text stringlengths 190 325k |
|---|
Imports:
```python
import typing
```
Type definitions:
Input Types: float, float, float
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: float, v2: float, v3: float):
self.assertLess(v2, v3, 'Test Configuration issue')
self.assertGreater(v1, v2)
self.assertLess(v1, v3)... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
self.__check_fastqc()
self.__check_trim_galore()
self.__check_kallisto()
``` |
Imports:
```python
import torch
from torch import optim
from torch.optim.optimizer import Optimizer
import typing
```
Type definitions:
Input Types:
Output Type: Optimizer
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> Optimizer:
v1 = self.args
v2 = optim.Adamax(self.model.parameters(), ... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, str
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: str) -> bool:
try:
self.find_category_from_names(v1, v2)
return True
except ValueError:
return False
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
if self._finalizer:
self._finalizer()
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: int
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: int):
v2 = '{{"id": "some-id", "count": {count}}}'
return v2.format(count=v1).encode()
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
self.set_models({'meeting/1': {'motion_poll_default_group_ids': [1], 'is_active_in_organization_id': 1}, 'group/1': {'used_as_motion_poll_default_id': 1}... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
self.coins_list = [200, 100, 50, 20, 10, 5, 2, 1, 0.5, 0.25, 0.1, 0.05, 0.01]
v1 = self.coins_list
v2 = self._coins_frame
[setattr(self, f'_{... |
Imports:
```python
import os, sys
import typing
```
Type definitions:
Input Types: str
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str) -> str:
if not os.path.exists(v1):
raise FileNotFoundError(f'Could not find {v1}.')
return v1
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any
Output Type: Dict
Dependencies:
Function Name: v0
Function:
```python
def v0(v1) -> Dict:
v2 = {}
for v3 in v1:
if '=' in v3:
(v4, v5) = v3.split('=', 1)
else:
(v4, v5) = (v3, None)
v2[v4] =... |
Imports:
```python
import re
import typing
```
Type definitions:
Input Types: str
Output Type: Dict[str, str]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str) -> Dict[str, str]:
v2 = re.split('\\t|\\s', v1)
v1 = {}
for v3 in v2:
if v3.strip():
v4 = v3.split(':'... |
Imports:
```python
import typing
```
Type definitions:
Input Types: dict
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: dict) -> str:
v2 = v1['Given']
v3 = v1['Given2']
v4 = v1['Maiden']
v5 = v1['Maiden2']
v6 = v1['Surname']
v7 = set()
if v6:
v7.add... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str):
with self.lock:
v2 = self._get_cached_node(v1)
v3 = v2.get_external_ip()
if v3 is None:
v2 = self._get_node(v1)
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Union[str, list]
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Union[str, list]) -> str:
v2 = 0
for v3 in range(13):
v2 += int(v1[v3]) * self.weights_second[v3]
v2 = v2 % 11
if v2 < 2:
... |
Imports:
```python
import subprocess
import typing
```
Type definitions:
Input Types: str
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str=DEFAULT_IMAGE) -> bool:
try:
subprocess.run(['docker', 'image', 'inspect', v1], check=True, stdout=subprocess.DEVNULL, stderr=subpr... |
Imports:
```python
import json
import typing
```
Type definitions:
Input Types: TextIO
Output Type: str
Dependencies:
```python
def v0(v1: str, v2: str='L4') -> str:
try:
v1 = json.dumps(v1)
v1 = {v2: v1}
return json.dumps(v1)
except Exception:
return json.dumps({})
```
```pytho... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> bool:
self._raise_from_pending()
return self._serve_thread.is_alive()
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, List[str], Any
Output Type: Any
Dependencies:
```python
def v0():
client_lock.acquire()
v1 = boto3.client('sqs')
client_lock.release()
return v1
```
```python
def v2(v3: str, v4=None) -> (str, Any):
if v4 is None:
v4 =... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
async def v0(self) -> None:
v1 = self._req
assert v1 is not None
v2 = self._payload_writer
