text stringlengths 190 325k |
|---|
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: Text
Output Type: np.ndarray
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Text) -> np.ndarray:
v2 = [self._v2i[ch] for v3 in v1.split('/') if v3 in self._v2i]
return np.array(v2, dtype=np.int64)
``` |
Imports:
```python
from rdkit import Chem
import typing
```
Type definitions:
Input Types: str, Optional[str]
Output Type: Tuple[bool, bool]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str, v2: Optional[str]=None) -> Tuple[bool, bool]:
v3 = False
with open(v1, 'r') as v4:
v5 = v4.re... |
Imports:
```python
import json
import os
import typing
```
Type definitions:
```python
v0 = Dict[str, Any]
```
Input Types: str
Output Type: List[v0]
Dependencies:
```python
def v1(v2: str) -> float:
v3 = v2.split(' ')
v4 = v3[0].replace('T', ' ')
v5 = dateutil.parser.parse(v4)
v6 = v5.timestamp()
i... |
Imports:
```python
import os
import typing
```
Type definitions:
Input Types: str, str
Output Type: Any
Dependencies:
```python
def v0(v1: str):
global CLIENT
if not v1:
raise UserResolvableError('Hark Cloud endpoint not set', '')
try:
v2 = os.environ['HASURA_ADMIN_SECRET']
except KeyEr... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str) -> bool:
v2 = self.get_feature_flags()
if v2 and v1 in v2:
return v2[v1]
return False
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, **v2):
v2.update(locals())
v3 = {'tags': ['cellularGateway', 'configure', 'portForwardingRules'], 'operation': 'updateDeviceCellularGatewayPortForw... |
Imports:
```python
import keras.utils
from keras import Sequential, Model, layers
from keras.preprocessing.sequence import pad_sequences
import typing
```
Type definitions:
Input Types: Model, Dict[str, int], int, List[Tuple[str, int]]
Output Type: List[Tuple[str, int, str]]
Dependencies:
```python
def v0(v1, v2, v3, ... |
Imports:
```python
import typing
```
Type definitions:
Input Types: []
Output Type: [[str]]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: []) -> [[str]]:
v2 = ''
v3 = []
for v4 in v1:
if v4.startswith('?'):
v4 = v4[1:]
if v4 not in v3:
v3.append(v4)... |
Imports:
```python
import typing
```
Type definitions:
```python
class v0(Common):
def __init__(self, v1=0, v2=0, v3=0):
self.x = v1
self.y = v2
self.z = v3
self.sorting = 0
self.normal = 0
def v4(self):
if not self.normal:
return f'{self.x} {self.y}... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int=-2) -> int:
v2 = self.collect_legal_coordinates()
if v2 == (-1, -1):
return -1
if v1 == -2:
return 9
if self.state.ravel()[v... |
Imports:
```python
import copy
import typing
```
Type definitions:
Input Types: dict, dict, str, int
Output Type: dict
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: dict, v2: dict, v3: str, v4: int) -> dict:
v5 = copy.deepcopy(v2)
v6 = v1['components'][v3]
v7 = v1['id']
v8 = v1[... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: 'bool'
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> 'bool':
if not self.queue:
return False
self.queue[self.start] = None
self.start = (self.start + 1) % self.max_size
return True
``` |
Imports:
```python
import logging
import typing
```
Type definitions:
Input Types: str
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str) -> str:
self.update_rotor_positions()
v2 = self.encode_rotor_right_left(len(self.rotors) - 1, v1)
v3 = self.reflector.encode(v2)... |
Imports:
```python
import logging
import numpy as np
import typing
```
Type definitions:
Input Types: int, bool
Output Type: Iterator[Tuple[List[str], Dict[str, torch.Tensor]]]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int, v2: bool=None) -> Iterator[Tuple[List[str], Dict[str, torch.Tensor]... |
Imports:
```python
import torch
import torch.nn.functional as F
import torch.nn as nn
from torch import Tensor
import typing
```
Type definitions:
Input Types:
Output Type: Tensor
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> Tensor:
v1 = torch.tanh(self.conv1(self.x, self.pos_edge_index, s... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any
Output Type: list
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1) -> list:
self._hosts.remove(v1)
return self.hosts
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: pathlib.Path, pathlib.Path
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: pathlib.Path, v2: pathlib.Path) -> bool:
if not v1.is_absolute() or not v2.is_absolute():
raise ValueError("Argument 'parent' and ... |
Imports:
```python
import re
import typing
```
Type definitions:
Input Types: str, str, str
Output Type: Tuple[str, Optional[str]]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str, v2: str, v3: str='date') -> Tuple[str, Optional[str]]:
if v2 == 'Y':
v4 = 'y(ear)?'
