
'''simple docstring'''

import json
import os
import unittest

from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin


@require_tokenizers
class  _UpperCAmelCase ( lowerCAmelCase__	,unittest.TestCase    ):

     """simple docstring"""

     a_    	=					CLIPTokenizer
     a_    	=					CLIPTokenizerFast
     a_    	=					True
     a_    	=					{}
     a_    	=					False


     def 							_lowerCAmelCase  (      self ):

       '''simple docstring'''

       super().setUp()

       # fmt: off
       a_      :	str      =							["""l""", """o""", """w""", """e""", """r""", """s""", """t""", """i""", """d""", """n""", """lo""", """l</w>""", """w</w>""", """r</w>""", """t</w>""", """low</w>""", """er</w>""", """lowest</w>""", """newer</w>""", """wider""", """<unk>""", """<|startoftext|>""", """<|endoftext|>"""]
       # fmt: on
       a_      :	int      =							dict(zip(lowerCAmelCase_							,		range(len(lowerCAmelCase_ ) ) ) )
       a_      :	List[str]      =							["""#version: 0.2""", """l o""", """lo w</w>""", """e r</w>"""]
       a_      :	Any      =							{"""unk_token""": """<unk>"""}

       a_      :	int      =							os.path.join(self.tmpdirname							,		VOCAB_FILES_NAMES["""vocab_file"""] )
       a_      :	Dict      =							os.path.join(self.tmpdirname							,		VOCAB_FILES_NAMES["""merges_file"""] )
       with open(self.vocab_file							,		"""w"""							,		encoding="""utf-8""" ) as fp:
         fp.write(json.dumps(lowerCAmelCase_ ) + """\n""" )
       with open(self.merges_file							,		"""w"""							,		encoding="""utf-8""" ) as fp:
         fp.write("""\n""".join(lowerCAmelCase_ ) )


     def 							_lowerCAmelCase  (      self							,		**lowerCAmelCase_ ):

       '''simple docstring'''

       kwargs.update(self.special_tokens_map )
       return CLIPTokenizer.from_pretrained(self.tmpdirname							,		**lowerCAmelCase_ )


     def 							_lowerCAmelCase  (      self							,		**lowerCAmelCase_ ):

       '''simple docstring'''

       kwargs.update(self.special_tokens_map )
       return CLIPTokenizerFast.from_pretrained(self.tmpdirname							,		**lowerCAmelCase_ )


     def 							_lowerCAmelCase  (      self							,		lowerCAmelCase_ ):

       '''simple docstring'''

       a_      :	str      =							"""lower newer"""
       a_      :	List[Any]      =							"""lower newer"""
       return input_text, output_text


     def 							_lowerCAmelCase  (      self ):

       '''simple docstring'''

       a_      :	Dict      =							CLIPTokenizer(self.vocab_file							,		self.merges_file							,		**self.special_tokens_map )
       a_      :	Optional[Any]      =							"""lower newer"""
       a_      :	int      =							["""lo""", """w""", """er</w>""", """n""", """e""", """w""", """er</w>"""]
       a_      :	List[str]      =							tokenizer.tokenize(lowerCAmelCase_ )
       self.assertListEqual(lowerCAmelCase_							,		lowerCAmelCase_ )

       a_      :	Optional[Any]      =							tokens + [tokenizer.unk_token]
       a_      :	Optional[int]      =							[10, 2, 16, 9, 3, 2, 16, 20]
       self.assertListEqual(tokenizer.convert_tokens_to_ids(lowerCAmelCase_ )							,		lowerCAmelCase_ )


     @require_ftfy
     def 							_lowerCAmelCase  (      self ):

       '''simple docstring'''

       for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
         with self.subTest(f'''{tokenizer.__class__.__name__} ({pretrained_name})''' ):
           a_      :	Optional[int]      =							self.tokenizer_class.from_pretrained(lowerCAmelCase_							,		**lowerCAmelCase_ )
           a_      :	Dict      =							self.rust_tokenizer_class.from_pretrained(lowerCAmelCase_							,		**lowerCAmelCase_ )

           a_      :	Any      =							"""A\n'll 11p223RF☆ho!!to?'d'd''d of a cat to-$''d."""
           a_      :	List[str]      =							tokenizer_s.tokenize(lowerCAmelCase_ )
           a_      :	Optional[Any]      =							tokenizer_r.tokenize(lowerCAmelCase_ )

           self.assertListEqual(lowerCAmelCase_							,		lowerCAmelCase_ )

