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# Copyright (c) Alibaba, Inc. and its affiliates.
from typing import Any, Dict, List, Optional, Tuple, Union
import numpy as np
import pandas as pd
def transform_jsonl_to_df(dict_list: List[Dict[str, Any]]) -> pd.DataFrame:
"""Relevant function: `io_utils.read_from_jsonl()`"""
data_dict: Dict[str, List[Any]] = {}
for i, obj in enumerate(dict_list):
for k, v in obj.items():
if k not in data_dict:
data_dict[k] = [None] * i
data_dict[k].append(v)
for k in set(data_dict.keys()) - set(obj.keys()):
data_dict[k].append(None)
return pd.DataFrame.from_dict(data_dict)
def get_seed(random_state: Optional[np.random.RandomState] = None) -> int:
if random_state is None:
random_state = np.random.RandomState()
seed_max = np.iinfo(np.int32).max
seed = random_state.randint(0, seed_max)
return seed
def stat_array(array: Union[np.ndarray, List[int], 'torch.Tensor']) -> Tuple[Dict[str, float], str]:
if isinstance(array, list):
array = np.array(array)
mean = array.mean().item()
std = array.std().item()
min_ = array.min().item()
max_ = array.max().item()
size = array.shape[0]
string = f'{mean:.6f}±{std:.6f}, min={min_:.6f}, max={max_:.6f}, size={size}'
return {'mean': mean, 'std': std, 'min': min_, 'max': max_, 'size': size}, string
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