

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
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices


lowercase_       		=  logging.get_logger(__name__)

lowercase_       		=  {
    "microsoft/resnet-50": "https://huggingface.co/microsoft/resnet-50/blob/main/config.json",
}


class  A						(							_UpperCAmelCase    ,							_UpperCAmelCase ):







    """simple docstring"""





    lowerCamelCase			=							'resnet'
    lowerCamelCase			=							['basic', 'bottleneck']


    def __init__(      self :       Optional[Any],lowercase_ :       int=3,lowercase_ :       List[str]=6_4,lowercase_ :       int=[2_5_6, 5_1_2, 1_0_2_4, 2_0_4_8],lowercase_ :       Tuple=[3, 4, 6, 3],lowercase_ :       Union[str, Any]="bottleneck",lowercase_ :       List[str]="relu",lowercase_ :       Tuple=False,lowercase_ :       List[str]=None,lowercase_ :       List[Any]=None,**lowercase_ :       str,)->    Optional[Any]:





        '''simple docstring'''







        super().__init__(**lowercase_		)
        if layer_type not in self.layer_types:
            raise ValueError(F'layer_type={layer_type} is not one of {",".join(self.layer_types		)}'		)
        A__          =   num_channels
        A__          =   embedding_size
        A__          =   hidden_sizes
        A__          =   depths
        A__          =   layer_type
        A__          =   hidden_act
        A__          =   downsample_in_first_stage
        A__          =   ['stem'] + [F'stage{idx}' for idx in range(1,len(lowercase_		) + 1		)]
        A__      ,						A__          =   get_aligned_output_features_output_indices(
            out_features=lowercase_,out_indices=lowercase_,stage_names=self.stage_names		)




class  A						(							_UpperCAmelCase ):







    """simple docstring"""





    lowerCamelCase			=							version.parse('1.11' )


    @property
    def 						snake_case__     (      self :       List[Any]		)->    Mapping[str, Mapping[int, str]]:





        '''simple docstring'''







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


    @property
    def 						snake_case__     (      self :       Any		)->    float:





        '''simple docstring'''







        return 1E-3



import json
import os
import unittest

from transformers.models.gptsan_japanese.tokenization_gptsan_japanese import (
    VOCAB_FILES_NAMES,
    GPTSanJapaneseTokenizer,
)
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin




@require_tokenizers
class 						lowercase__  (						_UpperCAmelCase     ,       unittest.TestCase  ):
	A__    :   Any				       =GPTSanJapaneseTokenizer
	A__    :   str				       =False
	A__    :   int				       ={"""do_clean_text""": False, """add_prefix_space""": False}
	def      A_				(			self							:   Any							):
						super().setUp()

						# fmt: off
						SCREAMING_SNAKE_CASE__													= ['こん', 'こんに', 'にちは', 'ばんは', '世界,㔺界', '、', '。', '<BR>', '<SP>', '<TAB>', '<URL>', '<EMAIL>', '<TEL>', '<DATE>', '<PRICE>', '<BLOCK>', '<KIGOU>', '<U2000U2BFF>', '<|emoji1|>', '<unk>', '<|bagoftoken|>', '<|endoftext|>']
						# fmt: on
						SCREAMING_SNAKE_CASE__													= {'emoji': {'\ud83d\ude00': '<|emoji1|>'}, 'emoji_inv': {'<|emoji1|>': '\ud83d\ude00'}}  # 😀
						SCREAMING_SNAKE_CASE__													= {'unk_token': '<unk>'}

						SCREAMING_SNAKE_CASE__													= os.path.join(self.tmpdirname       ,   VOCAB_FILES_NAMES['vocab_file']							)
						SCREAMING_SNAKE_CASE__													= os.path.join(self.tmpdirname       ,   VOCAB_FILES_NAMES['emoji_file']							)
						with open(self.vocab_file       ,   'w'       ,   encoding='utf-8'							) as vocab_writer:
											vocab_writer.write(''.join([x + '\n' for x in vocab_tokens]							)							)
						with open(self.emoji_file       ,   'w'							) as emoji_writer:
											emoji_writer.write(json.dumps(UpperCAmelCase_							)							)
	def      A_				(			self							:   str       ,   **UpperCAmelCase_							:   Optional[Any]							):
						kwargs.update(self.special_tokens_map							)
						return GPTSanJapaneseTokenizer.from_pretrained(self.tmpdirname       ,   **UpperCAmelCase_							)
	def      A_				(			self							:   int       ,   UpperCAmelCase_							:   List[str]							):
						SCREAMING_SNAKE_CASE__													= 'こんにちは、世界。 \nこんばんは、㔺界。😀'
						SCREAMING_SNAKE_CASE__													= 'こんにちは、世界。 \nこんばんは、世界。😀'
						return input_text, output_text
	def      A_				(			self							:   Any       ,   UpperCAmelCase_							:   str							):
						SCREAMING_SNAKE_CASE__						, SCREAMING_SNAKE_CASE__													= self.get_input_output_texts(UpperCAmelCase_							)
						SCREAMING_SNAKE_CASE__													= tokenizer.encode(UpperCAmelCase_       ,   add_special_tokens=UpperCAmelCase_							)
						SCREAMING_SNAKE_CASE__													= tokenizer.decode(UpperCAmelCase_       ,   clean_up_tokenization_spaces=UpperCAmelCase_							)
						return text, ids
	def      A_				(			self							:   str							):
						pass  # TODO add if relevant
	def      A_				(			self							:   Tuple							):
						pass  # TODO add if relevant
	def      A_				(			self							:   int							):
						pass  # TODO add if relevant
	def      A_				(			self							:   Optional[int]							):
						SCREAMING_SNAKE_CASE__													= self.get_tokenizer()