           # Test that the tokenization is identical on an example containing a character (Latin Small Letter A
           # with Tilde) encoded in 2 different ways
           a_      :	Any      =							"""xa\u0303y""" + """ """ + """x\xe3y"""
           a_      :	Optional[Any]      =							tokenizer_s.tokenize(lowerCAmelCase_ )
           a_      :	Tuple      =							tokenizer_r.tokenize(lowerCAmelCase_ )

           self.assertListEqual(lowerCAmelCase_							,		lowerCAmelCase_ )

           # Test that the tokenization is identical on unicode of space type
           a_      :	Optional[int]      =							[
               """\u0009""",  # (horizontal tab, '\t')
               """\u000B""",  # (vertical tab)
               """\u000C""",  # (form feed)
               """\u0020""",  # (space, ' ')
               """\u200E""",  # (left-to-right mark):w
               """\u200F""",  # (right-to-left mark)
           ]
           for unicode_seq in spaces_unicodes:
             a_      :	Optional[int]      =							tokenizer_s.tokenize(lowerCAmelCase_ )
             a_      :	Tuple      =							tokenizer_r.tokenize(lowerCAmelCase_ )

             self.assertListEqual(lowerCAmelCase_							,		lowerCAmelCase_ )

           # Test that the tokenization is identical on unicode of line break type
           a_      :	Any      =							[
               """\u000A""",  # (line feed, '\n')
               """\r\n""",  # (carriage return and line feed, '\r\n')
               """\u000D""",  # (carriage return, '\r')
               """\r""",  # (carriage return, '\r')
               """\u000D""",  # (carriage return, '\r')
               """\u2028""",  # (line separator)
               """\u2029""",  # (paragraph separator)
               # "\u0085", # (next line)
           ]

           # The tokenization is not identical for the character "\u0085" (next line). The slow version using ftfy transforms
           # it into the Horizontal Ellipsis character "…" ("\u2026") while the fast version transforms it into a
           # space (and thus into an empty list).

           for unicode_seq in line_break_unicodes:
             a_      :	Any      =							tokenizer_s.tokenize(lowerCAmelCase_ )
             a_      :	List[Any]      =							tokenizer_r.tokenize(lowerCAmelCase_ )

             self.assertListEqual(lowerCAmelCase_							,		lowerCAmelCase_ )


     def 							_lowerCAmelCase  (      self ):

       '''simple docstring'''

       for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
         with self.subTest(f'''{tokenizer.__class__.__name__} ({pretrained_name})''' ):
           a_      :	List[Any]      =							"""hello"""  # `hello` is a token in the vocabulary of `pretrained_name`
           a_      :	Tuple      =							f'''{text_of_1_token} {text_of_1_token}'''

           a_      :	List[str]      =							self.rust_tokenizer_class.from_pretrained(
               lowerCAmelCase_							,		use_fast=lowerCAmelCase_							,		)
           a_      :	List[str]      =							tokenizer_r(lowerCAmelCase_							,		return_offsets_mapping=lowerCAmelCase_							,		add_special_tokens=lowerCAmelCase_ )
           self.assertEqual(encoding.offset_mapping[0]							,		(0, len(lowerCAmelCase_ )) )
           self.assertEqual(
               encoding.offset_mapping[1]							,		(len(lowerCAmelCase_ ) + 1, len(lowerCAmelCase_ ) + 1 + len(lowerCAmelCase_ ))							,		)

           a_      :	Dict      =							f''' {text}'''

           a_      :	int      =							self.rust_tokenizer_class.from_pretrained(
               lowerCAmelCase_							,		use_fast=lowerCAmelCase_							,		)
           a_      :	Union[str, Any]      =							tokenizer_r(lowerCAmelCase_							,		return_offsets_mapping=lowerCAmelCase_							,		add_special_tokens=lowerCAmelCase_ )
           self.assertEqual(encoding.offset_mapping[0]							,		(1, 1 + len(lowerCAmelCase_ )) )
           self.assertEqual(
               encoding.offset_mapping[1]							,		(1 + len(lowerCAmelCase_ ) + 1, 1 + len(lowerCAmelCase_ ) + 1 + len(lowerCAmelCase_ ))							,		)


     def 							_lowerCAmelCase  (      self ):

