


'''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():
					a_						:       List[Any]      			=				"""pt"""
elif is_tf_available():
					a_						:       str      			=				"""tf"""
else:
					a_						:       Dict      			=				"""jax"""





class   snake_case					(					lowercase    ,		unittest.TestCase    ):





		"""simple docstring"""




		_lowerCamelCase						=						ByTaTokenizer
		_lowerCamelCase						=						False






		def 						snake_case	(					self  ):







			"""simple docstring"""
			super().setUp()
			lowerCamelCase_  				=						ByTaTokenizer()
			tokenizer.save_pretrained(self.tmpdirname  )






		@cached_property
		def 						snake_case	(					self  ):







			"""simple docstring"""
			return ByTaTokenizer.from_pretrained("google/byt5-small"  )






		def 						snake_case	(					self    ,						**UpperCamelCase  ):







			"""simple docstring"""
			return self.tokenizer_class.from_pretrained(self.tmpdirname    ,						**UpperCamelCase  )






		def 						snake_case	(					self    ,						UpperCamelCase    ,						UpperCamelCase=False    ,						UpperCamelCase=20    ,						UpperCamelCase=5  ):







			"""simple docstring"""
			lowerCamelCase_  				=						[]
			for i in range(len(UpperCamelCase  )  ):
				try:
					lowerCamelCase_  				=						tokenizer.decode([i]    ,						clean_up_tokenization_spaces=UpperCamelCase  )
				except UnicodeDecodeError:
					pass
				toks.append((i, tok)  )

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

			# Ensure consistency
			lowerCamelCase_  				=						tokenizer.decode(UpperCamelCase    ,						clean_up_tokenization_spaces=UpperCamelCase  )
			if " " not in output_txt and len(UpperCamelCase  ) > 1:
				lowerCamelCase_  				=						(
				    tokenizer.decode([toks_ids[0]]    ,						clean_up_tokenization_spaces=UpperCamelCase  )
				    + " "
				    + tokenizer.decode(toks_ids[1:]    ,						clean_up_tokenization_spaces=UpperCamelCase  )
				)
			if with_prefix_space:
				lowerCamelCase_  				=						" " + output_txt
			lowerCamelCase_  				=						tokenizer.encode(UpperCamelCase    ,						add_special_tokens=UpperCamelCase  )
			return output_txt, output_ids






		def 						snake_case	(					self  ):







			"""simple docstring"""
			lowerCamelCase_  				=						self.ta_base_tokenizer
			lowerCamelCase_  				=						tokenizer(["hi</s>", "I went to the gym</s>", "</s>"]  )
			lowerCamelCase_  				=						tokenizer(["hi", "I went to the gym", ""]  )
			self.assertListEqual(batch_with_eos_added["input_ids"]    ,						batch_without_eos_added["input_ids"]  )






		def 						snake_case	(					self  ):







			"""simple docstring"""
			lowerCamelCase_  				=						self.ta_base_tokenizer
			lowerCamelCase_  				=						"Unicode €."
			lowerCamelCase_  				=						tokenizer(UpperCamelCase  )
			lowerCamelCase_  				=						[88, 113, 108, 102, 114, 103, 104, 35, 229, 133, 175, 49, 1]
			self.assertEqual(encoded["input_ids"]    ,						UpperCamelCase  )

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

			lowerCamelCase_  				=						tokenizer("e è é ê ë"  )
			lowerCamelCase_  				=						[104, 35, 198, 171, 35, 198, 172, 35, 198, 173, 35, 198, 174, 1]
			self.assertEqual(encoded["input_ids"]    ,						UpperCamelCase  )
			# decoding
			lowerCamelCase_  				=						tokenizer.decode(UpperCamelCase  )
			self.assertEqual(UpperCamelCase    ,						"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 						snake_case	(					self  ):







			"""simple docstring"""
			lowerCamelCase_  				=						self.ta_base_tokenizer
			lowerCamelCase_  				=						["A long paragraph for summarization.", "Another paragraph for summarization."]
			# fmt: off
			lowerCamelCase_  				=						[68, 35, 111, 114, 113, 106, 35, 115, 100, 117, 100, 106, 117, 100, 115, 107, 35, 105, 114, 117, 35, 118, 120, 112, 112, 100, 117, 108, 125, 100, 119, 108, 114, 113, 49, 1, 0]
			# fmt: on
			lowerCamelCase_  				=						tokenizer(UpperCamelCase    ,						padding=UpperCamelCase    ,						return_tensors=UpperCamelCase  )
			self.assertIsInstance(UpperCamelCase    ,						UpperCamelCase  )

