text stringlengths 190 325k |
|---|
Imports:
```python
import math
import typing
```
Type definitions:
Input Types: str, int
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str, v2: int) -> str:
v3 = v2 - len(v1)
v4 = math.floor(v3 / 2)
v5 = math.ceil(v3 / 2)
return f"{' ' * v4}{v1}{' ' * v5}"
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str):
self.attr_name_stack.append(self.cur_attr_name)
self.cur_attr_name = self.cur_attr_name + '.' + v1 if self.cur_attr_name else v1
``` |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: str
Output Type: typing.Dict[str, np.ndarray]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str) -> typing.Dict[str, np.ndarray]:
print('Loading Glove Model')
v2 = open(v1, 'r', encoding='utf-8', errors='ig... |
Imports:
```python
import typing
```
Type definitions:
```python
@dataclass
class v0:
v1: Any
v2: Any
v3: Optional['Node'] = None
v4: Optional['Node'] = None
v5: Optional['Node'] = None
v6: int = 0
```
Input Types: v0
Output Type: None
Dependencies:
Function Name: v7
Function:
```python
def v7(... |
Imports:
```python
import pandas as pd
import typing
```
Type definitions:
Input Types: pd.DataFrame, Any
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: pd.DataFrame, v2):
v3 = v1.min(axis=1)
v4 = v1.eq(v3, axis='rows').sum(axis=0)
v5 = v1.ge(v2, axis='rows').sum(axis=0)
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: dict, str, Any, Any
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: dict, v2: str, v3, v4=''):
try:
v5 = v3()
except Exception:
v5 = v4
v1[v2] = v5
return v5
``` |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: list
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: list):
assert all([isinstance(d, np.ndarray) for v2 in v1])
assert all([v2.shape[1] == v1[0].shape[1] for v2 in v1])
assert all([all(v... |
Imports:
```python
import typing
```
Type definitions:
Input Types: 'FileProxy'
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: 'FileProxy'):
if not v1:
return None
if v1.path is None:
raise ValueError('file has no path')
return v1.path
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, int
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str, v2: int) -> str:
(v3, v4, v5) = (v1, '', '')
while len(v3) > 0 and (not v3[-1].isdigit()):
v5 = v3[-1] + v5
v3 = v3[:-1]
if not ... |
Imports:
```python
from base64 import b64encode
import typing
```
Type definitions:
Input Types: str
Output Type: Tuple[str, str]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str) -> Tuple[str, str]:
v2 = str()
v3 = str()
if not v1:
return (v2, v3)
if not isinstance(v1, str):... |
Imports:
```python
import datetime
import typing
```
Type definitions:
Input Types: Any
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1) -> int:
v2 = datetime.datetime.now() - datetime.timedelta(seconds=v1)
v3 = 0
for v4 in reversed(self._logs):
if v4['time_rec... |
Imports:
```python
import torch
import torch.nn as nn
import torch.nn.functional as nf
from torch.distributions import Distribution
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str):
if v1 == 'fit':
if self.pre_t... |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: tp.ArrayLike
Output Type: np.ndarray
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: tp.ArrayLike) -> np.ndarray:
v2 = self.transform_var.process(v1)
return np.array(v2)
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: List[str], str
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: List[str], v2: str) -> str:
for v3 in v1:
if v3.startswith(v2):
return v3
raise ValueError("Can't find dir matching '%s' in %s"... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Path
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Path):
for v2 in v1.open('r').readlines():
if 'password:' not in v2:
continue
v3 = v2.split('password:')[-1].strip()
if... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Text
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Text=None):
v2 = self.git_repo.git
v2.reset('HEAD', v1)
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, int
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: int):
v3 = ['[MAJOR]', '[MINOR]', '[INFO]']
if v2 == 0:
self.major += 1
elif v2 == 1:
self.minor += 1
else:
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any, nx.MultiDiGraph
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1, v2: nx.MultiDiGraph):
v3 = []
for v4 in v1:
v5 = v2.edges[v4[0][0], v4[0][1], 0]
v5['type'] = 'segment'
v5['has... |
Imports:
```python
import typing
```
Type definitions:
Input Types: dict
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: dict=None):
