text stringlengths 190 325k |
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Imports:
```python
import typing
```
Type definitions:
Input Types: Any
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0(v1) -> int:
v2 = v1.lower()
if 'u18' in v2 or 'normal' in v2 or 'sport' in v2:
return 0
return 1
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> int:
if self.top() is None:
return None
return self.stack[-1][1]
``` |
Imports:
```python
import math
import numpy as np
import typing
```
Type definitions:
Input Types: 'CLASSIFIER_TYPE', int, float, Optional[int], int, int, int, Callable[[], np.ndarray], Callable[[np.ndarray, int], np.ndarray]
Output Type: np.ndarray
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1:... |
Imports:
```python
from collections.abc import Iterable
import typing
```
Type definitions:
Input Types: bool
Output Type: list[str] | list[list[str]]
Dependencies:
```python
def v0(v1):
for v2 in v1:
if isinstance(v2, Iterable) and (not isinstance(v2, str)):
yield from v0(v2)
elif ' ' ... |
Imports:
```python
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
import typing
```
Type definitions:
Input Types: list, Any
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: list, v2=True):
v3 = []
v4 = []
v5 = []
for v6 in v1:
v7... |
Imports:
```python
import torch
import torch.autograd.profiler as profiler
import typing
```
Type definitions:
Input Types: torch.Tensor, torch.Tensor, Any
Output Type: Tuple[torch.Tensor, torch.Tensor, torch.Tensor]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: torch.Tensor, v2: torch.Tensor, ... |
Imports:
```python
import socket
import typing
```
Type definitions:
Input Types: Any, Any
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(v1, v2) -> None:
v3 = socket.socket()
v4 = v2.getaddr('ctrl', 'coord_addr')
v3.connect((v4[0], v4[1]))
v3.sendall(v1.command.encode('u... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
async def v0(self, v1: str):
v2 = await self.ledger.network.get_claims_for_name(v1)
v3 = await self.resolve(*(f"{claim['name']}#{claim['claim_id']}" for v4 in v2['claims... |
Imports:
```python
import typing
```
Type definitions:
Input Types: List[str]
Output Type: None
Dependencies:
```python
def v0(v1):
from IPython.display import Markdown, display
display(Markdown(v1))
```
Function Name: v2
Function:
```python
def v2(v3: List[str]) -> None:
v4 = '\n'.join((f'- `{line}`' for ... |
Imports:
```python
import typing
```
Type definitions:
```python
v0 = TypeVar('T')
```
Input Types: v0
Output Type: Set[Set[v0]]
Dependencies:
Function Name: v1
Function:
```python
def v1(self, v2: v0) -> Set[Set[v0]]:
v3 = frozenset((open_set for v4 in self.open_sets if v2 in v4))
return v3
``` |
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=None) -> str:
v3 = self.get_attdef(v1)
if v3 is None:
return v2
return v3.dxf.text
``` |
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 = 'SELECT tbl_name FROM ic_quranic_tbl_meta_data WHERE language=?'
v3 = self._fetch_data(v2, [v1], 1)
v4 = v3[0][0]
return v4
``... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
async def v0(self) -> None:
v1 = [command.to_dict() for v2 in self._queued_global_application_commands.values() if not v2.__application_command_parent__]
if not v1:
... |
Imports:
```python
import os
from copy import deepcopy
import typing
```
Type definitions:
Input Types:
Output Type: dict
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> dict:
v1 = deepcopy(self.all_keys)
v1.update({i.lower(): k for (v2, v3) in os.environ.items() if v2.lower() in self.all... |
Imports:
```python
import typing
```
Type definitions:
Input Types: list[int]
Output Type: Union[None, tuple[int]]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: list[int]=None) -> Union[None, tuple[int]]:
if v1 is None:
return (self.window.frameGeometry().width(), self.window.frameG... |
Imports:
```python
import math
from pathlib import Path
import matplotlib.pyplot as plt
import matplotlib.image as mpimg
import numpy as np
import typing
```
Type definitions:
Input Types: Union[str, List[str]], Union[str, List[str]], int, int
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v... |
Imports:
```python
import typing
```
Type definitions:
Input Types: list
Output Type: List
Dependencies:
```python
def v0(v1: Dict) -> Dict:
v2 = {'Name': v1['@name']}
if 'description' in v1:
v2['Description'] = v1['description']
if 'ip-netmask' in v1:
v2['IP_Netmask'] = v1['ip-netmask']
... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
v1 = self.instrument.query('VOLT?')
