
"""simple docstring"""

import json
import os
import unittest

from transformers import OpenAIGPTTokenizer, OpenAIGPTTokenizerFast
from transformers.models.openai.tokenization_openai import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_spacy, require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin

@require_tokenizers
class __lowerCAmelCase	(   lowerCAmelCase__    ,						unittest.TestCase    ):
     lowercase		     =		OpenAIGPTTokenizer
     lowercase		     =		OpenAIGPTTokenizerFast
     lowercase		     =		True
     lowercase		     =		False





     def 		UpperCAmelCase      (			self   ):

      '''simple docstring'''




      super().setUp()

      # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
      __UpperCamelCase       						= [
          'l',
          'o',
          'w',
          'e',
          'r',
          's',
          't',
          'i',
          'd',
          'n',
          'w</w>',
          'r</w>',
          't</w>',
          'lo',
          'low',
          'er</w>',
          'low</w>',
          'lowest</w>',
          'newer</w>',
          'wider</w>',
          '<unk>',
      ]
      __UpperCamelCase       						= dict(zip(_SCREAMING_SNAKE_CASE			,  range(len(_SCREAMING_SNAKE_CASE   )   )   )   )
      __UpperCamelCase       						= ['#version: 0.2', 'l o', 'lo w', 'e r</w>', '']

      __UpperCamelCase       						= os.path.join(self.tmpdirname			,  VOCAB_FILES_NAMES['vocab_file']   )
      __UpperCamelCase       						= os.path.join(self.tmpdirname			,  VOCAB_FILES_NAMES['merges_file']   )
      with open(self.vocab_file			,  'w'   ) as fp:
       fp.write(json.dumps(_SCREAMING_SNAKE_CASE   )   )
      with open(self.merges_file			,  'w'   ) as fp:
       fp.write('\n'.join(_SCREAMING_SNAKE_CASE   )   )





     def 		UpperCAmelCase      (			self			,  __UpperCAmelCase   ):

      '''simple docstring'''




      return "lower newer", "lower newer"





     def 		UpperCAmelCase      (			self   ):

      '''simple docstring'''




      __UpperCamelCase       						= OpenAIGPTTokenizer(self.vocab_file			,  self.merges_file   )

      __UpperCamelCase       						= 'lower'
      __UpperCamelCase       						= ['low', 'er</w>']
      __UpperCamelCase       						= tokenizer.tokenize(_SCREAMING_SNAKE_CASE   )
      self.assertListEqual(_SCREAMING_SNAKE_CASE			,  _SCREAMING_SNAKE_CASE   )

      __UpperCamelCase       						= tokens + ['<unk>']
      __UpperCamelCase       						= [14, 15, 20]
      self.assertListEqual(tokenizer.convert_tokens_to_ids(_SCREAMING_SNAKE_CASE   )			,  _SCREAMING_SNAKE_CASE   )





     def 		UpperCAmelCase      (			self			,  __UpperCAmelCase=15   ):

      '''simple docstring'''




      for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
       with self.subTest(F'{tokenizer.__class__.__name__} ({pretrained_name})'   ):
        __UpperCamelCase       						= self.rust_tokenizer_class.from_pretrained(_SCREAMING_SNAKE_CASE			,  **_SCREAMING_SNAKE_CASE   )

        # Simple input
        __UpperCamelCase       						= 'This is a simple input'
        __UpperCamelCase       						= ['This is a simple input 1', 'This is a simple input 2']
        __UpperCamelCase       						= ('This is a simple input', 'This is a pair')
        __UpperCamelCase       						= [
            ('This is a simple input 1', 'This is a simple input 2'),
            ('This is a simple pair 1', 'This is a simple pair 2'),
        ]

        # Simple input tests
        self.assertRaises(_SCREAMING_SNAKE_CASE			,  tokenizer_r.encode			,  _SCREAMING_SNAKE_CASE			,  max_length=_SCREAMING_SNAKE_CASE			,  padding='max_length'   )

        # Simple input
        self.assertRaises(_SCREAMING_SNAKE_CASE			,  tokenizer_r.encode_plus			,  _SCREAMING_SNAKE_CASE			,  max_length=_SCREAMING_SNAKE_CASE			,  padding='max_length'   )

        # Simple input
        self.assertRaises(
            _SCREAMING_SNAKE_CASE			,  tokenizer_r.batch_encode_plus			,  _SCREAMING_SNAKE_CASE			,  max_length=_SCREAMING_SNAKE_CASE			,  padding='max_length'			,  )

