





'''simple docstring'''

import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple

from transformers import AddedToken, BatchEncoding, ByTaTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available

from ...test_tokenization_common import TokenizerTesterMixin


if is_torch_available():
  __lowerCAmelCase							:	str			="pt"
elif is_tf_available():
  __lowerCAmelCase							:	Optional[int]			="tf"
else:
  __lowerCAmelCase							:	List[str]			="jax"






class    UpperCAmelCase	(       UpperCamelCase__			,       unittest.TestCase				):
 __lowercase   		=				ByTaTokenizer
 __lowercase   		=				False
 def      UpperCAmelCase_							(				self      :int							)->							Optional[Any]:
     super().setUp()
     A__				=			ByTaTokenizer()
     tokenizer.save_pretrained(self.tmpdirname							)
 @cached_property
 def      UpperCAmelCase_							(				self      :List[str]							)->							List[str]:
     return ByTaTokenizer.from_pretrained("google/byt5-small"							)
 def      UpperCAmelCase_							(				self      :str						,       **lowercase_      :Any							)->							ByTaTokenizer:
     return self.tokenizer_class.from_pretrained(self.tmpdirname						,       **lowercase_							)
 def      UpperCAmelCase_							(				self      :int						,       lowercase_      :List[str]						,       lowercase_      :List[Any]=False						,       lowercase_      :Any=20						,       lowercase_      :Any=5							)->							Tuple[str, list]:
     # XXX The default common tokenizer tests assume that every ID is decodable on its own.
     # This assumption is invalid for ByT5 because single bytes might not be
     # valid utf-8 (byte 128 for instance).
     # Here we're overriding the smallest possible method to provide
     # a clean sequence without making the same assumption.

     A__				=			[]
     for i in range(len(lowercase_							)							):
         try:
             A__				=			tokenizer.decode([i]						,       clean_up_tokenization_spaces=lowercase_							)
         except UnicodeDecodeError:
             pass
         toks.append((i, tok)							)

     A__				=			list(filter(lambda lowercase_							: re.match(R"^[ a-zA-Z]+$"						,       t[1]							)						,       lowercase_							)							)
     A__				=			list(filter(lambda lowercase_							: [t[0]] == tokenizer.encode(t[1]						,       add_special_tokens=lowercase_							)						,       lowercase_							)							)
     if max_length is not None and len(lowercase_							) > max_length:
         A__				=			toks[:max_length]
     if min_length is not None and len(lowercase_							) < min_length and len(lowercase_							) > 0:
         while len(lowercase_							) < min_length:
             A__				=			toks + toks
        # toks_str = [t[1] for t in toks]
     A__				=			[t[0] for t in toks]

     # Ensure consistency
     A__				=			tokenizer.decode(lowercase_						,       clean_up_tokenization_spaces=lowercase_							)
     if " " not in output_txt and len(lowercase_							) > 1:
         A__				=			(
             tokenizer.decode([toks_ids[0]]						,       clean_up_tokenization_spaces=lowercase_							)
             + " "
             + tokenizer.decode(toks_ids[1:]						,       clean_up_tokenization_spaces=lowercase_							)
         )
     if with_prefix_space:
         A__				=			" " + output_txt
     A__				=			tokenizer.encode(lowercase_						,       add_special_tokens=lowercase_							)
     return output_txt, output_ids
 def      UpperCAmelCase_							(				self      :Dict							)->							Union[str, Any]:
     A__				=			self.ta_base_tokenizer
     A__				=			tokenizer(["hi</s>", "I went to the gym</s>", "</s>"]							)
     A__				=			tokenizer(["hi", "I went to the gym", ""]							)
     self.assertListEqual(batch_with_eos_added["input_ids"]						,       batch_without_eos_added["input_ids"]							)
 def      UpperCAmelCase_							(				self      :Optional[int]							)->							Tuple:
     A__				=			self.ta_base_tokenizer
     A__				=			"Unicode €."
     A__				=			tokenizer(lowercase_							)
     A__				=			[88, 1_13, 1_08, 1_02, 1_14, 1_03, 1_04, 35, 2_29, 1_33, 1_75, 49, 1]
     self.assertEqual(encoded["input_ids"]						,       lowercase_							)

