


'''simple docstring'''






import os
import sys
import warnings
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union

import numpy as np
import pyarrow as pa

from .. import config
from ..download.streaming_download_manager import xopen
from ..table import array_cast
from ..utils.file_utils import is_local_path
from ..utils.py_utils import first_non_null_value, no_op_if_value_is_null, string_to_dict


if TYPE_CHECKING:
 import PIL.Image

 from .features import FeatureType


lowercase							=None
lowercase							='<' if sys.byteorder == 'little' else '>'
# Origin: https://github.com/python-pillow/Pillow/blob/698951e19e19972aeed56df686868f1329981c12/src/PIL/Image.py#L3126 minus "|i1" which values are not preserved correctly when saving and loading an image
lowercase							=[
    np.dtype('|b1'),
    np.dtype('|u1'),
    np.dtype('<u2'),
    np.dtype('>u2'),
    np.dtype('<i2'),
    np.dtype('>i2'),
    np.dtype('<u4'),
    np.dtype('>u4'),
    np.dtype('<i4'),
    np.dtype('>i4'),
    np.dtype('<f4'),
    np.dtype('>f4'),
    np.dtype('<f8'),
    np.dtype('>f8'),
]






@dataclass
class  __magic_name__							:
       UpperCAmelCase										=True
       UpperCAmelCase										=None
       # Automatically constructed
       UpperCAmelCase										="PIL.Image.Image"
       UpperCAmelCase										=pa.struct({"bytes": pa.binary(), "path": pa.string()}    )
       UpperCAmelCase										=field(default="Image" ,init=lowerCAmelCase ,repr=lowerCAmelCase    )






       def __call__(      self)						->  Tuple:




          '''simple docstring'''
          return self.pa_type






       def       lowerCAmelCase		(      self  ,							snake_case)						->  dict:




          '''simple docstring'''
          if config.PIL_AVAILABLE:
             import PIL.Image
          else:
             raise ImportError('To support encoding images, please install \'Pillow\'.')

          if isinstance(snake_case  ,							snake_case):
             _UpperCAmelCase       :       Optional[int]							   =np.array(snake_case)

          if isinstance(snake_case  ,							snake_case):
             return {"path": value, "bytes": None}
          elif isinstance(snake_case  ,							snake_case):
             return {"path": None, "bytes": value}
          elif isinstance(snake_case  ,							np.ndarray):
             # convert the image array to PNG/TIFF bytes
             return encode_np_array(snake_case)
          elif isinstance(snake_case  ,							PIL.Image.Image):
             # convert the PIL image to bytes (default format is PNG/TIFF)
             return encode_pil_image(snake_case)
          elif value.get('path') is not None and os.path.isfile(value['path']):
             # we set "bytes": None to not duplicate the data if they're already available locally
             return {"bytes": None, "path": value.get('path')}
          elif value.get('bytes') is not None or value.get('path') is not None:
             # store the image bytes, and path is used to infer the image format using the file extension
             return {"bytes": value.get('bytes'), "path": value.get('path')}
          else:
             raise ValueError(
                 f"An image sample should have one of 'path' or 'bytes' but they are missing or None in {value}.")






       def       lowerCAmelCase		(      self  ,							snake_case  ,							snake_case=None)						->  "PIL.Image.Image":




          '''simple docstring'''
          if not self.decode:
             raise RuntimeError('Decoding is disabled for this feature. Please use Image(decode=True) instead.')

          if config.PIL_AVAILABLE:
             import PIL.Image
          else:
             raise ImportError('To support decoding images, please install \'Pillow\'.')

          if token_per_repo_id is None:
             _UpperCAmelCase       :       List[str]							   ={}

