text stringlengths 190 325k |
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Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: float, int, float
Output Type: Tuple[np.ndarray, np.ndarray, np.ndarray]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: float, v2: int=14, v3: float=0.95) -> Tuple[np.ndarray, np.ndarray, np.ndarray]:
if s... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, Dict, Optional[Dict]
Output Type: Dict[str, Dict]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: Dict, v3: Optional[Dict]=None) -> Dict[str, Dict]:
try:
v4: Dict = self._create_app_type(**v2)
except... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: Iterable['LabelNode']
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> Iterable['LabelNode']:
yield self
for v1 in self.children:
yield from v1.flat_iter()
``` |
Imports:
```python
import numpy as np
import pandas as pd
import typing
```
Type definitions:
Input Types: Union[str, Path], type, bool
Output Type: np.ndarray
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: Union[str, Path], v2: type=np.float32, v3: bool=True) -> np.ndarray:
if v3:
return ... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, str
Output Type: Iterable[Path]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: str) -> Iterable[Path]:
v3 = self.FS_OUTPUT_PATTERN.format(main_dir=v1, output_id=v2)
return self.destination.rglob(v3)
``` |
Imports:
```python
import re
import typing
```
Type definitions:
Input Types: pathlib.Path
Output Type: Dict[str, List[str]]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: pathlib.Path) -> Dict[str, List[str]]:
v2 = False
v3 = False
v4 = {}
v5: List[str] = []
with open(v1, 'r', enc... |
Imports:
```python
import typing
```
Type definitions:
Input Types: np.ndarray, np.ndarray, int
Output Type: None
Dependencies:
```python
def v0(v1: int, v2: int, v3: int) -> Tuple[slice, Union[slice, None]]:
assert 0 < v2 <= v1, f'Must be: 0 < data_len {v2} <= buff_len {v1}'
v4 = v3 % v1
v5 = (v3 + v2) % ... |
Imports:
```python
import typing
```
Type definitions:
Input Types: List, Any
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: List, v2):
v3 = self.top
v4 = 0
v5 = len(self.rows)
v6 = len(self.columns)
for (v7, v8) in enumerate(self.rows):
v9 = self.lef... |
Imports:
```python
import torch
import typing
```
Type definitions:
Input Types:
Output Type: Iterator[Tuple[torch.Tensor, ...]]
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> Iterator[Tuple[torch.Tensor, ...]]:
v1 = torch.stack(self.obs, 1)
v2 = torch.stack(self.act, 1)
v3 = torch.s... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any, str, str, str
Output Type: Any
Dependencies:
```python
def v0(v1, v2):
if colored:
return colored(v1, v2)
else:
return v1
```
```python
def v3(v4: str, v5: list, v6: bool=False):
v7 = [str(val).upper() for v8 in v5]
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, Callable, Optional[Any], bool
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: Callable, v3: Optional[Any]=None, v4: bool=True):
if v4:
v5 = self._transform_functions
self._transf... |
Imports:
```python
import tensorflow.compat.v1 as tf
import typing
```
Type definitions:
Input Types: tf.Tensor, int, Any, Optional[Text]
Output Type: tf.Tensor
Dependencies:
```python
def v0(v1, v2, v3=None):
if v3 is None:
v3 = v1.name
v4 = {}
if isinstance(v2, int):
v4[v2] = True
els... |
Imports:
```python
import sys
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str='No reason given'):
print(f'Error: {v1}!', file=sys.stderr)
sys.exit(1)
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: Dict[str, Any]
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: Dict[str, Any]) -> str:
v2 = len(v1['early_morning'])
v3 = len(v1['morning'])
v4 = len(v1['afternoon'])
v5 = len(v1['night'])
v6 = len(... |
Imports:
```python
import tensorflow as tf
import typing
```
Type definitions:
```python
v0 = NamedTuple('RNNSpec', [('size', int), ('direction', str), ('cell_type', str)])
```
Input Types: tf.Tensor, tf.Tensor, v0
Output Type: Tuple[tf.Tensor, tf.Tensor]
Dependencies:
```python
def v1(v2: v0) -> Callable[[], tf.nn.rnn... |
Imports:
```python
import re
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 = 0
if v1 == 'char':
v3 = 1
