





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


_SCREAMING_SNAKE_CASE					=    logging.get_logger(__name__)




def    _lowerCAmelCase						(				lowerCamelCase_			:  int		,       lowerCamelCase_			:  Optional[Any]				):
			try:
						with open(lowerCamelCase_		,       '''rb'''				) as flax_state_f:
									__lowercase										=							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_			:  List[str]		,       lowerCamelCase_			:  Dict				):

			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
			__lowercase										=							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.'''				)
						__lowercase										=							jax.tree_util.tree_map(
						    lambda lowerCamelCase_				: params.astype(np.floataa				) if params.dtype == jnp.bfloataa else params		,       lowerCamelCase_				)

			__lowercase										=							''''''

			__lowercase										=							flatten_dict(lowerCamelCase_		,       sep='''.'''				)
			__lowercase										=							pt_model.state_dict()

			# keep track of unexpected & missing keys
			__lowercase										=							[]
			__lowercase										=							set(pt_model_dict.keys()				)

			for flax_key_tuple, flax_tensor in flax_state_dict.items():
						__lowercase										=							flax_key_tuple.split('''.'''				)

						if flax_key_tuple_array[-1] == "kernel" and flax_tensor.ndim == 4:
									__lowercase										=							flax_key_tuple_array[:-1] + ['''weight''']
									__lowercase										=							jnp.transpose(lowerCamelCase_		,       (3, 2, 0, 1)				)
						elif flax_key_tuple_array[-1] == "kernel":
									__lowercase										=							flax_key_tuple_array[:-1] + ['''weight''']
									__lowercase										=							flax_tensor.T
						elif flax_key_tuple_array[-1] == "scale":
									__lowercase										=							flax_key_tuple_array[:-1] + ['''weight''']

						if "time_embedding" not in flax_key_tuple_array:
									for i, flax_key_tuple_string in enumerate(lowerCamelCase_				):
												__lowercase										=							(
												    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'''				)
												)

						__lowercase										=							'''.'''.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
												__lowercase										=							np.asarray(lowerCamelCase_				) if not isinstance(lowerCamelCase_		,       np.ndarray				) else flax_tensor
												__lowercase										=							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
			__lowercase										=							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












'''simple docstring'''



import warnings

from ...utils import logging
from .image_processing_glpn import GLPNImageProcessor


_SCREAMING_SNAKE_CASE					=    logging.get_logger(__name__)






class 							__lowercase       (      lowerCAmelCase__						):







	'''simple docstring'''

	def __init__(self     ,*_lowerCamelCase     ,**_lowerCamelCase )							->							None:







				'''simple docstring'''





				warnings.warn(
				    '''The class GLPNFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please'''
				    ''' use GLPNImageProcessor instead.'''     ,_lowerCamelCase     ,)
				super().__init__(*_lowerCamelCase     ,**_lowerCamelCase )





