

import os
import unittest

from transformers import BatchEncoding
from transformers.models.bert.tokenization_bert import (
    BasicTokenizer,
    WordpieceTokenizer,
    _is_control,
    _is_punctuation,
    _is_whitespace,
)
from transformers.models.prophetnet.tokenization_prophetnet import VOCAB_FILES_NAMES, ProphetNetTokenizer
from transformers.testing_utils import require_torch, slow

from ...test_tokenization_common import TokenizerTesterMixin


class       SCREAMING_SNAKE_CASE__					(__snake_case		,       unittest.TestCase     ):
    __lowerCamelCase						:       Optional[Any]														=     ProphetNetTokenizer
    __lowerCamelCase						:       Tuple														=     False





    def       snake_case_				(      self):
         super().setUp()

         lowercase__    :   Any      =       [
             '[UNK]',
             '[CLS]',
             '[SEP]',
             '[PAD]',
             '[MASK]',
             'want',
             '##want',
             '##ed',
             'wa',
             'un',
             'runn',
             '##ing',
             ',',
             'low',
             'lowest',
         ]
         lowercase__    :   Optional[int]      =       os.path.join(self.tmpdirname						,   VOCAB_FILES_NAMES['vocab_file'])
         with open(self.vocab_file						,   'w'						,   encoding='utf-8') as vocab_writer:
              vocab_writer.write(''.join([x + '\n' for x in vocab_tokens]))





    def       snake_case_				(      self						,   a):
         lowercase__    :   List[Any]      =       'UNwant\u00E9d,running'
         lowercase__    :   Tuple      =       'unwanted, running'
         return input_text, output_text





    def       snake_case_				(      self):
         lowercase__    :   int      =       self.tokenizer_class(self.vocab_file)

         lowercase__    :   Optional[Any]      =       tokenizer.tokenize('UNwant\u00E9d,running')
         self.assertListEqual(a						,   ['un', '##want', '##ed', ',', 'runn', '##ing'])
         self.assertListEqual(tokenizer.convert_tokens_to_ids(a)						,   [9, 6, 7, 12, 10, 11])





    def       snake_case_				(      self):
         lowercase__    :   str      =       BasicTokenizer()

         self.assertListEqual(tokenizer.tokenize('ah\u535A\u63A8zz')						,   ['ah', '\u535A', '\u63A8', 'zz'])





    def       snake_case_				(      self):
         lowercase__    :   List[Any]      =       BasicTokenizer(do_lower_case=a)

         self.assertListEqual(
             tokenizer.tokenize(' \tHeLLo!how  \n Are yoU?  ')						,   ['hello', '!', 'how', 'are', 'you', '?'])
         self.assertListEqual(tokenizer.tokenize('H\u00E9llo')						,   ['hello'])





    def       snake_case_				(      self):
         lowercase__    :   Tuple      =       BasicTokenizer(do_lower_case=a						,   strip_accents=a)

         self.assertListEqual(
             tokenizer.tokenize(' \tHäLLo!how  \n Are yoU?  ')						,   ['hällo', '!', 'how', 'are', 'you', '?'])
         self.assertListEqual(tokenizer.tokenize('H\u00E9llo')						,   ['h\u00E9llo'])





    def       snake_case_				(      self):
         lowercase__    :   str      =       BasicTokenizer(do_lower_case=a						,   strip_accents=a)

         self.assertListEqual(
             tokenizer.tokenize(' \tHäLLo!how  \n Are yoU?  ')						,   ['hallo', '!', 'how', 'are', 'you', '?'])
         self.assertListEqual(tokenizer.tokenize('H\u00E9llo')						,   ['hello'])





    def       snake_case_				(      self):
         lowercase__    :   Any      =       BasicTokenizer(do_lower_case=a)

         self.assertListEqual(
             tokenizer.tokenize(' \tHäLLo!how  \n Are yoU?  ')						,   ['hallo', '!', 'how', 'are', 'you', '?'])
         self.assertListEqual(tokenizer.tokenize('H\u00E9llo')						,   ['hello'])





    def       snake_case_				(      self):
         lowercase__    :   str      =       BasicTokenizer(do_lower_case=a)

         self.assertListEqual(
             tokenizer.tokenize(' \tHeLLo!how  \n Are yoU?  ')						,   ['HeLLo', '!', 'how', 'Are', 'yoU', '?'])