return float(v1)
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: Dict[str, str]
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: Dict[str, str]):
for (v2, v3) in v1.items():
with open(v2, 'w') as v4:
v4.write(v3)
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: logging.Logger
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: logging.Logger) -> None:
for v2 in list(v1.handlers):
v1.removeHandler(v2)
v2.flush()
v2.close()
``` |
Imports:
```python
import pandas as pd
import typing
```
Type definitions:
```python
v0 = Union[Sequence[Any], Mapping[str, Any]]
```
Input Types: Union[str, sql.Composed], Optional[v0]
Output Type: pd.DataFrame
Dependencies:
Function Name: v1
Function:
```python
def v1(self, v2: Union[str, sql.Composed], v3: Optional... |
Imports:
```python
import typing
```
Type definitions:
Input Types: List[Tensor], List[Tensor], List[Tensor], List[str]
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: List[Tensor], v2: List[Tensor], v3: List[Tensor], v4: List[str]) -> None:
if len({len(v1), len(v2), len(v3), len(... |
Imports:
```python
import pandas as pd
from pandas.errors import ParserError
import typing
```
Type definitions:
Input Types: str
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str) -> None:
self.logger.debug('%s: filter date range.', self.name)
v2 = pd.Timestamp(self.d... |
Imports:
```python
import typing
```
Type definitions:
```python
v0 = Callable[[Node, Node, str], bool]
```
Input Types: str, str, str, v0
Output Type: (bool, List[bool])
Dependencies:
Function Name: v1
Function:
```python
def v1(self, v2: str, v3: str, v4: str, v5: v0) -> (bool, List[bool]):
v6 = []
for v7 in... |
Imports:
```python
import typing
```
Type definitions:
Input Types: bool, Optional[Mapping[str, str]], bool
Output Type: Mapping[str, str]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, *, v1: bool=False, v2: Optional[Mapping[str, str]]=None, v3: bool=False) -> Mapping[str, str]:
v4 = self._iter... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, Any, Any
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2=None, v3='.') -> Any:
v4 = self.raw
for v5 in self.__sub_dicts:
v4 = v4.get(v5, None)
for v6 in v1.split(v3):
if v... |
Imports:
```python
import random
import typing
```
Type definitions:
Input Types: Sequence, int
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: Sequence, v2: int):
v3 = set()
v4 = list(range(len(v1)))
while len(v3) != v2:
(v5, v6) = tuple(random.sample(v4, 2))
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, bool
Output Type: Tuple[List, List]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: bool=True) -> Tuple[List, List]:
v1 = v1.upper()
v3 = set()
v4 = set()
v5 = set()
v6 = v1.split('//')
v7 = ... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: Dict
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str) -> Dict:
v2 = self.normalize_path(v1)
v3 = '/labs' + f'{v2}/networks'
return self.client.get(v3)
``` |
Imports:
```python
import typing
```
Type definitions:
```python
v0 = torch.Tensor
```
Input Types: v0
Output Type: v0
Dependencies:
Function Name: v1
Function:
```python
def v1(self, v2: v0) -> v0:
v3 = super().forward(v2)
if self.__padding != 0:
return v3[:, :, :-self.__padding]
return v3
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any
Output Type: Callable
Dependencies:
```python
def v0(v1, *v2) -> pd.DataFrame:
v3 = [val for v4 in self.all_demo_values]
v5 = []
if self.is_weekly:
v1 = self.back_fill_missing_weekly(df=v1)
v1 = func(v1, *v2)
if self.is... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, dict
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str, v2: dict) -> str:
v3 = []
for (v4, v5) in v2.items():
if v4 in v1:
v3.append(v5)
return ','.join(v3)
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, str, dict
Output Type: List[dict]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: str, v3: dict) -> List[dict]:
v4: str = self.SPLITTER_METHOD_TO_GET_UNIQUE_BATCH_IDENTIFIERS_MAPPING[v2]
v5: Callable = self.... |
Imports:
```python
import os
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str):
if not os.path.isfile(v1):
