from collections import OrderedDict
from typing import Mapping

from packaging import version

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


_UpperCamelCase         =		logging.get_logger(__name__)

_UpperCamelCase         =		{
    "apple/mobilevit-small": "https://huggingface.co/apple/mobilevit-small/resolve/main/config.json",
    "apple/mobilevit-x-small": "https://huggingface.co/apple/mobilevit-x-small/resolve/main/config.json",
    "apple/mobilevit-xx-small": "https://huggingface.co/apple/mobilevit-xx-small/resolve/main/config.json",
    "apple/deeplabv3-mobilevit-small": (
        "https://huggingface.co/apple/deeplabv3-mobilevit-small/resolve/main/config.json"
    ),
    "apple/deeplabv3-mobilevit-x-small": (
        "https://huggingface.co/apple/deeplabv3-mobilevit-x-small/resolve/main/config.json"
    ),
    "apple/deeplabv3-mobilevit-xx-small": (
        "https://huggingface.co/apple/deeplabv3-mobilevit-xx-small/resolve/main/config.json"
    ),
    # See all MobileViT models at https://huggingface.co/models?filter=mobilevit
}
class 	__UpperCAmelCase						(__A    ):







			'''simple docstring'''
			_UpperCamelCase     :	str				    =							'mobilevit'





			def __init__( self      ,			snake_case_=3      ,			snake_case_=256      ,			snake_case_=2      ,			snake_case_=[144, 192, 240]      ,			snake_case_=[16, 32, 64, 96, 128, 160, 640]      ,			snake_case_=4      ,			snake_case_=2.0      ,			snake_case_=4.0      ,			snake_case_="silu"      ,			snake_case_=3      ,			snake_case_=32      ,			snake_case_=0.1      ,			snake_case_=0.0      ,			snake_case_=0.1      ,			snake_case_=0.02      ,			snake_case_=1E-5      ,			snake_case_=True      ,			snake_case_=256      ,			snake_case_=[6, 12, 18]      ,			snake_case_=0.1      ,			snake_case_=255      ,			**snake_case_      ,			):







										'''simple docstring'''


										super().__init__(**snake_case_       )

										A__					:    str														= num_channels
										A__					:    str														= image_size
										A__					:    str														= patch_size
										A__					:    Any														= hidden_sizes
										A__					:    str														= neck_hidden_sizes
										A__					:    Optional[int]														= num_attention_heads
										A__					:    int														= mlp_ratio
										A__					:    Tuple														= expand_ratio
										A__					:    int														= hidden_act
										A__					:    Any														= conv_kernel_size
										A__					:    Any														= output_stride
										A__					:    Union[str, Any]														= hidden_dropout_prob
										A__					:    Any														= attention_probs_dropout_prob
										A__					:    Optional[Any]														= classifier_dropout_prob
										A__					:    Dict														= initializer_range
										A__					:    Tuple														= layer_norm_eps
										A__					:    str														= qkv_bias

										# decode head attributes for semantic segmentation
										A__					:    Optional[int]														= aspp_out_channels
										A__					:    List[str]														= atrous_rates
										A__					:    Any														= aspp_dropout_prob
										A__					:    Union[str, Any]														= semantic_loss_ignore_index





class 	__UpperCAmelCase						(__A    ):







			'''simple docstring'''
			_UpperCamelCase     :	List[Any]				    =							version.parse('1.11'    )





			@property
			def 		lowerCamelCase				( self       ):







										'''simple docstring'''


										return OrderedDict([("""pixel_values""", {0: """batch""", 1: """num_channels""", 2: """height""", 3: """width"""})]       )





			@property
			def 		lowerCamelCase				( self       ):







										'''simple docstring'''


										if self.task == "image-classification":
																	return OrderedDict([("""logits""", {0: """batch"""})]       )
										else:
																	return OrderedDict([("""last_hidden_state""", {0: """batch"""}), ("""pooler_output""", {0: """batch"""})]       )





			@property
			def 		lowerCamelCase				( self       ):