elif v1 == 'short':
v3 = 2
elif v1 == 'int':
v3 = 4
eli... |
Imports:
```python
import os
import typing
```
Type definitions:
Input Types: str, dict, Any, Any
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str, v2: dict, v3, v4):
v5 = ['skewer', '-r', str(v2['max_error_rate']), '-d', str(v2['max_indel_rate']), '-m', str(v2['mode']), '-l', s... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: Dict
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> Dict:
v1 = {'summary': self.title, 'start': self.formatted_begin_time, 'end': self.formatted_end_time, 'reminders': {'useDefault': True}}
if self.location:... |
Imports:
```python
import torch
import typing
```
Type definitions:
Input Types: torch.Tensor, Tuple[int, ...], Optional[bool]
Output Type: torch.Tensor
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: torch.Tensor, v2: Tuple[int, ...], v3: Optional[bool]=None) -> torch.Tensor:
v4 = torch.reshape(v1... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str, v2: str='utf-8'):
with open(v1, 'r', encoding=v2) as v3:
for v4 in v3:
yield v4.strip()
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: int, int, int
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int, v2: int, v3: int) -> int:
if v1 <= v3:
return v1
while v1 > v3:
v1 -= 1
if v2 != self.srcCharCode[v1]:
... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> bool:
if self.driver.get_cookie('uid') is None:
return False
else:
return True
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> int:
for v1 in range(len(self.queue) - 1):
v2 = self.queue.popleft()
self.queue.append(v2)
self.rear = v2 if len(self.queue) > 1 else None
... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
self.__begin_task_id.clear()
self.__over_task_id.clear()
``` |
Imports:
```python
import re
import typing
```
Type definitions:
Input Types: str, list
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str, v2: list) -> str:
v3 = re.compile('\\b(' + '|'.join(v2) + ')\\b\\s*', re.IGNORECASE)
return v3.sub('', v1)
``` |
Imports:
```python
import torch
import torch.nn as nn
import torch.nn.functional as F
import typing
```
Type definitions:
Input Types: dict
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: dict, **v2):
v3 = {}
v4 = v1[f'input/s_onehot']
v5 = v1[f'input/onehot.*'][..., ... |
Imports:
```python
import re
import typing
```
Type definitions:
```python
class v0:
def __init__(self, v1='\n', v2=' ', v3=True, v4=None, v5=[], v6=[], v7='', v8=True):
self.sep = v1
self.add = v2
self.printFirst = v3
self.callSource = v4
self.definedVars = v5
se... |
Imports:
```python
import typing
```
Type definitions:
Input Types: np.ndarray
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: np.ndarray):
v2 = self.pose2d_estimator.run_single_image(v1)
return v2
``` |
Imports:
```python
import csv
import json
import typing
```
Type definitions:
Input Types: List[Dict], IO, List[str], bool, Any
Output Type: Any
Dependencies:
```python
def v0(v1: Any) -> Any:
if v1 is None:
return ''
if isinstance(v1, list) or isinstance(v1, dict):
return json.dumps(v1, cls=Dc... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> str:
v1 = format(self.elem, '02X')
if len(v1) % 2:
v1 = '0' + v1
return v1
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: list[list[int]]
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: list[list[int]]) -> int:
v2 = len(v1)
v3 = len(v1[0])
v4 = float('inf')
for v5 in range(v2):
for v6 in range(v3):
... |
Imports:
```python
import typing
```
Type definitions:
```python
class v0(Generic[T]):
v1: int = -1
def __init__(self, v2: List[T]=None):
self._path: List[T] = []
self._elements_in_path: Dict[T, int] = {}
self._index_of_cyclic_root: int = self._ACYCLIC_INDEX
self._hash = None
... |
Imports:
```python
import logging
import typing
```
Type definitions:
Input Types:
Output Type: Optional[str]
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> Optional[str]:
v1 = {}
for v2 in self._GetNetworkDevices():
v3 = self._GetNetworkDeviceProperties(v2)
v1[v2] = v3
... |
Imports:
```python
from typing import cast, Iterable
import typing
```
Type definitions:
Input Types: Any
Output Type: Iterable
Dependencies:
```python
def v0(v1, v2, v3, v4):
if v3:
if v4:
for v5 in v3:
