




"""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


lowerCAmelCase							:			Optional[List[str]]     							=							None
lowerCAmelCase							:			Optional[int]     							=							"""<""" 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
lowerCAmelCase							:			List[Any]     							=							[
    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__							:






				'''simple docstring'''
				__UpperCamelCase			  =						True
				__UpperCamelCase			  =						None
				# Automatically constructed
				__UpperCamelCase			  =						"PIL.Image.Image"
				__UpperCamelCase			  =						pa.struct({"bytes": pa.binary(), "path": pa.string()}				)
				__UpperCamelCase			  =						field(default="Image"						,					init=UpperCAmelCase__						,					repr=UpperCAmelCase__				)





				def __call__(       self ):





							"""simple docstring"""
							return self.pa_type





				def    _lowerCAmelCase				(       self		, _a ):





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

							if isinstance(_a		, _a ):
										lowerCamelCase			      =					np.array(_a )

							if isinstance(_a		, _a ):
										return {"path": value, "bytes": None}
							elif isinstance(_a		, _a ):
										return {"path": None, "bytes": value}
							elif isinstance(_a		, np.ndarray ):
										# convert the image array to PNG/TIFF bytes
										return encode_np_array(_a )
							elif isinstance(_a		, PIL.Image.Image ):
										# convert the PIL image to bytes (default format is PNG/TIFF)
										return encode_pil_image(_a )
							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		, _a		, _a=None ):





							"""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:
										lowerCamelCase			      =					{}

							lowerCamelCase      ,   lowerCamelCase			      =					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(_a ):
																lowerCamelCase			      =					PIL.Image.open(_a )
													else:
																lowerCamelCase			      =					path.split("""::""" )[-1]
																try:
																			lowerCamelCase			      =					string_to_dict(_a		, config.HUB_DATASETS_URL )["""repo_id"""]
																			lowerCamelCase			      =					token_per_repo_id.get(_a )
																except ValueError:
																			lowerCamelCase			      =					None
																with xopen(_a		, """rb"""		, use_auth_token=_a ) as f:
																			lowerCamelCase			      =					BytesIO(f.read() )
																lowerCamelCase			      =					PIL.Image.open(bytes_ )
							else:
										lowerCamelCase			      =					PIL.Image.open(BytesIO(bytes_ ) )
							image.load()  # to avoid "Too many open files" errors
							return image





				def    _lowerCAmelCase				(       self ):





							"""simple docstring"""
							from .features import Value

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





				def    _lowerCAmelCase				(       self		, _a ):





							"""simple docstring"""
							if pa.types.is_string(storage.type ):
										lowerCamelCase			      =					pa.array([None] * len(_a )		, type=pa.binary() )
										lowerCamelCase			      =					pa.StructArray.from_arrays([bytes_array, storage]		, ["""bytes""", """path"""]		, mask=storage.is_null() )
							elif pa.types.is_binary(storage.type ):
										lowerCamelCase			      =					pa.array([None] * len(_a )		, type=pa.string() )
										lowerCamelCase			      =					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:
													lowerCamelCase			      =					storage.field("""bytes""" )
										else:
													lowerCamelCase			      =					pa.array([None] * len(_a )		, type=pa.binary() )
										if storage.type.get_field_index("""path""" ) >= 0:
													lowerCamelCase			      =					storage.field("""path""" )
										else:
													lowerCamelCase			      =					pa.array([None] * len(_a )		, type=pa.string() )
										lowerCamelCase			      =					pa.StructArray.from_arrays([bytes_array, path_array]		, ["""bytes""", """path"""]		, mask=storage.is_null() )
							elif pa.types.is_list(storage.type ):
										lowerCamelCase			      =					pa.array(
										    [encode_np_array(np.array(_a ) )["""bytes"""] if arr is not None else None for arr in storage.to_pylist()]		, type=pa.binary()		, )
										lowerCamelCase			      =					pa.array([None] * len(_a )		, type=pa.string() )
										lowerCamelCase			      =					pa.StructArray.from_arrays(
										    [bytes_array, path_array]		, ["""bytes""", """path"""]		, mask=bytes_array.is_null() )
							return array_cast(_a		, self.pa_type )





				def    _lowerCAmelCase				(       self		, _a ):





