





'''simple docstring'''


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


lowerCAmelCase :					Optional[int] 							=logging.get_logger(__name__)
def 							UpperCAmelCase_  (						__lowerCamelCase : Optional[int]     ,__lowerCamelCase : List[str]			):
   try:
      with open(__lowerCamelCase     ,"rb"			) as flax_state_f:
         lowercase_      :Optional[Any]         =			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 							UpperCAmelCase_  (						__lowerCamelCase : List[str]     ,__lowerCamelCase : str			):

   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_      :Union[str, Any]         =			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_      :Union[str, Any]         =			jax.tree_util.tree_map(
          lambda __lowerCamelCase			: params.astype(np.floataa			) if params.dtype == jnp.bfloataa else params     ,__lowerCamelCase			)

   lowercase_      :List[Any]         =			""

   lowercase_      :Dict         =			flatten_dict(__lowerCamelCase     ,sep="."			)
   lowercase_      :Any         =			pt_model.state_dict()

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

   for flax_key_tuple, flax_tensor in flax_state_dict.items():
      lowercase_      :Dict         =			flax_key_tuple.split("."			)

      if flax_key_tuple_array[-1] == "kernel" and flax_tensor.ndim == 4:
         lowercase_      :List[str]         =			flax_key_tuple_array[:-1] + ["weight"]
         lowercase_      :List[Any]         =			jnp.transpose(__lowerCamelCase     ,(3, 2, 0, 1)			)
      elif flax_key_tuple_array[-1] == "kernel":
         lowercase_      :Optional[Any]         =			flax_key_tuple_array[:-1] + ["weight"]
         lowercase_      :Any         =			flax_tensor.T
      elif flax_key_tuple_array[-1] == "scale":
         lowercase_      :Optional[Any]         =			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_      :List[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"			)
            )

      lowercase_      :Any         =			".".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_      :str         =			np.asarray(__lowerCamelCase			) if not isinstance(__lowerCamelCase     ,np.ndarray			) else flax_tensor
            lowercase_      :Optional[int]         =			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_      :int         =			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'''


def 							UpperCAmelCase_  (						__lowerCamelCase : str     ,__lowerCamelCase : str			):
   lowercase_      :Optional[Any]         =			len(__lowerCamelCase			)
   lowercase_      :List[Any]         =			[]
   for i in range(len(__lowerCamelCase			) - pat_len + 1			):
      lowercase_      :Dict         =			True
      for j in range(__lowerCamelCase			):
         if s[i + j] != pattern[j]:
            lowercase_      :int         =			False
            break
      if match_found:
         position.append(__lowerCamelCase			)
   return position


if __name__ == "__main__":
 assert naive_pattern_search('''ABCDEFG''', '''DE''') == [3]
 print(naive_pattern_search('''ABAAABCDBBABCDDEBCABC''', '''ABC'''))