v2 = f'{self.endpoint}/v1/unit-amenity-properties'
v3 = self._headers()
return self._iterate_pages(v2, v3, v1)
``` |
Imports:
```python
import logging
import sys
import typing
```
Type definitions:
Input Types: bool
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: bool):
logging.basicConfig(level=logging.INFO, format='%(message)s', stream=sys.stdout)
if v1:
logging.getLogger().setLevel... |
Imports:
```python
import sys
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0() -> None:
global last_arguments
v1 = sys.argv
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: 'pl.Trainer'
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: 'pl.Trainer') -> None:
v2 = self._monitor_candidates(v1)
self._save_topk_checkpoint(v1, v2)
self._save_last_checkpoint(v1, v2)
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: list, bool
Output Type: float
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: list, v2: bool) -> float:
v3 = self.results.LossFunctionPerformance(v2, v1)
return v3[0]
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: int, int, Number
Output Type: Number
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int, v2: int, v3: Number=INF) -> Number:
if v1 == v2 or v3 == 0:
return v3
for v4 in range(self.last[v1], len(self.AL[v1])):
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Dict[int, Dict[str, Any]]
Output Type: int
Dependencies:
```python
def v0(v1: Dict[int, Dict[str, Any]]) -> Dict[int, Dict[str, Any]]:
return find_tiles_with_neighbours(2, v1)
```
```python
def v2(v3: int, v4: Dict[int, Dict[str, Any]]) -> Dict[in... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Optional[bool], Optional[bool]
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
async def v0(self, *, v1: Optional[bool]=None, v2: Optional[bool]=None) -> None:
v3 = {'send': v1, 'recv': v2}
v3 = {k: v for (v4, v5) in v3.... |
Imports:
```python
import os
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str):
os.makedirs(v1, exist_ok=True)
os.makedirs(os.path.join(v1, 'edw_temp'), exist_ok=True)
``` |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: np.array
Output Type: np.array
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: np.array) -> np.array:
v1 = np.array(v1)
if len(v1.shape) == 1:
v1 = v1.reshape(1, -1)
return self.model.predic... |
Imports:
```python
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import style
from matplotlib.patches import Ellipse
import typing
```
Type definitions:
Input Types: List[float], bool
Output Type: Any
Dependencies:
```python
def v0(v1: List[float]) -> dict:
v2 = np.diff(v1)
v3 = np.sqrt(np... |
Imports:
```python
import typing
```
Type definitions:
```python
class v0:
def __init__(self, v1):
self._guilds = v1
def v2(self):
"""Synchronously retrieves the data for all guilds saved in the database
Returns
-------
dict
All the guilds saved in t... |
Imports:
```python
import typing
```
Type definitions:
Input Types: 'str'
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: 'str') -> str:
with open(v1) as v2:
v3 = v2.read()
v4 = v3.split('#define Scope_ChannelTrigger ')[1].split('\n')[0]
return v4
``` |
Imports:
```python
import numpy as np
from datetime import date, datetime, timedelta
import typing
```
Type definitions:
Input Types: dict
Output Type: dict
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: dict) -> dict:
v2 = {'BOOLEAN': str, 'DATE': datetime, 'DATETIME': datetime, 'FLOAT': np.float... |
Imports:
```python
import typing
```
Type definitions:
Input Types: node.TopLevelNode
Output Type: list[str]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: node.TopLevelNode) -> list[str]:
v2 = []
for v3 in v1.labels.all():
v2.append(v3.name)
return v2
``` |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: 'VladEncoder'
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: 'VladEncoder') -> None:
self.num_clusters = v1.num_clusters
self.centroids = v1.centroids
self.centroids_l2 = v1.centr... |
Imports:
```python
import typing
```
Type definitions:
Input Types: DataFrame, Hashable, str, Any
Output Type: Tuple[DataFrame, str]
Dependencies:
```python
def v0(v1: str) -> bool:
return name_comparator in [f'{var_name}__{v1}' for v2 in var_names]
```
Function Name: v3
Function:
```python
def v3(v4: DataFrame, v... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1) -> None:
v2 = ''
with open(v1['file'], 'r') as v3:
v2 = v3.readlines()
v2[v1['line_number'] - 1] = v1['data'] + '\n'
with open(v1['... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
self._state_thread.start()
