






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_						:  str									=			logging.get_logger(__name__)






def  lowerCamelCase__ (_UpperCAmelCase):
			SCREAMING_SNAKE_CASE						 =       R'\w+[.]\d+'
			SCREAMING_SNAKE_CASE						 =       re.findall(lowerCAmelCase__							,				lowerCAmelCase__)
			for pat in pats:
						SCREAMING_SNAKE_CASE						 =       key.replace(lowerCAmelCase__							,				'_'.join(pat.split('.')))
			return key






def  lowerCamelCase__ (_UpperCAmelCase							,				_UpperCAmelCase							,				_UpperCAmelCase):
			SCREAMING_SNAKE_CASE						 =       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)
			):
						SCREAMING_SNAKE_CASE						 =       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:
						SCREAMING_SNAKE_CASE						 =       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:
						SCREAMING_SNAKE_CASE						 =       pt_tuple_key[:-1] + ('embedding',)
						return renamed_pt_tuple_key, pt_tensor

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

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

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

			# old PyTorch layer norm bias
			SCREAMING_SNAKE_CASE						 =       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__ (_UpperCAmelCase							,				_UpperCAmelCase							,				_UpperCAmelCase=42):
			SCREAMING_SNAKE_CASE						 =       {k: v.numpy() for k, v in pt_state_dict.items()}

			# Step 2: Since the model is stateless, get random Flax params
			SCREAMING_SNAKE_CASE						 =       flax_model.init_weights(PRNGKey(lowerCAmelCase__))

			SCREAMING_SNAKE_CASE						 =       flatten_dict(lowerCAmelCase__)
			SCREAMING_SNAKE_CASE						 =       {}

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

						# Correctly rename weight parameters
						SCREAMING_SNAKE_CASE						 =       rename_key_and_reshape_tensor(lowerCAmelCase__							,				lowerCAmelCase__							,				lowerCAmelCase__)

						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
						SCREAMING_SNAKE_CASE						 =       jnp.asarray(lowerCAmelCase__)

			return unflatten_dict(lowerCAmelCase__)









"""simple docstring"""







from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowercase__		:				Tuple          =	logging.get_logger(__name__)

lowercase__		:				Any          =	{
    """facebook/dpr-ctx_encoder-single-nq-base""": (
        """https://huggingface.co/facebook/dpr-ctx_encoder-single-nq-base/resolve/main/config.json"""
    ),
    """facebook/dpr-question_encoder-single-nq-base""": (
        """https://huggingface.co/facebook/dpr-question_encoder-single-nq-base/resolve/main/config.json"""
    ),
    """facebook/dpr-reader-single-nq-base""": (
        """https://huggingface.co/facebook/dpr-reader-single-nq-base/resolve/main/config.json"""
    ),
    """facebook/dpr-ctx_encoder-multiset-base""": (
        """https://huggingface.co/facebook/dpr-ctx_encoder-multiset-base/resolve/main/config.json"""
    ),
    """facebook/dpr-question_encoder-multiset-base""": (
        """https://huggingface.co/facebook/dpr-question_encoder-multiset-base/resolve/main/config.json"""
    ),
    """facebook/dpr-reader-multiset-base""": (
        """https://huggingface.co/facebook/dpr-reader-multiset-base/resolve/main/config.json"""
    ),
}







class       UpperCamelCase__   (	lowercase_  ):




      """simple docstring"""




      _SCREAMING_SNAKE_CASE  				=     """dpr"""



      def __init__(      self				:      List[Any]    ,			SCREAMING_SNAKE_CASE_				:      Tuple=3_0_5_2_2    ,			SCREAMING_SNAKE_CASE_				:      Any=7_6_8    ,			SCREAMING_SNAKE_CASE_				:      Dict=1_2    ,			SCREAMING_SNAKE_CASE_				:      List[str]=1_2    ,			SCREAMING_SNAKE_CASE_				:      int=3_0_7_2    ,			SCREAMING_SNAKE_CASE_				:      List[Any]="gelu"    ,			SCREAMING_SNAKE_CASE_				:      int=0.1    ,			SCREAMING_SNAKE_CASE_				:      int=0.1    ,			SCREAMING_SNAKE_CASE_				:      Union[str, Any]=5_1_2    ,			SCREAMING_SNAKE_CASE_				:      Optional[int]=2    ,			SCREAMING_SNAKE_CASE_				:      Optional[int]=0.02    ,			SCREAMING_SNAKE_CASE_				:      List[str]=1E-12    ,			SCREAMING_SNAKE_CASE_				:      List[Any]=0    ,			SCREAMING_SNAKE_CASE_				:      Optional[int]="absolute"    ,			SCREAMING_SNAKE_CASE_				:      int = 0    ,			**SCREAMING_SNAKE_CASE_				:      Optional[int]    ,			):
        super().__init__(pad_token_id=SCREAMING_SNAKE_CASE_    ,			**SCREAMING_SNAKE_CASE_       )

        lowerCAmelCase_   :				Optional[int]								= vocab_size
        lowerCAmelCase_   :				Tuple								= hidden_size
        lowerCAmelCase_   :				int								= num_hidden_layers
        lowerCAmelCase_   :				str								= num_attention_heads
        lowerCAmelCase_   :				Any								= hidden_act
        lowerCAmelCase_   :				List[str]								= intermediate_size
        lowerCAmelCase_   :				int								= hidden_dropout_prob
        lowerCAmelCase_   :				Union[str, Any]								= attention_probs_dropout_prob
        lowerCAmelCase_   :				Tuple								= max_position_embeddings
        lowerCAmelCase_   :				List[str]								= type_vocab_size
        lowerCAmelCase_   :				str								= initializer_range
        lowerCAmelCase_   :				str								= layer_norm_eps
        lowerCAmelCase_   :				List[str]								= projection_dim
        lowerCAmelCase_   :				List[str]								= position_embedding_type