if isinstance(v5, tuple) and isinstance(v5[0], OutputTag):
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any, Any, Any
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(v1, v2, v3='\r\n') -> bool:
v4 = v2.split('\n')
v5 = v1[:-1].split('\n')
while len(v5) < len(v4):
v5.append('')
while len(v4) < len(v5)... |
Imports:
```python
import typing
```
Type definitions:
Input Types: torch.Tensor, Optional[torch.Tensor]
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: torch.Tensor, *, v2: Optional[torch.Tensor]=None) -> None:
for v3 in self._losses_with_target():
v3.set_target_ima... |
Imports:
```python
import numpy as np
from sklearn.metrics import roc_auc_score
import typing
```
Type definitions:
Input Types: int
Output Type: Any
Dependencies:
```python
def v0(v1: torch.Tensor):
return v1.detach().cpu().numpy()
```
Function Name: v2
Function:
```python
def v2(self, v3: int):
def v4(v5: t... |
Imports:
```python
import torch
import typing
```
Type definitions:
Input Types: bool
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: bool, *v2):
if v1:
return torch.cuda.FloatTensor(*v2)
else:
return torch.FloatTensor(*v2)
``` |
Imports:
```python
import os
import typing
```
Type definitions:
Input Types: str, str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: str=None):
self._local = v1
if os.path.isfile(v1):
self._local_files = [v1]
elif os.path.isdir(v1):
if v2:
... |
Imports:
```python
import typing
```
Type definitions:
```python
class v0:
def __init__(self, v1=0, v2=None):
self.val = v1
self.next = v2
```
Input Types: v0
Output Type: int
Dependencies:
Function Name: v3
Function:
```python
def v3(self, v4: v0) -> int:
v5 = v4.val
while v4.next:
... |
Imports:
```python
import os
import os.path
import shutil
import stat
import typing
```
Type definitions:
Input Types: str, str
Output Type: None
Dependencies:
```python
def v0(v1: str) -> bool:
return stat.S_ISSOCK(os.lstat(v1).st_mode)
```
Function Name: v2
Function:
```python
def v2(v3: str, v4: str) -> None:
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str) -> None:
self.__unregister_vision_listener(v1)
if not self.__vision_listeners:
self.stop_looking()
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: List[int]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str) -> List[int]:
v2: List[int] = [self.characters.find(c) for v3 in v1]
return v2
``` |
Imports:
```python
import torch
import typing
```
Type definitions:
Input Types: Iterable[torch.Tensor]
Output Type: torch.Tensor
Dependencies:
```python
def v0(v1: torch.Tensor, v2: Optional[int]) -> int:
if v2 is None:
v2 = v1.get_device() if v1.is_cuda else -1
else:
v3 = False
if v1.... |
Imports:
```python
import typing
```
Type definitions:
Input Types: T.Set[str]
Output Type: T.Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: T.Set[str]=None) -> T.Any:
if v1 is not None:
v1.update(self.markers)
return self.result
``` |
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 = v1.split(' ')
for v3 in v2:
self.perform_move(v3)
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, List[Dict[str, Any]], List[Dict[str, Any]]
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str, v2: List[Dict[str, Any]], v3: List[Dict[str, Any]]) -> bool:
v4 = ''.join(('O' if item_in == item_out else 'X' f... |
Imports:
```python
import typing
```
Type definitions:
```python
v0 = NewType('Weights01Array', np.ndarray)
```
```python
v1 = NewType('Weights12Array', np.ndarray)
```
Input Types: v0, v1
Output Type: None
Dependencies:
Function Name: v2
Function:
```python
def v2(self, v3: v0, v4: v1) -> None:
self.weights_01 -=... |
Imports:
```python
import typing
```
Type definitions:
```python
class v0:
def __init__(self, v1):
self.val = v1
self.left = None
self.right = None
```
Input Types: v0, float
Output Type: int
Dependencies:
Function Name: v2
Function:
```python
def v2(self, v3: v0, v4: float) -> int:
v5... |
Imports:
```python
import typing
```
Type definitions:
```python
v0 = namedtuple('EbookStatus', ['available', 'owned', 'always_available', 'copies_available', 'copies_owned', 'for_removal'])
```
Input Types: v0
Output Type: bool
Dependencies:
Function Name: v1
Function:
```python
def v1(v2: v0) -> bool:
if v2.alwa... |
Imports:
```python
import typing