     # decoding
     A__				=			tokenizer.decode(lowercase_							)
     self.assertEqual(lowercase_						,       "Unicode €.</s>"							)

     A__				=			tokenizer("e è é ê ë"							)
     A__				=			[1_04, 35, 1_98, 1_71, 35, 1_98, 1_72, 35, 1_98, 1_73, 35, 1_98, 1_74, 1]
     self.assertEqual(encoded["input_ids"]						,       lowercase_							)
     # decoding
     A__				=			tokenizer.decode(lowercase_							)
     self.assertEqual(lowercase_						,       "e è é ê ë</s>"							)

     # encode/decode, but with `encode` instead of `__call__`
     self.assertEqual(tokenizer.decode(tokenizer.encode("e è é ê ë"							)							)						,       "e è é ê ë</s>"							)
 def      UpperCAmelCase_							(				self      :Optional[int]							)->							Tuple:
     A__				=			self.ta_base_tokenizer
     A__				=			["A long paragraph for summarization.", "Another paragraph for summarization."]
     # fmt: off
     A__				=			[68, 35, 1_11, 1_14, 1_13, 1_06, 35, 1_15, 1_00, 1_17, 1_00, 1_06, 1_17, 1_00, 1_15, 1_07, 35, 1_05, 1_14, 1_17, 35, 1_18, 1_20, 1_12, 1_12, 1_00, 1_17, 1_08, 1_25, 1_00, 1_19, 1_08, 1_14, 1_13, 49, 1, 0]
     # fmt: on
     A__				=			tokenizer(lowercase_						,       padding=lowercase_						,       return_tensors=lowercase_							)
     self.assertIsInstance(lowercase_						,       lowercase_							)

     if FRAMEWORK != "jax":
         A__				=			list(batch.input_ids.numpy()[0]							)
     else:
         A__				=			list(batch.input_ids.tolist()[0]							)

     self.assertListEqual(lowercase_						,       lowercase_							)

     self.assertEqual((2, 37)						,       batch.input_ids.shape							)
     self.assertEqual((2, 37)						,       batch.attention_mask.shape							)
 def      UpperCAmelCase_							(				self      :Optional[Any]							)->							Tuple:
     A__				=			self.ta_base_tokenizer
     A__				=			["A long paragraph for summarization.", "Another paragraph for summarization."]
     A__				=			tokenizer(lowercase_						,       padding=lowercase_						,       return_tensors=lowercase_							)
     # check if input_ids are returned and no decoder_input_ids
     self.assertIn("input_ids"						,       lowercase_							)
     self.assertIn("attention_mask"						,       lowercase_							)
     self.assertNotIn("decoder_input_ids"						,       lowercase_							)
     self.assertNotIn("decoder_attention_mask"						,       lowercase_							)
 def      UpperCAmelCase_							(				self      :Tuple							)->							List[Any]:
     A__				=			self.ta_base_tokenizer
     A__				=			[
         "Summary of the text.",
         "Another summary.",
     ]
     A__				=			tokenizer(
         text_target=lowercase_						,       max_length=32						,       padding="max_length"						,       truncation=lowercase_						,       return_tensors=lowercase_							)
     self.assertEqual(32						,       targets["input_ids"].shape[1]							)
 def      UpperCAmelCase_							(				self      :int							)->							Optional[Any]:
     A__				=			self.ta_base_tokenizer
     A__				=			["A long paragraph for summarization. </s>"]
     A__				=			["Summary of the text. </s>"]
     # fmt: off
     A__				=			[68, 35, 1_11, 1_14, 1_13, 1_06, 35, 1_15, 1_00, 1_17, 1_00, 1_06, 1_17, 1_00, 1_15, 1_07, 35, 1_05, 1_14, 1_17, 35, 1_18, 1_20, 1_12, 1_12, 1_00, 1_17, 1_08, 1_25, 1_00, 1_19, 1_08, 1_14, 1_13, 49, 35, 1]
     A__				=			[86, 1_20, 1_12, 1_12, 1_00, 1_17, 1_24, 35, 1_14, 1_05, 35, 1_19, 1_07, 1_04, 35, 1_19, 1_04, 1_23, 1_19, 49, 35, 1]
     # fmt: on