self.ble_status.encoding_active.register_value_update()
self.ble_status.system_ready.register_value_update()
self.... |
Imports:
```python
import json
import typing
```
Type definitions:
Input Types: str
Output Type: List[Dict[Any, Any]]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str) -> List[Dict[Any, Any]]:
v2 = json.JSONDecoder()
v3 = 0
v4 = []
while v3 < len(v1):
if v1[v3] in ' \t\n\r':
... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: List[List[str]]
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> List[List[str]]:
v1 = self._get_number_of_columns()
v2 = []
for v3 in v1:
v4 = []
for v5 in range(1, v3 + 1):
if... |
Imports:
```python
import json
import logging
import os
import typing
```
Type definitions:
Input Types: str
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str) -> None:
for v2 in ['bin']:
if v2 in self.release_manifest:
del self.release_manifest[v2]
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Union[int, None], str
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Union[int, None], v2: str) -> str:
v3 = self.__get_latest_messages(v1)
v4 = self.__get_group_titles()
v5 = self.__create_messages_... |
Imports:
```python
from csv import DictReader, DictWriter
from Bio.Seq import Seq
import typing
```
Type definitions:
Input Types: Union[str, Path], Optional[Dict[Seq, Seq]]
Output Type: Dict[Seq, Seq]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: Union[str, Path], v2: Optional[Dict[Seq, Seq]]=None) ... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: Tuple[str, List[str]]
Dependencies:
Function Name: v0
Function:
```python
def v0() -> Tuple[str, List[str]]:
v1 = ['chapter_id INTEGER PRIMARY KEY', 'series_id INTEGER', "chapter_title TEXT NOT NULL DEFAULT ''", 'chapter_number INTE... |
Imports:
```python
import numpy
import typing
```
Type definitions:
Input Types: Sequence[int]
Output Type: Any
Dependencies:
```python
def v0(v1):
def v2(*v3, **v4):
v5 = v3[0]
v6 = v5.ndim
if v6 in available_dims:
return v1(*v3, **v4)
else:
v7 = min(availa... |
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 = ''
if v1 in self.default_config and self.default_config[v1]:
v2 = ' '.join([key + ':' + val for (v3, v4) in self.default_confi... |
Imports:
```python
import os
import glob
import argparse
import tqdm
import numpy as np
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
```python
def v0(v1: str) -> namedtuple:
v2 = torchaudio.info(v1)
if hasattr(v2, 'num_frames'):
return Info(v2.num_frames, v2.sample_... |
Imports:
```python
from urllib.request import Request, urlopen, HTTPError
import typing
```
Type definitions:
Input Types: str, Any, int
Output Type: (int, List[List[str]])
Dependencies:
```python
def v0(v1):
v2 = ''
while v2 == '':
try:
print('Download string from ' + v1)
v3 = ... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, int, List[List[Path]], List[Path], List[int], List[str]
Output Type: None
Dependencies:
```python
def v0(v1: str, v2: int, v3: int) -> Tuple[List[Path], Path]:
v4: List[Path] = []
v4.append(*list(DATA_ROOT.glob(f'**/*{v1}_0{v2}_flair_pp.n... |
Imports:
```python
import json
import typing
```
Type definitions:
Input Types: str, str
Output Type: Any
Dependencies:
```python
def v0(v1: str) -> Dict[str, str]:
v2 = v1.split('|')
return {'Book': v2[0], 'Chapter': int(v2[1]), 'Verse': int(v2[2]), 'Text': v2[3][1:-1]}
```
Function Name: v3
Function:
```pyth... |
Imports:
```python
import numpy as np
from pandas._libs import lib
import pandas._libs.sparse as splib
from pandas._libs.sparse import BlockIndex, IntIndex, SparseIndex
from pandas._libs.tslibs import NaT
from pandas._typing import ArrayLike, AstypeArg, Dtype, NpDtype, PositionalIndexer, Scalar, ScalarIndexer, Sequence... |
Imports:
```python
import logging
import logging.handlers
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
if not self._active:
return
logging.info('Closing plugin')
self._connection.close()
self._exte... |
Imports:
```python
from pandas._libs import internals as libinternals, lib
from pandas._typing import ArrayLike, Dtype, DtypeObj, Shape
from pandas.errors import PerformanceWarning
from pandas.util._validators import validate_bool_kwarg
from pandas.core.dtypes.cast import find_common_type, infer_dtype_from_scalar
from ... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> str:
v1 = self
v2 = ''
while v1:
if v1.is_root:
v2 = v1.prefix + v1.main_splitter + v2
break
else:
v... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: Optional[str]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str) -> Optional[str]:
v2 = f'{self.internal_module.__name__}.'