```
Type definitions:
Input Types: list, int
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: list, v2: int) -> None:
try:
v1 = list(v1)
except:
raise ValueError('Parameter 1, invalid file type. Value should be list')
try:
... |
Imports:
```python
import os
import typing
```
Type definitions:
Input Types: ('a base filename', 'positional', None, str)
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: ('a base filename', 'positional', None, str)):
if v1 != os.path.basename(v1):
raise ValueError('Use onl... |
Imports:
```python
from math import log10
import typing
```
Type definitions:
Input Types: int, int
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int, v2: int):
v3 = self.unigram_cnts.get(v1, 0.0)
v4 = self.unigram_cnts.get(v2, 0.0)
v5 = self.bigram_cnts.get((v1, v2... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: int):
v2 = 1
v3 = 1
if v1 == 1:
print('0')
elif v1 == 2:
print('0', '1')
else:
print('0')
print(v2)
print(... |
Imports:
```python
from itertools import cycle, islice
import typing
```
Type definitions:
Input Types: Optional[Dict]
Output Type: Any
Dependencies:
```python
def v0(v1: Iterator, v2: int):
for v3 in range(v2):
try:
next(v1)
except StopIteration:
raise RuntimeError('Trying ... |
Imports:
```python
import typing
```
Type definitions:
Input Types: list
Output Type: set
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: list) -> set:
v2 = set()
for v3 in v1:
v4 = self._items.get(v3.mac)
if v4 is not None:
v4.update(event=v3)
v2.a... |
Imports:
```python
import typing
```
Type definitions:
Input Types: ArgumentParser
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: ArgumentParser):
super().configure(v1)
v1.add_argument('-i', '--include', metavar='PATTERN', action='append', type=str, required=True, help='... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, int, Optional[str]
Output Type: Optional[str]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str, v2: int=1024, v3: Optional[str]='py') -> Optional[str]:
v2 -= 8 + len(v3 or '')
if not v1:
return 'N/A'
if len(... |
Imports:
```python
import typing
```
Type definitions:
Input Types: list, list, list
Output Type: list
Dependencies:
```python
def v0(v1: list):
v2 = []
for v3 in v1:
v2 += [ItemRecord.from_db_row(db_row=v3)]
return v2
```
Function Name: v4
Function:
```python
def v4(self, v5: list, v6: list, v7: l... |
Imports:
```python
import typing
```
Type definitions:
```python
class v0:
def __init__(self, v1: str, v2: str):
self.name = os.path.splitext(os.path.basename(v2))[0].split('[')[0].strip()
self.path = v2
self.size = os.path.getsize(v2)
def v3(self) -> str:
return self.name + ' ... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
v1 = self.headers.get('accept-encoding')
if v1:
self.headers['accept-encoding'] = ', '.join((e for v2 in {'gzip', 'identity', 'deflate', 'br'... |
Imports:
```python
import logging
import numpy as np
import typing
```
Type definitions:
Input Types: Any
Output Type: float
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1) -> float:
v2 = np.average([self.camera_matrix[0, 0], self.camera_matrix[1, 1]])
v3 = 19.939
v4 = v2 * v3 / v1
... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
v1: Dict[str, Any] = {'pid': self.pid, 'simids': [self.simid]}
self.client._delete('simulations', v1)
``` |
Imports:
```python
import typing
```
Type definitions:
```python
class v0:
def __init__(self, v1: str, v2: int, v3=None, v4=None):
self.key = v1
self.idx_loc = v2
self.prev = v3
self.next = v4
```
Input Types: v0
Output Type: Any
Dependencies:
Function Name: v5
Function:
```python
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: dict, str
Output Type: Any
Dependencies:
```python
def v0(v1: str):
v2 = MongoClient(f'mongodb+srv://{DB_USERNAME}:{DB_PASSWORD}@cluster0-6gkyq.mongodb.net/test?retryWrites=true&w=majority&ssl_cert_reqs=CERT_NONE')
v3 = v2[DB_NAME]
v4 = v3... |
Imports:
```python
import pandas
import typing
```
Type definitions:
Input Types: pandas.DataFrame, []
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: pandas.DataFrame, v2: []):
v3 = v1['cluster_label'].unique().tolist()
v4 = pandas.DataFrame([])
for v5 in v3:
v6 = ... |
Imports:
```python
import typing
```
Type definitions:
```python
@dataclass
