
"""simple docstring"""




class 						a__		( a_		):
   pass


class 						a__		( a_		):
   pass


class 						a__		:
   def __init__(     self							):
          lowercase       :							int									=				[
              [],
              [],
              [],
          ]
   def      __magic_name__     (     self      ,       _a      ,       _a							):
          try:
                 if len(self.queues[priority]							) >= 100:
                        raise OverflowError("Maximum queue size is 100"							)
                 self.queues[priority].append(_a							)
          except IndexError:
                 raise ValueError("Valid priorities are 0, 1, and 2"							)
   def      __magic_name__     (     self							):
          for queue in self.queues:
                 if queue:
                        return queue.pop(0							)
          raise UnderFlowError("All queues are empty"							)

   def __str__(     self							):
          return "\n".join(f"""Priority {i}: {q}""" for i, q in enumerate(self.queues							)							)


class 						a__		:
   def __init__(     self							):
          lowercase       :							Optional[int]									=				[]
   def      __magic_name__     (     self      ,       _a							):
          if len(self.queue							) == 100:
                 raise OverFlowError("Maximum queue size is 100"							)
          self.queue.append(_a							)
   def      __magic_name__     (     self							):
          if not self.queue:
                 raise UnderFlowError("The queue is empty"							)
          else:
                 lowercase       :							Any									=				min(self.queue							)
                 self.queue.remove(_a							)
                 return data

   def __str__(     self							):
          return str(self.queue							)


def     __magic_name__      ( )					->							Union[str, Any]:
       lowercase       :							List[str]									=				FixedPriorityQueue()
       fpq.enqueue(0	,					10    )
       fpq.enqueue(1	,					70    )
       fpq.enqueue(0	,					100    )
       fpq.enqueue(2	,					1    )
       fpq.enqueue(2	,					5    )
       fpq.enqueue(1	,					7    )
       fpq.enqueue(2	,					4    )
       fpq.enqueue(1	,					64    )
       fpq.enqueue(0	,					128    )
       print(__snake_case    )
       print(fpq.dequeue()    )
       print(fpq.dequeue()    )
       print(fpq.dequeue()    )
       print(fpq.dequeue()    )
       print(fpq.dequeue()    )
       print(__snake_case    )
       print(fpq.dequeue()    )
       print(fpq.dequeue()    )
       print(fpq.dequeue()    )
       print(fpq.dequeue()    )
       print(fpq.dequeue()    )


def     __magic_name__      ( )					->							str:
       lowercase       :							List[Any]									=				ElementPriorityQueue()
       epq.enqueue(10    )
       epq.enqueue(70    )
       epq.enqueue(100    )
       epq.enqueue(1    )
       epq.enqueue(5    )
       epq.enqueue(7    )
       epq.enqueue(4    )
       epq.enqueue(64    )
       epq.enqueue(128    )
       print(__snake_case    )
       print(epq.dequeue()    )
       print(epq.dequeue()    )
       print(epq.dequeue()    )
       print(epq.dequeue()    )
       print(epq.dequeue()    )
       print(__snake_case    )
       print(epq.dequeue()    )
       print(epq.dequeue()    )
       print(epq.dequeue()    )
       print(epq.dequeue()    )
       print(epq.dequeue()    )


if __name__ == "__main__":
   fixed_priority_queue()
   element_priority_queue()




"""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__		( a_,     unittest.TestCase		):
   __lowerCAmelCase				=							GPTaTokenizer
   __lowerCAmelCase				=							GPTaTokenizerFast
   __lowerCAmelCase				=							True
   __lowerCAmelCase				=							{"""add_prefix_space""": True}
   __lowerCAmelCase				=							False
   def      __magic_name__     (     self							):
          super().setUp()

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

          lowercase       :							Tuple									=				os.path.join(self.tmpdirname      ,       VOCAB_FILES_NAMES["vocab_file"]							)
          lowercase       :							Optional[Any]									=				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(_a							) + "\n"							)
          with open(self.merges_file      ,       "w"      ,       encoding="utf-8"							) as fp:
                 fp.write("\n".join(_a							)							)
   def      __magic_name__     (     self      ,       **_a							):
          kwargs.update(self.special_tokens_map							)
          return GPTaTokenizer.from_pretrained(self.tmpdirname      ,       **_a							)
   def      __magic_name__     (     self      ,       **_a							):
          kwargs.update(self.special_tokens_map							)
          return GPTaTokenizerFast.from_pretrained(self.tmpdirname      ,       **_a							)
   def      __magic_name__     (     self      ,       _a							):
          lowercase       :							Tuple									=				"lower newer"
          lowercase       :							Dict									=				"lower newer"
          return input_text, output_text
   def      __magic_name__     (     self							):
          lowercase       :							str									=				GPTaTokenizer(self.vocab_file      ,       self.merges_file      ,       **self.special_tokens_map							)
          lowercase       :							Union[str, Any]									=				"lower newer"
          lowercase       :							Any									=				["\u0120low", "er", "\u0120", "n", "e", "w", "er"]
          lowercase       :							int									=				tokenizer.tokenize(_a      ,       add_prefix_space=_a							)
          self.assertListEqual(_a      ,       _a							)

