





import json
import os
import unittest

from transformers.models.xlm.tokenization_xlm import VOCAB_FILES_NAMES, XLMTokenizer
from transformers.testing_utils import slow

from ...test_tokenization_common import TokenizerTesterMixin

class 	A_       (a_     ,							unittest.TestCase			):
	UpperCAmelCase__					=			XLMTokenizer
	UpperCAmelCase__					=			False
	def      _lowercase				(    self		):






				'''simple docstring'''







				super().setUp()

				# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
				UpperCAmelCase   		=				[
				    '''l''',
				    '''o''',
				    '''w''',
				    '''e''',
				    '''r''',
				    '''s''',
				    '''t''',
				    '''i''',
				    '''d''',
				    '''n''',
				    '''w</w>''',
				    '''r</w>''',
				    '''t</w>''',
				    '''lo''',
				    '''low''',
				    '''er</w>''',
				    '''low</w>''',
				    '''lowest</w>''',
				    '''newer</w>''',
				    '''wider</w>''',
				    '''<unk>''',
				]
				UpperCAmelCase   		=				dict(zip(_A							,					range(len(_A		)		)		)		)
				UpperCAmelCase   		=				['''l o 123''', '''lo w 1456''', '''e r</w> 1789''', '''''']

				UpperCAmelCase   		=				os.path.join(self.tmpdirname							,					VOCAB_FILES_NAMES['''vocab_file''']		)
				UpperCAmelCase   		=				os.path.join(self.tmpdirname							,					VOCAB_FILES_NAMES['''merges_file''']		)
				with open(self.vocab_file							,					'''w'''		) as fp:
							fp.write(json.dumps(_A		)		)
				with open(self.merges_file							,					'''w'''		) as fp:
							fp.write('''\n'''.join(_A		)		)
	def      _lowercase				(    self							,					_A		):






				'''simple docstring'''







				UpperCAmelCase   		=				'''lower newer'''
				UpperCAmelCase   		=				'''lower newer'''
				return input_text, output_text
	def      _lowercase				(    self		):






				'''simple docstring'''







				UpperCAmelCase   		=				XLMTokenizer(self.vocab_file							,					self.merges_file		)

				UpperCAmelCase   		=				'''lower'''
				UpperCAmelCase   		=				['''low''', '''er</w>''']
				UpperCAmelCase   		=				tokenizer.tokenize(_A		)
				self.assertListEqual(_A							,					_A		)

				UpperCAmelCase   		=				tokens + ['''<unk>''']
				UpperCAmelCase   		=				[1_4, 1_5, 2_0]
				self.assertListEqual(tokenizer.convert_tokens_to_ids(_A		)							,					_A		)







	@slow
	def      _lowercase				(    self		):






				'''simple docstring'''







				UpperCAmelCase   		=				XLMTokenizer.from_pretrained('''xlm-mlm-en-2048'''		)

				UpperCAmelCase   		=				tokenizer.encode('''sequence builders'''							,					add_special_tokens=_A		)
				UpperCAmelCase   		=				tokenizer.encode('''multi-sequence build'''							,					add_special_tokens=_A		)

				UpperCAmelCase   		=				tokenizer.build_inputs_with_special_tokens(_A		)
				UpperCAmelCase   		=				tokenizer.build_inputs_with_special_tokens(_A							,					_A		)

				assert encoded_sentence == [0] + text + [1]
				assert encoded_pair == [0] + text + [1] + text_a + [1]










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


__A				:    Dict       =   logging.get_logger(__name__)

__A				:    str       =   {
    "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 	A_       (a_			):
	UpperCAmelCase__					=			'''longformer'''
	def __init__(    self							,					_A = 5_1_2							,					_A = 2							,					_A = 1							,					_A = 0							,					_A = 2							,					_A = 3_0_5_2_2							,					_A = 7_6_8							,					_A = 1_2							,					_A = 1_2							,					_A = 3_0_7_2							,					_A = "gelu"							,					_A = 0.1							,					_A = 0.1							,					_A = 5_1_2							,					_A = 2							,					_A = 0.02							,					_A = 1E-12							,					_A = False							,					**_A							,					):






				'''simple docstring'''







				super().__init__(pad_token_id=_A							,					**_A		)

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

class 	A_       (a_			):
	def __init__(    self							,					_A							,					_A = "default"							,					_A = None		):






				'''simple docstring'''







				super().__init__(_A							,					_A							,					_A		)
				UpperCAmelCase   		=				True
	@property
	def      _lowercase				(    self		):






				'''simple docstring'''







				if self.task == "multiple-choice":
							UpperCAmelCase   		=				{0: '''batch''', 1: '''choice''', 2: '''sequence'''}
				else:
							UpperCAmelCase   		=				{0: '''batch''', 1: '''sequence'''}
				return OrderedDict(
				    [
				        ('''input_ids''', dynamic_axis),
				        ('''attention_mask''', dynamic_axis),
				        ('''global_attention_mask''', dynamic_axis),
				    ]		)
	@property
	def      _lowercase				(    self		):






				'''simple docstring'''







				UpperCAmelCase   		=				super().outputs
				if self.task == "default":
							UpperCAmelCase   		=				{0: '''batch'''}
				return outputs
	@property
	def      _lowercase				(    self		):






				'''simple docstring'''







				return 1E-4
	@property
	def      _lowercase				(    self		):






				'''simple docstring'''







				return max(super().default_onnx_opset							,					1_4		)







	def      _lowercase				(    self							,					_A							,					_A = -1							,					_A = -1							,					_A = False							,					_A = None							,					):






				'''simple docstring'''







				UpperCAmelCase   		=				super().generate_dummy_inputs(
				    preprocessor=_A							,					batch_size=_A							,					seq_length=_A							,					is_pair=_A							,					framework=_A		)
				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
				UpperCAmelCase   		=				torch.zeros_like(inputs['''input_ids''']		)
				# make every second token global
				UpperCAmelCase   		=				1

				return inputs