    def       snake_case_				(      self):
         lowercase__    :   Optional[Any]      =       BasicTokenizer(do_lower_case=a						,   strip_accents=a)

         self.assertListEqual(
             tokenizer.tokenize(' \tHäLLo!how  \n Are yoU?  ')						,   ['HäLLo', '!', 'how', 'Are', 'yoU', '?'])





    def       snake_case_				(      self):
         lowercase__    :   str      =       BasicTokenizer(do_lower_case=a						,   strip_accents=a)

         self.assertListEqual(
             tokenizer.tokenize(' \tHäLLo!how  \n Are yoU?  ')						,   ['HaLLo', '!', 'how', 'Are', 'yoU', '?'])





    def       snake_case_				(      self):
         lowercase__    :   str      =       BasicTokenizer(do_lower_case=a						,   never_split=['[UNK]'])

         self.assertListEqual(
             tokenizer.tokenize(' \tHeLLo!how  \n Are yoU? [UNK]')						,   ['HeLLo', '!', 'how', 'Are', 'yoU', '?', '[UNK]'])





    def       snake_case_				(      self):
         lowercase__    :   List[Any]      =       ['[UNK]', '[CLS]', '[SEP]', 'want', '##want', '##ed', 'wa', 'un', 'runn', '##ing']

         lowercase__    :   List[Any]      =       {}
         for i, token in enumerate(a):
              lowercase__    :   Union[str, Any]      =       i
         lowercase__    :   Union[str, Any]      =       WordpieceTokenizer(vocab=a						,   unk_token='[UNK]')

         self.assertListEqual(tokenizer.tokenize('')						,   [])

         self.assertListEqual(tokenizer.tokenize('unwanted running')						,   ['un', '##want', '##ed', 'runn', '##ing'])

         self.assertListEqual(tokenizer.tokenize('unwantedX running')						,   ['[UNK]', 'runn', '##ing'])





    @require_torch
    def       snake_case_				(      self):
         lowercase__    :   Optional[Any]      =       self.tokenizer_class.from_pretrained('microsoft/prophetnet-large-uncased')

         lowercase__    :   List[Any]      =       ['A long paragraph for summarization.', 'Another paragraph for summarization.']
         lowercase__    :   Optional[Any]      =       [1037, 2146, 2_0423, 2005, 7680, 7849, 3989, 1012, 102]
         lowercase__    :   str      =       tokenizer(a						,   padding=a						,   return_tensors='pt')
         self.assertIsInstance(a						,   a)
         lowercase__    :   Optional[Any]      =       list(batch.input_ids.numpy()[0])
         self.assertListEqual(a						,   a)

         self.assertEqual((2, 9)						,   batch.input_ids.shape)
         self.assertEqual((2, 9)						,   batch.attention_mask.shape)





    def       snake_case_				(      self):
         self.assertTrue(_is_whitespace(' '))
         self.assertTrue(_is_whitespace('\t'))
         self.assertTrue(_is_whitespace('\r'))
         self.assertTrue(_is_whitespace('\n'))
         self.assertTrue(_is_whitespace('\u00A0'))

         self.assertFalse(_is_whitespace('A'))
         self.assertFalse(_is_whitespace('-'))





    def       snake_case_				(      self):
         self.assertTrue(_is_control('\u0005'))

         self.assertFalse(_is_control('A'))
         self.assertFalse(_is_control(' '))
         self.assertFalse(_is_control('\t'))
         self.assertFalse(_is_control('\r'))





    def       snake_case_				(      self):
         self.assertTrue(_is_punctuation('-'))
         self.assertTrue(_is_punctuation('$'))
         self.assertTrue(_is_punctuation('`'))
         self.assertTrue(_is_punctuation('.'))

         self.assertFalse(_is_punctuation('A'))
         self.assertFalse(_is_punctuation(' '))





    @slow
    def       snake_case_				(      self):
         lowercase__    :   int      =       self.tokenizer_class.from_pretrained('microsoft/prophetnet-large-uncased')

         lowercase__    :   Optional[Any]      =       tokenizer.encode('sequence builders'						,   add_special_tokens=a)
         lowercase__    :   str      =       tokenizer.encode('multi-sequence build'						,   add_special_tokens=a)

         lowercase__    :   Optional[int]      =       tokenizer.build_inputs_with_special_tokens(a)
         lowercase__    :   Optional[int]      =       tokenizer.build_inputs_with_special_tokens(a						,   a)

         assert encoded_sentence == text + [102]
         assert encoded_pair == text + [102] + text_a + [102]