          lowercase       :							int									=				tokens + [tokenizer.unk_token]
          lowercase       :							List[Any]									=				[14, 15, 10, 9, 3, 2, 15, 19]
          self.assertListEqual(tokenizer.convert_tokens_to_ids(_a							)      ,       _a							)
   def      __magic_name__     (     self							):
          if not self.test_rust_tokenizer:
                 return

          lowercase       :							Union[str, Any]									=				self.get_tokenizer()
          lowercase       :							int									=				self.get_rust_tokenizer(add_prefix_space=_a							)

          lowercase       :							Union[str, Any]									=				"lower newer"

          # Testing tokenization
          lowercase       :							Union[str, Any]									=				tokenizer.tokenize(_a      ,       add_prefix_space=_a							)
          lowercase       :							List[Any]									=				rust_tokenizer.tokenize(_a							)
          self.assertListEqual(_a      ,       _a							)

          # Testing conversion to ids without special tokens
          lowercase       :							Dict									=				tokenizer.encode(_a      ,       add_special_tokens=_a      ,       add_prefix_space=_a							)
          lowercase       :							Dict									=				rust_tokenizer.encode(_a      ,       add_special_tokens=_a							)
          self.assertListEqual(_a      ,       _a							)

          # Testing conversion to ids with special tokens
          lowercase       :							Any									=				self.get_rust_tokenizer(add_prefix_space=_a							)
          lowercase       :							Any									=				tokenizer.encode(_a      ,       add_prefix_space=_a							)
          lowercase       :							Any									=				rust_tokenizer.encode(_a							)
          self.assertListEqual(_a      ,       _a							)

          # Testing the unknown token
          lowercase       :							Union[str, Any]									=				tokens + [rust_tokenizer.unk_token]
          lowercase       :							str									=				[14, 15, 10, 9, 3, 2, 15, 19]
          self.assertListEqual(rust_tokenizer.convert_tokens_to_ids(_a							)      ,       _a							)
   def      __magic_name__     (     self      ,       *_a      ,       **_a							):
          # It's very difficult to mix/test pretokenization with byte-level
          # And get both GPT2 and Roberta to work at the same time (mostly an issue of adding a space before the string)
          pass
   def      __magic_name__     (     self      ,       _a=15							):
          for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
                 with self.subTest(f"""{tokenizer.__class__.__name__} ({pretrained_name})"""							):
                        lowercase       :							int									=				self.rust_tokenizer_class.from_pretrained(_a      ,       **_a							)

                        # Simple input
                        lowercase       :							int									=				"This is a simple input"
                        lowercase       :							Optional[int]									=				["This is a simple input 1", "This is a simple input 2"]
                        lowercase       :							Union[str, Any]									=				("This is a simple input", "This is a pair")
                        lowercase       :							Any									=				[
                            ("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(_a      ,       tokenizer_r.encode      ,       _a      ,       max_length=_a      ,       padding="max_length"							)

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

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

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

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

                        # Pair input
                        self.assertRaises(
                            _a      ,       tokenizer_r.batch_encode_plus      ,       _a      ,       max_length=_a      ,       padding="max_length"      ,       )
   def      __magic_name__     (     self							):
          lowercase       :							List[Any]									=				GPTaTokenizer.from_pretrained(self.tmpdirname      ,       pad_token="<pad>"							)