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

			self.assertListEqual(UpperCamelCase    ,						UpperCamelCase  )

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






		def 						snake_case	(					self  ):







			"""simple docstring"""
			lowerCamelCase_  				=						self.ta_base_tokenizer
			lowerCamelCase_  				=						["A long paragraph for summarization.", "Another paragraph for summarization."]
			lowerCamelCase_  				=						tokenizer(UpperCamelCase    ,						padding=UpperCamelCase    ,						return_tensors=UpperCamelCase  )
			# check if input_ids are returned and no decoder_input_ids
			self.assertIn("input_ids"    ,						UpperCamelCase  )
			self.assertIn("attention_mask"    ,						UpperCamelCase  )
			self.assertNotIn("decoder_input_ids"    ,						UpperCamelCase  )
			self.assertNotIn("decoder_attention_mask"    ,						UpperCamelCase  )






		def 						snake_case	(					self  ):







			"""simple docstring"""
			lowerCamelCase_  				=						self.ta_base_tokenizer
			lowerCamelCase_  				=						[
			    "Summary of the text.",
			    "Another summary.",
			]
			lowerCamelCase_  				=						tokenizer(
			    text_target=UpperCamelCase    ,						max_length=32    ,						padding="max_length"    ,						truncation=UpperCamelCase    ,						return_tensors=UpperCamelCase  )
			self.assertEqual(32    ,						targets["input_ids"].shape[1]  )






		def 						snake_case	(					self  ):







			"""simple docstring"""
			lowerCamelCase_  				=						self.ta_base_tokenizer
			lowerCamelCase_  				=						["A long paragraph for summarization. </s>"]
			lowerCamelCase_  				=						["Summary of the text. </s>"]
			# fmt: off
			lowerCamelCase_  				=						[68, 35, 111, 114, 113, 106, 35, 115, 100, 117, 100, 106, 117, 100, 115, 107, 35, 105, 114, 117, 35, 118, 120, 112, 112, 100, 117, 108, 125, 100, 119, 108, 114, 113, 49, 35, 1]
			lowerCamelCase_  				=						[86, 120, 112, 112, 100, 117, 124, 35, 114, 105, 35, 119, 107, 104, 35, 119, 104, 123, 119, 49, 35, 1]
			# fmt: on

			lowerCamelCase_  				=						tokenizer(UpperCamelCase    ,						text_target=UpperCamelCase  )

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






		def 						snake_case	(					self  ):







			"""simple docstring"""
			lowerCamelCase_  				=						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_  				=						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_  				=						tempfile.mkdtemp()

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

					lowerCamelCase_  				=						tokenizer.__class__.from_pretrained(UpperCamelCase  )
					lowerCamelCase_  				=						after_tokenizer.encode(UpperCamelCase    ,						add_special_tokens=UpperCamelCase  )
					self.assertListEqual(UpperCamelCase    ,						UpperCamelCase  )

					shutil.rmtree(UpperCamelCase  )

			lowerCamelCase_  				=						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_  				=						tempfile.mkdtemp()

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

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

					lowerCamelCase_  				=						tokenizer.__class__.from_pretrained(UpperCamelCase    ,						model_max_length=43  )
					self.assertEqual(tokenizer.model_max_length    ,						43  )

					shutil.rmtree(UpperCamelCase  )






		def 						snake_case	(					self  ):







			"""simple docstring"""
			lowerCamelCase_  				=						[]
			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(UpperCamelCase  )

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

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

					lowerCamelCase_  				=						[f'''<extra_id_{i}>''' for i in range(125  )]

					lowerCamelCase_  				=						added_tokens_extra_ids + [
					    "an_additional_special_token"
					]
					lowerCamelCase_  				=						added_tokens_extra_ids + [
					    "an_additional_special_token"
					]