assert v2 is not None
v3 = v1.version
v4 = 'HTTP/{}.{} {} {}'.fo... |
Imports:
```python
import socket
import typing
```
Type definitions:
Input Types: int, str, int, bool
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int=0, v2: str=None, v3: int=5, v4: bool=True) -> bool:
v5 = v2 if v2 else self.host
v6 = v1 if v1 else self.port
try... |
Imports:
```python
import sys
import typing
```
Type definitions:
Input Types: Any
Output Type: list
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1) -> list:
v2 = '/sys/devices/system/node/node%d/cpulist' % v1
try:
with open(v2, 'r') as v3:
v4 = v3.read()
except:
... |
Imports:
```python
import numpy
import typing
```
Type definitions:
Input Types: int, int, Tuple[int]
Output Type: Generator[List[numpy.ndarray], None, None]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: int, v2: int, v3: Tuple[int]) -> Generator[List[numpy.ndarray], None, None]:
v4 = 3
v5 = ... |
Imports:
```python
import cv2
import numpy as np
import typing
```
Type definitions:
Input Types: np.ndarray, np.ndarray, Any, Any
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: np.ndarray, v2: np.ndarray, v3, v4):
(v5, v6) = (v1.shape[0], v1.shape[1])
v7 = np.random.uniform(v... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str) -> int:
v2 = v1.encode('utf16')
v3 = len(v2) // 2
if v2[:2] in [b'\xff\xfe', b'\xff\xff', b'\xfe\xff']:
v3 -= 1
return v3
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: List[Optional[int]]
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: List[Optional[int]]) -> int:
self.remove_invalid(v1)
self.reposition_to_right_index(v1)
return self.find_first_missing(v1)
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: list
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: list):
for v2 in range(len(v1)):
v3 = v2
for v4 in range(v2 + 1, len(v1)):
if v1[v3] > v1[v4]:
v3 = v4
v5 = v... |
Imports:
```python
import typing
```
Type definitions:
Input Types: torch.Tensor
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: torch.Tensor):
v2 = v1.diag().sum() / v1.sum()
return v2.item()
``` |
Imports:
```python
import typing
```
Type definitions:
```python
class v0:
def __init__(self, v1: Todo, v2=None) -> None:
self.todo = v1
self.revision = v2
@cproperty
def v3(self) -> List[str]:
v4 = self.todo['DESCRIPTION']
v5 = re.findall('---\\n\\n(.*?)\\n\\nUpdated:', v4... |
Imports:
```python
import sys
import typing
```
Type definitions:
Input Types:
Output Type: int
Dependencies:
```python
def v0(v1: str, v2: Optional[Any]=None) -> Any:
from .Globals import global_get
return global_get('settings.{}'.format(v1), v2)
```
Function Name: v3
Function:
```python
def v3() -> int:
... |
Imports:
```python
import json
import logging
import typing
```
Type definitions:
```python
class v0:
v1: str
v2: Set['Node']
v3: Set['Node']
v4: NodeType
v5: 'DependencyGraph'
v6: 'Configuration'
v7: Optional[str]
v8: bool
v9: Optional[List[str]]
v10: Optional[List['Node']]
... |
Imports:
```python
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.blocks(v1)
return nn.Softmax(dim=1)(v2)
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, Sequence[str]
Output Type: Optional[str]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: Sequence[str]) -> Optional[str]:
v3 = v1.split()
for v4 in v3:
if v4.upper() in v2:
return v4.titl... |
Imports:
```python
import typing
```
Type definitions:
Input Types: float
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: float=0.1):
print(v1)
self['exact_goal_radius'] = v1
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str) -> str:
self.call_counter_start_execution += 1
self.__get_test_case_by_id(v1)
return str(self.call_counter_start_execution)
``` |
Imports:
```python
from pathlib import Path
import typing
```
Type definitions:
Input Types:
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0() -> str:
v1 = Path('/etc/alpine-release').read_text().split('.')
return f'alpine-{v1[0]}.{v1[1]}'
``` |
Imports:
```python
import pandas as pd
import typing
```
Type definitions:
Input Types: pd.DataFrame
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: pd.DataFrame) -> str:
if v1.empty is True:
return 'There is no prize data for this grade.'
