






"""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():
					lowercase__          = """pt"""
elif is_tf_available():
					lowercase__          = """tf"""
else:
					lowercase__          = """jax"""


class 		__lowerCamelCase				( A__ ,							unittest.TestCase			):





		'''simple docstring'''






		a_	:				List[str]            =							ByTaTokenizer
		a_	:				Dict            =							False





		def    lowerCamelCase       (   self							:	Union[str, Any]	):
				super().setUp()
				lowerCAmelCase_   :							Tuple									=			ByTaTokenizer()
				tokenizer.save_pretrained(self.tmpdirname	)





		@cached_property
		def    lowerCamelCase       (   self							:	Any	):
				return ByTaTokenizer.from_pretrained("google/byt5-small"	)





		def    lowerCamelCase       (   self							:	List[str]						,			**a_							:	Any	):
				return self.tokenizer_class.from_pretrained(self.tmpdirname						,			**SCREAMING_SNAKE_CASE__	)





		def    lowerCamelCase       (   self							:	Optional[int]						,			a_							:	List[str]						,			a_							:	Optional[Any]=False						,			a_							:	int=20						,			a_							:	List[str]=5	):
				lowerCAmelCase_   :							Tuple									=			[]
				for i in range(len(SCREAMING_SNAKE_CASE__	)	):
						try:
								lowerCAmelCase_   :							str									=			tokenizer.decode([i]						,			clean_up_tokenization_spaces=SCREAMING_SNAKE_CASE__	)
						except UnicodeDecodeError:
								pass
						toks.append((i, tok)	)

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

				# Ensure consistency
				lowerCAmelCase_   :							List[Any]									=			tokenizer.decode(SCREAMING_SNAKE_CASE__						,			clean_up_tokenization_spaces=SCREAMING_SNAKE_CASE__	)
				if " " not in output_txt and len(SCREAMING_SNAKE_CASE__	) > 1:
						lowerCAmelCase_   :							Optional[int]									=			(
						    tokenizer.decode([toks_ids[0]]						,			clean_up_tokenization_spaces=SCREAMING_SNAKE_CASE__	)
						    + ''' '''
						    + tokenizer.decode(toks_ids[1:]						,			clean_up_tokenization_spaces=SCREAMING_SNAKE_CASE__	)
						)
				if with_prefix_space:
						lowerCAmelCase_   :							List[str]									=			''' ''' + output_txt
				lowerCAmelCase_   :							int									=			tokenizer.encode(SCREAMING_SNAKE_CASE__						,			add_special_tokens=SCREAMING_SNAKE_CASE__	)
				return output_txt, output_ids





		def    lowerCamelCase       (   self							:	Union[str, Any]	):
				lowerCAmelCase_   :							str									=			self.ta_base_tokenizer
				lowerCAmelCase_   :							Optional[int]									=			tokenizer(["hi</s>", "I went to the gym</s>", "</s>"]	)
				lowerCAmelCase_   :							List[Any]									=			tokenizer(["hi", "I went to the gym", ""]	)
				self.assertListEqual(batch_with_eos_added["input_ids"]						,			batch_without_eos_added["input_ids"]	)





		def    lowerCamelCase       (   self							:	List[str]	):
				lowerCAmelCase_   :							Union[str, Any]									=			self.ta_base_tokenizer
				lowerCAmelCase_   :							Optional[int]									=			'''Unicode €.'''
				lowerCAmelCase_   :							List[Any]									=			tokenizer(SCREAMING_SNAKE_CASE__	)
				lowerCAmelCase_   :							List[str]									=			[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"]						,			SCREAMING_SNAKE_CASE__	)