          _UpperCAmelCase   ,	_UpperCAmelCase       :       Optional[Any]							   =value['path'], value['bytes']
          if bytes_ is None:
             if path is None:
                raise ValueError(f"An image should have one of 'path' or 'bytes' but both are None in {value}.")
             else:
                if is_local_path(snake_case):
                   _UpperCAmelCase       :       Dict							   =PIL.Image.open(snake_case)
                else:
                   _UpperCAmelCase       :       Union[str, Any]							   =path.split('::')[-1]
                   try:
                      _UpperCAmelCase       :       str							   =string_to_dict(snake_case  ,							config.HUB_DATASETS_URL)['repo_id']
                      _UpperCAmelCase       :       str							   =token_per_repo_id.get(snake_case)
                   except ValueError:
                      _UpperCAmelCase       :       Tuple							   =None
                   with xopen(snake_case  ,							'rb'  ,							use_auth_token=snake_case) as f:
                      _UpperCAmelCase       :       Any							   =BytesIO(f.read())
                   _UpperCAmelCase       :       str							   =PIL.Image.open(bytes_)
          else:
             _UpperCAmelCase       :       List[Any]							   =PIL.Image.open(BytesIO(bytes_))
          image.load()  # to avoid "Too many open files" errors
          return image






       def       lowerCAmelCase		(      self)						->  Union["FeatureType", Dict[str, "FeatureType"]]:




          '''simple docstring'''
          from .features import Value

          return (
              self
              if self.decode
              else {
                  "bytes": Value('binary'),
                  "path": Value('string'),
              }
          )






       def       lowerCAmelCase		(      self  ,							snake_case)						->  pa.StructArray:




          '''simple docstring'''
          if pa.types.is_string(storage.type):
             _UpperCAmelCase       :       Optional[Any]							   =pa.array([None] * len(snake_case)  ,							type=pa.binary())
             _UpperCAmelCase       :       Optional[int]							   =pa.StructArray.from_arrays([bytes_array, storage]  ,							['bytes', 'path']  ,							mask=storage.is_null())
          elif pa.types.is_binary(storage.type):
             _UpperCAmelCase       :       List[Any]							   =pa.array([None] * len(snake_case)  ,							type=pa.string())
             _UpperCAmelCase       :       Dict							   =pa.StructArray.from_arrays([storage, path_array]  ,							['bytes', 'path']  ,							mask=storage.is_null())
          elif pa.types.is_struct(storage.type):
             if storage.type.get_field_index('bytes') >= 0:
                _UpperCAmelCase       :       Any							   =storage.field('bytes')
             else:
                _UpperCAmelCase       :       Dict							   =pa.array([None] * len(snake_case)  ,							type=pa.binary())
             if storage.type.get_field_index('path') >= 0:
                _UpperCAmelCase       :       Optional[int]							   =storage.field('path')
             else:
                _UpperCAmelCase       :       Union[str, Any]							   =pa.array([None] * len(snake_case)  ,							type=pa.string())
             _UpperCAmelCase       :       Any							   =pa.StructArray.from_arrays([bytes_array, path_array]  ,							['bytes', 'path']  ,							mask=storage.is_null())
          elif pa.types.is_list(storage.type):
             _UpperCAmelCase       :       Optional[Any]							   =pa.array(
                 [encode_np_array(np.array(snake_case))['bytes'] if arr is not None else None for arr in storage.to_pylist()]  ,							type=pa.binary()  ,							)
             _UpperCAmelCase       :       Optional[Any]							   =pa.array([None] * len(snake_case)  ,							type=pa.string())
             _UpperCAmelCase       :       List[Any]							   =pa.StructArray.from_arrays(
                 [bytes_array, path_array]  ,							['bytes', 'path']  ,							mask=bytes_array.is_null())
          return array_cast(snake_case  ,							self.pa_type)






       def       lowerCAmelCase		(      self  ,							snake_case)						->  pa.StructArray:




          '''simple docstring'''

          @no_op_if_value_is_null
          def path_to_bytes(snake_case):
             with xopen(snake_case  ,							'rb') as f:
                _UpperCAmelCase       :       str							   =f.read()
             return bytes_

          _UpperCAmelCase       :       Optional[int]							   =pa.array(
              [
                  (path_to_bytes(x['path']) if x['bytes'] is None else x['bytes']) if x is not None else None
                  for x in storage.to_pylist()
              ]  ,							type=pa.binary()  ,							)
          _UpperCAmelCase       :       Union[str, Any]							   =pa.array(
              [os.path.basename(snake_case) if path is not None else None for path in storage.field('path').to_pylist()]  ,							type=pa.string()  ,							)
          _UpperCAmelCase       :       str							   =pa.StructArray.from_arrays([bytes_array, path_array]  ,							['bytes', 'path']  ,							mask=bytes_array.is_null())
          return array_cast(snake_case  ,							self.pa_type)






def lowerCamelCase__      (						):