else:
v1['year'] = pd.... |
Imports:
```python
import os
import typing
```
Type definitions:
Input Types:
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0() -> int:
v1 = 10
try:
v2 = int(os.environ.get('GLUU_WAIT_SLEEP_DURATION', v1))
except ValueError:
v2 = v1
return max(1, v2)
``` |
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):
for v3 in v2:
self.submit(v1, v3)
``` |
Imports:
```python
import os
import typing
```
Type definitions:
Input Types: str
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str) -> None:
v2 = f'{os.getcwd()}/{v1}'
os.makedirs(f'{v2}/src/templates')
os.mkdir(f'{v2}/src/static')
os.mkdir(f'{v2}/tests')
``` |
Imports:
```python
import subprocess
import typing
```
Type definitions:
Input Types: int, str, bool
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: int, v2: str, v3: bool):
v4 = ['./scop_modeling.sh', str(v1), v2]
if v3:
v4 = ['qsub', '-g', 'tga-ishidalab', '-N', 'mode... |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: list[int], int
Output Type: tuple[int, ...]
Dependencies:
```python
def v0(v1: int, v2: int) -> tuple[tuple[int, ...], tuple[int, ...]]:
v3 = (v2,) * (v1 // v2)
v4 = (v1 % v2,) if v1 % v2 else ()
return (v3, v4)
```
Func... |
Imports:
```python
import urllib
from io import BytesIO
import typing
```
Type definitions:
Input Types: str, str
Output Type: BytesIO
Dependencies:
```python
def v0(v1: str, v2: str) -> HTTPResponse:
if not validators.url(v1):
raise ValueError("Wrong URI format for 'file_uri' argument. ... |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: List, np.ndarray
Output Type: List[sitk.Euler3DTransform]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: List, v2: np.ndarray) -> List[sitk.Euler3DTransform]:
v3 = v1
v2 = np.insert(v2, 0, 0)
v2 = ... |
Imports:
```python
import datetime
import typing
```
Type definitions:
Input Types: str
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str) -> bool:
if self.filters.time and self._date_last is not None:
return self.accounts[v1].close_date < self._date_last
retur... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str) -> str:
v2 = v1
if v2.startswith('com.sun'):
v2 = v2[13:]
else:
v2 = self._ns_mod + '.' + v2
return v2
``` |
Imports:
```python
import os
import os.path as path
import typing
```
Type definitions:
Input Types: io.TextIOBase, int
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: io.TextIOBase, v2: int=128) -> str:
v3 = 2 * v2
v4 = v1.tell()
v1.seek(0, os.SEEK_END)
v5 = v1.tell()
... |
Imports:
```python
import typing
```
Type definitions:
```python
v0 = namedtuple('Context', 'objects, attributes, relations')
```
Input Types: v0, str
Output Type: Any
Dependencies:
Function Name: v1
Function:
```python
def v1(v2: v0, v3: str):
with open(v3, 'w') as v4:
v4.write('[Lattice]\n')
v4.w... |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
```python
class v0(IndexOpsMixin, PandasObject):
v1: frozenset[str] = PandasObject._hidden_attrs | IndexOpsMixin._hidden_attrs | frozenset(['contains', 'set_value'])
v2 = 1
def v3(self, v4: np.ndarray, v5: np.ndarray) -> np.ndarray:
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, bool
Output Type: Real
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: bool=True) -> Real:
if v2:
v3 = self.load_ann(v1)['fs']
else:
v4 = self._get_tranche(v1)
v3 = self.fs[v4]
re... |
Imports:
```python
import numpy as np
import pandas as pd
import typing
```
Type definitions:
Input Types: List[Tuple[int, int, float]], int, str, str
Output Type: List[Tuple[int, int]]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: List[Tuple[int, int, float]], v2: int, v3: str='linear', v4: str='bot... |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: np.ndarray, np.ndarray
Output Type: np.ndarray
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: np.ndarray, v2: np.ndarray) -> np.ndarray:
v3 = self._config['m']['overlay']
if v3['strategy'] in ['overlay... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Union[pd.DataFrame, ks.DataFrame], Union[pd.Series, ks.Series]
Output Type: Union[pd.DataFrame, ks.DataFrame]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Union[pd.DataFrame, ks.DataFrame], v2: Union[pd.Series, ks.Series]=None... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any
Output Type: List[Any]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1) -> List[Any]:
v2 = [f.changed_methods for v3 in v1.modified_files]
return [item for v4 in v2 for v5 in v4]
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, str, List[Any], asyncpg.exceptions.PostgresError
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str, v2: str, v3: List[Any], v4: asyncpg.exceptions.PostgresError) -> None:
if v3:
v3 = f'\n{v3}'
e... |
Imports:
```python
import typing
```
Type definitions:
Input Types: List[str]
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: List[str]) -> None:
v2 = v1[0][:1]
if v2 in ['(', '[', '{']:
v1[0] = ' ' + v1[0][1:]
v1[:] = [v2] + v1
v3 = v1[-1][-1:]
if v3 i... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str):
v1 = f'\n{v1}\n'
self.welcome_msg = v1
print(f'Welcome message :')
print(v1)
print()
``` |
Imports:
```python
import torch
from torch.autograd import Variable, Function
import typing
```
Type definitions:
Input Types: torch.Tensor, Any
Output Type: torch.Tensor
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: torch.Tensor, v2=None) -> torch.Tensor:
v1 = v1.long().view(-1, 1)
v2 = v2 i... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any, bool
Output Type: Any
Dependencies:
```python
def v0(v1):
v2 = [0 for v3 in range(1440)]
for v4 in range(len(v1)):
v5 = int(v1.at[v4, 'Charge_start'])
v6 = int(v1.at[v4, 'Charge_end'])
if var_power:
v7 ... |
Imports:
```python
import json
import typing
```
Type definitions:
Input Types: Any, str, str, str
Output Type: Any
Dependencies:
```python
@retry(stop=stop_after_attempt(5), retry=retry_if_exception_type(TryAgain), wait=wait_exponential(multiplier=1, min=2, max=5))
def v0(v1: Any, v2: Any, v3: bool=False, **v4):
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, int
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: int) -> None:
self.job_id = v1
self.committed = v2
``` |
Imports:
```python
import logging
import torch
from torch.nn.utils.rnn import pad_sequence
from tqdm import trange
import typing
```
Type definitions:
```python
v0 = torch.Tensor
```
Input Types: List[Tuple[v0, v0]], int, int
Output Type: List[Tuple[Tuple[v0, v0], Tuple[v0, v0]]]
Dependencies:
```python
def v1() -> Non... |
Imports:
```python
from logging import Logger, getLogger
import typing
```
Type definitions:
Input Types: str, Optional[Logger]
Output Type: Optional[Any]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: Optional[Logger]=None) -> Optional[Any]:
v2 = v2 if v2 is not None else getLogger... |
Imports:
```python
import typing
```
Type definitions:
```python
class v0(Node):
def __init__(self, v1: str, v2: int, v3: str, v4: int, v5: int, v6: bool, v7: str='disabled', v8: str='disabled', v9: typing.SupportsFloat=0):
super(v0, self).__init__()
self.shutdown_task = None
self.data_file... |
Imports:
```python
import numpy as np
import torch
import torch.distributions as D
from torch.utils.data import DataLoader, TensorDataset
import typing
```
Type definitions:
Input Types: pl.LightningDataModule, int, float, int, float, float, float, float, str, float
Output Type: DataLoader
Dependencies:
```python
def ... |
Imports:
```python
import datetime
import typing
```
Type definitions:
```python
class v0(Terms):
def __init__(self, v1: str, v2: Address, v3: Address, v4: Dict[str, int], v5: Dict[str, int], v6: bool, v7: str, v8: Optional[Dict[str, int]], v9: str, v10: str) -> None:
"""
Instantiate transaction.