       '''simple docstring'''

       with self.assertRaises(lowerCAmelCase_ ) as context:
         self.rust_tokenizer_class.from_pretrained("""robot-test/old-clip-tokenizer""" )

       self.assertTrue(
           context.exception.args[0].startswith(
               """The `backend_tokenizer` provided does not match the expected format.""" ) )


     @require_ftfy
     def 							_lowerCAmelCase  (      self ):

       '''simple docstring'''

       super().test_tokenization_python_rust_equals()






     def 							_lowerCAmelCase  (      self ):

       '''simple docstring'''

       pass




'''simple docstring'''

from typing import Mapping

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


__snake_case:  Tuple								=			logging.get_logger(__name__)

__snake_case:  Tuple								=			{
    "t5-small": "https://huggingface.co/t5-small/resolve/main/config.json",
    "t5-base": "https://huggingface.co/t5-base/resolve/main/config.json",
    "t5-large": "https://huggingface.co/t5-large/resolve/main/config.json",
    "t5-3b": "https://huggingface.co/t5-3b/resolve/main/config.json",
    "t5-11b": "https://huggingface.co/t5-11b/resolve/main/config.json",
}


class  _UpperCAmelCase ( lowerCAmelCase__    ):

     """simple docstring"""

     a_    	=					"t5"
     a_    	=					["past_key_values"]
     a_    	=					{"hidden_size": "d_model", "num_attention_heads": "num_heads", "num_hidden_layers": "num_layers"}


     def __init__(      self							,		lowerCAmelCase_=3_21_28							,		lowerCAmelCase_=5_12							,		lowerCAmelCase_=64							,		lowerCAmelCase_=20_48							,		lowerCAmelCase_=6							,		lowerCAmelCase_=None							,		lowerCAmelCase_=8							,		lowerCAmelCase_=32							,		lowerCAmelCase_=1_28							,		lowerCAmelCase_=0.1							,		lowerCAmelCase_=1E-6							,		lowerCAmelCase_=1.0							,		lowerCAmelCase_="relu"							,		lowerCAmelCase_=True							,		lowerCAmelCase_=True							,		lowerCAmelCase_=0							,		lowerCAmelCase_=1							,		**lowerCAmelCase_							,		):

       '''simple docstring'''

       a_      :	List[Any]      =							vocab_size
       a_      :	List[str]      =							d_model
       a_      :	Union[str, Any]      =							d_kv
       a_      :	List[Any]      =							d_ff
       a_      :	int      =							num_layers
       a_      :	Any      =							(
           num_decoder_layers if num_decoder_layers is not None else self.num_layers
       )  # default = symmetry
       a_      :	Union[str, Any]      =							num_heads
       a_      :	int      =							relative_attention_num_buckets
       a_      :	Dict      =							relative_attention_max_distance
       a_      :	Union[str, Any]      =							dropout_rate
       a_      :	Union[str, Any]      =							layer_norm_epsilon
       a_      :	List[Any]      =							initializer_factor
       a_      :	Any      =							feed_forward_proj
       a_      :	List[Any]      =							use_cache

       a_      :	Dict      =							self.feed_forward_proj.split("""-""" )
       a_      :	Union[str, Any]      =							act_info[-1]
       a_      :	str      =							act_info[0] == """gated"""

       if len(lowerCAmelCase_ ) > 1 and act_info[0] != "gated" or len(lowerCAmelCase_ ) > 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":
         a_      :	List[str]      =							"""gelu_new"""

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







class  _UpperCAmelCase ( lowerCAmelCase__    ):

     """simple docstring"""

     @property
     def 							_lowerCAmelCase  (      self ):

       '''simple docstring'''

       a_      :	List[Any]      =							{
           """input_ids""": {0: """batch""", 1: """encoder_sequence"""},
           """attention_mask""": {0: """batch""", 1: """encoder_sequence"""},
       }
       if self.use_past:
         a_      :	Tuple      =							"""past_encoder_sequence + sequence"""
         a_      :	str      =							{0: """batch"""}
         a_      :	Any      =							{0: """batch""", 1: """past_decoder_sequence + sequence"""}
       else:
         a_      :	List[Any]      =							{0: """batch""", 1: """decoder_sequence"""}
         a_      :	Optional[int]      =							{0: """batch""", 1: """decoder_sequence"""}

       if self.use_past:
         self.fill_with_past_key_values_(lowerCAmelCase_							,		direction="""inputs""" )

       return common_inputs






     @property
     def 							_lowerCAmelCase  (      self ):

       '''simple docstring'''

       return 13


