





'''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 					a_     (				snake_case_      ,    unittest.TestCase       ):

    '''simple docstring'''
    UpperCamelCase     = GPTaTokenizer
    UpperCamelCase     = GPTaTokenizerFast
    UpperCamelCase     = True
    UpperCamelCase     = {'''add_prefix_space''': True}
    UpperCamelCase     = False


    def 			snake_case_(		self       )		->   Union[str, Any]:
        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(UpperCamelCase__ ,		range(len(UpperCamelCase__       )       )       )       )
        _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(UpperCamelCase__       ) + """\n"""       )
        with open(self.merges_file ,		"""w""" ,		encoding="""utf-8"""       ) as fp:
            fp.write("""\n""".join(UpperCamelCase__       )       )


    def 			snake_case_(		self ,		**A       )		->   Union[str, Any]:
        kwargs.update(self.special_tokens_map       )
        return GPTaTokenizer.from_pretrained(self.tmpdirname ,		**UpperCamelCase__       )


    def 			snake_case_(		self ,		**A       )		->   Dict:
        kwargs.update(self.special_tokens_map       )
        return GPTaTokenizerFast.from_pretrained(self.tmpdirname ,		**UpperCamelCase__       )


    def 			snake_case_(		self ,		A       )		->   Dict:
        _SCREAMING_SNAKE_CASE									=			"lower newer"
        _SCREAMING_SNAKE_CASE									=			"lower newer"
        return input_text, output_text


    def 			snake_case_(		self       )		->   Any:
        _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(UpperCamelCase__ ,		add_prefix_space=UpperCamelCase__       )
        self.assertListEqual(UpperCamelCase__ ,		UpperCamelCase__       )

        _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(UpperCamelCase__       ) ,		UpperCamelCase__       )


    def 			snake_case_(		self       )		->   Optional[int]:




        if not self.test_rust_tokenizer:
            return

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

        _SCREAMING_SNAKE_CASE									=			"lower newer"

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

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

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

        # 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(UpperCamelCase__       ) ,		UpperCamelCase__       )


    def 			snake_case_(		self ,		*A ,		**A       )		->   Any:
        pass


    def 			snake_case_(		self ,		A=15       )		->   Optional[Any]:




        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(UpperCamelCase__ ,		**UpperCamelCase__       )

                # 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(UpperCamelCase__ ,		tokenizer_r.encode ,		UpperCamelCase__ ,		max_length=UpperCamelCase__ ,		padding="""max_length"""       )

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

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

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

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

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


    def 			snake_case_(		self       )		->   List[str]:
        _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(UpperCamelCase__ ,		padding="""max_length""" ,		max_length=30 ,		return_tensors="""np"""       )
        _SCREAMING_SNAKE_CASE									=			tokenizer(UpperCamelCase__ ,		padding=UpperCamelCase__ ,		truncate=UpperCamelCase__ ,		return_tensors="""np"""       )
        _SCREAMING_SNAKE_CASE									=			tokenizer(*UpperCamelCase__ ,		padding="""max_length""" ,		max_length=60 ,		return_tensors="""np"""       )
        _SCREAMING_SNAKE_CASE									=			tokenizer(UpperCamelCase__ ,		padding=UpperCamelCase__ ,		truncate=UpperCamelCase__ ,		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 			snake_case_(		self       )		->   Optional[Any]:
        _SCREAMING_SNAKE_CASE									=			"$$$"
        _SCREAMING_SNAKE_CASE									=			GPTaTokenizer.from_pretrained(self.tmpdirname ,		bos_token=UpperCamelCase__ ,		add_bos_token=UpperCamelCase__       )

        _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(UpperCamelCase__       )
        _SCREAMING_SNAKE_CASE									=			tokenizer(UpperCamelCase__       )

        self.assertEqual(out_s.input_ids[0] ,		UpperCamelCase__       )
        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] ,		UpperCamelCase__       )
        self.assertTrue(all(d.split()[0] == bos_token for d in decode_sa       )       )


