


'''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


UpperCamelCase__    					=      logging.get_logger(__name__)





def 					a__       (					lowerCAmelCase__						)    ->	Tuple:
    UpperCAmelCase__			:		Any													=				R'''\w+[.]\d+'''
    UpperCAmelCase__			:		Union[str, Any]													=				re.findall(__a  ,					__a						)
    for pat in pats:
        UpperCAmelCase__			:		int													=				key.replace(__a  ,					'''_'''.join(pat.split('''.'''						)						)						)
    return key





def 					a__       (					lowerCAmelCase__  ,					lowerCAmelCase__  ,					lowerCAmelCase__						)    ->	Tuple:
    UpperCAmelCase__			:		Dict													=				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)
    ):
        UpperCAmelCase__			:		Dict													=				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:
        UpperCAmelCase__			:		Optional[int]													=				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:
        UpperCAmelCase__			:		Union[str, Any]													=				pt_tuple_key[:-1] + ('''embedding''',)
        return renamed_pt_tuple_key, pt_tensor

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

    # linear layer
    UpperCAmelCase__			:		Dict													=				pt_tuple_key[:-1] + ('''kernel''',)
    if pt_tuple_key[-1] == "weight":
        UpperCAmelCase__			:		Union[str, Any]													=				pt_tensor.T
        return renamed_pt_tuple_key, pt_tensor

    # old PyTorch layer norm weight
    UpperCAmelCase__			:		Dict													=				pt_tuple_key[:-1] + ('''weight''',)
    if pt_tuple_key[-1] == "gamma":
        return renamed_pt_tuple_key, pt_tensor

    # old PyTorch layer norm bias
    UpperCAmelCase__			:		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 					a__       (					lowerCAmelCase__  ,					lowerCAmelCase__  ,					lowerCAmelCase__=42						)    ->	Optional[int]:
    UpperCAmelCase__			:		Tuple													=				{k: v.numpy() for k, v in pt_state_dict.items()}

    # Step 2: Since the model is stateless, get random Flax params
    UpperCAmelCase__			:		List[Any]													=				flax_model.init_weights(PRNGKey(__a						)						)

    UpperCAmelCase__			:		Optional[int]													=				flatten_dict(__a						)
    UpperCAmelCase__			:		Tuple													=				{}

    # Need to change some parameters name to match Flax names
    for pt_key, pt_tensor in pt_state_dict.items():
        UpperCAmelCase__			:		List[str]													=				rename_key(__a						)
        UpperCAmelCase__			:		Optional[Any]													=				tuple(renamed_pt_key.split('''.'''						)						)

        # Correctly rename weight parameters
        UpperCAmelCase__			:		List[str]													=				rename_key_and_reshape_tensor(__a  ,					__a  ,					__a						)

        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
        UpperCAmelCase__			:		Dict													=				jnp.asarray(__a						)

    return unflatten_dict(__a						)



def    __UpperCAmelCase (	__a      :			float	)			->     float:

					"""simple docstring"""

					return 10 - x * x



def    __UpperCAmelCase (	__a      :			float		,__a      :			float	)			->     float:

					"""simple docstring"""

					if equation(__a	) * equation(__a	) >= 0:
										raise ValueError('''Wrong space!'''	)

					_a	:    Dict         =		a
					while (b - a) >= 0.01:
										# Find middle point
										_a	:    Any         =		(a + b) / 2
										# Check if middle point is root
										if equation(__a	) == 0.0:
															break
										# Decide the side to repeat the steps
										if equation(__a	) * equation(__a	) < 0:
															_a	:    str         =		c
										else:
															_a	:    Union[str, Any]         =		c
					return c


if __name__ == "__main__":
			import doctest

			doctest.testmod()

			print(bisection(-2, 5))
			print(bisection(0, 6))



