text stringlengths 190 325k |
|---|
Imports:
```python
import typing
```
Type definitions:
Input Types: int
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int):
v2 = self.arr
while v1 > 0:
v3 = v1 + 1 >> 1
if self.less_than(v2[v1], v2[v3 - 1]):
v3 -= 1
v4 = v2[v1]
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, *v2) -> int:
if v1 == 'INSERT INTO Tasks (uuid, action_name, pickled, prio, running, run_count, created) VALUES (?,?,?,?,?,?,?)':
v3 = v2[0]
... |
Imports:
```python
import logging
import typing
```
Type definitions:
Input Types: Any, Any, Any
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1, v2, v3) -> None:
logging.warning('Web socket has been closed')
self._deinitialize_workers()
self._connection_established =... |
Imports:
```python
import torch
from torch.nn.modules import Dropout
import typing
```
Type definitions:
Input Types: int, List[int], torch.Tensor, Optional[List[List[int]]]
Output Type: Dict[str, Any]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int, v2: List[int], v3: torch.Tensor, v4: Optio... |
Imports:
```python
import re
import typing
```
Type definitions:
Input Types: str
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str) -> str:
v2 = re.compile('^\\{(\\w{8})-(\\w{4})-(\\w{4})-(\\w\\w)(\\w\\w)-(\\w\\w)(\\w\\w)(\\w\\w)(\\w\\w)(\\w\\w)(\\w\\w)\\}$')
v3 = v2.match(v... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
v1 = u'The story [Story 2](https://app.clubhouse.io/zulip/story/9) was unarchived.'
self.send_and_test_stream_message('story_unarchive', 'Story 2', v... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> str:
v1 = 'sgNom: [' + '] ['.join([f.value for v2 in self.sg_nom]) + '] \n'
v3 = 'sgGen: [' + '] ['.join([v2.value for v2 in self.sg_gen]) + '] \n'
v4 =... |
Imports:
```python
import re
import typing
```
Type definitions:
Input Types: str
Output Type: str
Dependencies:
```python
def v0(v1: str) -> str:
v2 = re.sub(' 0x[0-9a-fA-F]+', ' 0x...', v1)
v3 = re.sub('/tmp/[0-9a-fA-F]+', '/tmp/...', v2)
return v3
```
Function Name: v4
Function:
```python
def v4(v5: str... |
Imports:
```python
import os
import typing
```
Type definitions:
Input Types: str, str
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str, v2: str) -> str:
v3 = v2
if not os.path.isabs(v2):
v3 = os.path.join(v1, v2)
return v3
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str):
try:
v2 = self._call_node_url({'action': 'account_info', 'account': v1})
except Exception as e:
v2 = {'balance': 0}
return v2
... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> str:
v1 = str(self.generator.random.randrange(111111, 99999999))
v1 = v1.zfill(8)
v2 = 0
v3 = [0, 2, 4, 6]
for v4 in v3:
v5 = v1[v4]
... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
self.n = 0
self.sesum = 0.0
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: bool
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: bool):
if not self._done:
self._success = v1
self._done = True
self.emit('finished')
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: tf_metric_accumulators.TFMetricsAccumulator, metric_types.StandardMetricInputs
Output Type: tf_metric_accumulators.TFMetricsAccumulator
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: tf_metric_accumulators.TFMetricsAccumulator, ... |
Imports:
```python
import numpy as np
from numpy import ndarray
import typing
```
Type definitions:
Input Types: ndarray
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: ndarray):
v2 = v1.reshape(len(v1), -1)
return np.sort(v2, axis=1)
``` |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: int
Output Type: None
Dependencies:
```python
def v0(v1: list, v2: int=5) -> list:
assert len(v1) == 4, 'Bounding box can only have 4 corners'
v3 = []
for (v4, v5) in enumerate(v1):
if v4 < 2:
v3.appe... |
Imports:
```python
import os
import tensorflow as tf
from tensorflow.python.framework.convert_to_constants import convert_variables_to_constants_v2
from tensorflow.lite.python.util import get_grappler_config, run_graph_optimizations
import typing
```
Type definitions:
Input Types: Any, str, bool, str
Output Type: None... |
Imports:
```python
import typing
```
Type definitions:
Input Types: typing.Callable
Output Type: typing.Callable
Dependencies:
```python
def v0(v1: typing.Callable) -> typing.Callable:
@functools.wraps(v1)
def v2(*v3: typing.Any, **v4: typing.Any) -> typing.Any:
try:
return v1(*v3, **v4)
... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: dict
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> dict:
self.say('Alors, vous voulez que je vous inscrive aux notifications ? Oui, non ?')