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: asyncio.StreamReader, asyncio.StreamWriter
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
async def v0(self, v1: asyncio.StreamReader, v2: asyncio.StreamWriter):
self.DATA.append(await v1.readline())
v2.close()
``` |
Imports:
```python
import re
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str):
with open(v1, 'r') as v2:
v3 = v2.read()
v4 = re.search(pattern=self.__class__.function_pattern, string=v3, flags=re.I | re.M)
... |
Imports:
```python
import uuid
import typing
```
Type definitions:
Input Types: NDArray
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: NDArray):
v2 = [str(uuid.uuid4()) for v3 in range(v1.shape[0])]
for v4 in range(v1.shape[0]):
v5 = v2[v4]
for (v6, v7) i... |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: float, float, float, bool
Output Type: float
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: float, v2: float, v3: float, v4: bool=False) -> float:
v5 = 0 if v4 else self.pos_x
v6 = 0 if v4 else self.po... |
Imports:
```python
import typing
```
Type definitions:
Input Types: 'Polygon', 'Polygon'
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: 'Polygon', v2: 'Polygon') -> bool:
v3 = self._poly_to_geom(v1)
v4 = self._poly_to_geom(v2)
return v3.intersects(v4)
``` |
Imports:
```python
import copy
import typing
```
Type definitions:
Input Types: Any, dict
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1, v2: dict):
v1['type'] = self.txin_type
v3 = self.received.get(v1['prevout_hash'] + f":{v1['prevout_n']}")
(v4, v5, v6) = v3
v1... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, int, int
Output Type: Optional[dict]
Dependencies:
Function Name: v0
Function:
```python
async def v0(self, v1: str, v2: int, v3: int) -> Optional[dict]:
v4 = await self.get_reaction(v1, v2)
if v4 is None:
return None
return ... |
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
Output Type: List[int]
Dependencies:
Function Name: v2
Function:
```python
def v2(self, v3: v0) -> List[int]:
v4 = []
... |
Imports:
```python
import subprocess
import typing
```
Type definitions:
Input Types: Sequence[str]
Output Type: subprocess.CompletedProcess
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: Sequence[str], /, **v2) -> subprocess.CompletedProcess:
print(f"+ {' '.join(v1)}")
return subprocess.run(v... |
Imports:
```python
import typing
```
Type definitions:
Input Types: list
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: list):
if len(v1) <= 1:
raise ValueError('You called manage.py or python -m zacoby without specifying any commands to run.')
v2 = v1[0]
v3 ... |
Imports:
```python
import matplotlib
import matplotlib.pyplot as plt
from matplotlib.lines import Line2D
from matplotlib.text import Text
from matplotlib.collections import Collection, PathCollection
from matplotlib.quiver import QuiverKey, Quiver
import matplotlib.animation as animation
import typing
```
Type definiti... |
Imports:
```python
import typing
```
Type definitions:
```python
class v0:
def __init__(self, v1: int=-1) -> None:
self.label = v1
self.ops: List[Op] = []
self.error_handler: Optional[v0] = None
@property
def v2(self) -> bool:
"""Does the block end with a jump, branch or re... |
Imports:
```python
import torch.nn as nn
import torch.nn.functional as F
import torch
import torch.optim
import typing
```
Type definitions:
Input Types: Any, Any
Output Type: torch.Tensor
Dependencies:
```python
def v0(self, v1):
if layer == 'text_projection':
v1 = v1 @ self.text_projection
return... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int, int, int
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: int, v2: int, v3: int):
v4 = v1 % (v2 + v3)
if v4 // v2 == 0:
return True
return False
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: Dict[str, Set[str]]
Dependencies:
```python
def v0(v1: LoggingTransaction) -> Dict[str, Set[str]]:
v2 = "\n SELECT DISTINCT\n tc.table_name,\n ccu.table_name AS foreign_table_name\... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, str
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str, v2: str) -> bool:
if type(v1) != str or type(v2) != str:
return False
v1 = v1.lower().replace(' ', '')
v2 = v2.lower().replace(' ', '')... |
Imports:
```python
import tensorflow as tf
from keras.utils import losses_utils, metrics_utils
from keras.utils.tf_utils import is_tensor_or_variable