v3 = v1[len(self.namespace) + 1:] if v1.startswith(self.namespace + '.') else ... |
Imports:
```python
import typing
```
Type definitions:
Input Types: pd.DataFrame
Output Type: pd.DataFrame
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: pd.DataFrame) -> pd.DataFrame:
v1 = super().normalize(v1)
v2 = {'Mcnairy': 'McNairy', 'Mcminn': 'McMinn', 'Dekalb': 'DeKalb'}
v1['... |
Imports:
```python
import torch
import typing
```
Type definitions:
Input Types: list, list
Output Type: torch.Tensor
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: list, v2: list) -> torch.Tensor:
v1 = torch.stack(v1).float()
v2 = torch.stack(v2).float()
(v3, v4) = (v1.shape[0], v2.... |
Imports:
```python
import os
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.isfile(v1):
raise RuntimeError(f'Bamfile {v1} not found!')
v2 = v1.replace('.bam', '.bai')
if os.path.isfile... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int
Output Type: bytes
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int=-1) -> bytes:
if self._closed:
return b''
if v1 == -1:
return self.readall()
try:
while len(self._buffer) < v1:
... |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: bool
Output Type: List[str]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: bool=False) -> List[str]:
if not self.is_built:
return ['<%s>\n' % self.__class__.__name__, f' ntimes: {self.ntimes:d}\n'... |
Imports:
```python
import tensorflow as tf
import typing
```
Type definitions:
Input Types:
Output Type: tf.Tensor
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> tf.Tensor:
v1 = tf.matmul(self.input_tensor, self.weights['h1'])
v2 = tf.add(v1, self.biases['b1'])
v3 = tf.nn.relu(v2)
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: List[List[str]]
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: List[List[str]]) -> None:
if not v1 or not v1[0]:
return
(self.m, self.n) = (len(v1), len(v1[0]))
self.solveDFS(v1, 0, 0)
``` |
Imports:
```python
import re
import typing
```
Type definitions:
Input Types: 'str', 'Sequence[str]', Any
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: 'str', v2: 'Sequence[str]', v3=False):
v4 = re.compile('|'.join(v2), re.MULTILINE)
v5 = -1
for v6 in v4.finditer(v1):
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int, str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int, v2: str):
v3 = [[8, 1, 0], [8, 2, v1], [11, 3, v2]]
v4 = self.generateDummyProtocol('updateProfileAttribute', v3, 4)
return self.postPackD... |
Imports:
```python
import signal
import sys
import traceback
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
```python
def v0(v1: Any, v2: Any) -> None:
traceback.print_stack(v2, file=sys.stderr)
if callable(old_handler):
old_handler(v1, v2)
```
Function Name: v3
Funct... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: 'Pipette.DictType'
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> 'Pipette.DictType':
self._config_as_dict.update({'current_volume': self.current_volume, 'available_volume': self.available_volume, 'name': self.n... |
Imports:
```python
import urllib.parse as parse
import typing
```
Type definitions:
Input Types: str
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str) -> str:
v2 = parse.urlparse(v1)
v3 = v2[2]
if v2[3] != '':
v3 += ';' + v2[3]
if v2[4] != '':
v3 += '... |
Imports:
```python
import typing
```
Type definitions:
Input Types: List[int], List[int]
Output Type: List[int]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: List[int], v2: List[int]) -> List[int]:
v3: set = set()
for v4 in v1:
for v5 in v2:
if v4 == v5:
... |
Imports:
```python
import json
import requests
import typing
```
Type definitions:
Input Types: [str], str, dict, dict, dict, dict
Output Type: Iterator[dict]
Dependencies:
```python
def v0(v1: requests.Response, v2: int):
if v1.status_code != v2:
raise RequestException(v1)
```
Function Name: v3
Function:
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: dendropy.Tree
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: dendropy.Tree):
self.tree = v1
self.tree.resolve_polytomies()
v2 = 0
for v3 in self.tree.postorder_node_iter():
if v3 == self.... |
Imports:
```python
from collections import deque
import typing
```
Type definitions:
Input Types: List[int], int
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: List[int], v2: int) -> int:
