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Imports:
```python
import argparse
import typing
```
Type definitions:
Input Types:
Output Type: argparse.Namespace
Dependencies:
Function Name: v0
Function:
```python
def v0() -> argparse.Namespace:
v1 = argparse.ArgumentParser(description=__doc__)
v1.add_argument('requirements', nargs='+', help='Requiremen... |
Imports:
```python
import os
import typing
```
Type definitions:
Input Types: str, str, str, str, str, str, str, Any
Output Type: Any
Dependencies:
```python
def v0(v1: str, v2: str, v3: str, v4: str, v5: str, v6=None):
v7 = Selenzy.readTaxonomy(v2, fileLineage)
v8 = Selenzy2.superTax2(v7)
if v4 == str():
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: dict
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: dict):
v2 = next(iter(v1.items()))[1]
while v2.parent:
v2 = v2.parent
return v2
``` |
Imports:
```python
from decimal import Decimal
import typing
```
Type definitions:
Input Types: str
Output Type: List[str]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str) -> List[str]:
v2: int = int(Decimal('1e35'))
v3: int = int(Decimal('1e36'))
v4: List[int] = [erc20_token.cont... |
Imports:
```python
import argparse
import pathlib
import shutil
import typing
```
Type definitions:
Input Types: list[str]
Output Type: argparse.Namespace
Dependencies:
```python
def v0(v1: argparse.ArgumentParser, v2: str, v3: str=None, *, v4: bool=True, v5: str=None, v6: str=None) -> None:
v7 = v2.replace('_', '... |
Imports:
```python
import requests
from requests.exceptions import Timeout
import typing
```
Type definitions:
Input Types:
Output Type: list
Dependencies:
Function Name: v0
Function:
```python
def v0() -> list:
v1 = requests.get(url='https://xyquadrat.ch/polyring/data/members.json').json()
return v1
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: int
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int):
if self.geometry is not None:
v2 = self.ndim * self.natoms
return self.geometry[v1 * v2:(v1 + 1) * v2]
else:
return self.t... |
Imports:
```python
import typing
```
Type definitions:
Input Types: float
Output Type: Union[List[str], None]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: float=10) -> Union[List[str], None]:
v2 = None
try:
self._command_proc.join(timeout=self._timeout)
if self._command... |
Imports:
```python
import pandas as pd
import scipy.stats as stats
import typing
```
Type definitions:
Input Types: str, str, str, Any
Output Type: pd.Series
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: str, v3: str='spearman', v4=True) -> pd.Series:
v5 = self.get_cats()
v6 = ... |
Imports:
```python
from pathlib import Path
import typing
```
Type definitions:
Input Types: Path, str
Output Type: Path
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Path, v2: str=None) -> Path:
if v2 is None:
v2 = self.get_sub_lang_short(v1)
v3 = Path(self.media_path.parent, s... |
Imports:
```python
import typing
```
Type definitions:
Input Types: List[int]
Output Type: Union[int, None]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: List[int]) -> Union[int, None]:
if not v1:
return None
v2 = {}
for v3 in v1:
if v3 not in v2:
v2[v3] = 0
... |
Imports:
```python
import torch
from torch import nn, Tensor
import typing
```
Type definitions:
Input Types: Tensor, Optional[Dict[str, Tensor]]
Output Type: Tuple[Tensor, Optional[Dict[str, Tensor]]]
Dependencies:
```python
@torch.jit.unused
def v0(v1: Tensor) -> float:
return v1
```
```python
@torch.jit.unused
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str):
for v2 in (2, 3, 5, 7, 11, 13, 17, 19, 23, 29, 31):
if v1[v2] != '\x7f':
return False
return True
``` |
Imports:
```python
import subprocess
import typing
```
Type definitions:
Input Types: str, str
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: str) -> None:
v3 = ['azcopy', 'sync', v1, v2]
self.logger.info('copying base setup')
subprocess.check_output(v3)
``... |
Imports:
```python
import subprocess
import typing
```
Type definitions:
Input Types: typing.List[int]
Output Type: Any
Dependencies:
```python
def v0(v1: str, v2: typing.List[int]=None):
if v2:
v2 = [str(id) for v3 in v2]
v2 = ','.join(v2)
v4 = f'-i {v2}' if v2 else ''
v5 = subprocess.chec... |
Imports:
```python
import math
import numpy as np
from skimage.metrics import structural_similarity
import cv2
import typing
```
Type definitions:
Input Types: np.ndarray, np.ndarray
Output Type: float
Dependencies:
```python
def v0(v1: np.ndarray, v2: np.ndarray, v3: str):
v4 = f'Cannot calculate {v3}. Input shap... |
Imports:
```python
import pandas as pd
import typing
```
Type definitions:
Input Types: dict, list
Output Type: pd.DataFrame
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: dict, v2: list) -> pd.DataFrame:
v3 = []
for (v4, v5) in v1.items():
if type(v5) != pd.DataFrame:
v5 =... |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: Any
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1) -> Any:
v2 = 1
for v3 in v1:
v2 += 2 + len(v3)
v4 = np.zeros(v2, np.uint8)
v4[0] = len(v1)
v5 = 1
for v3 in v1:
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, Optional[str], Iterable[Optional[str]]
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str, v2: Optional[str], v3: Iterable[Optional[str]]) -> None:
if v2 not in v3:
v4 = ', '.join(['<None>' if v is N... |
Imports:
```python
import typing
```
Type definitions:
Input Types: dict
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: dict):
print('Exiting BetaKnuff...')