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


snake_case_			  = logging.get_logger(__name__)

snake_case_			  = {
    '''google/switch-base-8''': '''https://huggingface.co/google/switch-base-8/blob/main/config.json''',
}


class       SCREAMING_SNAKE_CASE__					(__snake_case     ):
    __lowerCamelCase						:       int														=     """switch_transformers"""
    __lowerCamelCase						:       Optional[Any]														=     ["""past_key_values"""]
    __lowerCamelCase						:       Any														=     {"""hidden_size""": """d_model""", """num_attention_heads""": """num_heads""", """num_hidden_layers""": """num_layers"""}





    def __init__(      self						,   a=3_2128						,   a=768						,   a=64						,   a=2048						,   a=64						,   a=12						,   a=3						,   a=12						,   a=3						,   a=12						,   a=8						,   a=False						,   a=0.01						,   a="float32"						,   a=False						,   a=32						,   a=128						,   a=0.1						,   a=1e-6						,   a=0.001						,   a=0.001						,   a=1.0						,   a="relu"						,   a=True						,   a=False						,   a=True						,   a=0						,   a=1						,   **a						,   ):
         lowercase__    :   Optional[int]      =       vocab_size
         lowercase__    :   List[Any]      =       d_model
         lowercase__    :   List[Any]      =       d_kv
         lowercase__    :   Any      =       d_ff

         lowercase__    :   Optional[int]      =       num_sparse_encoder_layers

         lowercase__    :   Tuple      =       num_layers
         lowercase__    :   Optional[Any]      =       (
             num_decoder_layers if num_decoder_layers is not None else self.num_layers
         )  # default = symmetry
         lowercase__    :   str      =       num_sparse_decoder_layers

         # This tells us, each how many encoder layer we'll have to set a sparse layer.
         if self.num_sparse_encoder_layers > 0:
              lowercase__    :   Optional[Any]      =       self.num_layers // self.num_sparse_encoder_layers
         else:
              lowercase__    :   Optional[int]      =       self.num_layers  # HACK: this will create 0 sparse layers

         # This tells us, each how many encoder layer we'll have to set a sparse layer.
         if self.num_sparse_decoder_layers > 0:
              lowercase__    :   Union[str, Any]      =       self.num_decoder_layers // self.num_sparse_decoder_layers
         else:
              lowercase__    :   int      =       self.num_decoder_layers  # HACK: this will create 0 sparse layers

         lowercase__    :   List[Any]      =       num_heads
         lowercase__    :   Union[str, Any]      =       num_experts
         lowercase__    :   str      =       expert_capacity
         lowercase__    :   List[Any]      =       router_bias
         lowercase__    :   Optional[int]      =       router_jitter_noise
         if router_dtype not in ["float32", "float16", "bfloat16"]:
              raise ValueError(f"""`router_dtype` must be one of 'float32', 'float16' or 'bfloat16', got {router_dtype}""")
         lowercase__    :   str      =       router_dtype

         lowercase__    :   Optional[int]      =       router_ignore_padding_tokens
         lowercase__    :   int      =       relative_attention_num_buckets
         lowercase__    :   Optional[Any]      =       relative_attention_max_distance

         lowercase__    :   List[str]      =       dropout_rate
         lowercase__    :   str      =       layer_norm_epsilon
         lowercase__    :   int      =       initializer_factor
         lowercase__    :   int      =       feed_forward_proj
         lowercase__    :   Dict      =       use_cache
         lowercase__    :   int      =       add_router_probs

         lowercase__    :   int      =       router_z_loss_coef
         lowercase__    :   List[Any]      =       router_aux_loss_coef

         lowercase__    :   int      =       self.feed_forward_proj.split('-')
         lowercase__    :   Optional[int]      =       act_info[-1]
         lowercase__    :   Dict      =       act_info[0] == 'gated'

         if len(a) > 1 and act_info[0] != "gated" or len(a) > 2:
              raise ValueError(
                  f"""`feed_forward_proj`: {feed_forward_proj} is not a valid activation function of the dense layer."""
                  'Please make sure `feed_forward_proj` is of the format `gated-{ACT_FN}` or `{ACT_FN}`, e.g. '
                  '\'gated-gelu\' or \'relu\'')

         # for backwards compatibility
         if feed_forward_proj == "gated-gelu":
              lowercase__    :   Optional[int]      =       'gelu_new'

         super().__init__(
             pad_token_id=a						,   eos_token_id=a						,   is_encoder_decoder=a						,   **a						,   )

