import json
import os
import re
import unittest

from transformers import CodeGenTokenizer, CodeGenTokenizerFast
from transformers.models.codegen.tokenization_codegen import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin






@require_tokenizers
class 		a__						(					A__    ,		unittest.TestCase					):
					A	       =							CodeGenTokenizer
					A	       =							CodeGenTokenizerFast
					A	       =							True
					A	       =							{'add_prefix_space': True}
					A	       =							False

					def 				__UpperCamelCase   (    self      :       Optional[int]    ):







							"""simple docstring"""






							super().setUp()

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

							SCREAMING_SNAKE_CASE_  :		Tuple				      =    os.path.join(self.tmpdirname,VOCAB_FILES_NAMES["vocab_file"]    )
							SCREAMING_SNAKE_CASE_  :		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 				__UpperCamelCase   (    self      :       Tuple,**_A      :       Optional[Any]    ):







							"""simple docstring"""






							kwargs.update(self.special_tokens_map    )
							return CodeGenTokenizer.from_pretrained(self.tmpdirname,**_A    )

					def 				__UpperCamelCase   (    self      :       Any,**_A      :       int    ):







							"""simple docstring"""






							kwargs.update(self.special_tokens_map    )
							return CodeGenTokenizerFast.from_pretrained(self.tmpdirname,**_A    )

					def 				__UpperCamelCase   (    self      :       Optional[Any],_A      :       Tuple    ):







							"""simple docstring"""






							SCREAMING_SNAKE_CASE_  :		Any				      =    "lower newer"
							SCREAMING_SNAKE_CASE_  :		Dict				      =    "lower newer"
							return input_text, output_text

					def 				__UpperCamelCase   (    self      :       List[str]    ):







							"""simple docstring"""






							SCREAMING_SNAKE_CASE_  :		List[str]				      =    CodeGenTokenizer(self.vocab_file,self.merges_file,**self.special_tokens_map    )
							SCREAMING_SNAKE_CASE_  :		int				      =    "lower newer"
							SCREAMING_SNAKE_CASE_  :		List[Any]				      =    ["\u0120low", "er", "\u0120", "n", "e", "w", "er"]
							SCREAMING_SNAKE_CASE_  :		Tuple				      =    tokenizer.tokenize(_A,add_prefix_space=_A    )
							self.assertListEqual(_A,_A    )

							SCREAMING_SNAKE_CASE_  :		int				      =    tokens + [tokenizer.unk_token]
							SCREAMING_SNAKE_CASE_  :		List[str]				      =    [14, 15, 10, 9, 3, 2, 15, 19]
							self.assertListEqual(tokenizer.convert_tokens_to_ids(_A    ),_A    )

					def 				__UpperCamelCase   (    self      :       Optional[int]    ):







							"""simple docstring"""






							if not self.test_rust_tokenizer:
									return

							SCREAMING_SNAKE_CASE_  :		Tuple				      =    self.get_tokenizer()
							SCREAMING_SNAKE_CASE_  :		Any				      =    self.get_rust_tokenizer(add_prefix_space=_A    )

							SCREAMING_SNAKE_CASE_  :		List[str]				      =    "lower newer"

							# Testing tokenization
							SCREAMING_SNAKE_CASE_  :		Optional[Any]				      =    tokenizer.tokenize(_A,add_prefix_space=_A    )
							SCREAMING_SNAKE_CASE_  :		Any				      =    rust_tokenizer.tokenize(_A    )
							self.assertListEqual(_A,_A    )

							# Testing conversion to ids without special tokens
							SCREAMING_SNAKE_CASE_  :		int				      =    tokenizer.encode(_A,add_special_tokens=_A,add_prefix_space=_A    )
							SCREAMING_SNAKE_CASE_  :		Optional[Any]				      =    rust_tokenizer.encode(_A,add_special_tokens=_A    )
							self.assertListEqual(_A,_A    )

							# Testing conversion to ids with special tokens
							SCREAMING_SNAKE_CASE_  :		int				      =    self.get_rust_tokenizer(add_prefix_space=_A    )
							SCREAMING_SNAKE_CASE_  :		int				      =    tokenizer.encode(_A,add_prefix_space=_A    )
							SCREAMING_SNAKE_CASE_  :		Optional[int]				      =    rust_tokenizer.encode(_A    )
							self.assertListEqual(_A,_A    )

							# Testing the unknown token
							SCREAMING_SNAKE_CASE_  :		int				      =    tokens + [rust_tokenizer.unk_token]
							SCREAMING_SNAKE_CASE_  :		Any				      =    [14, 15, 10, 9, 3, 2, 15, 19]
							self.assertListEqual(rust_tokenizer.convert_tokens_to_ids(_A    ),_A    )

					def 				__UpperCamelCase   (    self      :       Dict,*_A      :       Union[str, Any],**_A      :       Optional[int]    ):