exit()
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: ndarray, ndarray
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: ndarray, v2: ndarray):
v3: str = 'Outer fold\t\t\tANN\t\t\tLinear regression\t\t\tBaseline\n'
v3 += 'i\t\thᵢ\tEᵢ Test\t\tλᵢ\tEᵢ Test\t\t\tEᵢ Test... |
Imports:
```python
import tensorflow as tf
from tensorflow.keras import backend
from tensorflow.keras.metrics import Mean
from tensorflow.keras.metrics import get as get_metric
import typing
```
Type definitions:
Input Types: tf.Tensor, tf.Tensor, Optional[tf.Tensor], int
Output Type: tf.Tensor
Dependencies:
Function... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Callable
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
async def v0(self, v1: Callable, **v2):
v3 = await self.bind(v1, **v2)
await v3()
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any, Any, Optional[int], Any, Any
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1, v2=0, v3: Optional[int]=None, v4=None, v5=False):
if isinstance(v4, str):
v4 = {v4}
v6 = v1.byte_size(v4, v5)
return... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: List
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str) -> List:
v2 = v1.split('_')
v3 = [int(t) for v4 in v2[1:]]
return v3
``` |
Imports:
```python
from cvxpy.atoms.affine.affine_atom import AffAtom
import cvxpy.utilities as u
import cvxpy.lin_ops.lin_utils as lu
import typing
```
Type definitions:
Input Types: Any, Tuple[int, ...], Any
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1, v2: Tuple[int, ...], v... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, Optional[transport.PTransportSettings]
Output Type: bytes
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: Optional[transport.PTransportSettings]=None) -> bytes:
v1 = self.encode_path_param(v1)
v3 = self.get(... |
Imports:
```python
import matplotlib.pyplot as plt
import numpy as np
from numpy.polynomial.polynomial import Polynomial
import typing
```
Type definitions:
Input Types: float, float, int, int, Any, Any
Output Type: Any
Dependencies:
```python
def v0(v1: float, v2: float, v3: int):
v4 = v2 / v1
return v3 * pi_... |
Imports:
```python
import os
import typing
```
Type definitions:
Input Types: Union[str, Path], str
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: Union[str, Path], v2: str) -> str:
(v1, v3) = os.path.splitext(v1)
return v1 + v2 + v3
``` |
Imports:
```python
import torch
import torch.nn as nn
import torch.nn.functional as F
import typing
```
Type definitions:
Input Types: torch.Tensor, torch.Tensor, torch.Tensor, Optional[torch.Tensor], Optional[torch.Tensor], Optional[torch.Tensor], Optional[bool], Optional[Tuple[Dict[str, torch.Tensor], Dict[str, torc... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str):
v2 = v1.count('"')
if v2 not in (0, 2, 4):
raise ValueError('The format of the input relation is incorrect.')
