
'''simple docstring'''







import json
import os
import unittest

from transformers import AutoTokenizer, GPTaTokenizer, GPTaTokenizerFast
from transformers.models.gpta.tokenization_gpta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin


@require_tokenizers
class 			lowerCAmelCase (				__a		,     unittest.TestCase			):
		a							:					Tuple       =					GPTaTokenizer
		a							:					Optional[int]       =					GPTaTokenizerFast
		a							:					Optional[int]       =					True
		a							:					Optional[Any]       =					{"add_prefix_space": True}
		a							:					List[str]       =					False




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

								# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
								_SCREAMING_SNAKE_CASE				= [
								    "l",
								    "o",
								    "w",
								    "e",
								    "r",
								    "s",
								    "t",
								    "i",
								    "d",
								    "n",
								    "\u0120",
								    "\u0120l",
								    "\u0120n",
								    "\u0120lo",
								    "\u0120low",
								    "er",
								    "\u0120lowest",
								    "\u0120newer",
								    "\u0120wider",
								    "<unk>",
								    "<|endoftext|>",
								]
								_SCREAMING_SNAKE_CASE				= dict(zip(lowerCAmelCase_					,						range(len(lowerCAmelCase_      )      )      )      )
								_SCREAMING_SNAKE_CASE				= ["#version: 0.2", "\u0120 l", "\u0120l o", "\u0120lo w", "e r", ""]
								_SCREAMING_SNAKE_CASE				= {"unk_token": "<unk>"}

								_SCREAMING_SNAKE_CASE				= os.path.join(self.tmpdirname					,						VOCAB_FILES_NAMES["vocab_file"]      )
								_SCREAMING_SNAKE_CASE				= 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     lowercase       (				self					,						**UpperCamelCase      ):
								kwargs.update(self.special_tokens_map      )
								return GPTaTokenizer.from_pretrained(self.tmpdirname					,						**lowerCAmelCase_      )




		def     lowercase       (				self					,						**UpperCamelCase      ):
								kwargs.update(self.special_tokens_map      )
								return GPTaTokenizerFast.from_pretrained(self.tmpdirname					,						**lowerCAmelCase_      )




		def     lowercase       (				self					,						UpperCamelCase      ):
								_SCREAMING_SNAKE_CASE				= "lower newer"
								_SCREAMING_SNAKE_CASE				= "lower newer"
								return input_text, output_text




		def     lowercase       (				self      ):
								_SCREAMING_SNAKE_CASE				= GPTaTokenizer(self.vocab_file					,						self.merges_file					,						**self.special_tokens_map      )
								_SCREAMING_SNAKE_CASE				= "lower newer"
								_SCREAMING_SNAKE_CASE				= ["\u0120low", "er", "\u0120", "n", "e", "w", "er"]
								_SCREAMING_SNAKE_CASE				= tokenizer.tokenize(lowerCAmelCase_					,						add_prefix_space=lowerCAmelCase_      )
								self.assertListEqual(lowerCAmelCase_					,						lowerCAmelCase_      )

								_SCREAMING_SNAKE_CASE				= tokens + [tokenizer.unk_token]
								_SCREAMING_SNAKE_CASE				= [14, 15, 10, 9, 3, 2, 15, 19]
								self.assertListEqual(tokenizer.convert_tokens_to_ids(lowerCAmelCase_      )					,						lowerCAmelCase_      )




		def     lowercase       (				self      ):







								if not self.test_rust_tokenizer:
														return

								_SCREAMING_SNAKE_CASE				= self.get_tokenizer()
								_SCREAMING_SNAKE_CASE				= self.get_rust_tokenizer(add_prefix_space=lowerCAmelCase_      )

								_SCREAMING_SNAKE_CASE				= "lower newer"

								# Testing tokenization
								_SCREAMING_SNAKE_CASE				= tokenizer.tokenize(lowerCAmelCase_					,						add_prefix_space=lowerCAmelCase_      )
								_SCREAMING_SNAKE_CASE				= rust_tokenizer.tokenize(lowerCAmelCase_      )
								self.assertListEqual(lowerCAmelCase_					,						lowerCAmelCase_      )

								# Testing conversion to ids without special tokens
								_SCREAMING_SNAKE_CASE				= tokenizer.encode(lowerCAmelCase_					,						add_special_tokens=lowerCAmelCase_					,						add_prefix_space=lowerCAmelCase_      )
								_SCREAMING_SNAKE_CASE				= rust_tokenizer.encode(lowerCAmelCase_					,						add_special_tokens=lowerCAmelCase_      )
								self.assertListEqual(lowerCAmelCase_					,						lowerCAmelCase_      )