     A__				=			tokenizer(lowercase_						,       text_target=lowercase_							)

     self.assertEqual(lowercase_						,       batch["input_ids"][0]							)
     self.assertEqual(lowercase_						,       batch["labels"][0]							)
 def      UpperCAmelCase_							(				self      :str							)->							Union[str, Any]:
     # safety check on max_len default value so we are sure the test works
     A__				=			self.get_tokenizers()
     for tokenizer in tokenizers:
         with self.subTest(F"{tokenizer.__class__.__name__}"							):
             self.assertNotEqual(tokenizer.model_max_length						,       42							)

        # Now let's start the test
     A__				=			self.get_tokenizers()
     for tokenizer in tokenizers:
         with self.subTest(F"{tokenizer.__class__.__name__}"							):
             # Isolate this from the other tests because we save additional tokens/etc
             A__				=			tempfile.mkdtemp()

             A__				=			" He is very happy, UNwant\u00E9d,running"
             A__				=			tokenizer.encode(lowercase_						,       add_special_tokens=lowercase_							)
             tokenizer.save_pretrained(lowercase_							)

             A__				=			tokenizer.__class__.from_pretrained(lowercase_							)
             A__				=			after_tokenizer.encode(lowercase_						,       add_special_tokens=lowercase_							)
             self.assertListEqual(lowercase_						,       lowercase_							)

             shutil.rmtree(lowercase_							)

     A__				=			self.get_tokenizers(model_max_length=42							)
     for tokenizer in tokenizers:
         with self.subTest(F"{tokenizer.__class__.__name__}"							):
             # Isolate this from the other tests because we save additional tokens/etc
             A__				=			tempfile.mkdtemp()

             A__				=			" He is very happy, UNwant\u00E9d,running"
             tokenizer.add_tokens(["bim", "bambam"]							)
             A__				=			tokenizer.additional_special_tokens
             additional_special_tokens.append("new_additional_special_token"							)
             tokenizer.add_special_tokens({"additional_special_tokens": additional_special_tokens}							)
             A__				=			tokenizer.encode(lowercase_						,       add_special_tokens=lowercase_							)
             tokenizer.save_pretrained(lowercase_							)

             A__				=			tokenizer.__class__.from_pretrained(lowercase_							)
             A__				=			after_tokenizer.encode(lowercase_						,       add_special_tokens=lowercase_							)
             self.assertListEqual(lowercase_						,       lowercase_							)
             self.assertIn("new_additional_special_token"						,       after_tokenizer.additional_special_tokens							)
             self.assertEqual(after_tokenizer.model_max_length						,       42							)

             A__				=			tokenizer.__class__.from_pretrained(lowercase_						,       model_max_length=43							)
             self.assertEqual(tokenizer.model_max_length						,       43							)

             shutil.rmtree(lowercase_							)
 def      UpperCAmelCase_							(				self      :Union[str, Any]							)->							Tuple:
     A__				=			[]
     if self.test_slow_tokenizer:
         tokenizer_list.append((self.tokenizer_class, self.get_tokenizer())							)

     if self.test_rust_tokenizer:
         tokenizer_list.append((self.rust_tokenizer_class, self.get_rust_tokenizer())							)

     for tokenizer_class, tokenizer_utils in tokenizer_list:
         with tempfile.TemporaryDirectory() as tmp_dir:
             tokenizer_utils.save_pretrained(lowercase_							)

             with open(os.path.join(lowercase_						,       "special_tokens_map.json"							)						,       encoding="utf-8"							) as json_file:
                 A__				=			json.load(lowercase_							)

             with open(os.path.join(lowercase_						,       "tokenizer_config.json"							)						,       encoding="utf-8"							) as json_file:
                 A__				=			json.load(lowercase_							)