if v2 == 4:
v3 = (v1.s... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: List[str]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str='') -> List[str]:
v2 = ['somepath.txt', 'abc/someotherpath.txt', 'abc/def/anotherpath.txt']
if len(v1) > 0:
return [u for v3 in v2 if v3.sta... |
Imports:
```python
import typing
```
Type definitions:
```python
v0 = namedtuple('ClientParam', ['name', 'type', 'mechanism'])
```
Input Types: List[v0]
Output Type: str
Dependencies:
```python
def v1() -> str:
return f'const {stub_ptr_alias()}& stub'
```
```python
def v2():
return 'StubPtr'
```
```python
def v... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str):
v2 = 1
if v1 == 'm':
v2 = 60
elif v1 == 'h':
v2 = 60 * 60
elif v1 == 'd':
v2 = 60 * 60 * 24
return v2
``` |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: list, list
Output Type: (float, float)
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: list, v2: list) -> (float, float):
(v1, v2) = (np.array(v1), np.array(v2))
v3 = np.mean(np.abs(v1 - v2))
v4 = np.mean... |
Imports:
```python
import typing
```
Type definitions:
Input Types: np.ndarray, (int, int)
Output Type: np.ndarray
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: np.ndarray, v2: (int, int)) -> np.ndarray:
if v2 == (1, 0):
return v1.copy()
elif v2 == (0, 0):
return v1[::-1, :].c... |
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': {'is_active_in_organization_id': 1}, 'group/7': {'name': 'group_LxAHErRs', 'user_ids': [], 'meeting_id': 1}, 'mediafile/110... |
Imports:
```python
import io
from contextlib import redirect_stderr, redirect_stdout
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
```python
def v0(v1: Union[PathLike, str], v2: JsonLike=None, v3: bool=True) -> str:
with io.StringIO() as v4, redirect_stderr(v4):
runmany(... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> int:
if self.cached_count is None:
self.cached_count = self.provide_count()
return self.cached_count
``` |
Imports:
```python
import json, os
import typing
```
Type definitions:
Input Types:
Output Type: List
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> List:
with open(self.file_path, 'r+', encoding='utf-8') as v1:
v2 = json.loads(v1.read())
return v2
``` |
Imports:
```python
from numbers import Integral
import typing
```
Type definitions:
Input Types: int
Output Type: int
Dependencies:
```python
def v0(v1: int) -> int:
if v1 not in cache:
cache[v1] = v0(v1 - 2) + v0(v1 - 1)
return cache[v1]
```
Function Name: v2
Function:
```python
def v2(v3: int) -> int... |
Imports:
```python
import typing
```
Type definitions:
```python
v0 = Union[Event, List[Event]]
```
Input Types: v0
Output Type: v0
Dependencies:
Function Name: v1
Function:
```python
def v1(self, v2: v0) -> v0:
for v3 in v2:
self._enrich_event_metadata(v3)
return v2
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: bytes, Any
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: bytes, v2):
if v2 not in self.clients:
self.clients.append(v2)
if v1 in (b'Hello UDP', b"I'm not a dead client"):
return
for ... |
Imports:
```python
import heapq
import typing
```
Type definitions:
Input Types: int
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int) -> None:
self.count += 1
heapq.heappush(self.max_heap, (-v1, v1))
(v2, v3) = heapq.heappop(self.max_heap)
heapq.heappush(self... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, float
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: float):
v3 = ['depth', 'vertical_uncertainty', 'horizontal_uncertainty']
for v4 in v3:
v5 = self._return_all_surface_tiles(v1, v... |
Imports:
```python
import os
import typing
```
Type definitions:
Input Types: str, str
Output Type: str
Dependencies:
```python
def v0(v1: str) -> GitConfig:
if not os.path.exists(v1):
return None
v2 = {}
v3 = []
v4 = []
with open(v1, 'rb') as v5:
v6 = None
v7 = []
v... |
Imports:
```python
import typing
```
Type definitions:
```python
class v0:
def __init__(self, v1: State, v2: Dict) -> None:
self._channels: Dict[int, GuildChannels] = {}
self._members: Dict[int, Member] = {}
self._roles: Dict[int, Role] = {}
self._emojis: Dict[int, Emoji] = {}
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: 'OrderedDict[str, str]'
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: 'OrderedDict[str, str]'):
self.classes = v1
self._mid_to_idx = {mid: idx for (v2, v3) in enumerate(self.classes)}
``` |
Imports:
```python
import getopt
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
self.assertTrue(getopt.short_has_arg('a', 'a:'))