class v0(Event):
v1: str
v2: Position
v3: ast.AST
```
Input Types: str
Output Type: Optional[List[v0]]
Dependencies:
Function Name: v4
Function:
```python
def v4(self, v5: str) -> Optional[List[v0]]:
v6 = self.namespace
whi... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str) -> bool:
if v1 is None:
return False
v2 = self.__root
for v3 in v1:
if not v2.has_child(v3):
return False
... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: list
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> list:
v1 = self.http_get(self.chapter)
v2 = self.document_fromstring(v1)
return self._images_helper(v2, '.chapter-img', 'data-original', 'src')
``` |
Imports:
```python
import json
import typing
```
Type definitions:
Input Types:
Output Type: bytes
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> bytes:
v1 = {'state': str(self.state.value), 'worker': self.worker}
return json.dumps(v1).encode('utf8')
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: list
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: list):
v2 = list()
for v3 in v1:
if v3.marker:
v2.append(v3.marker)
else:
v2.append(v3.channel)
return v2
``` |
Imports:
```python
import socket
import ssl
import sys
import typing
```
Type definitions:
Input Types: Any, Any, Any, callable, Any
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1, v2, v3, v4: callable, v5=60):
self._hostname = v1
self._port = v2
self._token = v3
... |
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.dataframes[v1]
v3 = v2.shape[0]
v2.loc[v3 - 1, 'forward_af'] = 1.0
for v4 in range(v3 - 1):
v2.loc[v3 - 2 - v4, 'forward... |
Imports:
```python
import re
import typing
```
Type definitions:
Input Types: list
Output Type: list
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: list) -> list:
v2 = [x.lower() for v3 in v1]
v2 = [v3.replace('\\n', ' ') for v3 in v2]
v2 = [v3.replace('\\t', ' ') for v3 in v2]
v2 = [v... |
Imports:
```python
import os
import typing
```
Type definitions:
Input Types: Any, bool, Optional[str]
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1, v2: bool=False, v3: Optional[str]=None):
if v2:
v1.show()
if v3 is not None:
if not os.path.exists(f'{sel... |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: np.ndarray
Output Type: np.ndarray
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: np.ndarray) -> np.ndarray:
(v2, v3, v4) = np.sin(v1)
(v5, v6, v7) = np.cos(v1)
return np.array([[v7 * v6, v7 * v3 * v2 - ... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
v1 = self.get_body('message_info_missing_channel_name')
v2 = self.build_webhook_url()
v3 = self.client_post(v2, v1, content_type='application/x-w... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> bool:
if not self._device_info:
v1 = None
else:
v1 = self._device_info.get('model')
if v1 in {'temp_deck_v1', 'temp_deck_v1.1', 'temp_d... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str) -> str:
print('fastbpe', v1)
return self.bpe.apply([v1])[0]
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: int, int
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int, v2: int):
(v3, v4) = self.cells[v1][v2]
if v4:
return
self.cells[v1][v2][1] = True
if bool(v3):
if self.isComplete():
... |
Imports:
```python
import re
from urllib.parse import urlparse, unquote
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
```python
def v0(v1: str):
v2 = set_of_html_img_file_paths_from(v1)
v3 = set_of_html_href_file_paths_from(v1)
return v2 | v3
```
```python
def v4(v5):
... |
Imports:
```python
import numbers
import typing
```
Type definitions:
Input Types:
Output Type: dict
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> dict:
v1 = {'id': self.id}
v2 = self.all_results()
for (v3, v4) in v2.items():
if not isinstance(v4, numbers.Number):
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: fmf.Tree, str
Output Type: Optional[fmf.Tree]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: fmf.Tree, v2: str) -> Optional[fmf.Tree]:
while v1.parent:
if v1.get(v2) != v1.parent.get(v2):
break
v1 = v1.... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: 'ScalaTypeInfo'
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str) -> 'ScalaTypeInfo':
if v1 is None:
return self
if self.template_type is None:
self.template_type = [v1]