elif v2 == 'M' and ... |
Imports:
```python
from subprocess import Popen, PIPE
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str=None):
v2 = v1 or self.command_line_client
v3 = f'Could not test run "{v2} --help"!'
try:
v4 = Popen(... |
Imports:
```python
import pandas as pd
import typing
```
Type definitions:
Input Types:
Output Type: pd.DataFrame
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> pd.DataFrame:
v1 = {k: [v] for (v2, v3) in self.get_statistics().items()}
return pd.DataFrame.from_dict(v1, orient='columns')
`... |
Imports:
```python
from itertools import product
import typing
```
Type definitions:
Input Types: str
Output Type: int
Dependencies:
```python
def v0(v1: int, v2: int) -> List[Tuple[int, int]]:
return [(r0, c0) for (v3, v4) in product({v1 - 1, v1, v1 + 1}, {v2 - 1, v2, v2 + 1}) if 0 <= v3 < 10 and 0 <= v4 < 10 and... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str) -> None:
if not v1:
raise KeyError('Invalid store group name')
self._child_list.append(v1)
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> int:
assert not self.empty()
v1 = self.curr.value
if self._number_of_elems == 1:
self.curr = None
else:
v2 = self.curr.prev_node
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: np.ndarray, np.ndarray
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: np.ndarray, v2: np.ndarray, **v3) -> None:
(v4, v5) = self._apply_preprocessing(v1, v2, fit=True)
self.model.fit(v4, v5, **v3)
s... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: List[Any]
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> List[Any]:
self._eval()
if self._ort_value is None:
return []
return self._ort_value.numpy().tolist()
``` |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: dict
Output Type: dict
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: dict) -> dict:
for (v2, v3) in v1.items():
if isinstance(v3, np.ndarray):
v4 = np.nan_to_num(v3, nan=123456789, posinf=1e... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any, discord.Message
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
async def v0(v1, v2: discord.Message):
if not v2.guild:
return commands.when_mentioned_or(v1.default_prefix)(v1, v2)
v3 = v1.prefixes.get(v2.gui... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str):
v2 = self.driver.current_url + v1
return self.driver.get(v2)
``` |
Imports:
```python
from copy import copy
import typing
```
Type definitions:
```python
v0 = Union[Vector, Location, Shape, Sketch]
```
```python
v1 = TypeVar('T', bound='Workplane')
```
Input Types: Iterable[v0]
Output Type: v1
Dependencies:
Function Name: v2
Function:
```python
def v2(self: v1, v3: Iterable[v0]) -> v... |
Imports:
```python
import math
import typing
```
Type definitions:
```python
class v0(BatcherSchedulerConfig):
v1: float = 5
```
Input Types: int, v0, int
Output Type: int
Dependencies:
Function Name: v2
Function:
```python
def v2(self, v3: int, v4: v0, v5: int) -> int:
if v5 > self.get_max_steps():
re... |
Imports:
```python
import json
import typing
```
Type definitions:
Input Types: str, str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: str):
v3 = 'SELECT count(url) from ' + v1
try:
v4 = self._client.query(v3 + ' where time > now() - ' + v2)
v5 ... |
Imports:
```python
import torch, math
import typing
```
Type definitions:
Input Types: Any, int, bool
Output Type: Any
Dependencies:
```python
def v0(v1, v2: int=10, v3: int=2):
assert v2 > 0, 'The number of sifting times should be at least one.'