raise RuntimeError("Files does not exist '{}'".format(v1))
v2 = open(v1, 'r')
v3 = v2.read()
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Path, str, Path
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: Path, v2: str='lsd2', v3: Path=Path.cwd() / 'rate.txt') -> None:
if v2 == 'lsd2':
with v1.open('r') as v4, v3.open('w') as v5:
fo... |
Imports:
```python
import typing
```
Type definitions:
```python
v0 = Tuple[Query, List[Location], Rating, dict]
```
Input Types: List[v0], Any
Output Type: Dict[str, List[v0]]
Dependencies:
Function Name: v1
Function:
```python
def v1(v2: List[v0], v3=Callable) -> Dict[str, List[v0]]:
v4: Dict[str, List[v0]] = {}... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any, Any, Any
Output Type: float
Dependencies:
Function Name: v0
Function:
```python
def v0(v1, v2, v3) -> float:
v4 = 0.0
(v5, v6) = ([v1.root], 0)
while len(v5) > 0:
v7 = []
for v8 in v5:
for v9 in v8.nodes:
... |
Imports:
```python
import typing
```
Type definitions:
```python
class v0:
def __init__(self, v1):
self.content: any = v1
self.parent: v0 = None
self.right: v0 = None
self.left: v0 = None
self.color: color = color.BLACK
```
```python
class v2:
def __init__(self):
... |
Imports:
```python
from qiskit import circuit
from qiskit.circuit.library import standard_gates as gates
from qiskit.circuit.parameterexpression import ParameterExpression, ParameterValueType
from qiskit.pulse import channels as chans, configuration, exceptions, instructions, macros, library, transforms, utils
from qis... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: Dict[str, Any]
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> Dict[str, Any]:
v1 = self._load_args
v2 = self._save_args
if 'properties' in v1:
v3 = v1['properties'].copy()
v3.pop('user', ... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int, Any
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int, v2):
self.graph = [[] for v3 in range(v1 + 1)]
self.marked = [0] * (v1 + 1)
for v4 in v2:
(v5, v6) = v4
self.graph[v5].app... |
Imports:
```python
import numpy
import typing
```
Type definitions:
Input Types: 'list[float]'
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: 'list[float]'):
v2 = numpy.sqrt(numpy.power(v1[0], 2) + v1[1])
v3 = numpy.sqrt(v1[2] * v1[2] + v2 * v2)
return v3
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any, Any, Any
Output Type: int
Dependencies:
```python
def v0(*v1) -> bytes:
v2 = b''.join((str(arg).encode('utf-8') for v3 in v1))
return hash_functions[HASH_TYPE](v2).digest()
```
Function Name: v4
Function:
```python
def v4(v5, v6, v7) -> i... |
Imports:
```python
import torch
import torch.nn as nn
import typing
```
Type definitions:
Input Types: torch.Tensor
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: torch.Tensor):
v2 = v1 + self._position_encoding[:, :v1.shape[1]].to(v1.device)
v3 = self._dropout_positiona... |
Imports:
```python
import typing
```
Type definitions:
Input Types: bytes
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: bytes):
v2 = self._sock.sendall(v1)
self._log.debug('sending request %s', v1)
return v2
``` |
Imports:
```python
import typing
```
Type definitions:
```python
class v0(so.SubclassableObject, so.DerivableObject, s_abc.Type):
v1 = so.SchemaField(s_expr.Expression, default=None, coerce=True, compcoef=0.909)
v2 = so.SchemaField(ExprType, default=None, compcoef=0.909)
v3 = so.SchemaField(bool, default=Fa... |
Imports:
```python
import typing
```
Type definitions:
```python
v0 = Enum
```
Input Types: Optional[v0], v0
Output Type: bool
Dependencies:
Function Name: v1
Function:
```python
def v1(self, v2: Optional[v0], v3: v0) -> bool:
v4 = v2
while v4 is not None:
if v3 == v4:
return True
v... |
Imports:
```python
from collections import defaultdict
import typing
```
Type definitions:
```python
v0 = Tuple[str, FrozenSet[str], bool]
```
```python
class v1(DFSNode):
def __init__(self, v2: Package, v3: list[Package], v4: v1 | None=None, v5: None | (DirectoryDependency | FileDependency | URLDependency | VCSDe... |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: Tuple[int, ...], Tuple[int, ...]