(v3, v4) = (deque([0] * 7), deque([0, 0]))
for v5 in v1:
v3[v5] += 1
for v6 i... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> str:
self.uid_count += 1
return f'__cse_{self.uid_count}'
``` |
Imports:
```python
import typing
```
Type definitions:
```python
@dataclass(frozen=True)
class v0:
v1: str
v2: str = '1.0'
v3: str = ''
v4: int = 0
v5: str = ''
v6: FrozenSet[str] = field(default_factory=frozenset)
v7: int = field(default_factory=lambda : int(time.mktime(time.gmtime()) * 100... |
Imports:
```python
import inspect
from datetime import datetime
import typing
```
Type definitions:
```python
class v0:
def __init__(self, v1: 'PandasStore', v2: str):
self.store = v1
self.path = v2
@property
def v3(self):
return self.store.get_storer(self.path).attrs
def v4(s... |
Imports:
```python
import logging
from tqdm import tqdm
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str):
logging.info(f'Reading file into dict: {v1}')
print(f'This will fail if you have not downloaded or generated ... |
Imports:
```python
from pathlib import Path
import numpy as np
import typing
```
Type definitions:
Input Types: float, List[float], int, Union[int, float]
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: float, v2: List[float], v3: int=None, v4: Union[int, float]=None) -> None:
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: float, str
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: float, v2: str='hms') -> str:
(v3, v4) = divmod(v1, 60)
if v2 == 'ms':
v5 = '{:d}m:{:02d}s'.format(int(v3), int(v4))
elif v2 == 'hms':
... |
Imports:
```python
import torch
import typing
```
Type definitions:
```python
v0 = Dict[str, torch.Tensor]
```
Input Types: Mapping[str, np.ndarray], Sequence[str]
Output Type: v0
Dependencies:
Function Name: v1
Function:
```python
def v1(v2: Mapping[str, np.ndarray], v3: Sequence[str]) -> v0:
v4 = {k: torch.tenso... |
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 = ''
v3 = 2 * len(v1) + 1
v4 = 0
for v5 in range(v3):
if v5 % 2 == 1:
v2 += v1[v4]
v4 += 1
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: Optional[Dict[str, int]]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str) -> Optional[Dict[str, int]]:
v2 = self.object.getTermPositions(self.reader, v1)
if v2 is None:
return None
v3 = {}... |
Imports:
```python
import typing
```
Type definitions:
Input Types: 'TreeNode', 'TreeNode', 'TreeNode'
Output Type: 'TreeNode'
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: 'TreeNode', v2: 'TreeNode', v3: 'TreeNode') -> 'TreeNode':
if v1.val == v2 or v1.val == v3:
return v1
if v... |
Imports:
```python
import typing
```
Type definitions:
Input Types: bool
Output Type: dict[str, Any]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: bool=True) -> dict[str, Any]:
v2 = self.emoji() if v1 else self.score
return {'n': self.n, 'Soln': str(self.soln), 'Guess': str(self.guess),... |
Imports:
```python
import logging
import re
import typing
```
Type definitions:
```python
class v0:
def __init__(self, v1: str, v2: str, v3: int, v4: int, v5: Optional[str]=None, v6: Optional[str]=None):
self.filepath = v1
self.description = v2
self.line_number = v3
self.line_count ... |
Imports:
```python
import numpy as np
import tensorflow as tf
import typing
```
Type definitions:
Input Types: Tuple[np.ndarray, np.ndarray], tf.keras.Model, int, int
Output Type: np.ndarray
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: Tuple[np.ndarray, np.ndarray], v2: tf.keras.Model, v3: int, v4: ... |
Imports:
```python
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.utils.data import Dataset
from torch.utils.data import DataLoader
from torch.utils.data import TensorDataset
from torch.nn.utils.rnn import pack_sequence
from torch.nn.utils.rnn import pad_packed_sequence
from torch.nn.util... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1) -> bool:
v2 = self.get_standby()
return any((v1 in mgr for v3 in v2))
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, Mapping[str, str]
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: Mapping[str, str]) -> str:
v3 = v2.copy()
v3['__value__'] = v1
return self.format_env(v3, self.global_env)['__value__']
... |
Imports:
```python
import typing
```
Type definitions:
```python
class v0:
@overload
def __init__(self, v1: Iterable, v2: bool=False) -> v0:
...