             A__				=			[F"<extra_id_{i}>" for i in range(1_25							)]

             A__				=			added_tokens_extra_ids + [
                 "an_additional_special_token"
             ]
             A__				=			added_tokens_extra_ids + [
                 "an_additional_special_token"
             ]

             with open(os.path.join(lowercase_						,       "special_tokens_map.json"							)						,       "w"						,       encoding="utf-8"							) as outfile:
                 json.dump(lowercase_						,       lowercase_							)
             with open(os.path.join(lowercase_						,       "tokenizer_config.json"							)						,       "w"						,       encoding="utf-8"							) as outfile:
                 json.dump(lowercase_						,       lowercase_							)

             # the following checks allow us to verify that our test works as expected, i.e. that the tokenizer takes
             # into account the new value of additional_special_tokens given in the "tokenizer_config.json" and
             # "special_tokens_map.json" files
             A__				=			tokenizer_class.from_pretrained(
                 lowercase_						,       )
             self.assertIn(
                 "an_additional_special_token"						,       tokenizer_without_change_in_init.additional_special_tokens							)
             # self.assertIn("an_additional_special_token",tokenizer_without_change_in_init.get_vocab()) # ByT5Tokenization no vocab
             self.assertEqual(
                 ["an_additional_special_token"]						,       tokenizer_without_change_in_init.convert_ids_to_tokens(
                     tokenizer_without_change_in_init.convert_tokens_to_ids(["an_additional_special_token"]							)							)						,       )

             # Now we test that we can change the value of additional_special_tokens in the from_pretrained
             A__				=			added_tokens_extra_ids + [AddedToken("a_new_additional_special_token"						,       lstrip=lowercase_							)]
             A__				=			tokenizer_class.from_pretrained(
                 lowercase_						,       additional_special_tokens=lowercase_						,       )

             self.assertIn("a_new_additional_special_token"						,       tokenizer.additional_special_tokens							)
             self.assertEqual(
                 ["a_new_additional_special_token"]						,       tokenizer.convert_ids_to_tokens(
                     tokenizer.convert_tokens_to_ids(["a_new_additional_special_token"]							)							)						,       )
 def      UpperCAmelCase_							(				self      :str							)->							Union[str, Any]:
     A__				=			[]
     if self.test_slow_tokenizer:
         tokenizer_list.append((self.tokenizer_class, self.get_tokenizer())							)

     if self.test_rust_tokenizer:
         tokenizer_list.append((self.rust_tokenizer_class, self.get_rust_tokenizer())							)

     for tokenizer_class, tokenizer_utils in tokenizer_list:
         with tempfile.TemporaryDirectory() as tmp_dir:
             tokenizer_utils.save_pretrained(lowercase_							)

             A__				=			tokenizer_class.from_pretrained(lowercase_							)

             self.assertTrue(tokenizer.decode([2_55]							) == ""							)
 def      UpperCAmelCase_							(				self      :Dict							)->							int:
     pass
 def      UpperCAmelCase_							(				self      :Tuple							)->							Optional[int]:
     pass
 def      UpperCAmelCase_							(				self      :Any							)->							int:
     pass
 def      UpperCAmelCase_							(				self      :Optional[int]							)->							Tuple:
     pass
 def      UpperCAmelCase_							(				self      :Optional[Any]							)->							int:
     # The default common tokenizer tests uses invalid tokens for ByT5 that can only accept one-character strings
     # and special added tokens as tokens
     A__				=			self.get_tokenizers(fast=lowercase_						,       do_lower_case=lowercase_							)
     for tokenizer in tokenizers:
         with self.subTest(F"{tokenizer.__class__.__name__}"							):
             A__				=			["t", "h", "i", "s", " ", "i", "s", " ", "a", " ", "t", "e", "x", "t", "</s>"]
             A__				=			tokenizer.convert_tokens_to_string(lowercase_							)

             self.assertIsInstance(lowercase_						,       lowercase_							)



 def      UpperCAmelCase_							(				self      :Optional[int]							)->							Optional[Any]:
     A__				=			self.get_tokenizers()
     for tokenizer in tokenizers:
         with self.subTest(F"{tokenizer.__class__.__name__}"							):
             A__				=			[
                 "bos_token",
                 "eos_token",
                 "unk_token",
                 "sep_token",
                 "pad_token",
                 "cls_token",
                 "mask_token",
             ]