return self.to_platform_dict()
``` |
Imports:
```python
import math
import numpy as np
import typing
```
Type definitions:
Input Types: str, str, int, bool
Output Type: List[float]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str, v2: str, v3: int, v4: bool) -> List[float]:
if v3 < 1:
raise ValueError(f"Subject {v2}: Invali... |
Imports:
```python
import typing
```
Type definitions:
```python
v0 = graph_nets.graphs.GraphsTuple
```
Input Types: v0, Optional[int], Optional[int]
Output Type: tf.Tensor
Dependencies:
Function Name: v1
Function:
```python
def v1(self, v2: v0, v3: Optional[int]=None, v4: Optional[int]=None) -> tf.Tensor:
(v3, v4... |
Imports:
```python
import typing
```
Type definitions:
```python
@attr.s(frozen=True)
class v0(GenericConverter, abc.ABC):
v1: ClassVar[Dict[Type, Type['AttributeConverter']]] = {}
v2: attr.Attribute = attr.ib()
v3: Optional[Type[MutableSequence]]
v4: Type
v5: List[Type]
v6: int
v7: bool
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any
Output Type: List['OptNode']
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1=None) -> List['OptNode']:
v2 = self._operator.ordered_subnodes_hierarchy(v1)
return [self._node_adapter.adapt(node) for v3 in v2]
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: Dict[str, str]
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> Dict[str, str]:
if self.hasScore():
v1 = {}
v1['date'] = self.getMatchDate()
v1['score'] = self.getMatchScore()
for v... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
self.program_counter = 64738
self.stack_pointer = 509
self.cycles = 0
self.flag_i = True
self.flag_d = False
self.flag_b = True
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: List[int], List[int]
Output Type: List[int]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: List[int], v2: List[int]) -> List[int]:
assert len(v1) == len(v2), 'Misaligned inputs ({0} vs {1})'.format(len(v1), len(v2))
return [x ... |
Imports:
```python
import typing
```
Type definitions:
Input Types: list, Any
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: list, v2=None):
v3 = 0
for (v4, v5) in enumerate(v1):
for (v6, v7) in enumerate(v5['dialogue']):
yield (v4, v5, v6, v7)
... |
Imports:
```python
from selenium.common.exceptions import TimeoutException, InvalidElementStateException, NoSuchElementException, StaleElementReferenceException
from selenium.webdriver.common.action_chains import ActionChains
from selenium.webdriver.common.keys import Keys
from selenium.webdriver.remote.webelement impo... |
Imports:
```python
import typing
```
Type definitions:
Input Types: List[List[str]]
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: List[List[str]]) -> None:
if len(v1) == 0:
return
self.row = len(v1)
self.col = len(v1[0])
for v2 in range(self.row):
... |
Imports:
```python
import torch
import typing
```
Type definitions:
Input Types: torch.Tensor, torch.Tensor, Optional[Union[str, Callable]], Optional[int]
Output Type: Tuple[torch.Tensor, int]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: torch.Tensor, v2: torch.Tensor, v3: Optional[Union[str, Callab... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: Optional[str]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str) -> Optional[str]:
v2 = []
for v3 in self.pipelines:
v4 = v3.comments
for v5 in v4:
v6 = v5.get('associated_id... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: torch.Tensor
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str) -> torch.Tensor:
v2 = self.get_wav_tensor_from_file(v1)
return self.get_mel_tensor(v2)
``` |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: str
Output Type: List[float]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str) -> List[float]:
v2: List[float] = []
if ':' in v1:
v3 = v1.split(':')
v4 = float(v3[0])
v5 = float(v3[... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str) -> None:
v2 = self.current_line
(v3, v4) = self.nvim.current.window.cursor
self.current_line = v2[0:v4 + 1] + v1 + v2[v4 + 1:]
self.nvim.c... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
if self.count >= self.total:
self.mark_completed()
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