v1 = torch.as_tensor(v1).double()
v4 = v1.device
v5 = v1... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
self.update()
self.timeout_add(self.update_interval, self.timer_setup)
``` |
Imports:
```python
from datetime import date, datetime, timedelta
from math import isnan
import typing
```
Type definitions:
```python
@dataclass
class v0:
v1: v1
v2: float
```
Input Types: List[v0], date, date
Output Type: Any
Dependencies:
```python
def v3(v4: List[v0], v5: int):
v6 = v5
while v6 >= 0... |
Imports:
```python
import re
import typing
```
Type definitions:
Input Types: str, List[str]
Output Type: List[str]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str, v2: List[str]) -> List[str]:
v3 = []
v4 = ''.join(v2)
v5 = '.*warnings\\.filter.*'
if bool(re.search(v5, v4)):
... |
Imports:
```python
import math
import numpy as np
import typing
```
Type definitions:
Input Types: np.ndarray
Output Type: Tuple[float, float, float]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: np.ndarray) -> Tuple[float, float, float]:
v1 = np.round(v1, decimals=7)
if v1[2][0] != 1 and v1[... |
Imports:
```python
import collections
import typing
```
Type definitions:
Input Types: pd.Series, int, str, bool
Output Type: Any
Dependencies:
```python
def v0(v1: str, v2: int):
return zip(*[v1[i:] for v3 in range(v2)])
```
Function Name: v4
Function:
```python
def v4(v5: pd.Series, v6: int, v7: str=' ', v8: boo... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Token, Token
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Token, v2: Token):
(v3, v4, v5, v6) = self.get_gender_number_info(v1, directly=True)
(v7, v8, v9, v10) = self.get_gender_number_info(v2, direct... |
Imports:
```python
import typing
```
Type definitions:
```python
@dataclass_json
@dataclass
class v0:
v1: List[str] = field(default_factory=list)
def v2(self, v3: List[str]) -> v0:
self.LoadtypesForPostprocessing = v3
return self
v4: Optional[str] = ''
def v5(self, v6: str) -> v0:
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int):
v2 = list()
v3 = self.show_question.find().sort('_id', -1).limit(10).skip(v1)
for v4 in v3:
del v4['_id']
v2.append(v4)
re... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: int) -> bool:
try:
v2 = input('Would you like to proceed with iteration {}? [y/N]'.format(v1))
if v2 != 'y':
return False
els... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, List[str], Union[hlapi.CommunityData, hlapi.UsmUserData], str, int, int, hlapi.SnmpEngine, hlapi.ContextData
Output Type: List[Dict[str, str]]
Dependencies:
```python
def v0(v1: Any) -> Any:
try:
return int(v1)
except (ValueError,... |
Imports:
```python
import re
import typing
```
Type definitions:
Input Types: str, str, str, Optional[int]
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: str, v3: str, v4: Optional[int]=None) -> bool:
v5 = False
v6 = self.get_line_info_from_file(fn=v1)
v7 =... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str) -> None:
for v2 in self.data:
if v2['variable_name'].lower() == v1.lower():
self.accumulator += int(v2['value'])
``` |
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 < len(self._categories) and v1 > -1:
self._categories.remove(self._categories[v1])
``` |
Imports:
```python
import typing
```
Type definitions:
```python
@dataclasses.dataclass(frozen=True)
class v0:
v1: typing.Dict['Category', int]
v2: typing.Dict['Category', int]
v3: typing.Dict['Categorization', typing.Set['Category']]
v4: str = ''
v5: typing.Optional[int] = None
v6: typing.Optio... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Optional[str], Literal['sequence', 'frame']
Output Type: Optional[str]
Dependencies:
```python
def v0(v1: str):
if v1 not in ['sequence', 'frame']:
raise ValueError(f"kind has to be either 'sequence' or 'frame': {v1}")