from tensorflow.keras import backend
from tensorflow.keras.metrics import Mean
from tensorflow.keras.metrics import get as get_metric
import typing
```
Type definitions:
... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
if not self.enabled:
return
self.enabled = False
self.state = 'disabled'
self.timer_started = False
self.debug_log('Disabling...'... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int) -> None:
self.login_status = False
v2: str = self.getApiErrorMsg(v1)
self.gateway.write_log(f'交易服务器连接断开，原因：{v1}，{v2}')
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1) -> None:
self.closeSignal.emit()
v1.accept()
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1) -> None:
self.result.msg = f"number for stop_wavelength changed to '{v1}'"
self.result.value = v1
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
assert self._epoch_end_reached
v1 = self.metrics
self._progress_bar_metrics.update(v1['pbar'])
self._callback_metrics.update(v1['callback'])
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: torch.Tensor, 'Prior', Any
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: torch.Tensor, v2: 'Prior', v3=True):
v4 = v1 if v3 else v2.get_constrained(v1)
if v3:
v5 = v2().support.check(v4)
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Iterable, Any
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: Iterable, v2=None):
v3 = iter(v1)
v4 = next(v3) if v2 is None else v2
v5 = v4.data
for v6 in v3:
v5 = v6.mul_data(v5, v6.data)
r... |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: dm_env.TimeStep, np.ndarray
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: dm_env.TimeStep, v2: np.ndarray):
v3 = np.array(v1.reward or 0, np.float32)
self._episode_reward += v3
se... |
Imports:
```python
import typing
```
Type definitions:
Input Types: float, int, str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: float=WEIGHT, v2: int=HEIGHT, v3: str=SEX):
if v3 == 'female':
v4 = 1.07 * v1 - 148 * (v1 / v2 * (v1 / v2))
else:
v4 = 1.1 * v1 - ... |
Imports:
```python
import numpy as np
import torch
from torch.nn.functional import cross_entropy
import typing
```
Type definitions:
Input Types: Image
Output Type: torch.Tensor
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: Image) -> torch.Tensor:
v2 = np.array(v1).transpose(2, 0, 1)[np.newaxis, ... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any, Any, int, bool
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1, v2, v3: int, v4: bool=True):
for v5 in range(v3):
(v1, v2) = self._shuffle_data(v1, v2)
v6 = 0
while v6 < len(v1):
... |
Imports:
```python
import random
import typing
```
Type definitions:
Input Types: int
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int=0) -> str:
v2 = '{}_{}'.format(random.choice(self._left), random.choice(self._right))
if v2 == 'boring_wozniak':
return self.g... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: 'IApiCursor'
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> 'IApiCursor':
if self.conn is None:
raise Exception('cursor. Empty conn!!')
return self.conn.cursor()
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: list[str]
Output Type: int
Dependencies:
```python
def v0(v1: list[str]) -> tuple[dict[Vector2D, int], Vector2D]:
v2 = {}
for (v3, v4) in enumerate(v1):
for (v5, v6) in enumerate(v4):
v2[v5, v3] = int(v6)
v7 = (len(v1) ... |
Imports:
```python
import os
import healpy as hp
import numpy as np
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str):
assert os.path.isfile(v1)
self.map = np.load(v1, allow_pickle=True)
self.nside = hp.npix2nsid... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, str
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: str) -> str:
if v2 == '*':
v3 = v1
elif v1 == '未定義語':
v3 = '未定義語-その他'
else:
v3 = f'{v1}-{v2}'
if v3 in sel... |
Imports:
```python
import typing
```
Type definitions:
Input Types: List[str]
Output Type: Tuple[List[str], List[str], List[str]]
Dependencies:
```python
def v0(v1: str) -> List[str]:
v2 = v1.lower()
v3 = []
for (v4, v5) in BANNED_WORDS.items():
if v4 in v2:
if 'realm_name' in v2:
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: dict, Union[dict, list]
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: dict, v2: Union[dict, list]):
v3 = getattr(self, self._id_parsing_function['object'])('observed-data', v1)
v4 = {'id': v3, 'type': '... |
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