   '''simple docstring'''




   if config.PIL_AVAILABLE:
      import PIL.Image
   else:
      raise ImportError('To support encoding images, please install \'Pillow\'.'							)

   global _IMAGE_COMPRESSION_FORMATS
   if _IMAGE_COMPRESSION_FORMATS is None:
      PIL.Image.init()
      _UpperCAmelCase       :       List[str]							   =list(set(PIL.Image.OPEN.keys()							) & set(PIL.Image.SAVE.keys()							)							)
   return _IMAGE_COMPRESSION_FORMATS





def lowerCamelCase__      (						__lowerCamelCase	:							"PIL.Image.Image"							):







   '''simple docstring'''




   _UpperCAmelCase       :       List[str]							   =BytesIO()
   if image.format in list_image_compression_formats():
      _UpperCAmelCase       :       str							   =image.format
   else:
      _UpperCAmelCase       :       Dict							   ='PNG' if image.mode in ['1', 'L', 'LA', 'RGB', 'RGBA'] else 'TIFF'
   image.save(__lowerCamelCase	,   format=__lowerCamelCase							)
   return buffer.getvalue()





def lowerCamelCase__      (						__lowerCamelCase	:							"PIL.Image.Image"							):







   '''simple docstring'''




   if hasattr(__lowerCamelCase	,   'filename'							) and image.filename != "":
      return {"path": image.filename, "bytes": None}
   else:
      return {"path": None, "bytes": image_to_bytes(__lowerCamelCase							)}





def lowerCamelCase__      (						__lowerCamelCase	:							np.ndarray							):







   '''simple docstring'''




   if config.PIL_AVAILABLE:
      import PIL.Image
   else:
      raise ImportError('To support encoding images, please install \'Pillow\'.'							)

   _UpperCAmelCase       :       List[str]							   =array.dtype
   _UpperCAmelCase       :       int							   =dtype.byteorder if dtype.byteorder != '=' else _NATIVE_BYTEORDER
   _UpperCAmelCase       :       Optional[int]							   =dtype.kind
   _UpperCAmelCase       :       Tuple							   =dtype.itemsize

   _UpperCAmelCase       :       Union[str, Any]							   =None

   # Multi-channel array case (only np.dtype("|u1") is allowed)
   if array.shape[2:]:
      _UpperCAmelCase       :       List[str]							   =np.dtype('|u1'							)
      if dtype_kind not in ["u", "i"]:
         raise TypeError(
             f"Unsupported array dtype {dtype} for image encoding. Only {dest_dtype} is supported for multi-channel arrays."							)
      if dtype is not dest_dtype:
         warnings.warn(f"Downcasting array dtype {dtype} to {dest_dtype} to be compatible with 'Pillow'"							)
    # Exact match
   elif dtype in _VALID_IMAGE_ARRAY_DTPYES:
      _UpperCAmelCase       :       Union[str, Any]							   =dtype
   else:  # Downcast the type within the kind (np.can_cast(from_type, to_type, casting="same_kind") doesn't behave as expected, so do it manually)
      while dtype_itemsize >= 1:
         _UpperCAmelCase       :       Optional[int]							   =dtype_byteorder + dtype_kind + str(__lowerCamelCase							)
         _UpperCAmelCase       :       str							   =np.dtype(__lowerCamelCase							)
         if dest_dtype in _VALID_IMAGE_ARRAY_DTPYES:
            warnings.warn(f"Downcasting array dtype {dtype} to {dest_dtype} to be compatible with 'Pillow'"							)
            break
         else:
            dtype_itemsize //= 2

   if dest_dtype is None:
      raise TypeError(
          f"Cannot convert dtype {dtype} to a valid image dtype. Valid image dtypes: {_VALID_IMAGE_ARRAY_DTPYES}"							)
   _UpperCAmelCase       :       Optional[int]							   =PIL.Image.fromarray(array.astype(__lowerCamelCase							)							)
   return {"path": None, "bytes": image_to_bytes(__lowerCamelCase							)}





def lowerCamelCase__      (						__lowerCamelCase	:							Union[List[str], List[dict], List[np.ndarray], List["PIL.Image.Image"]]							):







