




from pickle import UnpicklingError

import jax
import jax.numpy as jnp
import numpy as np
from flax.serialization import from_bytes
from flax.traverse_util import flatten_dict

from ..utils import logging


UpperCAmelCase_		:				Tuple									=     logging.get_logger(__name__)




def 		lowerCAmelCase_   (	lowerCamelCase	,     lowerCamelCase   ):
				try:
								with open(lowerCamelCase	,     """rb"""   ) as flax_state_f:
												__magic_name__	:	Dict								=from_bytes(lowerCamelCase	,     flax_state_f.read()   )
				except UnpicklingError as e:
								try:
												with open(lowerCamelCase   ) as f:
																if f.read().startswith("""version"""   ):
																				raise OSError(
																				    """You seem to have cloned a repository without having git-lfs installed. Please"""
																				    """ install git-lfs and run `git lfs install` followed by `git lfs pull` in the"""
																				    """ folder you cloned."""   )
																else:
																				raise ValueError from e
								except (UnicodeDecodeError, ValueError):
												raise EnvironmentError(F"Unable to convert {model_file} to Flax deserializable object. "   )

				return load_flax_weights_in_pytorch_model(lowerCamelCase	,     lowerCamelCase   )




def 		lowerCAmelCase_   (	lowerCamelCase	,     lowerCamelCase   ):

				try:
								import torch  # noqa: F401
				except ImportError:
								logger.error(
								    """Loading Flax weights in PyTorch requires both PyTorch and Flax to be installed. Please see"""
								    """ https://pytorch.org/ and https://flax.readthedocs.io/en/latest/installation.html for installation"""
								    """ instructions."""   )
								raise

				# check if we have bf16 weights
				__magic_name__	:	int								=flatten_dict(jax.tree_util.tree_map(lambda lowerCamelCase   : x.dtype == jnp.bfloataa	,     lowerCamelCase   )   ).values()
				if any(lowerCamelCase   ):
								# convert all weights to fp32 if they are bf16 since torch.from_numpy can-not handle bf16

								# and bf16 is not fully supported in PT yet.
								logger.warning(
								    """Found ``bfloat16`` weights in Flax model. Casting all ``bfloat16`` weights to ``float32`` """
								    """before loading those in PyTorch model."""   )
								__magic_name__	:	List[Any]								=jax.tree_util.tree_map(
								    lambda lowerCamelCase   : params.astype(np.floataa   ) if params.dtype == jnp.bfloataa else params	,     lowerCamelCase   )

				__magic_name__	:	int								=""""""

				__magic_name__	:	Any								=flatten_dict(lowerCamelCase	,     sep="""."""   )
				__magic_name__	:	List[Any]								=pt_model.state_dict()

				# keep track of unexpected & missing keys
				__magic_name__	:	Any								=[]
				__magic_name__	:	List[str]								=set(pt_model_dict.keys()   )

				for flax_key_tuple, flax_tensor in flax_state_dict.items():
								__magic_name__	:	Tuple								=flax_key_tuple.split("""."""   )

								if flax_key_tuple_array[-1] == "kernel" and flax_tensor.ndim == 4:
												__magic_name__	:	int								=flax_key_tuple_array[:-1] + ["""weight"""]
												__magic_name__	:	str								=jnp.transpose(lowerCamelCase	,     (3, 2, 0, 1)   )
								elif flax_key_tuple_array[-1] == "kernel":
												__magic_name__	:	Tuple								=flax_key_tuple_array[:-1] + ["""weight"""]
												__magic_name__	:	str								=flax_tensor.T
								elif flax_key_tuple_array[-1] == "scale":
												__magic_name__	:	Tuple								=flax_key_tuple_array[:-1] + ["""weight"""]

								if "time_embedding" not in flax_key_tuple_array:
												for i, flax_key_tuple_string in enumerate(lowerCamelCase   ):
																__magic_name__	:	Optional[Any]								=(
																    flax_key_tuple_string.replace("""_0"""	,     """.0"""   )
																    .replace("""_1"""	,     """.1"""   )
																    .replace("""_2"""	,     """.2"""   )
																    .replace("""_3"""	,     """.3"""   )
																    .replace("""_4"""	,     """.4"""   )
																    .replace("""_5"""	,     """.5"""   )
																    .replace("""_6"""	,     """.6"""   )
																    .replace("""_7"""	,     """.7"""   )
																    .replace("""_8"""	,     """.8"""   )
																    .replace("""_9"""	,     """.9"""   )
																)