if self.sync_batchnorm:
self.model = self.configure_sync_batchnorm(self.model)
self.configure_ddp()
self.barrier()
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: ast.Assign
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: ast.Assign) -> None:
self.in_assign += 1
for v2 in v1.targets:
self.visit(v2)
self.in_assign -= 1
self.visit(v1.value)
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: Optional['ExperimentData']
Output Type: 'ExperimentData'
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Optional['ExperimentData']=None) -> 'ExperimentData':
if v1 is None:
v1 = self.__class__(experiment=self.experim... |
Imports:
```python
import typing
```
Type definitions:
Input Types: List[str], pyexiv2.metadata.ImageMetadata, Union[float, None], Union[List[int], None], Union[str, None]
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: List[str], v2: pyexiv2.metadata.ImageMetadata, v3: Union[float, N... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str):
v2 = []
with open(v1, 'rb') as v3:
v2 = [char if isinstance(char, bytes) else bytes([char]) for v4 in v3.read(720)]
return v2
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: Callable
Output Type: Callable
Dependencies:
```python
def v0(v1: int, v2: Iterator[Iterator[int]]) -> Iterator[Optional[int]]:
for v3 in v2:
v4 = skip_func(v3, v1)
if v4 is True:
for v5 in v0(v1, v2):
y... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Dict[str, models.DbtCatalogNode], str, str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: Dict[str, models.DbtCatalogNode], v2: str, v3: str):
v4 = v1.get(v2)
v5 = None if v4 is None else v4.columns.get(v3)
... |
Imports:
```python
import numpy as np
from pandas._libs import Timestamp, internals as libinternals, lib, writers
from pandas._libs.internals import BlockPlacement
from pandas._libs.tslibs import IncompatibleFrequency
from pandas._typing import ArrayLike, DtypeObj, F, Shape, npt
from pandas.errors import AbstractMethod... |
Imports:
```python
import typing
```
Type definitions:
Input Types: dict
Output Type: dict
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: dict) -> dict:
if not v1:
return dict()
v2 = v1.get('reputation', None)
v2 = dict() if not v2 else v2
v3 = v2.get('counts', None)
... |
Imports:
```python
import io
import os
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
v1 = os.path.join(self._tmpdir, 'async.txt')
try:
with self._pathmgr.opena(v1, 'wb') as v2:
v2.write(b'012345... |
Imports:
```python
import statsmodels.tsa.stattools as ts
import typing
```
Type definitions:
Input Types: int, float
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int=1, v2: float=0.05):
(v3, v4, v5, v6, v7) = ts.adfuller(self.time_series, maxlag=v1)
return v4 < v2 and... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, **v2):
if v1 == 'flash':
self.flash(**v2)
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any
Output Type: Optional[str]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Any) -> Optional[str]:
if not self._root:
return None
return self._search_helper(self._root, v1)
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: nodes.FunctionDef
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: nodes.FunctionDef) -> None:
for v2 in self._function_matchers:
if not v2.need_to_check_function(v1) or v1.is_method():
co... |
Imports:
```python
import gzip
import pickle
import typing
```
Type definitions:
Input Types: Union[str, Path], bool, bool, str, Optional[int]
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Union[str, Path], v2: bool=False, v3: bool=False, v4: str='jsonpickle', v5: Optional[int]... |
Imports:
```python
import typing
```
Type definitions:
```python
v0 = Dict[str, Union[bool, Tuple[str], 'SIGLIST_TYPE']]
```
Input Types: str, v0, List[Tuple[str, List[Tuple[str]]]], List[Tuple[str, List[Tuple[str]]]], bool, Optional[str], Sequence[str]
Output Type: Any
Dependencies:
Function Name: v1
Function:
```pyt... |
Imports:
```python
import typing
```
Type definitions:
Input Types: list, int
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: list, v2: int) -> int:
v3 = sum((1 if v2 == i else 0 for (v4, v5) in v1))
return v3
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0() -> None:
v1 = list(map(int, input().split()))
v1.sort()
assert len(v1) == 26
assert v1 == list(range(1, 26 + 1))
``` |
Imports:
```python
import numpy as np
from matplotlib import pyplot as plt
from matplotlib.axes import Axes
from matplotlib.ticker import MaxNLocator
import typing
```
Type definitions:
Input Types: Optional[Axes]
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Optional[Axes]=No... |
Imports:
```python
import sys, os, glob, subprocess
import typing
```
Type definitions:
Input Types:
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0() -> bool:
v1 = any([e.startswith('-i') for v2 in sys.argv])
return v1
``` |
Imports:
```python
import torch
import torch.nn as nn
from torch import optim, Tensor
import typing
```
Type definitions:
Input Types: Tensor
Output Type: Tuple[Optional[Tensor], Optional[Tensor], Optional[Tensor]]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Tensor) -> Tuple[Optional[Tensor],... |
Imports:
```python
import typing
```
Type definitions:
Input Types: DataFrame, str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: DataFrame, v2: str):
v1 = v1[v1['//prepare/phase_1_bytes'] > 10000000]
v1 = v1[['when', '//sync/phase_2_ms']]
v3 = v1.groupby('when').agg(['min... |
Imports:
```python
import cvxpy as cp
import cvxpy.settings as s
from cvxpy import Minimize, Problem
from cvxpy.expressions.constants import Constant, Parameter
from cvxpy.expressions.variable import Variable
from cvxpy.reductions.solvers.defines import INSTALLED_MI_SOLVERS
from cvxpy.tests.base_test import BaseTest
fr... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, int
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: int) -> str:
v3 = []
for v4 in v1:
if not v3:
v3.append([1, v4])
elif v3[-1][1] == v4:
v3[-1][0] +... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, str
Output Type: List[dict]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: str) -> List[dict]:
v3 = '/'.join((self._make_url(v1, contents=True), v2, 'extra_files'))
return self._get(url=v3)
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str):
v2 = open(v1, 'rt')
v3 = v2.read().splitlines()
v4 = []
v5 = len(v3)
for v6 in range(v5):
v7 = v3[v6]
v8 = v7.split(',')
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: tf.keras.metrics.Metric
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: tf.keras.metrics.Metric):
if not hasattr(self, '_tfasr_metrics'):
self._tfasr_metrics = {}
self._tfasr_metrics[v1.name] = v1... |
Imports:
```python
import requests
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
```python
def v0(v1: str):
v2 = f'http://{v1}:9090/api/v1/targets'
v3 = time.time()
v4 = 120
while time.time() - v3 < v4:
try:
v5 = requests.get(v2, timeout=10)
... |
Imports:
```python
from pathlib import Path
import torch
import torch.nn as nn
import torch.nn.functional as F
import typing
```
Type definitions:
Input Types: str, str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str=None, v2: str=''):
if v1 is None:
v3 = self.che... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: any
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> any:
v1 = self.build_graph()
return len(v1.find_ancestors('shiny gold'))
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: 'DocumentArray'
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: 'DocumentArray'):
v2 = self.exec_embedding_cls_type
if v2.is_dense:
return v1.all_embeddings
else:
return v1.get_all_spa... |
Imports:
```python
import csv
import typing
```
Type definitions:
Input Types: str
Output Type: list
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str) -> list:
with open(v1, 'r', encoding='utf-8') as v2:
v3 = csv.reader(v2, delimiter=';')
v4 = []
for v5 in v3:
... |
Imports:
```python
import typing
```
Type definitions:
```python
class v0(NamedTuple):
v1: int
v2: int
v3: str
v4: str
```
Input Types: List[v0]
Output Type: int
Dependencies:
Function Name: v5
Function:
```python
def v5(v6: List[v0]) -> int:
v7: int = 0
for v8 in v6:
v9 = len(v8.passwo... |
Imports:
```python
import base64
import hashlib
import typing
```
Type definitions:
Input Types: int, bytes
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int, v2: bytes) -> None:
v3 = hashlib.sha256(v2).digest()
self._session.client('ebs').put_snapshot_block(SnapshotId... |
Imports:
```python
import numpy
import typing
```
Type definitions:
Input Types: int
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int=0):
if v1 <= 0 or v1 > self._sum_tree.size:
v1 = self._sum_tree.size
v2: [] = []
v3: [] = []
v4: [] = []
v5: [] = [... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: Generator
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str) -> Generator:
for v2 in [v2.strip() for v2 in v1.split(',')]:
if '-' in v2:
(v3, v4) = v2.split('-')
if '>' in v4:
... |
Imports:
```python
import typing
```
Type definitions:
```python
class v0(Protocol):
v1: str
v2: int
v3: int
v4: str
def v5(self, v6, v7=False) -> Optional['RemoteObjectProtocol']:
pass
```
Input Types: v0
Output Type: str
Dependencies:
Function Name: v8
Function:
```python
def v8(self, v9... |
Imports:
```python
from itertools import combinations
import typing
```
Type definitions:
Input Types: Sequence[int], int
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: Sequence[int], v2: int) -> int:
for (v3, v4) in enumerate(v1[v2:], start=v2):
v5 = (sum(combination) for... |
Imports:
```python
from copy import deepcopy
import typing
```
Type definitions:
Input Types: nx.DiGraph
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: nx.DiGraph):
v2 = deepcopy(v1)
for (v3, v4) in v1.edges:
v5 = deepcopy(v1.edges[v3, v4])
v5['pKa'] = -v5['pKa... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, int, int
Output Type: None
Dependencies:
```python
def v0(v1: int, v2: int) -> str:
return f'\x1b[{v2};{v1}f'
```
```python
def v3(v4: int, v5: int) -> bool:
v6 = 0 <= v4 <= 96
v7 = 0 <= v5 <= 30
return not (v6 and v7)
```
```pyth... |
Imports:
```python
from math import inf
import typing
```
Type definitions:
Input Types: str, str, float, float, float, float
Output Type: float
Dependencies:
```python
def v0(v1: str, v2: str) -> int:
return int(v1 != v2)
```
Function Name: v3
Function:
```python
def v3(v4: str, v5: str, v6: float=2.0, v7: float=... |
Imports:
```python
from collections import Counter
import typing
```
Type definitions:
Input Types: Sequence[str]
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: Sequence[str]) -> int:
v2 = 0
v3 = 0
for v4 in v1:
v5 = Counter(v4)
if 3 in v5.values():
... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: list
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> list:
v1 = []
for v2 in self.json_response.keys():
if v2 not in self.__class__._JSON_ATTRS:
v1.append(v2)
return v1
``` |
Imports:
```python
import random
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
random.shuffle(self.datasets['train'])
return
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: Optional[str]
Output Type: Optional[str]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: Optional[str]=None) -> Optional[str]:
nonlocal _current_conf_file
if v1 is not None:
v2 = v1
return v2
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: Dict[Any, Any], Dict[Any, Any]
Output Type: Dict[Any, Any]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: Dict[Any, Any], v2: Dict[Any, Any]) -> Dict[Any, Any]:
v1 = v1.copy()
v1.setdefault('environment', {})
v1['environme... |
Imports:
```python
import matplotlib.pyplot as plt
import typing
```
Type definitions:
Input Types: Image.Image, Image.Image, Image.Image, tuple
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: Image.Image, v2: Image.Image, v3: Image.Image, v4: tuple=(18, 6)):
plt.subplots(1, 3, fig... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: Optional[str]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str) -> Optional[str]:
if v1[-6:] in self.shortened_url_map:
return self.shortened_url_map[v1[-6:]]
return None
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, Any
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: Any):
v3 = self._get_hash(v1)
if not self.map[v3]:
self.map[v3] = [[v1, v2]]