Output Type: Tuple[Tuple[int, ...], Tuple[int, ...]]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: Tuple[int, ...], v2: Tuple[int, ...]) -> Tuple[Tuple[int, ...], Tuple[int, ...]]:
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: spec.Workload, Iterator[Tuple[spec.Tensor, spec.Tensor]], spec.OptimizerState, spec.ParameterContainer, spec.Hyperparamters, int, spec.RandomState
Output Type: Tuple[spec.Tensor, spec.Tensor]
Dependencies:
Function Name: v0
Function:
```python
def v0... |
Imports:
```python
from os.path import isdir as osp_isdir, getsize as osp_getsize, join as osp_join, isfile as osp_isfile
from os import mkdir as os_mkdir, listdir as os_listdir, remove as os_remove, walk as os_walk, rename as os_rename
import typing
```
Type definitions:
Input Types: Any
Output Type: None
Dependencie... |
Imports:
```python
import os
import typing
```
Type definitions:
Input Types: pkg_resources.Distribution, str
Output Type: str | None
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: pkg_resources.Distribution, v2: str) -> str | None:
v3 = os.path.join(v2, v1.project_name) + '.egg-link'
if os.pa... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any, str, Any
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1, v2: str, v3=0):
v4 = 0
while True:
try:
v5 = v2.index(v1, v4)
except ValueError:
return
v6 = v5 + le... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int
Output Type: Optional[np.ndarray]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int) -> Optional[np.ndarray]:
if not self.available[v1]:
return None
self.available[v1] = False
return self.lines[v1]
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: typing.Union[int, str], bool
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: typing.Union[int, str]=None, v2: bool=False):
if v1 == 'all':
for v3 in range(1, self.max + 1):
self.extract_on... |
Imports:
```python
import numpy
import typing
```
Type definitions:
Input Types: float, str
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: float, v2: str) -> None:
assert not (v1 == self._time).any(), 'this boundary exists already'
v3 = numpy.searchsorted(self._time, nu... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Dict[str, Any], List[str]
Output Type: bool
Dependencies:
```python
def v0(v1, v2):
if v2 not in v1:
return False
v3 = v1[v2]
if isinstance(v3, str) and v3 == '':
return False
return True
```
Function Name: v4
Function:... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
```python
def v0(v1: 'TestInterpreter', v2: str, v3: Dict[str, Any], v4: List[Dict[str, Any]]) -> None:
v5 = list(execute_query(v1.adapter, v2, v3))
v1.assertCountEqual(v4, v5)
```
Function Name: v6
Function:
`... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, **v1) -> None:
del kwargs
if self._validate_handler:
self.mc.events.remove_handler(self._validate_handler)
if hasattr(self.mc, 'sounds'):
... |
Imports:
```python
from collections import Counter
import typing
```
Type definitions:
Input Types: List[int]
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: List[int]):
v2 = Counter(v1)
for v3 in tuple(v2.keys()):
v2[self.jpy_classes[v3]] = v2.pop(v3)
return ... |
Imports:
```python
import asyncio
from typing import TYPE_CHECKING, Any, Callable, Dict, List, NamedTuple, Optional, cast
import typing
```
Type definitions:
Input Types: asyncio.BaseTransport
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: asyncio.BaseTransport) -> None:
se... |
Imports:
```python
import warnings
import typing
```
Type definitions:
Input Types:
Output Type: bytearray
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> bytearray:
warnings.warn('byte_repr is deprecated, directly cast to bytes instead', DeprecationWarning)
return bytearray(bytes(self))
... |
Imports:
```python
import warnings
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
```python
def v0():
with open(str(CONFIG_PATH), 'r') as v1:
v2 = yaml.safe_load(v1)
return v2
```
```python
def v3():
v4 = {'Chunked_Data_Path': '', 'PrePd_Data_Path': '', 'Raw_Dat... |
Imports:
```python
import logging
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
v1 = self.file_entry.get()
v2 = self.option_entry.get()
logging.info('Execute %s with options %s', v1, v2)
self.app.core.execu... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Dict[Any, List[Any]]
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: Dict[Any, List[Any]]) -> int:
v2 = [len(v) for (v3, v4) in v1.items()]
if len(v2) == 0:
return 0
return max(v2)
``` |
Imports:
```python
import datetime
import typing
```
Type definitions:
Input Types:
Output Type: List[str]
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> List[str]:
assert self.manager is not None
v1 = []
v2 = self.manager.iteration
v3 = self.manager.epoch_detail