								# Testing conversion to ids with special tokens
								_SCREAMING_SNAKE_CASE				= self.get_rust_tokenizer(add_prefix_space=lowerCAmelCase_      )
								_SCREAMING_SNAKE_CASE				= tokenizer.encode(lowerCAmelCase_					,						add_prefix_space=lowerCAmelCase_      )
								_SCREAMING_SNAKE_CASE				= rust_tokenizer.encode(lowerCAmelCase_      )
								self.assertListEqual(lowerCAmelCase_					,						lowerCAmelCase_      )

								# Testing the unknown token
								_SCREAMING_SNAKE_CASE				= tokens + [rust_tokenizer.unk_token]
								_SCREAMING_SNAKE_CASE				= [14, 15, 10, 9, 3, 2, 15, 19]
								self.assertListEqual(rust_tokenizer.convert_tokens_to_ids(lowerCAmelCase_      )					,						lowerCAmelCase_      )




		def     lowercase       (				self					,						*UpperCamelCase					,						**UpperCamelCase      ):
								pass




		def     lowercase       (				self					,						UpperCamelCase=15      ):







								for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
														with self.subTest(F'{tokenizer.__class__.__name__} ({pretrained_name})'      ):
																				_SCREAMING_SNAKE_CASE				= self.rust_tokenizer_class.from_pretrained(lowerCAmelCase_					,						**lowerCAmelCase_      )

																				# Simple input
																				_SCREAMING_SNAKE_CASE				= "This is a simple input"
																				_SCREAMING_SNAKE_CASE				= ["This is a simple input 1", "This is a simple input 2"]
																				_SCREAMING_SNAKE_CASE				= ("This is a simple input", "This is a pair")
																				_SCREAMING_SNAKE_CASE				= [
																				    ("This is a simple input 1", "This is a simple input 2"),
																				    ("This is a simple pair 1", "This is a simple pair 2"),
																				]

																				# Simple input tests
																				self.assertRaises(lowerCAmelCase_					,						tokenizer_r.encode					,						lowerCAmelCase_					,						max_length=lowerCAmelCase_					,						padding="max_length"      )

																				# Simple input
																				self.assertRaises(lowerCAmelCase_					,						tokenizer_r.encode_plus					,						lowerCAmelCase_					,						max_length=lowerCAmelCase_					,						padding="max_length"      )

																				# Simple input
																				self.assertRaises(
																				    lowerCAmelCase_					,						tokenizer_r.batch_encode_plus					,						lowerCAmelCase_					,						max_length=lowerCAmelCase_					,						padding="max_length"					,						)

																				# Pair input
																				self.assertRaises(lowerCAmelCase_					,						tokenizer_r.encode					,						lowerCAmelCase_					,						max_length=lowerCAmelCase_					,						padding="max_length"      )

																				# Pair input
																				self.assertRaises(lowerCAmelCase_					,						tokenizer_r.encode_plus					,						lowerCAmelCase_					,						max_length=lowerCAmelCase_					,						padding="max_length"      )

																				# Pair input
																				self.assertRaises(
																				    lowerCAmelCase_					,						tokenizer_r.batch_encode_plus					,						lowerCAmelCase_					,						max_length=lowerCAmelCase_					,						padding="max_length"					,						)




		def     lowercase       (				self      ):
								_SCREAMING_SNAKE_CASE				= GPTaTokenizer.from_pretrained(self.tmpdirname					,						pad_token="<pad>"      )

								# Simple input
								_SCREAMING_SNAKE_CASE				= "This is a simple input"
								_SCREAMING_SNAKE_CASE				= ["This is a simple input looooooooong", "This is a simple input"]
								_SCREAMING_SNAKE_CASE				= ("This is a simple input", "This is a pair")
								_SCREAMING_SNAKE_CASE				= [
								    ("This is a simple input loooooong", "This is a simple input"),
								    ("This is a simple pair loooooong", "This is a simple pair"),
								]

								_SCREAMING_SNAKE_CASE				= tokenizer.pad_token_id

								_SCREAMING_SNAKE_CASE				= tokenizer(lowerCAmelCase_					,						padding="max_length"					,						max_length=30					,						return_tensors="np"      )
								_SCREAMING_SNAKE_CASE				= tokenizer(lowerCAmelCase_					,						padding=lowerCAmelCase_					,						truncate=lowerCAmelCase_					,						return_tensors="np"      )
								_SCREAMING_SNAKE_CASE				= tokenizer(*lowerCAmelCase_					,						padding="max_length"					,						max_length=60					,						return_tensors="np"      )
								_SCREAMING_SNAKE_CASE				= tokenizer(lowerCAmelCase_					,						padding=lowerCAmelCase_					,						truncate=lowerCAmelCase_					,						return_tensors="np"      )