    def 			snake_case_(		self       )		->   Dict:
        pass





    def 			snake_case_(		self       )		->   Union[str, Any]:
        _SCREAMING_SNAKE_CASE									=			[self.get_tokenizer(do_lower_case=UpperCamelCase__ ,		add_bos_token=UpperCamelCase__       )]
        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(UpperCamelCase__ ,		add_special_tokens=UpperCamelCase__       )
                encoded_sequence += tokenizer.encode(UpperCamelCase__ ,		add_special_tokens=UpperCamelCase__       )
                _SCREAMING_SNAKE_CASE									=			tokenizer.encode_plus(
                    UpperCamelCase__ ,		UpperCamelCase__ ,		add_special_tokens=UpperCamelCase__ ,		return_special_tokens_mask=UpperCamelCase__ ,		)
                _SCREAMING_SNAKE_CASE									=			encoded_sequence_dict["input_ids"]
                _SCREAMING_SNAKE_CASE									=			encoded_sequence_dict["special_tokens_mask"]
                self.assertEqual(len(UpperCamelCase__       ) ,		len(UpperCamelCase__       )       )

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




@require_tokenizers
class 					a_     (				unittest.TestCase       ):

    '''simple docstring'''


    def 			snake_case_(		self       )		->   List[str]:
        _SCREAMING_SNAKE_CASE									=			AutoTokenizer.from_pretrained("""facebook/opt-350m""" ,		from_slow=UpperCamelCase__       )
        _SCREAMING_SNAKE_CASE									=			"A photo of a cat"

        _SCREAMING_SNAKE_CASE									=			tokenizer.encode(
            UpperCamelCase__ ,		)
        self.assertEqual(UpperCamelCase__ ,		[2, 250, 1345, 9, 10, 4758]       )
        tokenizer.save_pretrained("""test_opt"""       )

        _SCREAMING_SNAKE_CASE									=			AutoTokenizer.from_pretrained("""./test_opt"""       )
        _SCREAMING_SNAKE_CASE									=			tokenizer.encode(
            UpperCamelCase__ ,		)
        self.assertEqual(UpperCamelCase__ ,		[2, 250, 1345, 9, 10, 4758]       )


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

        _SCREAMING_SNAKE_CASE									=			tokenizer.encode(
            UpperCamelCase__ ,		)
        # Same as above
        self.assertEqual(UpperCamelCase__ ,		[2, 250, 1345, 9, 10, 4758]       )





    @unittest.skip("""This test is failing because of a bug in the fast tokenizer"""       )
    def 			snake_case_(		self       )		->   List[str]:
        _SCREAMING_SNAKE_CASE									=			AutoTokenizer.from_pretrained("""facebook/opt-350m""" ,		from_slow=UpperCamelCase__       )

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

        _SCREAMING_SNAKE_CASE									=			"A photo of a cat"
        _SCREAMING_SNAKE_CASE									=			tokenizer.encode(
            UpperCamelCase__ ,		)
        # We changed the bos token
        self.assertEqual(UpperCamelCase__ ,		[3_1957, 250, 1345, 9, 10, 4758]       )
        tokenizer.save_pretrained("""./tok"""       )
        _SCREAMING_SNAKE_CASE									=			AutoTokenizer.from_pretrained("""./tok"""       )
        self.assertTrue(tokenizer.is_fast       )
        _SCREAMING_SNAKE_CASE									=			tokenizer.encode(
            UpperCamelCase__ ,		)
        self.assertEqual(UpperCamelCase__ ,		[3_1957, 250, 1345, 9, 10, 4758]       )







"""simple docstring"""



def   __lowerCAmelCase						(						lowercase  :  list )	->						int:


    """simple docstring"""





    if not grid or not grid[0]:
        raise TypeError("The grid does not contain the appropriate information" )

    for cell_n in range(1						,							len(grid[0] ) ):
        grid[0][cell_n] += grid[0][cell_n - 1]
    snake_case    :      int      					=    grid[0]

    for row_n in range(1						,							len(lowercase ) ):
        snake_case    :      Optional[Any]      					=    grid[row_n]
        snake_case    :      List[str]      					=    fill_row(lowercase						,							lowercase )
        snake_case    :      Optional[int]      					=    grid[row_n]

    return grid[-1][-1]







def   __lowerCAmelCase						(						lowercase  :  list						,							lowercase  :  list )	->						list:


    """simple docstring"""





    current_row[0] += row_above[0]
    for cell_n in range(1						,							len(lowercase ) ):
        current_row[cell_n] += min(current_row[cell_n - 1]						,							row_above[cell_n] )

    return current_row


if __name__ == "__main__":
  import doctest

  doctest.testmod()