return True
else:
for v4 in self.... |
Imports:
```python
import pandas as pd
import typing
```
Type definitions:
```python
class v0(object):
def __init__(self):
self.train_size = 0.8
self.batch_size = 2
self.epochs = 50
self.lr = 0.01
self.path = '..\\data\\train.csv'
self.target = 'Survived'
sel... |
Imports:
```python
from rdkit.Chem import MolFromSmiles, MolToSmiles, PathToSubmol, RemoveHs, SanitizeMol
from rdkit.Chem.rdchem import Mol, RWMol
from rdkit.Chem.rdmolops import FindAtomEnvironmentOfRadiusN as SearchAtomEnv
import typing
```
Type definitions:
Input Types: Mol, int
Output Type: Tuple
Dependencies:
```... |
Imports:
```python
import csv
import gzip
import typing
```
Type definitions:
Input Types: pl.Path, Sequence[str], Sequence[np.ndarray]
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: pl.Path, v2: Sequence[str], v3: Sequence[np.ndarray]) -> None:
assert len(v2) == len(v3)
asse... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str):
v2 = [*map(int, v1.split('+'))]
return sum(v2)
``` |
Imports:
```python
import random
import numpy as np
from math import sqrt
import typing
```
Type definitions:
Input Types: np.array, int, int
Output Type: np.array
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: np.array, v2: int, v3: int=5) -> np.array:
v4 = len(v1)
v5 = np.array([random.randi... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int):
if v1 == 2:
self.handler.sign_node.connect(self.node2_drawwindow.addPoint)
self.node2_drawwindow.start(v1)
elif v1 == 3:
s... |
Imports:
```python
import numpy as np
from numpy.linalg import solve
import typing
```
Type definitions:
```python
class v0:
def __init__(self, v1: car.CarParams):
"""
Args:
CP: Car Parameters
"""
self.m: float = v1.mass
self.j: float = v1.rotationalInertia
self.l: flo... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, str
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str, v2: str) -> str:
if v1[-1] != '/':
v1 = v1 + '/'
assert v2.startswith(v1)
return v2[len(v1):]
``` |
Imports:
```python
from inspect import signature
from typing import Callable, Dict, List, Type
import typing
```
Type definitions:
Input Types: Callable
Output Type: bool
Dependencies:
```python
def v0(v1):
if getattr(v1, '__origin__', None):
return v1.__origin__
if hasattr(v1, '_gorg') and hasattr(v1.... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1=None) -> None:
if v1 is not None:
if not 0 <= v1 < len(self._data):
raise ValueError('invalid size value')
self._cursor = v1
... |
Imports:
```python
import typing
```
Type definitions:
```python
class v0(SimpleStatement):
def __init__(self, v1: VariableDeclaration, v2: Optional[Expression]=None):
"""
:param variable_declaration:
:param expr: can be None
"""
super().__init__()
self.variable_dec... |
Imports:
```python
import ast
import typing
```
Type definitions:
Input Types: str, Dict[str, str]
Output Type: str
Dependencies:
```python
def v0(v1: str, v2: ast.AST, v3: Dict[str, str]) -> str:
v4 = ImportsParser(v3)
v4.visit(v2)
for (v5, v6) in v4.replacements.items():
v1 = v1.replace(v5, v6)
... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: Callable
Dependencies:
```python
def v0(v1: int, v2: int) -> int:
v0.executed = True
return v1 + v2
```
Function Name: v3
Function:
```python
def v3() -> Callable:
def v4(v5: int, v6: int) -> int:
v4.executed = True
... |
Imports:
```python
import typing
```
Type definitions:
```python
class v0:
def __init__(self, v1: str):
self.symbol = v1
self.index = 0
self.quote = dict()
```
Input Types: v0, list
Output Type: Any
Dependencies:
Function Name: v2
Function:
```python
def v2(self, v3: v0, v4: list):
v5 ... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
with self._descs_lock:
self.cleanup_registry()
self.verify_registry()
``` |
Imports:
```python
import os
import tempfile
import typing
```
Type definitions:
Input Types: str, str
Output Type: str
Dependencies:
```python
def v0(v1: str, v2: str) -> str:
v3 = tempfile.NamedTemporaryFile(prefix=v1 + ' ', suffix='.' + v2).name
return v3
```
Function Name: v4
Function:
```python
def v4(v5:... |
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