
'''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


lowercase			:				Optional[int]    		=			logging.get_logger(__name__)







def 		lowerCAmelCase_				(   snake_case__						):




    '''simple docstring'''



    A       :   Union[str, Any]					=						R'''\w+[.]\d+'''
    A       :   Optional[int]					=						re.findall(snake_case__		,				snake_case__						)
    for pat in pats:
        A       :   List[Any]					=						key.replace(snake_case__		,				'''_'''.join(pat.split('''.'''						)						)						)
    return key







def 		lowerCAmelCase_				(   snake_case__		,				snake_case__		,				snake_case__						):




    '''simple docstring'''



    A       :   Optional[Any]					=						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)
    ):
        A       :   Tuple					=						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:
        A       :   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:
        A       :   Dict					=						pt_tuple_key[:-1] + ('''embedding''',)
        return renamed_pt_tuple_key, pt_tensor

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

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

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

    # old PyTorch layer norm bias
    A       :   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 		lowerCAmelCase_				(   snake_case__		,				snake_case__		,				snake_case__=42						):




    '''simple docstring'''



    A       :   Dict					=						{k: v.numpy() for k, v in pt_state_dict.items()}

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

    A       :   Optional[Any]					=						flatten_dict(snake_case__						)
    A       :   int					=						{}

    # Need to change some parameters name to match Flax names
    for pt_key, pt_tensor in pt_state_dict.items():
        A       :   Any					=						rename_key(snake_case__						)
        A       :   Dict					=						tuple(renamed_pt_key.split('''.'''						)						)

        # Correctly rename weight parameters
        A,  A       :   Optional[Any]					=						rename_key_and_reshape_tensor(snake_case__		,				snake_case__		,				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
        A       :   Union[str, Any]					=						jnp.asarray(snake_case__						)

    return unflatten_dict(snake_case__						)






'''simple docstring'''




import pytest

import datasets.config
from datasets.utils.info_utils import is_small_dataset







@pytest.mark.parametrize('''dataset_size'''		,				[None, 400 * 2**20, 600 * 2**20]						)
@pytest.mark.parametrize('''input_in_memory_max_size'''		,				['''default''', 0, 100 * 2**20, 900 * 2**20]						)
def 		lowerCAmelCase_				(   snake_case__		,				snake_case__		,				snake_case__						):




    '''simple docstring'''



    if input_in_memory_max_size != "default":
        monkeypatch.setattr(datasets.config		,				'''IN_MEMORY_MAX_SIZE'''		,				snake_case__						)
    A       :   Dict					=						datasets.config.IN_MEMORY_MAX_SIZE
    if input_in_memory_max_size == "default":
        assert in_memory_max_size == 0
    else:
        assert in_memory_max_size == input_in_memory_max_size
    if dataset_size and in_memory_max_size:
        A       :   Dict					=						dataset_size < in_memory_max_size
    else:
        A       :   Tuple					=						False
    A       :   int					=						is_small_dataset(snake_case__						)
    assert result == expected