							"""simple docstring"""






							pass

					def 				__UpperCamelCase   (    self      :       Dict,_A      :       Any=15    ):







							"""simple docstring"""






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

											# Simple input
											SCREAMING_SNAKE_CASE_  :		Optional[int]				      =    "This is a simple input"
											SCREAMING_SNAKE_CASE_  :		Dict				      =    ["This is a simple input 1", "This is a simple input 2"]
											SCREAMING_SNAKE_CASE_  :		Optional[Any]				      =    ("This is a simple input", "This is a pair")
											SCREAMING_SNAKE_CASE_  :		Union[str, 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 				__UpperCamelCase   (    self      :       Tuple    ):







							"""simple docstring"""






							SCREAMING_SNAKE_CASE_  :		int				      =    CodeGenTokenizer.from_pretrained(self.tmpdirname,pad_token="<pad>"    )

							# Simple input
							SCREAMING_SNAKE_CASE_  :		Any				      =    "This is a simple input"
							SCREAMING_SNAKE_CASE_  :		str				      =    ["This is a simple input looooooooong", "This is a simple input"]
							SCREAMING_SNAKE_CASE_  :		int				      =    ("This is a simple input", "This is a pair")
							SCREAMING_SNAKE_CASE_  :		List[str]				      =    [
							    ("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_  :		Dict				      =    tokenizer.pad_token_id

							SCREAMING_SNAKE_CASE_  :		str				      =    tokenizer(_A,padding="max_length",max_length=30,return_tensors="np"    )
							SCREAMING_SNAKE_CASE_  :		Tuple				      =    tokenizer(_A,padding=_A,truncate=_A,return_tensors="np"    )
							SCREAMING_SNAKE_CASE_  :		Union[str, Any]				      =    tokenizer(*_A,padding="max_length",max_length=60,return_tensors="np"    )
							SCREAMING_SNAKE_CASE_  :		Union[str, 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 				__UpperCamelCase   (    self      :       Union[str, Any]    ):







							"""simple docstring"""






							SCREAMING_SNAKE_CASE_  :		Tuple				      =    "$$$"
							SCREAMING_SNAKE_CASE_  :		str				      =    CodeGenTokenizer.from_pretrained(self.tmpdirname,bos_token=_A,add_bos_token=_A    )

							SCREAMING_SNAKE_CASE_  :		str				      =    "This is a simple input"
							SCREAMING_SNAKE_CASE_  :		Optional[Any]				      =    ["This is a simple input 1", "This is a simple input 2"]

							SCREAMING_SNAKE_CASE_  :		Tuple				      =    tokenizer.bos_token_id

							SCREAMING_SNAKE_CASE_  :		List[Any]				      =    tokenizer(_A    )
							SCREAMING_SNAKE_CASE_  :		Optional[int]				      =    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    )    )

							SCREAMING_SNAKE_CASE_  :		Optional[int]				      =    tokenizer.decode(out_s.input_ids    )
							SCREAMING_SNAKE_CASE_  :		int				      =    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    )    )

					@slow
					def 				__UpperCamelCase   (    self      :       Dict    ):







							"""simple docstring"""






							SCREAMING_SNAKE_CASE_  :		Optional[Any]				      =    CodeGenTokenizer.from_pretrained("Salesforce/codegen-350M-mono"    )

							SCREAMING_SNAKE_CASE_  :		List[str]				      =    "\nif len_a > len_b:\n    result = a\nelse:\n    result = b\n\n\n\n#"
							SCREAMING_SNAKE_CASE_  :		int				      =    "\nif len_a > len_b:      result = a\nelse:      result = b"

							SCREAMING_SNAKE_CASE_  :		Optional[int]				      =    tokenizer.encode(_A    )
							SCREAMING_SNAKE_CASE_  :		Union[str, Any]				      =    ["^#", re.escape("<|endoftext|>"    ), "^'''", "^\"\"\"", "\n\n\n"]
							SCREAMING_SNAKE_CASE_  :		Optional[Any]				      =    tokenizer.decode(_A,truncate_before_pattern=_A    )
							self.assertEqual(_A,_A    )






					def 				__UpperCamelCase   (    self      :       Tuple    ):







							"""simple docstring"""






							pass







"""simple docstring"""





from collections import OrderedDict
from typing import TYPE_CHECKING, Any, List, Mapping, Optional, Union

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import TensorType, logging


if TYPE_CHECKING:
       from ...onnx.config import PatchingSpec
       from ...tokenization_utils_base import PreTrainedTokenizerBase


SCREAMING_SNAKE_CASE__					=   logging.get_logger(__name__)