          # Simple input
          lowercase       :							int									=				"This is a simple input"
          lowercase       :							Tuple									=				["This is a simple input looooooooong", "This is a simple input"]
          lowercase       :							Any									=				("This is a simple input", "This is a pair")
          lowercase       :							str									=				[
              ("This is a simple input loooooong", "This is a simple input"),
              ("This is a simple pair loooooong", "This is a simple pair"),
          ]

          lowercase       :							List[Any]									=				tokenizer.pad_token_id

          lowercase       :							List[Any]									=				tokenizer(_a      ,       padding="max_length"      ,       max_length=30      ,       return_tensors="np"							)
          lowercase       :							List[str]									=				tokenizer(_a      ,       padding=_a      ,       truncate=_a      ,       return_tensors="np"							)
          lowercase       :							List[Any]									=				tokenizer(*_a      ,       padding="max_length"      ,       max_length=60      ,       return_tensors="np"							)
          lowercase       :							Any									=				tokenizer(_a      ,       padding=_a      ,       truncate=_a      ,       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      __magic_name__     (     self							):
          lowercase       :							List[Any]									=				"$$$"
          lowercase       :							List[str]									=				GPTaTokenizer.from_pretrained(self.tmpdirname      ,       bos_token=_a      ,       add_bos_token=_a							)

          lowercase       :							List[Any]									=				"This is a simple input"
          lowercase       :							str									=				["This is a simple input 1", "This is a simple input 2"]

          lowercase       :							Union[str, Any]									=				tokenizer.bos_token_id

          lowercase       :							List[str]									=				tokenizer(_a							)
          lowercase       :							Any									=				tokenizer(_a							)

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

          lowercase       :							List[Any]									=				tokenizer.decode(out_s.input_ids							)
          lowercase       :							Tuple									=				tokenizer.batch_decode(out_sa.input_ids							)

          self.assertEqual(decode_s.split()[0]      ,       _a							)
          self.assertTrue(all(d.split()[0] == bos_token for d in decode_sa							)							)
   def      __magic_name__     (     self							):
          pass

   def      __magic_name__     (     self							):
          # TODO: change to self.get_tokenizers() when the fast version is implemented
          lowercase       :							Dict									=				[self.get_tokenizer(do_lower_case=_a      ,       add_bos_token=_a							)]
          for tokenizer in tokenizers:
                 with self.subTest(f"""{tokenizer.__class__.__name__}"""							):
                        lowercase       :							Optional[Any]									=				"Encode this."
                        lowercase       :							Union[str, Any]									=				"This one too please."
                        lowercase       :							Dict									=				tokenizer.encode(_a      ,       add_special_tokens=_a							)
                        encoded_sequence += tokenizer.encode(_a      ,       add_special_tokens=_a							)
                        lowercase       :							Optional[Any]									=				tokenizer.encode_plus(
                            _a      ,       _a      ,       add_special_tokens=_a      ,       return_special_tokens_mask=_a      ,       )
                        lowercase       :							Tuple									=				encoded_sequence_dict["input_ids"]
                        lowercase       :							int									=				encoded_sequence_dict["special_tokens_mask"]
                        self.assertEqual(len(_a							)      ,       len(_a							)							)

                        lowercase       :							List[str]									=				[
                            (x if not special_tokens_mask[i] else None) for i, x in enumerate(_a							)
                        ]
                        lowercase       :							List[str]									=				[x for x in filtered_sequence if x is not None]
                        self.assertEqual(_a      ,       _a							)


@require_tokenizers
class 						a__		( unittest.TestCase		):
   def      __magic_name__     (     self							):
          # More context:
          # https://huggingface.co/wjmcat/opt-350m-paddle/discussions/1
          # https://huggingface.slack.com/archives/C01N44FJDHT/p1653511495183519
          # https://github.com/huggingface/transformers/pull/17088#discussion_r871246439

          lowercase       :							Tuple									=				AutoTokenizer.from_pretrained("facebook/opt-350m"      ,       from_slow=_a							)
          lowercase       :							Any									=				"A photo of a cat"

          lowercase       :							List[str]									=				tokenizer.encode(
              _a      ,       )
          self.assertEqual(_a      ,       [2, 250, 1_345, 9, 10, 4_758]							)
          tokenizer.save_pretrained("test_opt"							)

          lowercase       :							Union[str, Any]									=				AutoTokenizer.from_pretrained("./test_opt"							)
          lowercase       :							Tuple									=				tokenizer.encode(
              _a      ,       )
          self.assertEqual(_a      ,       [2, 250, 1_345, 9, 10, 4_758]							)
   def      __magic_name__     (     self							):
          lowercase       :							Union[str, Any]									=				AutoTokenizer.from_pretrained("facebook/opt-350m"      ,       use_slow=_a							)
          lowercase       :							Union[str, Any]									=				"A photo of a cat"

          lowercase       :							Union[str, Any]									=				tokenizer.encode(
              _a      ,       )
          # Same as above
          self.assertEqual(_a      ,       [2, 250, 1_345, 9, 10, 4_758]							)

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

          lowercase       :							List[Any]									=				"bos"
          lowercase       :							Optional[int]									=				tokenizer.get_vocab()["bos"]

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