@overload
def __init__(self, v3: List[int, int], v4: bool=True) -> v0:
...
@overload
def __init__(self, v5: Tuple[int, int], v6: boo... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(self, **v1) -> bool:
v2 = self.raw_param.get('no_wait')
return v2
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: dict, str, list
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: dict, v2: str, v3: list):
if v2.lower() in v1['name'] or v2.lower() in v1['id']:
v3.append(v1)
``` |
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(self, v1: np.ndarray) -> np.ndarray:
v2 = np.zeros_like(v1[:-1], dtype=float)
for (v3, v4) in zip(self.grows.dist0_fr, self.grows... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int, List[float]
Output Type: Tuple[List[float], List[float], List[float]]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: int, v2: List[float]) -> Tuple[List[float], List[float], List[float]]:
v3 = [v2[i] / (v2[i] + v2[i + 1]) for... |
Imports:
```python
import typing
```
Type definitions:
Input Types: float
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: float):
v2 = str(v1)
v3 = v2.find('.')
v4 = 0
for (v5, v6) in enumerate(v2[:v3]):
v4 += int(v6) * 2 ** (v3 - v5 - 1)
for (v5, v6) in enu... |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: np.ndarray
Output Type: float
Dependencies:
```python
def v0(v1: float, v2: float, v3: float) -> float:
assert v3 > v2, 'Upper bound should be larger than lower bound'
if v2 < v1 < v3:
return -np.log(np.log(v3 / v2))... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1) -> bool:
for v2 in ['p', 'g']:
if v2 not in v1.model.keys():
continue
for (v3, v4) in v1.model[v2].items():
for v5 ... |
Imports:
```python
import typing
```
Type definitions:
Input Types: List[int], List[int]
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: List[int], v2: List[int]) -> bool:
v3 = [max(v1[0], v2[0]), max(v1[1], v2[1])]
v4 = [min(v1[2], v2[2]), min(v1[3], v2[3])]
if v3[0... |
Imports:
```python
import datetime
import typing
```
Type definitions:
Input Types: Union[datetime.datetime, int, float, str], bool, Optional[datetime.tzinfo]
Output Type: datetime.datetime
Dependencies:
```python
def v0(v1: str) -> datetime.datetime:
return dateutil.parser.isoparse(v1)
```
Function Name: v2
Funct... |
Imports:
```python
import typing
```
Type definitions:
```python
v0 = TypeVar('T')
```
Input Types: v0
Output Type: Any
Dependencies:
Function Name: v1
Function:
```python
def v1(self, v2: v0):
v3 = self.joined_plaintext_printer
return v3(v2)
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any, Any, Any, Any, Any, Any
Output Type: 'abs_lat_stab_uty'
Dependencies:
Function Name: v0
Function:
```python
def v0(v1, v2, v3, v4, v5, v6) -> 'abs_lat_stab_uty':
v7 = v6 * (v1 + v4 * v2) / (v4 * v5 + v3)
return v7
``` |
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