             A__				=			0
             A__				=			tokenizer.convert_ids_to_tokens(
                 lowercase_						,       skip_special_tokens=lowercase_							)

             for attr in attributes_list:
                 setattr(lowercase_						,       attr + "_id"						,       lowercase_							)
                 self.assertEqual(getattr(lowercase_						,       lowercase_							)						,       lowercase_							)
                 self.assertEqual(getattr(lowercase_						,       attr + "_id"							)						,       lowercase_							)

                 setattr(lowercase_						,       attr + "_id"						,       lowercase_							)
                 self.assertEqual(getattr(lowercase_						,       lowercase_							)						,       lowercase_							)
                 self.assertEqual(getattr(lowercase_						,       attr + "_id"							)						,       lowercase_							)

             setattr(lowercase_						,       "additional_special_tokens_ids"						,       []							)
             self.assertListEqual(getattr(lowercase_						,       "additional_special_tokens"							)						,       []							)
             self.assertListEqual(getattr(lowercase_						,       "additional_special_tokens_ids"							)						,       []							)

             setattr(lowercase_						,       "additional_special_tokens_ids"						,       [token_id_to_test_setters]							)
             self.assertListEqual(getattr(lowercase_						,       "additional_special_tokens"							)						,       [token_to_test_setters]							)
             self.assertListEqual(getattr(lowercase_						,       "additional_special_tokens_ids"							)						,       [token_id_to_test_setters]							)










'''simple docstring'''

import warnings

from transformers import AutoTokenizer
from transformers.utils import is_torch_available
from transformers.utils.generic import ExplicitEnum

from ...processing_utils import ProcessorMixin


if is_torch_available():
  import torch






class    UpperCAmelCase	(       UpperCamelCase__				):
 __lowercase   		=				"""char"""
 __lowercase   		=				"""bpe"""
 __lowercase   		=				"""wp"""

__lowerCAmelCase							:	Union[str, Any]			=(DecodeType.CHARACTER, DecodeType.BPE, DecodeType.WORDPIECE)






class    UpperCAmelCase	(       UpperCamelCase__				):
 __lowercase   		=				["""image_processor""", """char_tokenizer"""]
 __lowercase   		=				"""ViTImageProcessor"""
 __lowercase   		=				"""MgpstrTokenizer"""
 def __init__(				self      :int						,       lowercase_      :int=None						,       lowercase_      :List[str]=None						,       **lowercase_      :List[Any]							)->							Optional[Any]:
     A__				=			None
     if "feature_extractor" in kwargs:
         warnings.warn(
             "The `feature_extractor` argument is deprecated and will be removed in v5, use `image_processor`"
             " instead."						,       lowercase_						,       )
         A__				=			kwargs.pop("feature_extractor"							)

     A__				=			image_processor if image_processor is not None else feature_extractor
     if image_processor is None:
         raise ValueError("You need to specify an `image_processor`."							)
     if tokenizer is None:
         raise ValueError("You need to specify a `tokenizer`."							)