SCREAMING_SNAKE_CASE__					=   {
    "allenai/longformer-base-4096": "https://huggingface.co/allenai/longformer-base-4096/resolve/main/config.json",
    "allenai/longformer-large-4096": "https://huggingface.co/allenai/longformer-large-4096/resolve/main/config.json",
    "allenai/longformer-large-4096-finetuned-triviaqa": (
        "https://huggingface.co/allenai/longformer-large-4096-finetuned-triviaqa/resolve/main/config.json"
    ),
    "allenai/longformer-base-4096-extra.pos.embd.only": (
        "https://huggingface.co/allenai/longformer-base-4096-extra.pos.embd.only/resolve/main/config.json"
    ),
    "allenai/longformer-large-4096-extra.pos.embd.only": (
        "https://huggingface.co/allenai/longformer-large-4096-extra.pos.embd.only/resolve/main/config.json"
    ),
}

class 		lowercase					(					_UpperCAmelCase					):
      _SCREAMING_SNAKE_CASE					=      'longformer'





      def __init__(       self      ,						lowercase = 512      ,						lowercase = 2      ,						lowercase = 1      ,						lowercase = 0      ,						lowercase = 2      ,						lowercase = 30_522      ,						lowercase = 768      ,						lowercase = 12      ,						lowercase = 12      ,						lowercase = 3_072      ,						lowercase = "gelu"      ,						lowercase = 0.1      ,						lowercase = 0.1      ,						lowercase = 512      ,						lowercase = 2      ,						lowercase = 0.02      ,						lowercase = 1e-12      ,						lowercase = False      ,						**lowercase      ,						)		->     Optional[int]:
            super().__init__(pad_token_id=lowercase      ,						**lowercase )

            lowerCAmelCase  						=       attention_window
            lowerCAmelCase  						=       sep_token_id
            lowerCAmelCase  						=       bos_token_id
            lowerCAmelCase  						=       eos_token_id
            lowerCAmelCase  						=       vocab_size
            lowerCAmelCase  						=       hidden_size
            lowerCAmelCase  						=       num_hidden_layers
            lowerCAmelCase  						=       num_attention_heads
            lowerCAmelCase  						=       hidden_act
            lowerCAmelCase  						=       intermediate_size
            lowerCAmelCase  						=       hidden_dropout_prob
            lowerCAmelCase  						=       attention_probs_dropout_prob
            lowerCAmelCase  						=       max_position_embeddings
            lowerCAmelCase  						=       type_vocab_size
            lowerCAmelCase  						=       initializer_range
            lowerCAmelCase  						=       layer_norm_eps
            lowerCAmelCase  						=       onnx_export







class 		lowercase					(					_UpperCAmelCase					):





      def __init__(       self      ,						lowercase      ,						lowercase = "default"      ,						lowercase = None )		->     Tuple:
            super().__init__(lowercase      ,						lowercase      ,						lowercase )
            lowerCAmelCase  						=       True





      @property
      def     _snake_case			(       self )		->     Mapping[str, Mapping[int, str]]:
            if self.task == "multiple-choice":
                  lowerCAmelCase  						=       {0: """batch""", 1: """choice""", 2: """sequence"""}
            else:
                  lowerCAmelCase  						=       {0: """batch""", 1: """sequence"""}
            return OrderedDict(
                [
                    ("""input_ids""", dynamic_axis),
                    ("""attention_mask""", dynamic_axis),
                    ("""global_attention_mask""", dynamic_axis),
                ] )





      @property
      def     _snake_case			(       self )		->     Mapping[str, Mapping[int, str]]:
            lowerCAmelCase  						=       super().outputs
            if self.task == "default":
                  lowerCAmelCase  						=       {0: """batch"""}
            return outputs





      @property
      def     _snake_case			(       self )		->     float:
            return 1e-4





      @property
      def     _snake_case			(       self )		->     int:
            # needs to be >= 14 to support tril operator
            return max(super().default_onnx_opset      ,						14 )





      def     _snake_case			(       self      ,						lowercase      ,						lowercase = -1      ,						lowercase = -1      ,						lowercase = False      ,						lowercase = None      ,						)		->     Mapping[str, Any]:
            lowerCAmelCase  						=       super().generate_dummy_inputs(
                preprocessor=lowercase      ,						batch_size=lowercase      ,						seq_length=lowercase      ,						is_pair=lowercase      ,						framework=lowercase )
            import torch

            # for some reason, replacing this code by inputs["global_attention_mask"] = torch.randint(2, inputs["input_ids"].shape, dtype=torch.int64)
            # makes the export fail randomly
            lowerCAmelCase  						=       torch.zeros_like(inputs["""input_ids"""] )
            # make every second token global
            lowerCAmelCase  						=       1

            return inputs