								# s
								# test single string max_length padding
								self.assertEqual(out_s["input_ids"].shape[-1]					,						30      )
								self.assertTrue(pad_token_id in out_s["input_ids"]      )
								self.assertTrue(0 in out_s["attention_mask"]      )

								# s2
								# test automatic padding
								self.assertEqual(out_sa["input_ids"].shape[-1]					,						33      )
								# long slice doesn't have padding
								self.assertFalse(pad_token_id in out_sa["input_ids"][0]      )
								self.assertFalse(0 in out_sa["attention_mask"][0]      )
								# short slice does have padding
								self.assertTrue(pad_token_id in out_sa["input_ids"][1]      )
								self.assertTrue(0 in out_sa["attention_mask"][1]      )

								# p
								# test single pair max_length padding
								self.assertEqual(out_p["input_ids"].shape[-1]					,						60      )
								self.assertTrue(pad_token_id in out_p["input_ids"]      )
								self.assertTrue(0 in out_p["attention_mask"]      )

								# p2
								# test automatic padding pair
								self.assertEqual(out_pa["input_ids"].shape[-1]					,						52      )
								# long slice pair doesn't have padding
								self.assertFalse(pad_token_id in out_pa["input_ids"][0]      )
								self.assertFalse(0 in out_pa["attention_mask"][0]      )
								# short slice pair does have padding
								self.assertTrue(pad_token_id in out_pa["input_ids"][1]      )
								self.assertTrue(0 in out_pa["attention_mask"][1]      )




		def     lowercase       (				self      ):
								_SCREAMING_SNAKE_CASE				= "$$$"
								_SCREAMING_SNAKE_CASE				= GPTaTokenizer.from_pretrained(self.tmpdirname					,						bos_token=lowerCAmelCase_					,						add_bos_token=lowerCAmelCase_      )

								_SCREAMING_SNAKE_CASE				= "This is a simple input"
								_SCREAMING_SNAKE_CASE				= ["This is a simple input 1", "This is a simple input 2"]

								_SCREAMING_SNAKE_CASE				= tokenizer.bos_token_id

								_SCREAMING_SNAKE_CASE				= tokenizer(lowerCAmelCase_      )
								_SCREAMING_SNAKE_CASE				= tokenizer(lowerCAmelCase_      )

								self.assertEqual(out_s.input_ids[0]					,						lowerCAmelCase_      )
								self.assertTrue(all(o[0] == bos_token_id for o in out_sa.input_ids      )      )

								_SCREAMING_SNAKE_CASE				= tokenizer.decode(out_s.input_ids      )
								_SCREAMING_SNAKE_CASE				= tokenizer.batch_decode(out_sa.input_ids      )

								self.assertEqual(decode_s.split()[0]					,						lowerCAmelCase_      )
								self.assertTrue(all(d.split()[0] == bos_token for d in decode_sa      )      )




		def     lowercase       (				self      ):
								pass




		def     lowercase       (				self      ):
								_SCREAMING_SNAKE_CASE				= [self.get_tokenizer(do_lower_case=lowerCAmelCase_					,						add_bos_token=lowerCAmelCase_      )]
								for tokenizer in tokenizers:
														with self.subTest(F'{tokenizer.__class__.__name__}'      ):
																				_SCREAMING_SNAKE_CASE				= "Encode this."
																				_SCREAMING_SNAKE_CASE				= "This one too please."
																				_SCREAMING_SNAKE_CASE				= tokenizer.encode(lowerCAmelCase_					,						add_special_tokens=lowerCAmelCase_      )
																				encoded_sequence += tokenizer.encode(lowerCAmelCase_					,						add_special_tokens=lowerCAmelCase_      )
																				_SCREAMING_SNAKE_CASE				= tokenizer.encode_plus(
																				    lowerCAmelCase_					,						lowerCAmelCase_					,						add_special_tokens=lowerCAmelCase_					,						return_special_tokens_mask=lowerCAmelCase_					,						)
																				_SCREAMING_SNAKE_CASE				= encoded_sequence_dict["input_ids"]
																				_SCREAMING_SNAKE_CASE				= encoded_sequence_dict["special_tokens_mask"]
																				self.assertEqual(len(lowerCAmelCase_      )					,						len(lowerCAmelCase_      )      )