				# decoding
				lowerCAmelCase_   :							Optional[Any]									=			tokenizer.decode(SCREAMING_SNAKE_CASE__	)
				self.assertEqual(SCREAMING_SNAKE_CASE__						,			"Unicode €.</s>"	)

				lowerCAmelCase_   :							Dict									=			tokenizer("e è é ê ë"	)
				lowerCAmelCase_   :							str									=			[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"]						,			SCREAMING_SNAKE_CASE__	)
				# decoding
				lowerCAmelCase_   :							Optional[int]									=			tokenizer.decode(SCREAMING_SNAKE_CASE__	)
				self.assertEqual(SCREAMING_SNAKE_CASE__						,			"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    lowerCamelCase       (   self							:	Optional[Any]	):
				lowerCAmelCase_   :							List[str]									=			self.ta_base_tokenizer
				lowerCAmelCase_   :							Any									=			['''A long paragraph for summarization.''', '''Another paragraph for summarization.''']
				# fmt: off
				lowerCAmelCase_   :							int									=			[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
				lowerCAmelCase_   :							int									=			tokenizer(SCREAMING_SNAKE_CASE__						,			padding=SCREAMING_SNAKE_CASE__						,			return_tensors=SCREAMING_SNAKE_CASE__	)
				self.assertIsInstance(SCREAMING_SNAKE_CASE__						,			SCREAMING_SNAKE_CASE__	)

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

				self.assertListEqual(SCREAMING_SNAKE_CASE__						,			SCREAMING_SNAKE_CASE__	)

				self.assertEqual((2, 37)						,			batch.input_ids.shape	)
				self.assertEqual((2, 37)						,			batch.attention_mask.shape	)





		def    lowerCamelCase       (   self							:	Optional[Any]	):
				lowerCAmelCase_   :							Union[str, Any]									=			self.ta_base_tokenizer
				lowerCAmelCase_   :							Optional[Any]									=			['''A long paragraph for summarization.''', '''Another paragraph for summarization.''']
				lowerCAmelCase_   :							List[str]									=			tokenizer(SCREAMING_SNAKE_CASE__						,			padding=SCREAMING_SNAKE_CASE__						,			return_tensors=SCREAMING_SNAKE_CASE__	)
				# check if input_ids are returned and no decoder_input_ids
				self.assertIn("input_ids"						,			SCREAMING_SNAKE_CASE__	)
				self.assertIn("attention_mask"						,			SCREAMING_SNAKE_CASE__	)
				self.assertNotIn("decoder_input_ids"						,			SCREAMING_SNAKE_CASE__	)
				self.assertNotIn("decoder_attention_mask"						,			SCREAMING_SNAKE_CASE__	)





		def    lowerCamelCase       (   self							:	Optional[int]	):
				lowerCAmelCase_   :							Tuple									=			self.ta_base_tokenizer
				lowerCAmelCase_   :							int									=			[
				    '''Summary of the text.''',
				    '''Another summary.''',
				]
				lowerCAmelCase_   :							Tuple									=			tokenizer(
				    text_target=SCREAMING_SNAKE_CASE__						,			max_length=32						,			padding="max_length"						,			truncation=SCREAMING_SNAKE_CASE__						,			return_tensors=SCREAMING_SNAKE_CASE__	)
				self.assertEqual(32						,			targets["input_ids"].shape[1]	)





		def    lowerCamelCase       (   self							:	Any	):
				lowerCAmelCase_   :							Tuple									=			self.ta_base_tokenizer
				lowerCAmelCase_   :							Optional[int]									=			['''A long paragraph for summarization. </s>''']
				lowerCAmelCase_   :							Any									=			['''Summary of the text. </s>''']
				# fmt: off
				lowerCAmelCase_   :							Tuple									=			[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]
				lowerCAmelCase_   :							int									=			[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

				lowerCAmelCase_   :							str									=			tokenizer(SCREAMING_SNAKE_CASE__						,			text_target=SCREAMING_SNAKE_CASE__	)

				self.assertEqual(SCREAMING_SNAKE_CASE__						,			batch["input_ids"][0]	)
				self.assertEqual(SCREAMING_SNAKE_CASE__						,			batch["labels"][0]	)





		def    lowerCamelCase       (   self							:	str	):
				lowerCAmelCase_   :							Union[str, Any]									=			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
				lowerCAmelCase_   :							Optional[int]									=			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
								lowerCAmelCase_   :							Tuple									=			tempfile.mkdtemp()