```
```python
def v2... |
Imports:
```python
import torch
import torch.nn as nn
import typing
```
Type definitions:
Input Types: torch.Tensor
Output Type: torch.Tensor
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: torch.Tensor) -> torch.Tensor:
v2 = self.pooling(v1.rename(None))
v2.names = ('B', 'N', 'E')
v2... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any, Any
Output Type: Dict[str, Any]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1, v2, **v3) -> Dict[str, Any]:
v4 = {}
if self._serializer:
v4 = self._serializer(self, v1, v2, **v3)
elif self._serializer_cl... |
Imports:
```python
from string import ascii_letters
import typing
```
Type definitions:
Input Types: List[str]
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: List[str]) -> str:
v2: dict = {idx: letter for (v3, v4) in enumerate(ascii_letters, start=1)}
if v1[0].islower():
... |
Imports:
```python
import os
import typing
```
Type definitions:
Input Types: str
Output Type: str
Dependencies:
```python
def v0(v1: str) -> str:
return os.path.abspath(os.path.join('..', v1))
```
Function Name: v2
Function:
```python
def v2(v3: str) -> str:
v4 = v0('sens_maps')
v3 = v3.replace('-', '_').... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any, bool, bool
Output Type: List[pygsheets.Cell]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1, v2: bool=True, v3: bool=True) -> List[pygsheets.Cell]:
v4 = []
for v5 in self.list_ws():
v4 += v5.find(v1, matchCas... |
Imports:
```python
import typing
```
Type definitions:
Input Types: list[list[int]]
Output Type: list[tuple[int, int]]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: list[list[int]]) -> list[tuple[int, int]]:
v2 = []
for v3 in v1:
v2 += zip(v3, v3[1:] + v3[:1])
return v2
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0(v1) -> int:
v2 = v1.find_all('span', class_='macro-value')
if len(v2) != 0:
return int(v2[0].get_text())
else:
return int(v1.get_text())
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: int, Any
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int, v2={}) -> int:
if v1 == 1 or v1 == 2:
return v1
if v1 in v2:
return v2[v1]
else:
v2[v1] = self.climbStairs(v1 - 1,... |
Imports:
```python
from math import isnan
import typing
```
Type definitions:
Input Types:
Output Type: float
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> float:
v1 = self.raw_param.get('spot_max_price', float('nan'))
if isnan(v1):
v1 = -1
if self.agentpool and self.agentpo... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any
Output Type: 'ConverterBase'
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Any) -> 'ConverterBase':
self.data_to_convert = v1
return self
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> str:
v1 = str(self.pos)
if self.length is not None:
v1 += f'/{self.length}'
return v1
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: Dict
Output Type: Any
Dependencies:
```python
def v0(v1):
v2 = v1.get('properties', {})
for v3 in v2:
if 'datetime' in v3:
v4 = v2[v3]
if isinstance(v4, str):
v2[v3] = default_utc(ciso8601.parse_... |
Imports:
```python
import threading
import typing
```
Type definitions:
Input Types: list, Queue
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: list, v2: Queue) -> None:
print('Creating data and putting it on the queue')
for v3 in v1:
v4 = threading.Event()
v2... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int) -> int:
v2 = v1 - 1
if v2 == 0:
v2 = self.datalen
while v2 in self.picked:
v2 -= 1
if v2 == 0:
v2 = self.da... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int
Output Type: float
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int=0) -> float:
if v1 < 0:
raise ValueError(f'tax_exemption_amount should be a positive number, but received {v1} instead.')