self.assertFalse(getopt.short_has_arg('a', 'a'))
self.assertError(getopt.short_has... |
Imports:
```python
import typing
```
Type definitions:
```python
class v0:
def __init__(self, v1: str='/', v2: bool=True) -> None:
self.path = v1
self.array = ()
self.args = ()
self.size = 0
self.isExist = False
self.isFolder = False
self.isFile = False
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: caffe2_pb2.NetDef, str, str, int, List[Tuple[List[Tuple[str, int]], List[Tuple[str, int]]]], Dict[str, int], Dict[str, int]
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: caffe2_pb2.NetDef, v2: str, v3: str, v4: int, ... |
Imports:
```python
from math import log
import typing
```
Type definitions:
Input Types: Iterable[Number], bool
Output Type: Generator
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: Iterable[Number], v2: bool=False) -> Generator:
v3 = iter(v1)
v4 = next(v3)
for v5 in v3:
yield (log... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, int
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: int) -> bool:
for v3 in self.docker.services.list():
if v3.name == v1:
v4 = v3.attrs['Spec']['Labels']
v4['tr... |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: np.ndarray, Optional[List[int]]
Output Type: np.ndarray
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: np.ndarray, v2: Optional[List[int]]=None) -> np.ndarray:
v3 = self.get_coefficient_history()
v4 = ... |
Imports:
```python
import torch
import torch.nn as nn
import torch.nn.functional as F
import typing
```
Type definitions:
Input Types: torch.Tensor, int, str
Output Type: torch.Tensor
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: torch.Tensor, v2: int=5, v3: str='replicate') -> torch.Tensor:
v4 =... |
Imports:
```python
import torch
from sklearn.metrics.pairwise import cosine_similarity
import typing
```
Type definitions:
Input Types: str, List[str], List[str], str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: List[str], v3: List[str], v4: str):
(v5, v6) = self.... |
Imports:
```python
import typing
```
Type definitions:
Input Types: commands.Context, discord.TextChannel
Output Type: discord.Message
Dependencies:
Function Name: v0
Function:
```python
async def v0(self, v1: commands.Context, v2: discord.TextChannel) -> discord.Message:
v3 = await self._source.get_page(self.cur... |
Imports:
```python
import pickle
import typing
```
Type definitions:
Input Types: List[str]
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: List[str]):
v2 = []
v3 = []
for v4 in v1:
with open(v4, 'rb') as v5:
try:
while True:
... |
Imports:
```python
import pickle
import numpy as np
from gensim.models import FastText
import typing
```
Type definitions:
Input Types: str, str
Output Type: Union[Dict, Any]
Dependencies:
```python
def v0(v1: str, *v2: np.array) -> Tuple[str, np.array]:
return (v1, np.asarray(v2, dtype='float32'))
```
Function Na... |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: List[cv2.KeyPoint]
Output Type: cv2.KeyPoint
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: List[cv2.KeyPoint]) -> cv2.KeyPoint:
v2 = None
v3 = None
for v4 in v1:
(v5, v6) = self._get_keypo... |
Imports:
```python
import string
import typing
```
Type definitions:
Input Types: bytes
Output Type: Any
Dependencies:
```python
def v0(v1: bytes, v2: str):
assert v1 == decrypt(encrypt(v1, v2), v2)
```
Function Name: v3
Function:
```python
def v3(v4: bytes):
for v5 in ['', 'testpassword', string.printable]:
... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: Dict[str, acme_specs.Array]
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> Dict[str, acme_specs.Array]:
v1 = {}
for v2 in self._agents:
v1[v2] = self._agent_specs[v2].observations.observation
ret... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Dict, int
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Dict, v2: int) -> str:
v3 = ' ' * v2
v4 = ' {}"{}": {},'
v5 = [v4.format(v3, key, self.format_metadata(value, v2 + 4, key)) for (v6, v7) in... |
Imports:
```python
import typing
```
Type definitions:
Input Types: list
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: list) -> bool:
if 'token' not in v1 or not v1['token']:
return False
if 'data_interval' not in v1 or not v1['data_interval']:
return F... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int, float, float, bool, float, float, float
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int, v2: float, v3: float, v4: bool, v5: float, v6: float, v7: float) -> None:
self.pad_compound.set(v1 + 1)
s... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Dict, Dict
Output Type: Dict
Dependencies:
```python
def v0(v1: Dict, v2) -> Dict:
v3 = {}
v4 = sorted(v1.items(), key=lambda _s: (_s[0] in PACKAGES_SECTIONS, _s))
for (v5, v6) in v4:
if v5 not in PACKAGES_SECTIONS:
v3[... |
Imports:
```python
from collections import defaultdict
import typing
```
Type definitions:
```python
v0 = TypeVar('A')
```
```python
v1 = TypeVar('B')
```
Input Types: Dict[v0, v1]
Output Type: Dict[v1, List[v0]]
Dependencies:
Function Name: v2
Function:
```python
def v2(v3: Dict[v0, v1]) -> Dict[v1, List[v0]]:
v4... |
Imports:
```python
from pathlib import Path
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
```python
def v0(v1: Path) -> str:
return v1.as_posix()
```
Function Name: v2
Function:
```python
def v2(self) -> None:
def v3(v4: Path) -> str:
return v4.as_posix()
v5 = [... |
Imports:
```python
import torch as th
import torch.distributions as td
import typing
```
Type definitions:
Input Types: th.Tensor
Output Type: th.Tensor
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: th.Tensor) -> th.Tensor:
v2 = self._action_sigma if self._is_train_mode else 0.0
v3 = th... |
Imports:
```python
from functools import reduce
import typing
```
Type definitions:
```python
v0 = TypeVar('S')
```
```python
v1 = TypeVar('T')
```
Input Types: Callable[[v0, List[v1]], v0], List[v1], v0, int
Output Type: Any
Dependencies:
```python
def v2(v3: List[v1], v4: int) -> Generator[List[v1], None, None]:
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: str
Dependencies:
```python
def v0(v1: str) -> str:
v2 = {'A': 'U', 'T': 'A', 'G': 'C', 'C': 'G'}
v3 = ''
for v4 in v1:
v3 = v3 + v2[v4]
return v3
```
Function Name: v5
Function:
```python
def v5(v6: str) -> st... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any, Any
Output Type: dict
Dependencies:
Function Name: v0
Function:
```python
def v0(v1, v2) -> dict:
v3 = v1.get('NEMSPDCaseFile').get('NemSpdInputs').get('PeriodCollection').get('Period').get('InterconnectorPeriodCollection').get('Interconnect... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
async def v0(self, v1: str) -> None:
for v2 in self.plugins:
await v2.on_cache_miss(v1)
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: pd.Series, pd.Series
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: pd.Series, v2: pd.Series) -> None:
v3 = -v2.amount / v1.amount
self._wallet.add(v1.asset, amount=v1.amount, price=v3, fee=v2.fee)
... |
Imports:
```python
import torch
import torch.nn as nn
import torch.nn.functional as F
import typing
```
Type definitions:
Input Types: torch.Tensor, torch.Tensor
Output Type: torch.Tensor
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: torch.Tensor, v2: torch.Tensor) -> torch.Tensor:
v3 = F.c... |
Imports:
```python
import typing
```
Type definitions:
```python
v0 = TypeVar('T')
```
Input Types: Union[List[v0], Tuple[v0, ...]], Callable[[v0], str]
Output Type: List[v0]
Dependencies:
Function Name: v1
Function:
```python
def v1(v2: Union[List[v0], Tuple[v0, ...]], *, v3: Callable[[v0], str]=str) -> List[v0]:
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: int) -> str:
v2: int = 0
v3: str = str()
while v2 != len(str(v1)):
v3 += str(v1)[v2]
if not v2 + 1 >= len(str(v1)):
if int(str... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Quotecast.Request
Output Type: Optional[bool]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Quotecast.Request) -> Optional[bool]:
v2 = self.connection_storage.session_id
v3 = self.session_storage.session
v4 = self.l... |
Imports:
```python
import urllib
from urllib.parse import quote, urlencode
import typing
```
Type definitions:
Input Types: str, str
Output Type: Tuple[str, str, Optional[str], Optional[str], Optional[dict]]
Dependencies:
```python
def v0(v1: str) -> Tuple[Optional[str], Optional[int], Optional[dict]]:
v2 = self._... |
Imports:
```python
import typing
```
Type definitions:
Input Types: datetime
Output Type: List[int]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: datetime) -> List[int]:
(v2, v3, v4, v5, v6, v6, v6, v6, v6) = v1.timetuple()
return [v2, v3, v4, v5]
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0() -> int:
v1: List[int] = []
with open('input.txt', 'r') as v2:
for v3 in v2:
v1.extend([int(s) for v4 in v3.split(',')])
for v5 in range(80)... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: dict
Dependencies:
Function Name: v0
Function:
```python
def v0() -> dict:
v1 = {'kafka': ['pykafka==2.8.*'], 'couchbase': ['couchbase==2.5.*'], 'postgres': ['sqlalchemy==1.3.*', 'psycopg2==2.8.*'], 'mssql': ['pyodbc==4.0.*', 'sqlal... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str) -> str:
for (v2, v3) in iter(tuple({':aqua;': ':#0ff;', ':blue;': ':#00f;', ':fuchsia;': ':#f0f;', ':yellow;': ':#ff0;'}.items())):
v1 = v1.replace(v... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: tuple
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str) -> tuple:
self.fw('\x08' * len(v1))
self.console.print(f'[white]{v1}[/white]', end='')
return (False, '')
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: Tuple[int, int]
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Tuple[int, int]):
self.window_resolution = v1
self.ui_window_stack.window_resolution = v1
self.root_container.set_dimensions(v1)
``` |
Imports:
```python
import re
import typing
```
Type definitions:
Input Types:
Output Type: Union[str, None]
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> Union[str, None]:
v1 = re.match('data:[a-zA-Z]+/[a-zA-Z0-9]+;base64,(?P<contents>.+)', self.contents)
return v1 and v1.groupdict()['c... |
Imports:
```python
import random
import typing
```
Type definitions:
Input Types: Any, Any, Any
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(v1=settings.SHORT_URL_LENGTH, v2=None, v3=settings.ALPHABET) -> str:
if v2:
return v2
return ''.join((random.SystemRandom().choice... |
Imports:
```python
from scipy.optimize import minimize, LinearConstraint
from scipy.interpolate import interp1d
import pandas as pd
import numpy as np
import typing
```
Type definitions:
Input Types: int, bool
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int=11, v2: bool=True)... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str) -> int:
if v1.lower().startswith(self._strategies_light):
v2 = ':'.join(v1.split(':', 2)[:2])
return len(v2)
return v1.find(':')
``... |
Imports:
```python
import io
from matplotlib import figure
import matplotlib.pyplot as plt
import numpy as np
from PIL import Image
from matplotlib.animation import FFMpegFileWriter
from matplotlib import collections as mc
import matplotlib.patches as patches
from matplotlib.patches import Circle, Wedge
import scipy.st... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int, list
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int, v2: list):
if v2[v1] != -1:
return v2[v1]
if v1 < 2:
v2[v1] = 1
else:
v2[v1] = self.fib(v1 - 1, v2) + self.fib(v1... |
Imports:
```python
import typing
```
Type definitions:
Input Types: float
Output Type: (float, float)
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: float) -> (float, float):
v2 = 0
while v1 >= 10:
v2 += 1
v1 /= 10
while v1 < 1:
v2 -= 1
v1 *= 10
return (... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1) -> None:
self._fetched = True
self.related_objects = v1
``` |
Imports:
```python
import tensorflow as tf
import typing
```
Type definitions:
Input Types: Optional[tf.distribute.InputContext]
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Optional[tf.distribute.InputContext]=None):
if self._shards:
v2 = tf.data.Dataset.from_tens... |
Imports:
```python
import pandas as pd
import typing
```
Type definitions:
Input Types: pd.DataFrame
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: pd.DataFrame):
v2 = self.col_tf.transformers_[0][1].inverse_transform(v1[self.non_nominal_col])
v3 = pd.DataFrame(v2, colum... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, str, str
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: str, v3: str) -> str:
v2 = v2.replace('"', '\\"')
v2 = v2.replace("'", "\\'")
return ' <!-- {} -->\n <string name="{}">{}</... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str) -> str:
if v1.startswith('#'):
return ''
v2 = v1.rsplit('#', 1)[0]
if v2.count('"') % 2 == 0 and v2.count("'") % 2 == 0:
return v2.st... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int) -> int:
super().read_wire_out(v1)
v2 = self._simulated_response_queues['wire_outs']
v3 = v2[v1]
v4 = v3.get_nowait()
if not isinstance(... |
Imports:
```python
import json
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
while True:
try:
self.queue.put(json.loads(self._read_payload()))
except ValueError:
break
ex... |
Imports:
```python
import typing
```
Type definitions:
Input Types: dict
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: dict):
v2 = v1['name']
v3 = v1['value']
if v2 == 'cmap_min':
self.set_low(v3)
elif v2 == 'cmap_mid':
self.set_mid(v3)
elif ... |
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