   '''simple docstring'''




   if config.PIL_AVAILABLE:
      import PIL.Image
   else:
      raise ImportError('To support encoding images, please install \'Pillow\'.'							)

   if objs:
      _UpperCAmelCase   ,	_UpperCAmelCase       :       Optional[int]							   =first_non_null_value(__lowerCamelCase							)
      if isinstance(__lowerCamelCase	,   __lowerCamelCase							):
         return [{"path": obj, "bytes": None} if obj is not None else None for obj in objs]
      if isinstance(__lowerCamelCase	,   np.ndarray							):
         _UpperCAmelCase       :       List[Any]							   =no_op_if_value_is_null(__lowerCamelCase							)
         return [obj_to_image_dict_func(__lowerCamelCase							) for obj in objs]
      elif isinstance(__lowerCamelCase	,   PIL.Image.Image							):
         _UpperCAmelCase       :       int							   =no_op_if_value_is_null(__lowerCamelCase							)
         return [obj_to_image_dict_func(__lowerCamelCase							) for obj in objs]
      else:
         return objs
   else:
      return objs





'''simple docstring'''






from typing import Any





def lowerCamelCase__      (						__lowerCamelCase	:							list	,   __lowerCamelCase	:							list	,   __lowerCamelCase	:							dict	,   __lowerCamelCase	:							dict	,   __lowerCamelCase	:							dict	,   ):







   '''simple docstring'''




   _validation(
       __lowerCamelCase	,   __lowerCamelCase	,   __lowerCamelCase	,   __lowerCamelCase	,   __lowerCamelCase	,   )
   # Creates data structures and fill initial step
   _UpperCAmelCase       :       dict							   ={}
   _UpperCAmelCase       :       dict							   ={}
   for state in states_space:
      _UpperCAmelCase       :       int							   =observations_space[0]
      _UpperCAmelCase       :       int							   =(
          initial_probabilities[state] * emission_probabilities[state][observation]
      )
      _UpperCAmelCase       :       int							   =None

   # Fills the data structure with the probabilities of
   # different transitions and pointers to previous states
   for o in range(1	,   len(__lowerCamelCase							)							):
      _UpperCAmelCase       :       List[Any]							   =observations_space[o]
      _UpperCAmelCase       :       Optional[int]							   =observations_space[o - 1]
      for state in states_space:
         # Calculates the argmax for probability function
         _UpperCAmelCase       :       List[str]							   =''
         _UpperCAmelCase       :       Dict							   =-1
         for k_state in states_space:
            _UpperCAmelCase       :       List[str]							   =(
                probabilities[(k_state, prior_observation)]
                * transition_probabilities[k_state][state]
                * emission_probabilities[state][observation]
            )
            if probability > max_probability:
               _UpperCAmelCase       :       int							   =probability
               _UpperCAmelCase       :       List[Any]							   =k_state

            # Update probabilities and pointers dicts
         _UpperCAmelCase       :       str							   =(
             probabilities[(arg_max, prior_observation)]
             * transition_probabilities[arg_max][state]
             * emission_probabilities[state][observation]
         )

         _UpperCAmelCase       :       List[Any]							   =arg_max

    # The final observation
   _UpperCAmelCase       :       int							   =observations_space[len(__lowerCamelCase							) - 1]

   # argmax for given final observation
   _UpperCAmelCase       :       Any							   =''
   _UpperCAmelCase       :       Union[str, Any]							   =-1
   for k_state in states_space:
      _UpperCAmelCase       :       Optional[int]							   =probabilities[(k_state, final_observation)]
      if probability > max_probability:
         _UpperCAmelCase       :       Union[str, Any]							   =probability
         _UpperCAmelCase       :       int							   =k_state
   _UpperCAmelCase       :       int							   =arg_max