v2 = 0.05
if... |
Imports:
```python
from itertools import chain, combinations, product
import numpy as np
from scipy.cluster.hierarchy import fcluster, linkage
from scipy.spatial.distance import squareform
import typing
```
Type definitions:
Input Types: Structure, Any
Output Type: int
Dependencies:
Function Name: v0
Function:
```pyt... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: 'GenerationInfoByTarget'
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str) -> 'GenerationInfoByTarget':
if v1 not in self._info.keys():
raise RuntimeError('Could not find target in GenerationInfoBy... |
Imports:
```python
import torch
from torch import Tensor
import typing
```
Type definitions:
Input Types: Dict[str, Tensor], str
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Dict[str, Tensor], v2: str) -> None:
v3 = 0
v4 = self.param_names(0, v2, no_suffix=True)['weig... |
Imports:
```python
import os
import shutil
import re
import typing
```
Type definitions:
Input Types: Any, str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1, v2: str):
for (v3, v4) in v1:
try:
v5 = re.sub('\\W+', '', v4)
except Exception:
pr... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int
Output Type: bytes
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int) -> bytes:
self.cursor += v1
return self.stream[self.cursor - v1:self.cursor]
``` |
Imports:
```python
import re
import requests
import typing
```
Type definitions:
Input Types: str, str
Output Type: (str, requests.session)
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str, v2: str) -> (str, requests.session):
v3 = {'user-agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleW... |
Imports:
```python
import sys
import os
import typing
```
Type definitions:
Input Types:
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> str:
if sys.platform.startswith('linux'):
return os.path.join('/etc', self.config_directory_name)
else:
raise self._not... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str) -> str:
v2 = {}
for v3 in v1:
if v3 not in v2:
v2[v3] = 1
else:
v2[v3] += 1
print(v2)
v4 = ''
while l... |
Imports:
```python
import torch
import typing
```
Type definitions:
Input Types: torch.Tensor, Union[torch.Tensor, _k2.RaggedInt]
Output Type: Union[torch.Tensor, _k2.RaggedInt]
Dependencies:
```python
def v0(v1: torch.Tensor, v2: torch.Tensor) -> torch.Tensor:
v3 = _IndexSelectFunction.apply(v1, v2)
return v3... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int, int
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: int, v2: int) -> int:
assert v1 >= 0
assert v2 >= 0
v3: int = (v1 + v2) * (v1 + v2 + 1) // 2 + v2
return v3
``` |
Imports:
```python
import tensorflow.python as tf
from tensorflow.contrib import slim
from tensorflow.python import keras
import tensorflow.python.keras.backend as K
from tensorflow.python.keras.layers import *
import typing
```
Type definitions:
Input Types: Any, Any, Any
Output Type: [keras.Model, keras.Model]
Depen... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: np.ndarray
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> np.ndarray:
v1 = self.cache[self.cache_pointer][1]
self.cache_pointer += 1
return v1
``` |
Imports:
```python
import numpy as np
from pandas._libs import algos, hashtable, lib
from pandas._libs.hashtable import unique_label_indices
from pandas._typing import IndexKeyFunc
from pandas.core.dtypes.common import ensure_int64, ensure_platform_int, is_extension_array_dtype
from pandas.core.dtypes.generic import AB... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
super().prepare_for_removal()
self.mc.events.remove_handlers_by_keys(self._control_events)
self._control_events = list()
self.stop()
``` |
Imports:
```python
import warnings
import torch.distributed as dist
import typing
```
Type definitions:
Input Types:
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0() -> int:
if not dist.is_available():
warnings.warn('Torch distributed is not available; returning 0 for global ... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any
Output Type: t.Iterator[int]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1) -> t.Iterator[int]:
with open(v1, 'r') as v2:
v3 = v2.readline()
yield from (int(fish) for v4 in v3.split(','))
``` |
Imports:
```python
import os
import logging
import configparser
import typing
```
Type definitions:
Input Types: argparse.ArgumentParser
Output Type: job_config.JobConfig
Dependencies:
```python
def v0(v1: argparse.ArgumentParser):
logging.info('Reading schema of the BQ table : {}'.format(v1.bq_table))
v2 = bq... |
Imports:
```python
import csv
import typing
```
Type definitions:
Input Types: Any, list
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1, v2: list):
print('Writing to csv...')
with open(v1, 'a', newline='') as v3:
v4 = csv.writer(v3)
for v5 in v2:
v4.... |
Imports:
```python
import tensorflow as tf
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str):
self.interpreter = tf.lite.Interpreter(model_path=v1)
self.interpreter.allocate_tensors()
self.input_details = self.in... |
Imports:
```python
from .io import dump, group_and_sort, load, parse
import typing
```
Type definitions:
Input Types: str, int
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str, v2: int) -> None:
v3 = load(v1, v2).frames
assert len(v3) == 10
assert v3[0].url == 'https://... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: Dict[str, int]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str=None) -> Dict[str, int]:
v2 = dict(zip(self.model_data['genres']['name'], self.model_data['genres']['id']))
if v1 is not None:
v2... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: Union[list, None]
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> Union[list, None]:
if self.mode != 'r':
v1 = "Invalid operation, cannot read from a file opened in 'w' mode."