     A__				=			tokenizer
     A__				=			AutoTokenizer.from_pretrained("gpt2"							)
     A__				=			AutoTokenizer.from_pretrained("bert-base-uncased"							)

     super().__init__(lowercase_						,       lowercase_							)
 def __call__(				self      :Optional[Any]						,       lowercase_      :Any=None						,       lowercase_      :Tuple=None						,       lowercase_      :List[str]=None						,       **lowercase_      :Union[str, Any]							)->							Optional[Any]:
     if images is None and text is None:
         raise ValueError("You need to specify either an `images` or `text` input to process."							)

     if images is not None:
         A__				=			self.image_processor(lowercase_						,       return_tensors=lowercase_						,       **lowercase_							)
     if text is not None:
         A__				=			self.char_tokenizer(lowercase_						,       return_tensors=lowercase_						,       **lowercase_							)

     if text is None:
         return inputs
     elif images is None:
         return encodings
     else:
         A__				=			encodings["input_ids"]
         return inputs
 def      UpperCAmelCase_							(				self      :List[str]						,       lowercase_      :int							)->							int:
     A__,	A__,	A__				=			sequences
     A__				=			char_preds.size(0							)

     A__,	A__				=			self._decode_helper(lowercase_						,       "char"							)
     A__,	A__				=			self._decode_helper(lowercase_						,       "bpe"							)
     A__,	A__				=			self._decode_helper(lowercase_						,       "wp"							)

     A__				=			[]
     A__				=			[]
     for i in range(lowercase_							):
         A__				=			[char_scores[i], bpe_scores[i], wp_scores[i]]
         A__				=			[char_strs[i], bpe_strs[i], wp_strs[i]]
         A__				=			scores.index(max(lowercase_							)							)
         final_strs.append(strs[max_score_index]							)
         final_scores.append(scores[max_score_index]							)

     A__				=			{}
     A__				=			final_strs
     A__				=			final_scores
     A__				=			char_strs
     A__				=			bpe_strs
     A__				=			wp_strs
     return out
 def      UpperCAmelCase_							(				self      :Union[str, Any]						,       lowercase_      :List[str]						,       lowercase_      :str							)->							Optional[Any]:
     if format == DecodeType.CHARACTER:
         A__				=			self.char_decode
         A__				=			1
         A__				=			"[s]"
     elif format == DecodeType.BPE:
         A__				=			self.bpe_decode
         A__				=			2
         A__				=			"#"
     elif format == DecodeType.WORDPIECE:
         A__				=			self.wp_decode
         A__				=			1_02
         A__				=			"[SEP]"
     else:
         raise ValueError(F"Format {format} is not supported."							)

     A__,	A__				=			[], []
     A__				=			pred_logits.size(0							)
     A__				=			pred_logits.size(1							)
     A__,	A__				=			pred_logits.topk(1						,       dim=-1						,       largest=lowercase_						,       sorted=lowercase_							)
     A__				=			preds_index.view(-1						,       lowercase_							)[:, 1:]
     A__				=			decoder(lowercase_							)
     A__,	A__				=			torch.nn.functional.softmax(lowercase_						,       dim=2							).max(dim=2							)
     A__				=			preds_max_prob[:, 1:]

     for index in range(lowercase_							):
         A__				=			preds_str[index].find(lowercase_							)
         A__				=			preds_str[index][:pred_eos]
         A__				=			preds_index[index].cpu().tolist()
         A__				=			pred_index.index(lowercase_							) if eos_token in pred_index else -1
         A__				=			preds_max_prob[index][: pred_eos_index + 1]
         A__				=			pred_max_prob.cumprod(dim=0							)[-1] if pred_max_prob.nelement() != 0 else 0.0
         dec_strs.append(lowercase_							)
         conf_scores.append(lowercase_							)

     return dec_strs, conf_scores
 def      UpperCAmelCase_							(				self      :Dict						,       lowercase_      :Optional[Any]							)->							int:
     A__				=			[seq.replace(" "						,       ""							) for seq in self.char_tokenizer.batch_decode(lowercase_							)]
     return decode_strs
 def      UpperCAmelCase_							(				self      :List[Any]						,       lowercase_      :Optional[Any]							)->							List[str]:
     return self.bpe_tokenizer.batch_decode(lowercase_							)



 def      UpperCAmelCase_							(				self      :Optional[int]						,       lowercase_      :List[str]							)->							Union[str, Any]:
     A__				=			[seq.replace(" "						,       ""							) for seq in self.wp_tokenizer.batch_decode(lowercase_							)]
     return decode_strs