							"""simple docstring"""

							@no_op_if_value_is_null
							def path_to_bytes(_a ):
										with xopen(_a		, """rb""" ) as f:
													lowerCamelCase			      =					f.read()
										return bytes_

							lowerCamelCase			      =					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()		, )
							lowerCamelCase			      =					pa.array(
							    [os.path.basename(_a ) if path is not None else None for path in storage.field("""path""" ).to_pylist()]		, type=pa.string()		, )
							lowerCamelCase			      =					pa.StructArray.from_arrays([bytes_array, path_array]		, ["""bytes""", """path"""]		, mask=bytes_array.is_null() )
							return array_cast(_a		, self.pa_type )




def     a__ (				)						->					List[str]:
			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()
						lowerCamelCase			      =					list(set(PIL.Image.OPEN.keys()				) & set(PIL.Image.SAVE.keys()				)				)
			return _IMAGE_COMPRESSION_FORMATS



def     a__ (				snake_case__				)						->					bytes:
			lowerCamelCase			      =					BytesIO()
			if image.format in list_image_compression_formats():
						lowerCamelCase			      =					image.format
			else:
						lowerCamelCase			      =					"""PNG""" if image.mode in ["""1""", """L""", """LA""", """RGB""", """RGBA"""] else """TIFF"""
			image.save(snake_case__       , format=snake_case__				)
			return buffer.getvalue()



def     a__ (				snake_case__				)						->					dict:
			if hasattr(snake_case__       , """filename"""				) and image.filename != "":
						return {"path": image.filename, "bytes": None}
			else:
						return {"path": None, "bytes": image_to_bytes(snake_case__				)}



def     a__ (				snake_case__				)						->					dict:
			if config.PIL_AVAILABLE:
						import PIL.Image
			else:
						raise ImportError("""To support encoding images, please install 'Pillow'."""				)

			lowerCamelCase			      =					array.dtype
			lowerCamelCase			      =					dtype.byteorder if dtype.byteorder != """=""" else _NATIVE_BYTEORDER
			lowerCamelCase			      =					dtype.kind
			lowerCamelCase			      =					dtype.itemsize

			lowerCamelCase			      =					None

			# Multi-channel array case (only np.dtype("|u1") is allowed)
			if array.shape[2:]:
						lowerCamelCase			      =					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:
						lowerCamelCase			      =					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:
									lowerCamelCase			      =					dtype_byteorder + dtype_kind + str(snake_case__				)
									lowerCamelCase			      =					np.dtype(snake_case__				)
									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}'				)
			lowerCamelCase			      =					PIL.Image.fromarray(array.astype(snake_case__				)				)
			return {"path": None, "bytes": image_to_bytes(snake_case__				)}



def     a__ (				snake_case__				)						->					List[dict]:
			if config.PIL_AVAILABLE:
						import PIL.Image
			else:
						raise ImportError("""To support encoding images, please install 'Pillow'."""				)

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









"""simple docstring"""




from typing import Any



def     a__ (				snake_case__       , snake_case__       , snake_case__       , snake_case__       , snake_case__       , )						->					list:
			_validation(
			    snake_case__       , snake_case__       , snake_case__       , snake_case__       , snake_case__       , )
			# Creates data structures and fill initial step
			lowerCamelCase			      =					{}
			lowerCamelCase			      =					{}
			for state in states_space:
						lowerCamelCase			      =					observations_space[0]
						lowerCamelCase			      =					(
						    initial_probabilities[state] * emission_probabilities[state][observation]
						)
						lowerCamelCase			      =					None