   # Process pointers backwards
   _UpperCAmelCase       :       List[str]							   =last_state
   _UpperCAmelCase       :       Optional[int]							   =[]
   for o in range(len(__lowerCamelCase							) - 1	,   -1	,   -1							):
      result.append(__lowerCamelCase							)
      _UpperCAmelCase       :       Optional[Any]							   =pointers[previous, observations_space[o]]
   result.reverse()

   return result





def lowerCamelCase__      (						__lowerCamelCase	:							Any	,   __lowerCamelCase	:							Any	,   __lowerCamelCase	:							Any	,   __lowerCamelCase	:							Any	,   __lowerCamelCase	:							Any	,   ):







   '''simple docstring'''




   _validate_not_empty(
       __lowerCamelCase	,   __lowerCamelCase	,   __lowerCamelCase	,   __lowerCamelCase	,   __lowerCamelCase	,   )
   _validate_lists(__lowerCamelCase	,   __lowerCamelCase							)
   _validate_dicts(
       __lowerCamelCase	,   __lowerCamelCase	,   __lowerCamelCase							)





def lowerCamelCase__      (						__lowerCamelCase	:							Any	,   __lowerCamelCase	:							Any	,   __lowerCamelCase	:							Any	,   __lowerCamelCase	:							Any	,   __lowerCamelCase	:							Any	,   ):







   '''simple docstring'''




   if not all(
       [
           observations_space,
           states_space,
           initial_probabilities,
           transition_probabilities,
           emission_probabilities,
       ]							):
      raise ValueError('There\'s an empty parameter'							)





def lowerCamelCase__      (						__lowerCamelCase	:							Any	,   __lowerCamelCase	:							Any							):







   '''simple docstring'''




   _validate_list(__lowerCamelCase	,   'observations_space'							)
   _validate_list(__lowerCamelCase	,   'states_space'							)





def lowerCamelCase__      (						__lowerCamelCase	:							Any	,   __lowerCamelCase	:							str							):







   '''simple docstring'''




   if not isinstance(_object	,   __lowerCamelCase							):
      _UpperCAmelCase       :       Any							   =f"{var_name} must be a list"
      raise ValueError(__lowerCamelCase							)
   else:
      for x in _object:
         if not isinstance(__lowerCamelCase	,   __lowerCamelCase							):
            _UpperCAmelCase       :       Optional[int]							   =f"{var_name} must be a list of strings"
            raise ValueError(__lowerCamelCase							)





def lowerCamelCase__      (						__lowerCamelCase	:							Any	,   __lowerCamelCase	:							Any	,   __lowerCamelCase	:							Any	,   ):







   '''simple docstring'''




   _validate_dict(__lowerCamelCase	,   'initial_probabilities'	,   __lowerCamelCase							)
   _validate_nested_dict(__lowerCamelCase	,   'transition_probabilities'							)
   _validate_nested_dict(__lowerCamelCase	,   'emission_probabilities'							)





def lowerCamelCase__      (						__lowerCamelCase	:							Any	,   __lowerCamelCase	:							str							):







   '''simple docstring'''




   _validate_dict(_object	,   __lowerCamelCase	,   __lowerCamelCase							)
   for x in _object.values():
      _validate_dict(__lowerCamelCase	,   __lowerCamelCase	,   __lowerCamelCase	,   __lowerCamelCase							)





def lowerCamelCase__      (						__lowerCamelCase	:							Any	,   __lowerCamelCase	:							str	,   __lowerCamelCase	:							type	,   __lowerCamelCase	:							bool = False							):







   '''simple docstring'''




   if not isinstance(_object	,   __lowerCamelCase							):
      _UpperCAmelCase       :       List[str]							   =f"{var_name} must be a dict"
      raise ValueError(__lowerCamelCase							)
   if not all(isinstance(__lowerCamelCase	,   __lowerCamelCase							) for x in _object							):
      _UpperCAmelCase       :       str							   =f"{var_name} all keys must be strings"
      raise ValueError(__lowerCamelCase							)
   if not all(isinstance(__lowerCamelCase	,   __lowerCamelCase							) for x in _object.values()							):
      _UpperCAmelCase       :       int							   ='nested dictionary ' if nested else ''
      _UpperCAmelCase       :       Optional[int]							   =f"{var_name} {nested_text}all values must be {value_type.__name__}"
      raise ValueError(__lowerCamelCase							)


if __name__ == "__main__":
 from doctest import testmod

 testmod()

