


"""simple docstring"""

import os
from typing import Dict, List, Union

import tensorflow as tf
from keras_nlp.tokenizers import BytePairTokenizer
from tensorflow_text import pad_model_inputs

from .tokenization_gpta import GPTaTokenizer





class    lowerCamelCase__						(		tf.keras.layers.Layer    ):
      def __init__(		self	:	List[str]      ,       A_	:	Dict[str, int]      ,       A_	:	List[str]      ,       A_	:	int = None      ,       A_	:	int = None							):






       '''simple docstring'''


       super().__init__()
       __lowercase									=	pad_token_id
       __lowercase									=	max_length
       __lowercase									=	vocab
       __lowercase									=	merges
       __lowercase									=	BytePairTokenizer(A_      ,       A_      ,       sequence_length=A_							)
      @classmethod
      def SCREAMING_SNAKE_CASE_	(		cls	:	Any      ,       A_	:	GPTaTokenizer      ,       *A_	:	Any      ,       **A_	:	List[Any]							):






       '''simple docstring'''


       __lowercase									=	[""" """.join(A_							) for m in tokenizer.bpe_ranks.keys()]
       __lowercase									=	tokenizer.get_vocab()
       return cls(A_      ,       A_      ,       *A_      ,       **A_							)
      @classmethod
      def SCREAMING_SNAKE_CASE_	(		cls	:	Union[str, Any]      ,       A_	:	Union[str, os.PathLike]      ,       *A_	:	Optional[int]      ,       **A_	:	List[Any]							):






       '''simple docstring'''


       __lowercase									=	GPTaTokenizer.from_pretrained(A_      ,       *A_      ,       **A_							)
       return cls.from_tokenizer(A_      ,       *A_      ,       **A_							)
      @classmethod
      def SCREAMING_SNAKE_CASE_	(		cls	:	List[Any]      ,       A_	:	Tuple							):






       '''simple docstring'''


       return cls(**A_							)
      def SCREAMING_SNAKE_CASE_	(		self	:	Any							):






       '''simple docstring'''


       return {
           "vocab": self.vocab,
           "merges": self.merges,
           "max_length": self.max_length,
           "pad_token_id": self.pad_token_id,
       }






      def SCREAMING_SNAKE_CASE_	(		self	:	Tuple      ,       A_	:	Dict      ,       A_	:	int = None							):






       '''simple docstring'''


       __lowercase									=	self.tf_tokenizer(A_							)
       __lowercase									=	tf.ones_like(A_							)

       if self.pad_token_id is not None:
        # pad the tokens up to max length
        __lowercase									=	max_length if max_length is not None else self.max_length

        if max_length is not None:
         __lowercase							,		__lowercase									=	pad_model_inputs(
             A_      ,       max_seq_length=A_      ,       pad_value=self.pad_token_id							)

       return {"attention_mask": attention_mask, "input_ids": input_ids}




"""simple docstring"""

import warnings
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__  							={
    "nvidia/segformer-b0-finetuned-ade-512-512": (
        "https://huggingface.co/nvidia/segformer-b0-finetuned-ade-512-512/resolve/main/config.json"
    ),
    # See all SegFormer models at https://huggingface.co/models?filter=segformer
}





class    lowerCamelCase__						(		_a    ):
      a :     Optional[int]											=		"""segformer"""
      def __init__(		self	:	str      ,       A_	:	Optional[int]=3      ,       A_	:	Any=4      ,       A_	:	Optional[int]=[2, 2, 2, 2]      ,       A_	:	str=[8, 4, 2, 1]      ,       A_	:	Any=[3_2, 6_4, 1_6_0, 2_5_6]      ,       A_	:	Union[str, Any]=[7, 3, 3, 3]      ,       A_	:	Any=[4, 2, 2, 2]      ,       A_	:	int=[1, 2, 5, 8]      ,       A_	:	Union[str, Any]=[4, 4, 4, 4]      ,       A_	:	Optional[Any]="gelu"      ,       A_	:	List[str]=0.0      ,       A_	:	Any=0.0      ,       A_	:	Optional[Any]=0.1      ,       A_	:	List[str]=0.02      ,       A_	:	Tuple=0.1      ,       A_	:	Optional[Any]=1e-6      ,       A_	:	Optional[int]=2_5_6      ,       A_	:	Optional[Any]=2_5_5      ,       **A_	:	Union[str, Any]      ,       ):






       '''simple docstring'''


       super().__init__(**A_							)

       if "reshape_last_stage" in kwargs and kwargs["reshape_last_stage"] is False:
        warnings.warn(
            """Reshape_last_stage is set to False in this config. This argument is deprecated and will soon be"""
            """ removed, as the behaviour will default to that of reshape_last_stage = True."""      ,       A_      ,       )

       __lowercase									=	num_channels
       __lowercase									=	num_encoder_blocks
       __lowercase									=	depths
       __lowercase									=	sr_ratios
       __lowercase									=	hidden_sizes
       __lowercase									=	patch_sizes
       __lowercase									=	strides
       __lowercase									=	mlp_ratios
       __lowercase									=	num_attention_heads
       __lowercase									=	hidden_act
       __lowercase									=	hidden_dropout_prob
       __lowercase									=	attention_probs_dropout_prob
       __lowercase									=	classifier_dropout_prob
       __lowercase									=	initializer_range
       __lowercase									=	drop_path_rate
       __lowercase									=	layer_norm_eps
       __lowercase									=	decoder_hidden_size
       __lowercase									=	kwargs.get("""reshape_last_stage"""      ,       A_							)
       __lowercase									=	semantic_loss_ignore_index






class    lowerCamelCase__						(		_a    ):
      a :     List[str]											=		version.parse("""1.11"""    )
      @property
      def SCREAMING_SNAKE_CASE_	(		self	:	Any							):






       '''simple docstring'''


       return OrderedDict(
           [
               ("""pixel_values""", {0: """batch""", 1: """num_channels""", 2: """height""", 3: """width"""}),
           ]							)
      @property
      def SCREAMING_SNAKE_CASE_	(		self	:	int							):






       '''simple docstring'''


       return 1e-4






      @property
      def SCREAMING_SNAKE_CASE_	(		self	:	int							):






       '''simple docstring'''


       return 1_2