						# Testing tokenization
						SCREAMING_SNAKE_CASE__													= 'こんにちは、世界。　こんばんは、㔺界。'
						SCREAMING_SNAKE_CASE__													= ['こん', 'にちは', '、', '世界', '。', '<SP>', 'こん', 'ばんは', '、', '㔺界', '。']
						SCREAMING_SNAKE_CASE__													= tokenizer.tokenize(UpperCAmelCase_							)
						self.assertListEqual(UpperCAmelCase_       ,   UpperCAmelCase_							)

						# Testing conversion to ids without special tokens
						SCREAMING_SNAKE_CASE__													= [0, 2, 5, 4, 6, 8, 0, 3, 5, 4, 6]
						SCREAMING_SNAKE_CASE__													= tokenizer.convert_tokens_to_ids(UpperCAmelCase_							)
						self.assertListEqual(UpperCAmelCase_       ,   UpperCAmelCase_							)

						# Testing conversion to ids with special tokens
						SCREAMING_SNAKE_CASE__													= tokens + [tokenizer.unk_token]
						SCREAMING_SNAKE_CASE__													= [0, 2, 5, 4, 6, 8, 0, 3, 5, 4, 6, 19]
						SCREAMING_SNAKE_CASE__													= tokenizer.convert_tokens_to_ids(UpperCAmelCase_							)
						self.assertListEqual(UpperCAmelCase_       ,   UpperCAmelCase_							)
	def      A_				(			self							:   Union[str, Any]							):
						SCREAMING_SNAKE_CASE__													= self.get_tokenizer()

						# Testing tokenization
						SCREAMING_SNAKE_CASE__													= 'こんにちは、<|bagoftoken|>世界。こんばんは、<|bagoftoken|>㔺界。'
						SCREAMING_SNAKE_CASE__													= 'こんにちは、、、、世界。こんばんは、、、、世界。'
						SCREAMING_SNAKE_CASE__													= tokenizer.encode(UpperCAmelCase_							)
						SCREAMING_SNAKE_CASE__													= tokenizer.decode(UpperCAmelCase_							)
						self.assertEqual(UpperCAmelCase_       ,   UpperCAmelCase_							)
	@slow
	def      A_				(			self							:   str							):
						SCREAMING_SNAKE_CASE__													= self.tokenizer_class.from_pretrained('Tanrei/GPTSAN-japanese'							)

						# Testing tokenization
						SCREAMING_SNAKE_CASE__													= 'こんにちは、世界。'
						SCREAMING_SNAKE_CASE__													= 'こんばんは、㔺界。😀'
						SCREAMING_SNAKE_CASE__													= 'こんにちは、世界。こんばんは、世界。😀'
						SCREAMING_SNAKE_CASE__													= tokenizer.encode(prefix_text + input_text							)
						SCREAMING_SNAKE_CASE__													= tokenizer.encode(''       ,   prefix_text=prefix_text + input_text							)
						SCREAMING_SNAKE_CASE__													= tokenizer.encode(UpperCAmelCase_       ,   prefix_text=UpperCAmelCase_							)
						SCREAMING_SNAKE_CASE__													= tokenizer.decode(UpperCAmelCase_							)
						SCREAMING_SNAKE_CASE__													= tokenizer.decode(UpperCAmelCase_							)
						SCREAMING_SNAKE_CASE__													= tokenizer.decode(UpperCAmelCase_							)
						self.assertEqual(UpperCAmelCase_       ,   UpperCAmelCase_							)
						self.assertEqual(UpperCAmelCase_       ,   UpperCAmelCase_							)
						self.assertEqual(UpperCAmelCase_       ,   UpperCAmelCase_							)
	@slow
	def      A_				(			self							:   Union[str, Any]							):
						SCREAMING_SNAKE_CASE__													= self.tokenizer_class.from_pretrained('Tanrei/GPTSAN-japanese'							)

