productExceptSelf(self, nums):
""":type nums: List[int] :rtype: List[int]"""
n = len(nums)
L = [1] * n
R = [1] * n
for i in range(1, n):
L[i] = L[i - 1] * nums[i - 1]
for i in range(n - 2, -1, -1):
R[i] = R[i + 1] * nums[i +... | the_stack_v2_python_sparse | 0238_Product_of_Array_Except_Self.py | bingli8802/leetcode | train | 0 |
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