								__magic_name__	:	str								=""".""".join(lowerCamelCase   )

								if flax_key in pt_model_dict:
												if flax_tensor.shape != pt_model_dict[flax_key].shape:
																raise ValueError(
																    F"Flax checkpoint seems to be incorrect. Weight {flax_key_tuple} was expected "
																    F"to be of shape {pt_model_dict[flax_key].shape}, but is {flax_tensor.shape}."   )
												else:
																# add weight to pytorch dict
																__magic_name__	:	int								=np.asarray(lowerCamelCase   ) if not isinstance(lowerCamelCase	,     np.ndarray   ) else flax_tensor
																__magic_name__	:	List[str]								=torch.from_numpy(lowerCamelCase   )
																# remove from missing keys
																missing_keys.remove(lowerCamelCase   )
								else:
												# weight is not expected by PyTorch model
												unexpected_keys.append(lowerCamelCase   )

				pt_model.load_state_dict(lowerCamelCase   )

				# re-transform missing_keys to list
				__magic_name__	:	Dict								=list(lowerCamelCase   )

				if len(lowerCamelCase   ) > 0:
								logger.warning(
								    """Some weights of the Flax model were not used when initializing the PyTorch model"""
								    F" {pt_model.__class__.__name__}: {unexpected_keys}\n- This IS expected if you are initializing"
								    F" {pt_model.__class__.__name__} from a Flax model trained on another task or with another architecture"
								    """ (e.g. initializing a BertForSequenceClassification model from a FlaxBertForPreTraining model).\n- This"""
								    F" IS NOT expected if you are initializing {pt_model.__class__.__name__} from a Flax model that you expect"
								    """ to be exactly identical (e.g. initializing a BertForSequenceClassification model from a"""
								    """ FlaxBertForSequenceClassification model)."""   )
				if len(lowerCamelCase   ) > 0:
								logger.warning(
								    F"Some weights of {pt_model.__class__.__name__} were not initialized from the Flax model and are newly"
								    F" initialized: {missing_keys}\nYou should probably TRAIN this model on a down-stream task to be able to"
								    """ use it for predictions and inference."""   )

				return pt_model










UpperCAmelCase_		:				int									=     [
    999,
    800,
    799,
    600,
    599,
    500,
    400,
    399,
    377,
    355,
    333,
    311,
    288,
    266,
    244,
    222,
    200,
    199,
    177,
    155,
    133,
    111,
    88,
    66,
    44,
    22,
    0,
]

UpperCAmelCase_		:				Optional[Any]									=     [
    999,
    976,
    952,
    928,
    905,
    882,
    858,
    857,
    810,
    762,
    715,
    714,
    572,
    429,
    428,
    286,
    285,
    238,
    190,
    143,
    142,
    118,
    95,
    71,
    47,
    24,
    0,
]

UpperCAmelCase_		:				int									=     [
    999,
    988,
    977,
    966,
    955,
    944,
    933,
    922,
    911,
    900,
    899,
    879,
    859,
    840,
    820,
    800,
    799,
    766,
    733,
    700,
    699,
    650,
    600,
    599,
    500,
    499,
    400,
    399,
    350,
    300,
    299,
    266,
    233,
    200,
    199,
    179,
    159,
    140,
    120,
    100,
    99,
    88,
    77,
    66,
    55,
    44,
    33,
    22,
    11,
    0,
]

UpperCAmelCase_		:				Dict									=     [
    999,
    995,
    992,
    989,
    985,
    981,
    978,
    975,
    971,
    967,
    964,
    961,
    957,
    956,
    951,
    947,
    942,
    937,
    933,
    928,
    923,
    919,
    914,
    913,
    908,
    903,
    897,
    892,
    887,
    881,
    876,
    871,
    870,
    864,
    858,
    852,
    846,
    840,
    834,
    828,
    827,
    820,
    813,
    806,
    799,
    792,
    785,
    784,
    777,
    770,
    763,
    756,
    749,
    742,
    741,
    733,
    724,
    716,
    707,
    699,
    698,
    688,
    677,
    666,
    656,
    655,
    645,
    634,
    623,
    613,
    612,
    598,
    584,
    570,
    569,
    555,
    541,
    527,
    526,
    505,
    484,
    483,
    462,
    440,
    439,
    396,
    395,
    352,
    351,
    308,
    307,
    264,
    263,
    220,
    219,
    176,
    132,
    88,
    44,
    0,
]