if self.trai... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int, int
Output Type: Iterator[Tuple[int, int]]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: int, v2: int) -> Iterator[Tuple[int, int]]:
v3 = v1 // 2
v4 = v1 - v3
while v3 > 0 and v4 <= v2:
yield (v3, v4)
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: bool
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: bool):
self.online_network.set_is_training(v1)
if self.has_target:
self.target_network.set_is_training(v1)
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: bool
Output Type: dict
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: bool) -> dict:
v2 = super().describe(v1)
v2['model_name'] = self.model_name
v2['related_name'] = self.related_name
v2['forward_key'] = self.fo... |
Imports:
```python
import datetime
import typing
```
Type definitions:
Input Types: str
Output Type: datetime.timedelta
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str) -> datetime.timedelta:
(v2, v3) = map(int, v1.split(':'))
return datetime.timedelta(hours=v2, minutes=v3)
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any, Any, Any, Any
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1, v2, v3, v4) -> None:
self.log.info(f'feature=service, event=topic-subscription, topic={self.args.tc_svc_server_topic}')
self.message_bro... |
Imports:
```python
import typing
```
Type definitions:
Input Types: List[str]
Output Type: Dict[str, List[str]]
Dependencies:
```python
def v0(v1: str) -> str:
if not len(v1.split('.')) >= 2:
raise ValueError(f"version not in expected format: '{v1}'")
return '.'.join(v1.split('.')[:2])
```
Function Nam... |
Imports:
```python
import logging
import torch
import torch.nn
import torch.optim
import typing
```
Type definitions:
Input Types: str, torch.nn.Module, bool, str
Output Type: Any
Dependencies:
```python
def v0(v1: Dict[str, Union[float, torch.Tensor]], v2: Dict[str, Union[float, torch.Tensor]]):
v3 = {}
for (... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int, int
Output Type: chr
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int, v2: int) -> chr:
for v3 in self.entity_pos:
if (v1, v2) in self.entity_pos[v3]:
return v3
return ''
``` |
Imports:
```python
import typing
```
Type definitions:
```python
class v0(models.Model):
v1 = 40
v2 = 1000
v3 = 40
v4 = 128
v5 = 3000
v6 = 10000
v7 = ['Google', 'Email', 'GitHub', 'LDAP', 'Dev', 'RemoteUser', 'AzureAD', 'SAML', 'GitLab', 'Apple']
v8 = ''
v9 = 15
v10: int = models... |
Imports:
```python
import subprocess
import typing
```
Type definitions:
Input Types: str
Output Type: bool
Dependencies:
```python
def v0(v1: str):
return subprocess.run(['kubectl', 'run', 'workload', '--rm', '--tty', '-i', '--restart', 'Never', '--namespace', 'default', '--image', workload['image'], *[x for (v2,... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str='formula_unit') -> None:
v2 = self._normalization_factor(v1)
self.composition /= v2
self._energy /= v2
``` |
Imports:
```python
import torch
from torch.fx import GraphModule
from torch.fx.experimental.proxy_tensor import make_fx
from torch._prims.utils import getnvFuserDtype, Number
from torch._prims.context import TorchRefsMode
import torch.overrides
from torch.utils._pytree import tree_map
import typing
```
Type definitions... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: pd.Series
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> pd.Series:
v1 = None if self.criteria_start == 0 else self.criteria_start
v2 = None if self.criteria_stop == 0 else self.criteria_stop
v3 = slice(... |
Imports:
```python
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
import typing
```
Type definitions:
Input Types: int, float, float
Output Type: torch.Tensor
Dependencies:
```python
def v0(v1, v2):
return v1.lgamma() + v2.lgamma() - (v1 + v2).lgamma()
```
```python
def v3(v4... |
Imports:
```python
import os
import typing
```
Type definitions:
Input Types: str, str
Output Type: bool
Dependencies:
```python
def v0():
v1 = os.path.dirname(os.path.abspath(__file__))
v2 = os.path.join(v1, 'speak-test-ids_2019-11-29.txt')
v3 = os.path.join(v1, 'speak-test-ids_2020-05-27.txt')
assert... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int
Output Type: Optional[int]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int) -> Optional[int]:
if v1 in self.cache:
self.hits += 1
self.list.add(self.list.remove(self.cache[v1]))
return self.cac... |
Imports:
```python
import datetime
import typing
```
Type definitions:
Input Types: range_config_pb2.RangeConfig, bool, bool, Optional[Text]
Output Type: Union[Text, List[Text]]
Dependencies:
```python
def v0(v1: int) -> Tuple[int, int, int]:
v2 = UNIX_EPOCH_DATE + datetime.timedelta(v1)
return (v2.year, v2.mo... |
Imports:
```python