										'''simple docstring'''


										return 1E-4






"""simple docstring"""



from dataclasses import dataclass

_UpperCamelCase         =		"0.1"
_UpperCamelCase         =		"Lucia Harcekova"
@dataclass
class 	__UpperCAmelCase						:







			'''simple docstring'''
			_UpperCamelCase     :	int
			_UpperCamelCase     :	int
			_UpperCamelCase     :	str





			def __repr__( self       ):







										'''simple docstring'''


										return F'''({self.offset}, {self.length}, {self.indicator})'''





class 	__UpperCAmelCase						:







			'''simple docstring'''





			def __init__( self      ,			snake_case_ = 13      ,			snake_case_ = 6       ):







										'''simple docstring'''


										A__					:    str														= window_size
										A__					:    Optional[int]														= lookahead_buffer_size
										A__					:    Optional[Any]														= self.window_size - self.lookahead_buffer_size





			def 		lowerCamelCase				( self      ,			snake_case_       ):







										'''simple docstring'''


										A__					:    str														= []
										A__					:    Any														= """"""

										# while there are still characters in text to compress
										while text:
																	# find the next encoding phrase
																	# - triplet with offset, length, indicator (the next encoding character)
																	A__					:    Optional[Any]														= self._find_encoding_token(snake_case_      ,			snake_case_       )

																	# update the search buffer:
																	# - add new characters from text into it
																	# - check if size exceed the max search buffer size, if so, drop the
																	#   oldest elements
																	search_buffer += text[: token.length + 1]
																	if len(snake_case_       ) > self.search_buffer_size:
																								A__					:    Any														= search_buffer[-self.search_buffer_size :]

																	# update the text
																	A__					:    Optional[Any]														= text[token.length + 1 :]

																	# append the token to output
																	output.append(snake_case_       )

										return output





			def 		lowerCamelCase				( self      ,			snake_case_       ):







										'''simple docstring'''


										A__					:    List[Any]														= """"""

										for token in tokens:
																	for _ in range(token.length       ):
																								output += output[-token.offset]
																	output += token.indicator

										return output





			def 		lowerCamelCase				( self      ,			snake_case_      ,			snake_case_       ):







										'''simple docstring'''


										if not text:
																	raise ValueError("""We need some text to work with."""       )

										# Initialise result parameters to default values
										A__							,       A__					:    List[Any]														= 0, 0

										if not search_buffer:
																	return Token(snake_case_      ,			snake_case_      ,			text[length]       )

										for i, character in enumerate(snake_case_       ):
																	A__					:    Tuple														= len(snake_case_       ) - i
																	if character == text[0]:
																								A__					:    Tuple														= self._match_length_from_index(snake_case_      ,			snake_case_      ,			0      ,			snake_case_       )
																								# if the found length is bigger than the current or if it's equal,
																								# which means it's offset is smaller: update offset and length
																								if found_length >= length:
																															A__							,       A__					:    List[str]														= found_offset, found_length

										return Token(snake_case_      ,			snake_case_      ,			text[length]       )





			def 		lowerCamelCase				( self      ,			snake_case_      ,			snake_case_      ,			snake_case_      ,			snake_case_       ):







										'''simple docstring'''


										if not text or text[text_index] != window[window_index]:
																	return 0
										return 1 + self._match_length_from_index(
										    snake_case_      ,			window + text[text_index]      ,			text_index + 1      ,			window_index + 1       )


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

				testmod()
				# Initialize compressor class
				_UpperCamelCase         =		LZaaCompressor(window_size=13, lookahead_buffer_size=6)

				# Example
				_UpperCamelCase         =		"cabracadabrarrarrad"
				_UpperCamelCase         =		lzaa_compressor.compress(TEXT)
				print(lzaa_compressor.compress("ababcbababaa"))
				_UpperCamelCase         =		lzaa_compressor.decompress(compressed_text)
				assert decompressed_text == TEXT, "The LZ77 algorithm returned the invalid result."