UpperCAmelCase_		:				int									=     [
    999,
    997,
    995,
    992,
    990,
    988,
    986,
    984,
    981,
    979,
    977,
    975,
    972,
    970,
    968,
    966,
    964,
    961,
    959,
    957,
    956,
    954,
    951,
    949,
    946,
    944,
    941,
    939,
    936,
    934,
    931,
    929,
    926,
    924,
    921,
    919,
    916,
    914,
    913,
    910,
    907,
    905,
    902,
    899,
    896,
    893,
    891,
    888,
    885,
    882,
    879,
    877,
    874,
    871,
    870,
    867,
    864,
    861,
    858,
    855,
    852,
    849,
    846,
    843,
    840,
    837,
    834,
    831,
    828,
    827,
    824,
    821,
    817,
    814,
    811,
    808,
    804,
    801,
    798,
    795,
    791,
    788,
    785,
    784,
    780,
    777,
    774,
    770,
    766,
    763,
    760,
    756,
    752,
    749,
    746,
    742,
    741,
    737,
    733,
    730,
    726,
    722,
    718,
    714,
    710,
    707,
    703,
    699,
    698,
    694,
    690,
    685,
    681,
    677,
    673,
    669,
    664,
    660,
    656,
    655,
    650,
    646,
    641,
    636,
    632,
    627,
    622,
    618,
    613,
    612,
    607,
    602,
    596,
    591,
    586,
    580,
    575,
    570,
    569,
    563,
    557,
    551,
    545,
    539,
    533,
    527,
    526,
    519,
    512,
    505,
    498,
    491,
    484,
    483,
    474,
    466,
    457,
    449,
    440,
    439,
    428,
    418,
    407,
    396,
    395,
    381,
    366,
    352,
    351,
    330,
    308,
    307,
    286,
    264,
    263,
    242,
    220,
    219,
    176,
    175,
    132,
    131,
    88,
    44,
    0,
]

UpperCAmelCase_		:				str									=     [
    999,
    991,
    982,
    974,
    966,
    958,
    950,
    941,
    933,
    925,
    916,
    908,
    900,
    899,
    874,
    850,
    825,
    800,
    799,
    700,
    600,
    500,
    400,
    300,
    200,
    100,
    0,
]

UpperCAmelCase_		:				Any									=     [
    999,
    992,
    985,
    978,
    971,
    964,
    957,
    949,
    942,
    935,
    928,
    921,
    914,
    907,
    900,
    899,
    879,
    859,
    840,
    820,
    800,
    799,
    766,
    733,
    700,
    699,
    650,
    600,
    599,
    500,
    499,
    400,
    399,
    300,
    299,
    200,
    199,
    100,
    99,
    0,
]

UpperCAmelCase_		:				Any									=     [
    999,
    996,
    992,
    989,
    985,
    982,
    979,
    975,
    972,
    968,
    965,
    961,
    958,
    955,
    951,
    948,
    944,
    941,
    938,
    934,
    931,
    927,
    924,
    920,
    917,
    914,
    910,
    907,
    903,
    900,
    899,
    891,
    884,
    876,
    869,
    861,
    853,
    846,
    838,
    830,
    823,
    815,
    808,
    800,
    799,
    788,
    777,
    766,
    755,
    744,
    733,
    722,
    711,
    700,
    699,
    688,
    677,
    666,
    655,
    644,
    633,
    622,
    611,
    600,
    599,
    585,
    571,
    557,
    542,
    528,
    514,
    500,
    499,
    485,
    471,
    457,
    442,
    428,
    414,
    400,
    399,
    379,
    359,
    340,
    320,
    300,
    299,
    279,
    259,
    240,
    220,
    200,
    199,
    166,
    133,
    100,
    99,
    66,
    33,
    0,
]