import io
import typing
```
Type definitions:
Input Types: base.String, Optional[base.InputFile], Optional[base.Integer], Optional[base.Integer], Optional[base.Boolean]
Output Type: Union[io.BytesIO, io.FileIO]
Dependencies:
Function Name: v0
Function:
```python
async def v0(self, v1: base.String, ... |
Imports:
```python
import typing
```
Type definitions:
Input Types: List[str]
Output Type: Dict[str, List[str]]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: List[str]) -> Dict[str, List[str]]:
v2 = {}
for v3 in self.IDENTIFIERS.keys():
v4 = [tag for v5 in v1 if v5.startswith(v3... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, bool
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: bool=True) -> str:
v3 = f'{self.progress:.2f}% complete, {self.elapsed} elapsed'
if v2:
return f'{v3} - {v1}'
else:
r... |
Imports:
```python
import typing
```
Type definitions:
Input Types: List[List[int]], int
Output Type: List[int]
Dependencies:
```python
def v0(v1: List[int]) -> int:
if v1[0] == 0:
return 0
(v2, v3) = (0, len(v1) - 1)
while v2 < v3:
v4 = (v2 + v3) // 2 + 1
if v1[v4] == 0:
... |
Imports:
```python
import requests
import typing
```
Type definitions:
Input Types: str, dict
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: dict, **v3):
v2.update(v3)
v4 = requests.post(self.HOST + v1, json=self.prepare_body(v2))
return v4.json()
``` |
Imports:
```python
import pandas as pd
import typing
```
Type definitions:
Input Types: v1, str
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: v1, v2: str) -> None:
v3 = pd.DataFrame(v1)
v3.to_csv(v2, header=False, index=False, encoding='UTF-8')
print('{} is created.'.for... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, int
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: int) -> int:
if len(v1) < v2:
return 0
v3 = min(set(v1), key=v1.count)
if v1.count(v3) >= v2:
return len(v1)
retur... |
Imports:
```python
import re
import typing
```
Type definitions:
Input Types: str, Dict, bool
Output Type: Union[Dict, List]
Dependencies:
```python
def v0(v1: str) -> List[str]:
v2 = re.compile('\\$metadata#Cellsets\\(Cells\\(([A-Za-z,]+)\\)\\)/\\$entity')
v3 = v2.match(v1)
if not v3:
raise ValueE... |
Imports:
```python
import matplotlib.pyplot as plt
import numpy as np
import typing
```
Type definitions:
```python
v0 = pd.DataFrame
```
Input Types: Any, v0, str
Output Type: None
Dependencies:
Function Name: v1
Function:
```python
def v1(v2: Any, v3: v0, v4: str) -> None:
assert hasattr(v2, 'feature_importances... |
Imports:
```python
import math
import numpy as np
from scipy.special import expn
import typing
```
Type definitions:
```python
v0 = namedtuple('NoiseProfile', 'sampling_rate window_size len1 len2 win n_fft noise_mu2')
```
Input Types: Any, v0, Any
Output Type: Any
Dependencies:
```python
def v1(v2, v3):
if v3 == np... |
Imports:
```python
import argparse
from argparse import Namespace
import typing
```
Type definitions:
Input Types: Namespace
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: Namespace, cls):
if not hasattr(cls, 'add_args'):
return
v2 = argparse.ArgumentParser(argument_de... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
async def v0(self) -> None:
async with self._amqp_pool.acquire() as v1:
await v1.set_qos(prefetch_count=1)
for (v2, v3) in self.mapping.items():
aw... |
Imports:
```python
import numpy as np
from scipy import interpolate, integrate
from scipy import optimize
from scipy.interpolate import interp1d
import typing
```
Type definitions:
Input Types: Any
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1) -> None:
v2 = np.arange(0.0, ... |
Imports:
```python
import typing
```
Type definitions:
Input Types: th.Tensor, bool
Output Type: Tuple[th.Tensor, th.Tensor, th.Tensor]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: th.Tensor, v2: bool=False) -> Tuple[th.Tensor, th.Tensor, th.Tensor]:
v3 = self.action_dist(v1)
v4 = v3.m... |
Imports:
```python
import numpy as np
import numpy.typing as npt
import typing
```
Type definitions:
```python
class v0:
def __init__(self, v1: RotationMatrixLike, v2: VectorLike) -> None:
"""Frame (transformation) constructor.
Basic constructor method of a frame object.
The arguments rot ... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: Callable[[], None]
Dependencies:
```python
def v0() -> None:
v1 = self.get_program_byte()
v2 = self.registers['a']
if self.io is not None:
self.io.send_output(v1, v2)
```
Function Name: v3
Function:
```python
def v3(s... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Optional[int]
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Optional[int]=None) -> str:
while not self._buffer:
try:
self._buffer = next(self._iter)
except StopIteration:
... |
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