																				_SCREAMING_SNAKE_CASE				= [
																				    (x if not special_tokens_mask[i] else None) for i, x in enumerate(lowerCAmelCase_      )
																				]
																				_SCREAMING_SNAKE_CASE				= [x for x in filtered_sequence if x is not None]
																				self.assertEqual(lowerCAmelCase_					,						lowerCAmelCase_      )


@require_tokenizers
class 			lowerCAmelCase (				unittest.TestCase			):




		def     lowercase       (				self      ):
								_SCREAMING_SNAKE_CASE				= AutoTokenizer.from_pretrained("facebook/opt-350m"					,						from_slow=lowerCAmelCase_      )
								_SCREAMING_SNAKE_CASE				= "A photo of a cat"

								_SCREAMING_SNAKE_CASE				= tokenizer.encode(
								    lowerCAmelCase_					,						)
								self.assertEqual(lowerCAmelCase_					,						[2, 250, 1_345, 9, 10, 4_758]      )
								tokenizer.save_pretrained("test_opt"      )

								_SCREAMING_SNAKE_CASE				= AutoTokenizer.from_pretrained("./test_opt"      )
								_SCREAMING_SNAKE_CASE				= tokenizer.encode(
								    lowerCAmelCase_					,						)
								self.assertEqual(lowerCAmelCase_					,						[2, 250, 1_345, 9, 10, 4_758]      )




		def     lowercase       (				self      ):
								_SCREAMING_SNAKE_CASE				= AutoTokenizer.from_pretrained("facebook/opt-350m"					,						use_slow=lowerCAmelCase_      )
								_SCREAMING_SNAKE_CASE				= "A photo of a cat"

								_SCREAMING_SNAKE_CASE				= tokenizer.encode(
								    lowerCAmelCase_					,						)
								# Same as above
								self.assertEqual(lowerCAmelCase_					,						[2, 250, 1_345, 9, 10, 4_758]      )




		@unittest.skip("This test is failing because of a bug in the fast tokenizer"      )
		def     lowercase       (				self      ):
								_SCREAMING_SNAKE_CASE				= AutoTokenizer.from_pretrained("facebook/opt-350m"					,						from_slow=lowerCAmelCase_      )

								_SCREAMING_SNAKE_CASE				= "bos"
								_SCREAMING_SNAKE_CASE				= tokenizer.get_vocab()["bos"]

								_SCREAMING_SNAKE_CASE				= "A photo of a cat"
								_SCREAMING_SNAKE_CASE				= tokenizer.encode(
								    lowerCAmelCase_					,						)
								# We changed the bos token
								self.assertEqual(lowerCAmelCase_					,						[31_957, 250, 1_345, 9, 10, 4_758]      )
								tokenizer.save_pretrained("./tok"      )
								_SCREAMING_SNAKE_CASE				= AutoTokenizer.from_pretrained("./tok"      )
								self.assertTrue(tokenizer.is_fast      )
								_SCREAMING_SNAKE_CASE				= tokenizer.encode(
								    lowerCAmelCase_					,						)
								self.assertEqual(lowerCAmelCase_					,						[31_957, 250, 1_345, 9, 10, 4_758]      )

'''simple docstring'''







# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run

import sys
import warnings
from os.path import abspath, dirname, join


# allow having multiple repository checkouts and not needing to remember to rerun
# 'pip install -e .[dev]' when switching between checkouts and running tests.
_snake_case				:   Optional[Any]     =				abspath(join(dirname(dirname(dirname(__file__))), """src"""))
sys.path.insert(1, git_repo_path)


# silence FutureWarning warnings in tests since often we can't act on them until
# they become normal warnings - i.e. the tests still need to test the current functionality
warnings.simplefilter(action="""ignore""", category=FutureWarning)



def 			_a		(	_SCREAMING_SNAKE_CASE		:   Tuple  ):
						from transformers.testing_utils import pytest_addoption_shared

						pytest_addoption_shared(_SCREAMING_SNAKE_CASE  )




def 			_a		(	_SCREAMING_SNAKE_CASE		:   Union[str, Any]  ):
						from transformers.testing_utils import pytest_terminal_summary_main

						_SCREAMING_SNAKE_CASE				= terminalreporter.config.getoption("--make-reports"  )
						if make_reports:
												pytest_terminal_summary_main(_SCREAMING_SNAKE_CASE	,			id=_SCREAMING_SNAKE_CASE  )