								lowerCAmelCase_   :							Tuple									=			''' He is very happy, UNwant\u00E9d,running'''
								lowerCAmelCase_   :							Optional[Any]									=			tokenizer.encode(SCREAMING_SNAKE_CASE__						,			add_special_tokens=SCREAMING_SNAKE_CASE__	)
								tokenizer.save_pretrained(SCREAMING_SNAKE_CASE__	)

								lowerCAmelCase_   :							Union[str, Any]									=			tokenizer.__class__.from_pretrained(SCREAMING_SNAKE_CASE__	)
								lowerCAmelCase_   :							int									=			after_tokenizer.encode(SCREAMING_SNAKE_CASE__						,			add_special_tokens=SCREAMING_SNAKE_CASE__	)
								self.assertListEqual(SCREAMING_SNAKE_CASE__						,			SCREAMING_SNAKE_CASE__	)

								shutil.rmtree(SCREAMING_SNAKE_CASE__	)

				lowerCAmelCase_   :							Optional[Any]									=			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
								lowerCAmelCase_   :							Tuple									=			tempfile.mkdtemp()

								lowerCAmelCase_   :							Optional[Any]									=			''' He is very happy, UNwant\u00E9d,running'''
								tokenizer.add_tokens(["bim", "bambam"]	)
								lowerCAmelCase_   :							Any									=			tokenizer.additional_special_tokens
								additional_special_tokens.append("new_additional_special_token"	)
								tokenizer.add_special_tokens({"additional_special_tokens": additional_special_tokens}	)
								lowerCAmelCase_   :							Optional[int]									=			tokenizer.encode(SCREAMING_SNAKE_CASE__						,			add_special_tokens=SCREAMING_SNAKE_CASE__	)
								tokenizer.save_pretrained(SCREAMING_SNAKE_CASE__	)

								lowerCAmelCase_   :							Optional[Any]									=			tokenizer.__class__.from_pretrained(SCREAMING_SNAKE_CASE__	)
								lowerCAmelCase_   :							Optional[Any]									=			after_tokenizer.encode(SCREAMING_SNAKE_CASE__						,			add_special_tokens=SCREAMING_SNAKE_CASE__	)
								self.assertListEqual(SCREAMING_SNAKE_CASE__						,			SCREAMING_SNAKE_CASE__	)
								self.assertIn("new_additional_special_token"						,			after_tokenizer.additional_special_tokens	)
								self.assertEqual(after_tokenizer.model_max_length						,			42	)

								lowerCAmelCase_   :							str									=			tokenizer.__class__.from_pretrained(SCREAMING_SNAKE_CASE__						,			model_max_length=43	)
								self.assertEqual(tokenizer.model_max_length						,			43	)

								shutil.rmtree(SCREAMING_SNAKE_CASE__	)





		def    lowerCamelCase       (   self							:	Any	):
				lowerCAmelCase_   :							str									=			[]
				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(SCREAMING_SNAKE_CASE__	)

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

								with open(os.path.join(SCREAMING_SNAKE_CASE__						,			"tokenizer_config.json"	)						,			encoding="utf-8"	) as json_file:
										lowerCAmelCase_   :							Optional[Any]									=			json.load(SCREAMING_SNAKE_CASE__	)

								lowerCAmelCase_   :							Tuple									=			[f'''<extra_id_{i}>''' for i in range(1_25	)]

								lowerCAmelCase_   :							Tuple									=			added_tokens_extra_ids + [
								    '''an_additional_special_token'''
								]
								lowerCAmelCase_   :							int									=			added_tokens_extra_ids + [
								    '''an_additional_special_token'''
								]

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

								# 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
								lowerCAmelCase_   :							Dict									=			tokenizer_class.from_pretrained(
								    SCREAMING_SNAKE_CASE__						,			)
								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
								lowerCAmelCase_   :							Optional[Any]									=			added_tokens_extra_ids + [AddedToken("a_new_additional_special_token"						,			lstrip=SCREAMING_SNAKE_CASE__	)]
								lowerCAmelCase_   :							str									=			tokenizer_class.from_pretrained(
								    SCREAMING_SNAKE_CASE__						,			additional_special_tokens=SCREAMING_SNAKE_CASE__						,			)