        # Pair input
        self.assertRaises(_SCREAMING_SNAKE_CASE			,  tokenizer_r.encode			,  _SCREAMING_SNAKE_CASE			,  max_length=_SCREAMING_SNAKE_CASE			,  padding='max_length'   )

        # Pair input
        self.assertRaises(_SCREAMING_SNAKE_CASE			,  tokenizer_r.encode_plus			,  _SCREAMING_SNAKE_CASE			,  max_length=_SCREAMING_SNAKE_CASE			,  padding='max_length'   )

        # Pair input
        self.assertRaises(
            _SCREAMING_SNAKE_CASE			,  tokenizer_r.batch_encode_plus			,  _SCREAMING_SNAKE_CASE			,  max_length=_SCREAMING_SNAKE_CASE			,  padding='max_length'			,  )







     def 		UpperCAmelCase      (			self   ):

      '''simple docstring'''




      pass


@require_ftfy
@require_spacy
@require_tokenizers
class __lowerCAmelCase	(   lowerCAmelCase__    ):
     pass





"""simple docstring"""

from typing import List

from ...configuration_utils import PretrainedConfig
from ...utils import logging


UpperCamelCase			:       Tuple									=				logging.get_logger(__name__)

UpperCamelCase			:       List[str]									=				{
    "snap-research/efficientformer-l1-300": (
        "https://huggingface.co/snap-research/efficientformer-l1-300/resolve/main/config.json"
    ),
}

class __lowerCAmelCase	(   __SCREAMING_SNAKE_CASE    ):
     lowercase		     =		"efficientformer"





     def __init__(			self			,  __UpperCAmelCase = [3, 2, 6, 4]			,  __UpperCAmelCase = [48, 96, 224, 448]			,  __UpperCAmelCase = [True, True, True, True]			,  __UpperCAmelCase = 448			,  __UpperCAmelCase = 32			,  __UpperCAmelCase = 4			,  __UpperCAmelCase = 7			,  __UpperCAmelCase = 5			,  __UpperCAmelCase = 8			,  __UpperCAmelCase = 4			,  __UpperCAmelCase = 0.0			,  __UpperCAmelCase = 16			,  __UpperCAmelCase = 3			,  __UpperCAmelCase = 3			,  __UpperCAmelCase = 3			,  __UpperCAmelCase = 2			,  __UpperCAmelCase = 1			,  __UpperCAmelCase = 0.0			,  __UpperCAmelCase = 1			,  __UpperCAmelCase = True			,  __UpperCAmelCase = True			,  __UpperCAmelCase = 1E-5			,  __UpperCAmelCase = "gelu"			,  __UpperCAmelCase = 0.0_2			,  __UpperCAmelCase = 1E-12			,  __UpperCAmelCase = 224			,  __UpperCAmelCase = 1E-05			,  **__UpperCAmelCase			,  ):

      '''simple docstring'''




      super().__init__(**__UpperCAmelCase   )

      __UpperCamelCase       						= hidden_act
      __UpperCamelCase       						= hidden_dropout_prob
      __UpperCamelCase       						= hidden_sizes
      __UpperCamelCase       						= num_hidden_layers
      __UpperCamelCase       						= num_attention_heads
      __UpperCamelCase       						= initializer_range
      __UpperCamelCase       						= layer_norm_eps
      __UpperCamelCase       						= patch_size
      __UpperCamelCase       						= num_channels
      __UpperCamelCase       						= depths
      __UpperCamelCase       						= mlp_expansion_ratio
      __UpperCamelCase       						= downsamples
      __UpperCamelCase       						= dim
      __UpperCamelCase       						= key_dim
      __UpperCamelCase       						= attention_ratio
      __UpperCamelCase       						= resolution
      __UpperCamelCase       						= pool_size
      __UpperCamelCase       						= downsample_patch_size
      __UpperCamelCase       						= downsample_stride
      __UpperCamelCase       						= downsample_pad
      __UpperCamelCase       						= drop_path_rate
      __UpperCamelCase       						= num_metaad_blocks
      __UpperCamelCase       						= distillation
      __UpperCamelCase       						= use_layer_scale
      __UpperCamelCase       						= layer_scale_init_value
      __UpperCamelCase       						= image_size
      __UpperCamelCase       						= batch_norm_eps



