
'''simple docstring'''
import random

def 						UpperCamelCase_     (	__SCREAMING_SNAKE_CASE       ):
    """simple docstring"""






    snake_case_ :    Any     			=						num - 1
    snake_case_ :    Union[str, Any]     			=						0

    while s % 2 == 0:
        snake_case_ :    Union[str, Any]     			=						s // 2
        t += 1

    for _ in range(5       ):
        snake_case_ :    str     			=						random.randrange(2,		num - 1       )
        snake_case_ :    Union[str, Any]     			=						pow(__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE       )
        if v != 1:
            snake_case_ :    Tuple     			=						0
            while v != (num - 1):
                if i == t - 1:
                    return False
                else:
                    snake_case_ :    Any     			=						i + 1
                    snake_case_ :    Optional[Any]     			=						(v**2) % num
    return True

def 						UpperCamelCase_     (	__SCREAMING_SNAKE_CASE       ):
    """simple docstring"""






    if num < 2:
        return False

    snake_case_ :    int     			=						[
        2,
        3,
        5,
        7,
        1_1,
        1_3,
        1_7,
        1_9,
        2_3,
        2_9,
        3_1,
        3_7,
        4_1,
        4_3,
        4_7,
        5_3,
        5_9,
        6_1,
        6_7,
        7_1,
        7_3,
        7_9,
        8_3,
        8_9,
        9_7,
        1_0_1,
        1_0_3,
        1_0_7,
        1_0_9,
        1_1_3,
        1_2_7,
        1_3_1,
        1_3_7,
        1_3_9,
        1_4_9,
        1_5_1,
        1_5_7,
        1_6_3,
        1_6_7,
        1_7_3,
        1_7_9,
        1_8_1,
        1_9_1,
        1_9_3,
        1_9_7,
        1_9_9,
        2_1_1,
        2_2_3,
        2_2_7,
        2_2_9,
        2_3_3,
        2_3_9,
        2_4_1,
        2_5_1,
        2_5_7,
        2_6_3,
        2_6_9,
        2_7_1,
        2_7_7,
        2_8_1,
        2_8_3,
        2_9_3,
        3_0_7,
        3_1_1,
        3_1_3,
        3_1_7,
        3_3_1,
        3_3_7,
        3_4_7,
        3_4_9,
        3_5_3,
        3_5_9,
        3_6_7,
        3_7_3,
        3_7_9,
        3_8_3,
        3_8_9,
        3_9_7,
        4_0_1,
        4_0_9,
        4_1_9,
        4_2_1,
        4_3_1,
        4_3_3,
        4_3_9,
        4_4_3,
        4_4_9,
        4_5_7,
        4_6_1,
        4_6_3,
        4_6_7,
        4_7_9,
        4_8_7,
        4_9_1,
        4_9_9,
        5_0_3,
        5_0_9,
        5_2_1,
        5_2_3,
        5_4_1,
        5_4_7,
        5_5_7,
        5_6_3,
        5_6_9,
        5_7_1,
        5_7_7,
        5_8_7,
        5_9_3,
        5_9_9,
        6_0_1,
        6_0_7,
        6_1_3,
        6_1_7,
        6_1_9,
        6_3_1,
        6_4_1,
        6_4_3,
        6_4_7,
        6_5_3,
        6_5_9,
        6_6_1,
        6_7_3,
        6_7_7,
        6_8_3,
        6_9_1,
        7_0_1,
        7_0_9,
        7_1_9,
        7_2_7,
        7_3_3,
        7_3_9,
        7_4_3,
        7_5_1,
        7_5_7,
        7_6_1,
        7_6_9,
        7_7_3,
        7_8_7,
        7_9_7,
        8_0_9,
        8_1_1,
        8_2_1,
        8_2_3,
        8_2_7,
        8_2_9,
        8_3_9,
        8_5_3,
        8_5_7,
        8_5_9,
        8_6_3,
        8_7_7,
        8_8_1,
        8_8_3,
        8_8_7,
        9_0_7,
        9_1_1,
        9_1_9,
        9_2_9,
        9_3_7,
        9_4_1,
        9_4_7,
        9_5_3,
        9_6_7,
        9_7_1,
        9_7_7,
        9_8_3,
        9_9_1,
        9_9_7,
    ]

    if num in low_primes:
        return True

    for prime in low_primes:
        if (num % prime) == 0:
            return False

    return rabin_miller(__SCREAMING_SNAKE_CASE       )

def 						UpperCamelCase_     (	__SCREAMING_SNAKE_CASE = 1_0_2_4       ):
    """simple docstring"""






    while True:
        snake_case_ :    Optional[int]     			=						random.randrange(2 ** (keysize - 1),		2 ** (keysize)       )
        if is_prime_low_num(__SCREAMING_SNAKE_CASE       ):
            return num


if __name__ == "__main__":
  a_											=						generate_large_prime()
  print(("Prime number:", num))
  print(("is_prime_low_num:", is_prime_low_num(num)))