else:
... |
Imports:
```python
import typing
```
Type definitions:
```python
class v0:
def __init__(self, v1: str, v2: str, v3: str, v4: str, v5: str):
self.ticker = v1
self.ebit = self.parse_float(v2)
self.pl = self.parse_float(v3)
self.roe = self.parse_float(v4)
self.liquidez = self.p... |
Imports:
```python
import numpy as np
from numpy.typing import ArrayLike
from sklearn.metrics import f1_score
import typing
```
Type definitions:
Input Types: ArrayLike, ArrayLike, float
Output Type: Tuple[Union[str, float]]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: ArrayLike, v2: ArrayLike, v3: ... |
Imports:
```python
import torch
import typing
```
Type definitions:
```python
class v0(NamedTuple):
v1: List[int]
v2: torch.Tensor
v3: List[List[torch.Tensor]]
v4: float
v5: List[int]
v6: int
v7: str
```
Input Types: torch.Tensor, List[v0], torch.device
Output Type: torch.Tensor
Dependencies... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, int, int, int
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str, v2: int, v3: int, v4: int=4) -> bool:
if v4 is None:
v5 = True
else:
v5 = len(v1) == v4
return v5 and v1.isdigit() an... |
Imports:
```python
import numpy as np
from pandas._config import get_option
from pandas._typing import Axis, FilePathOrBuffer, FrameOrSeries, IndexLabel, Scalar
from pandas.compat._optional import import_optional_dependency
from pandas.util._decorators import doc
import pandas as pd
from pandas import IndexSlice, Range... |
Imports:
```python
import random
import typing
```
Type definitions:
Input Types: int, Any, igraph.Graph, int
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: int, v2, v3: igraph.Graph, v4: int):
v5 = v2([None] * v4)
v5.i_type = v1
v5.n_repro = 0
for v6 in range(v4):
... |
Imports:
```python
from pathlib import Path
import typing
```
Type definitions:
Input Types: str, int
Output Type: Any
Dependencies:
```python
def v0(v1: str, v2: int=2):
v3 = 0
with open(v1) as v4:
v5 = v4.readlines()
for v6 in v5:
if '** BUILD SUCCEEDED **' in v6:
v3 += 1
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int, int, str, bool, bool
Output Type: dict
Dependencies:
```python
def v0(v1: bool=False) -> int:
if v1:
v2 = 1
else:
v2 = 0
return v2
```
```python
def v3(v4: str=None, v5: dict[str, dict]=None, v6: str=None, v7: bool=Tru... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
v1 = self.callmakervisitor.keywords
self.print()
with self.indent():
if not v1:
self.print('@Override')
self.prin... |
Imports:
```python
import copy
import typing
```
Type definitions:
Input Types: Any, bool
Output Type: 'Volumes'
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1, v2: bool=False) -> 'Volumes':
if not v2 and self.device == v1:
return self
v3 = self.clone()
if self.device != v1:
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Image.Image, Image.Image
Output Type: Tuple[float, int]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Image.Image, v2: Image.Image) -> Tuple[float, int]:
(v3, v4) = (self.x, self.y)
(v5, v6) = v1.size
(v7, v8) = v2.... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, int, bool
Output Type: 'NeuralNetwork'
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: int=1, v3: bool=True) -> 'NeuralNetwork':
if v3:
self.train_set = self.train_set.drop(v1, v2)
self.test_set ... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int
Output Type: List[int]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int) -> List[int]:
if v1 == 0:
return [1]
elif v1 == 1:
return [1, 1]
else:
v2 = self.getRow(v1 - 1)
v3 = len(... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, **v1) -> None:
self._sorting_info = v1['SortingInfo']
v2 = ('SortingInfo',)
v3 = v1.copy()
for v4 in v2:
del v3[v4]
super()._init(**v3)
``... |
Imports:
```python
import pickle as binlib
import typing
```
Type definitions:
Input Types: str
Output Type: Dict
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str) -> Dict:
with open('maps/' + v1 + '.bin', 'rb') as v2:
return binlib.load(v2)
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1) -> bool:
if v1 in ['keystore', 'ps_keystore']:
return False
v2 = ['x%d/' % i for v3 in range(1, 16)]
if v1 in v2:
return False
... |
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