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

					# 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_  				=						tokenizer_class.from_pretrained(
					    UpperCamelCase    ,						)
					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_  				=						added_tokens_extra_ids + [AddedToken("a_new_additional_special_token"    ,						lstrip=UpperCamelCase  )]
					lowerCamelCase_  				=						tokenizer_class.from_pretrained(
					    UpperCamelCase    ,						additional_special_tokens=UpperCamelCase    ,						)

					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 						snake_case	(					self  ):







			"""simple docstring"""
			lowerCamelCase_  				=						[]
			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(UpperCamelCase  )

					lowerCamelCase_  				=						tokenizer_class.from_pretrained(UpperCamelCase  )

					self.assertTrue(tokenizer.decode([255]  ) == ""  )






		def 						snake_case	(					self  ):







			"""simple docstring"""
			pass






		def 						snake_case	(					self  ):







			"""simple docstring"""
			pass






		def 						snake_case	(					self  ):







			"""simple docstring"""
			pass






		def 						snake_case	(					self  ):







			"""simple docstring"""
			pass






		def 						snake_case	(					self  ):







			"""simple docstring"""
			lowerCamelCase_  				=						self.get_tokenizers(fast=UpperCamelCase    ,						do_lower_case=UpperCamelCase  )
			for tokenizer in tokenizers:
				with self.subTest(f'''{tokenizer.__class__.__name__}'''  ):
					lowerCamelCase_  				=						["t", "h", "i", "s", " ", "i", "s", " ", "a", " ", "t", "e", "x", "t", "</s>"]
					lowerCamelCase_  				=						tokenizer.convert_tokens_to_string(UpperCamelCase  )

					self.assertIsInstance(UpperCamelCase    ,						UpperCamelCase  )







		def 						snake_case	(					self  ):







			"""simple docstring"""
			lowerCamelCase_  				=						self.get_tokenizers()
			for tokenizer in tokenizers:
				with self.subTest(f'''{tokenizer.__class__.__name__}'''  ):
					lowerCamelCase_  				=						[
					    "bos_token",
					    "eos_token",
					    "unk_token",
					    "sep_token",
					    "pad_token",
					    "cls_token",
					    "mask_token",
					]

					lowerCamelCase_  				=						0
					lowerCamelCase_  				=						tokenizer.convert_ids_to_tokens(
					    UpperCamelCase    ,						skip_special_tokens=UpperCamelCase  )

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

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

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

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







'''simple docstring'''

import numpy as np
from matplotlib import pyplot as plt
from sklearn.datasets import load_iris
from sklearn.metrics import ConfusionMatrixDisplay
from sklearn.model_selection import train_test_split
from xgboost import XGBClassifier





def __snake_case      (   UpperCAmelCase_		:		dict	):
 return (data["data"], data["target"])





def __snake_case      (   UpperCAmelCase_		:		np.ndarray      ,       UpperCAmelCase_		:		np.ndarray	):
 lowerCamelCase_  				=						XGBClassifier()
 classifier.fit(UpperCAmelCase_      ,       UpperCAmelCase_	)
 return classifier





def __snake_case      (   ):
 lowerCamelCase_  				=						load_iris()
 lowerCamelCase_				,lowerCamelCase_  				=						data_handling(UpperCAmelCase_	)
 lowerCamelCase_				,lowerCamelCase_				,lowerCamelCase_				,lowerCamelCase_  				=						train_test_split(
     UpperCAmelCase_      ,       UpperCAmelCase_      ,       test_size=0.25	)

 lowerCamelCase_  				=						iris["target_names"]

 # Create an XGBoost Classifier from the training data
 lowerCamelCase_  				=						xgboost(UpperCAmelCase_      ,       UpperCAmelCase_	)

 # Display the confusion matrix of the classifier with both training and test sets
 ConfusionMatrixDisplay.from_estimator(
     UpperCAmelCase_      ,       UpperCAmelCase_      ,       UpperCAmelCase_      ,       display_labels=UpperCAmelCase_      ,       cmap="Blues"      ,       normalize="true"      ,       )
 plt.title("Normalized Confusion Matrix - IRIS Dataset"	)
 plt.show()


if __name__ == "__main__":
     import doctest

     doctest.testmod(verbose=True)
     main()