'''simple docstring'''
import re

import jax.numpy as jnp
from flax.traverse_util import flatten_dict, unflatten_dict
from jax.random import PRNGKey

from ..utils import logging


a_											=						logging.get_logger(__name__)

def 						UpperCamelCase_     (	__SCREAMING_SNAKE_CASE       ):
    """simple docstring"""






    snake_case_ :    List[Any]     			=						r"\w+[.]\d+"
    snake_case_ :    Tuple     			=						re.findall(__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE       )
    for pat in pats:
        snake_case_ :    Union[str, Any]     			=						key.replace(__SCREAMING_SNAKE_CASE,		"_".join(pat.split("."       )       )       )
    return key

def 						UpperCamelCase_     (	__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE       ):
    """simple docstring"""






    snake_case_ :    Tuple     			=						pt_tuple_key[:-1] + ("scale",)
    if (
        any("norm" in str_ for str_ in pt_tuple_key       )
        and (pt_tuple_key[-1] == "bias")
        and (pt_tuple_key[:-1] + ("bias",) not in random_flax_state_dict)
        and (pt_tuple_key[:-1] + ("scale",) in random_flax_state_dict)
    ):
        snake_case_ :    int     			=						pt_tuple_key[:-1] + ("scale",)
        return renamed_pt_tuple_key, pt_tensor
    elif pt_tuple_key[-1] in ["weight", "gamma"] and pt_tuple_key[:-1] + ("scale",) in random_flax_state_dict:
        snake_case_ :    Dict     			=						pt_tuple_key[:-1] + ("scale",)
        return renamed_pt_tuple_key, pt_tensor

    # embedding
    if pt_tuple_key[-1] == "weight" and pt_tuple_key[:-1] + ("embedding",) in random_flax_state_dict:
        snake_case_ :    List[Any]     			=						pt_tuple_key[:-1] + ("embedding",)
        return renamed_pt_tuple_key, pt_tensor

    # conv layer
    snake_case_ :    List[str]     			=						pt_tuple_key[:-1] + ("kernel",)
    if pt_tuple_key[-1] == "weight" and pt_tensor.ndim == 4:
        snake_case_ :    str     			=						pt_tensor.transpose(2,		3,		1,		0       )
        return renamed_pt_tuple_key, pt_tensor

    # linear layer
    snake_case_ :    str     			=						pt_tuple_key[:-1] + ("kernel",)
    if pt_tuple_key[-1] == "weight":
        snake_case_ :    Any     			=						pt_tensor.T
        return renamed_pt_tuple_key, pt_tensor

    # old PyTorch layer norm weight
    snake_case_ :    Union[str, Any]     			=						pt_tuple_key[:-1] + ("weight",)
    if pt_tuple_key[-1] == "gamma":
        return renamed_pt_tuple_key, pt_tensor

    # old PyTorch layer norm bias
    snake_case_ :    Union[str, Any]     			=						pt_tuple_key[:-1] + ("bias",)
    if pt_tuple_key[-1] == "beta":
        return renamed_pt_tuple_key, pt_tensor

    return pt_tuple_key, pt_tensor


def 						UpperCamelCase_     (	__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE=4_2       ):
    """simple docstring"""






    snake_case_ :    int     			=						{k: v.numpy() for k, v in pt_state_dict.items()}

    # Step 2: Since the model is stateless, get random Flax params
    snake_case_ :    Optional[int]     			=						flax_model.init_weights(PRNGKey(__SCREAMING_SNAKE_CASE       )       )

    snake_case_ :    Union[str, Any]     			=						flatten_dict(__SCREAMING_SNAKE_CASE       )
    snake_case_ :    str     			=						{}

    # Need to change some parameters name to match Flax names
    for pt_key, pt_tensor in pt_state_dict.items():
        snake_case_ :    List[str]     			=						rename_key(__SCREAMING_SNAKE_CASE       )
        snake_case_ :    Tuple     			=						tuple(renamed_pt_key.split("."       )       )

        # Correctly rename weight parameters
        snake_case_			, snake_case_ :    Dict     			=						rename_key_and_reshape_tensor(__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE       )

        if flax_key in random_flax_state_dict:
            if flax_tensor.shape != random_flax_state_dict[flax_key].shape:
                raise ValueError(
                    f'PyTorch checkpoint seems to be incorrect. Weight {pt_key} was expected to be of shape '
                    f'{random_flax_state_dict[flax_key].shape}, but is {flax_tensor.shape}.'       )

        # also add unexpected weight so that warning is thrown
        snake_case_ :    Any     			=						jnp.asarray(__SCREAMING_SNAKE_CASE       )

    return unflatten_dict(__SCREAMING_SNAKE_CASE       )