raise IOError(v1)
... |
Imports:
```python
import typing
```
Type definitions:
```python
v0 = TypeVar('TValue')
```
Input Types: Optional[int]
Output Type: Optional[v0]
Dependencies:
Function Name: v1
Function:
```python
def v1(self, v2: Optional[int]) -> Optional[v0]:
if v2 is None:
return None
return self.entries[v2][1]
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(v1) -> None:
self.output_border.refresh()
pass
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any, Any
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: Any, v2=['True', 'true', 'False', 'false']) -> bool:
if v1 is None:
return False
if isinstance(v1, bool):
return True
if isinstance(... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0() -> int:
v1 = self.example_user('hamlet')
self.login_user(v1)
v2 = self.send_stream_message(v1, 'Scotland', topic_name='editing', content='before edit')
ret... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
for v1 in reversed(self.lines):
if v1:
break
else:
self.lines.pop()
if len(self.lines) == 2:
if self.... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
self.assertSuppressErrors({2: [{'code': '0', 'description': 'Some error'}]}, '\n def foo() -> None:\n # FIXME[]\n ... |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
```python
class v0:
def __init__(self, v1: DimensionalSystem, v2: Iterable[float]):
v3 = np.asarray(v2).astype(float)
assert len(v3) == len(v1)
self.e = v3
self.dimsys = v1
def __repr__(self) -> str:
... |
Imports:
```python
from cgitb import text
import math
import typing
```
Type definitions:
Input Types: str, tuple, int
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: tuple, v3: int) -> int:
v4 = len(v1)
if v3 < 0:
v3 = v3 * -1
v5 = math.ceil(v3 / mat... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: list
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str) -> list:
v2 = self.get_type_list('object_types')
v3 = [t for v4 in v2 if v1.startswith(v4 + '_')]
return v3
``` |
Imports:
```python
import typing
```
Type definitions:
```python
class v0:
def __init__(self, v1: int):
self._id = int(v1)
self._enabled = True
self._words: List[WordPattern] = []
def v2(self, v3: Union[int, v0]):
if isinstance(v3, v0):
return self._id == v3._id
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: py.path.local
Output Type: None
Dependencies:
```python
def v0(v1: OTBNSim) -> ExecutionStats:
v1.run(verbose=False, collect_stats=True)
assert v1.state.ext_regs.read('ERR_BITS', False) == 0
assert v1.stats
return v1.stats
```
```pytho... |
Imports:
```python
import numpy as np
from numpy import ndarray
import typing
```
Type definitions:
Input Types: ndarray, ndarray, ndarray, ndarray, ndarray, ndarray, ndarray, float
Output Type: Tuple[ndarray, ndarray]
Dependencies:
```python
def v0(v1: ndarray, v2: ndarray, v3: ndarray, v4: ndarray, v5: ndarray, v6: ... |
Imports:
```python
import typing
```
Type definitions:
Input Types: List[List[int]]
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: List[List[int]]) -> None:
v2 = len(v1)
v3 = v2 // 2
for v4 in range(v3):
self.helper(v1, v4)
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: Path, Namespace
Output Type: Path
Dependencies:
```python
def v0(v1: Path) -> Path:
v2 = 1
v3 = v1.with_stem(f'{v1.stem}^{v2}')
while v3.is_dir():
v2 += 1
v3 = v1.with_stem(f'{v1.stem}^{v2}')
return v3
```
Function Name... |
Imports:
```python
import torch
import torch.fx
import torch.fx.experimental.fx_acc.acc_ops as acc_ops
import typing
```
Type definitions:
Input Types: torch.fx.GraphModule
Output Type: Any
Dependencies:
```python
def v0(v1: torch.fx.Node):
v2 = len(v1.meta['tensor_meta'].shape)
v3 = list((i % v2 for v4 in v1.... |
Imports:
```python
import json
import typing
```
Type definitions:
Input Types:
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> Any:
assert self.schema_content != '', 'Schema content must not be empty'
return json.loads(self.schema_content)
``` |
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