								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    lowerCamelCase       (   self							:	Union[str, Any]	):
				lowerCAmelCase_   :							int									=			[]
				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(SCREAMING_SNAKE_CASE__	)

								lowerCAmelCase_   :							Tuple									=			tokenizer_class.from_pretrained(SCREAMING_SNAKE_CASE__	)

								self.assertTrue(tokenizer.decode([2_55]	) == ""	)





		def    lowerCamelCase       (   self							:	Tuple	):
				pass





		def    lowerCamelCase       (   self							:	Optional[int]	):
				pass





		def    lowerCamelCase       (   self							:	int	):
				pass





		def    lowerCamelCase       (   self							:	Dict	):
				pass





		def    lowerCamelCase       (   self							:	Optional[int]	):
				lowerCAmelCase_   :							List[str]									=			self.get_tokenizers(fast=SCREAMING_SNAKE_CASE__						,			do_lower_case=SCREAMING_SNAKE_CASE__	)
				for tokenizer in tokenizers:
						with self.subTest(f'''{tokenizer.__class__.__name__}'''	):
								lowerCAmelCase_   :							Any									=			['''t''', '''h''', '''i''', '''s''', ''' ''', '''i''', '''s''', ''' ''', '''a''', ''' ''', '''t''', '''e''', '''x''', '''t''', '''</s>''']
								lowerCAmelCase_   :							int									=			tokenizer.convert_tokens_to_string(SCREAMING_SNAKE_CASE__	)

								self.assertIsInstance(SCREAMING_SNAKE_CASE__						,			SCREAMING_SNAKE_CASE__	)





		def    lowerCamelCase       (   self							:	Tuple	):
				lowerCAmelCase_   :							Optional[Any]									=			self.get_tokenizers()
				for tokenizer in tokenizers:
						with self.subTest(f'''{tokenizer.__class__.__name__}'''	):
								lowerCAmelCase_   :							Optional[Any]									=			[
								    '''bos_token''',
								    '''eos_token''',
								    '''unk_token''',
								    '''sep_token''',
								    '''pad_token''',
								    '''cls_token''',
								    '''mask_token''',
								]

								lowerCAmelCase_   :							Any									=			0
								lowerCAmelCase_   :							Optional[int]									=			tokenizer.convert_ids_to_tokens(
								    SCREAMING_SNAKE_CASE__						,			skip_special_tokens=SCREAMING_SNAKE_CASE__	)

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

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

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

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







"""simple docstring"""
from typing import TYPE_CHECKING

from ...file_utils import _LazyModule, is_tokenizers_available, is_torch_available, is_vision_available
from ...utils import OptionalDependencyNotAvailable


lowerCamelCase_								=		{"configuration_dpt": ["DPT_PRETRAINED_CONFIG_ARCHIVE_MAP", "DPTConfig"]}

try:
  if not is_vision_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  lowerCamelCase_								=		["DPTFeatureExtractor"]
  lowerCamelCase_								=		["DPTImageProcessor"]

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  lowerCamelCase_								=		[
      "DPT_PRETRAINED_MODEL_ARCHIVE_LIST",
      "DPTForDepthEstimation",
      "DPTForSemanticSegmentation",
      "DPTModel",
      "DPTPreTrainedModel",
  ]


if TYPE_CHECKING:
  from .configuration_dpt import DPT_PRETRAINED_CONFIG_ARCHIVE_MAP, DPTConfig

  try:
    if not is_vision_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .feature_extraction_dpt import DPTFeatureExtractor
    from .image_processing_dpt import DPTImageProcessor

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_dpt import (
        DPT_PRETRAINED_MODEL_ARCHIVE_LIST,
        DPTForDepthEstimation,
        DPTForSemanticSegmentation,
        DPTModel,
        DPTPreTrainedModel,
    )


else:
  import sys

  lowerCamelCase_								=		_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)