			# Fills the data structure with the probabilities of
			# different transitions and pointers to previous states
			for o in range(1       , len(snake_case__				)				):
						lowerCamelCase			      =					observations_space[o]
						lowerCamelCase			      =					observations_space[o - 1]
						for state in states_space:
									# Calculates the argmax for probability function
									lowerCamelCase			      =					""""""
									lowerCamelCase			      =					-1
									for k_state in states_space:
												lowerCamelCase			      =					(
												    probabilities[(k_state, prior_observation)]
												    * transition_probabilities[k_state][state]
												    * emission_probabilities[state][observation]
												)
												if probability > max_probability:
															lowerCamelCase			      =					probability
															lowerCamelCase			      =					k_state

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

									lowerCamelCase			      =					arg_max

    # The final observation
			lowerCamelCase			      =					observations_space[len(snake_case__				) - 1]

			# argmax for given final observation
			lowerCamelCase			      =					""""""
			lowerCamelCase			      =					-1
			for k_state in states_space:
						lowerCamelCase			      =					probabilities[(k_state, final_observation)]
						if probability > max_probability:
									lowerCamelCase			      =					probability
									lowerCamelCase			      =					k_state
			lowerCamelCase			      =					arg_max

			# Process pointers backwards
			lowerCamelCase			      =					last_state
			lowerCamelCase			      =					[]
			for o in range(len(snake_case__				) - 1       , -1       , -1				):
						result.append(snake_case__				)
						lowerCamelCase			      =					pointers[previous, observations_space[o]]
			result.reverse()

			return result



def     a__ (				snake_case__       , snake_case__       , snake_case__       , snake_case__       , snake_case__       , )						->					None:
			_validate_not_empty(
			    snake_case__       , snake_case__       , snake_case__       , snake_case__       , snake_case__       , )
			_validate_lists(snake_case__       , snake_case__				)
			_validate_dicts(
			    snake_case__       , snake_case__       , snake_case__				)



def     a__ (				snake_case__       , snake_case__       , snake_case__       , snake_case__       , snake_case__       , )						->					None:
			if not all(
			    [
			        observations_space,
			        states_space,
			        initial_probabilities,
			        transition_probabilities,
			        emission_probabilities,
			    ]				):
						raise ValueError("""There's an empty parameter"""				)



def     a__ (				snake_case__       , snake_case__				)						->					None:
			_validate_list(snake_case__       , """observations_space"""				)
			_validate_list(snake_case__       , """states_space"""				)



def     a__ (				snake_case__       , snake_case__				)						->					None:
			if not isinstance(_object       , snake_case__				):
						lowerCamelCase			      =					F'{var_name} must be a list'
						raise ValueError(snake_case__				)
			else:
						for x in _object:
									if not isinstance(snake_case__       , snake_case__				):
												lowerCamelCase			      =					F'{var_name} must be a list of strings'
												raise ValueError(snake_case__				)



def     a__ (				snake_case__       , snake_case__       , snake_case__       , )						->					None:
			_validate_dict(snake_case__       , """initial_probabilities"""       , snake_case__				)
			_validate_nested_dict(snake_case__       , """transition_probabilities"""				)
			_validate_nested_dict(snake_case__       , """emission_probabilities"""				)



def     a__ (				snake_case__       , snake_case__				)						->					None:
			_validate_dict(_object       , snake_case__       , snake_case__				)
			for x in _object.values():
						_validate_dict(snake_case__       , snake_case__       , snake_case__       , snake_case__				)



def     a__ (				snake_case__       , snake_case__       , snake_case__       , snake_case__ = False				)						->					None:
			if not isinstance(_object       , snake_case__				):
						lowerCamelCase			      =					F'{var_name} must be a dict'
						raise ValueError(snake_case__				)
			if not all(isinstance(snake_case__       , snake_case__				) for x in _object				):
						lowerCamelCase			      =					F'{var_name} all keys must be strings'
						raise ValueError(snake_case__				)
			if not all(isinstance(snake_case__       , snake_case__				) for x in _object.values()				):
						lowerCamelCase			      =					"""nested dictionary """ if nested else """"""
						lowerCamelCase			      =					F'{var_name} {nested_text}all values must be {value_type.__name__}'
						raise ValueError(snake_case__				)


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

					testmod()