						# Testing tokenization
						SCREAMING_SNAKE_CASE__													= 'こんにちは、世界。'
						SCREAMING_SNAKE_CASE__													= 'こんばんは、㔺界。😀'

						SCREAMING_SNAKE_CASE__													= len(tokenizer.encode(UpperCAmelCase_							)							) - 2
						SCREAMING_SNAKE_CASE__													= len(tokenizer.encode(UpperCAmelCase_							)							) - 2

						SCREAMING_SNAKE_CASE__													= [1] + [0] * (len_prefix + len_text + 1)
						SCREAMING_SNAKE_CASE__													= [1] * (len_prefix + len_text + 1) + [0]
						SCREAMING_SNAKE_CASE__													= [1] + [1] * (len_prefix) + [0] * (len_text + 1)

						SCREAMING_SNAKE_CASE__													= tokenizer(prefix_text + input_text							).token_type_ids
						SCREAMING_SNAKE_CASE__													= tokenizer(''       ,   prefix_text=prefix_text + input_text							).token_type_ids
						SCREAMING_SNAKE_CASE__													= tokenizer(UpperCAmelCase_       ,   prefix_text=UpperCAmelCase_							).token_type_ids
						self.assertListEqual(UpperCAmelCase_       ,   UpperCAmelCase_							)
						self.assertListEqual(UpperCAmelCase_       ,   UpperCAmelCase_							)
						self.assertListEqual(UpperCAmelCase_       ,   UpperCAmelCase_							)
	@slow
	def      A_				(			self							:   Tuple							):
						SCREAMING_SNAKE_CASE__													= self.tokenizer_class.from_pretrained('Tanrei/GPTSAN-japanese'							)

						SCREAMING_SNAKE_CASE__													= tokenizer.encode('あンいワ'							)
						SCREAMING_SNAKE_CASE__													= tokenizer.encode(''       ,   prefix_text='あンいワ'							)
						SCREAMING_SNAKE_CASE__													= tokenizer.encode('いワ'       ,   prefix_text='あン'							)

						self.assertEqual(tokenizer.decode(UpperCAmelCase_							)       ,   tokenizer.decode(UpperCAmelCase_							)							)
						self.assertEqual(tokenizer.decode(UpperCAmelCase_							)       ,   tokenizer.decode(UpperCAmelCase_							)							)
						self.assertNotEqual(UpperCAmelCase_       ,   UpperCAmelCase_							)
						self.assertNotEqual(UpperCAmelCase_       ,   UpperCAmelCase_							)
						self.assertEqual(x_token_a[1]       ,   x_token_a[-1]							)  # SEG token
						self.assertEqual(x_token_a[1]       ,   x_token_a[3]							)  # SEG token
	@slow
	def      A_				(			self							:   Union[str, Any]							):
						SCREAMING_SNAKE_CASE__													= self.tokenizer_class.from_pretrained('Tanrei/GPTSAN-japanese'							)

						SCREAMING_SNAKE_CASE__													= [['武田信玄', 'は、'], ['織田信長', 'の配下の、']]
						SCREAMING_SNAKE_CASE__													= tokenizer(UpperCAmelCase_       ,   padding=UpperCAmelCase_							)
						SCREAMING_SNAKE_CASE__													= tokenizer.batch_encode_plus(UpperCAmelCase_       ,   padding=UpperCAmelCase_							)

						# fmt: off
						SCREAMING_SNAKE_CASE__													= [[35993, 8640, 25948, 35998, 30647, 35675, 35999, 35999], [35993, 10382, 9868, 35998, 30646, 9459, 30646, 35675]]
						SCREAMING_SNAKE_CASE__													= [[1, 1, 1, 0, 0, 0, 0, 0], [1, 1, 1, 0, 0, 0, 0, 0]]
						SCREAMING_SNAKE_CASE__													= [[1, 1, 1, 1, 1, 1, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1]]
						# fmt: on
						self.assertListEqual(x_token.input_ids       ,   UpperCAmelCase_							)
						self.assertListEqual(x_token.token_type_ids       ,   UpperCAmelCase_							)
						self.assertListEqual(x_token.attention_mask       ,   UpperCAmelCase_							)
						self.assertListEqual(x_token_a.input_ids       ,   UpperCAmelCase_							)
						self.assertListEqual(x_token_a.token_type_ids       ,   UpperCAmelCase_							)
						self.assertListEqual(x_token_a.attention_mask       ,   UpperCAmelCase_							)
	def      A_				(			self							:   Tuple							):
						# Intentionally convert some words to accommodate character fluctuations unique to Japanese
						pass





	def      A_				(			self							:   List[str]							):
						# tokenizer has no padding token
						pass





