


"""simple docstring"""
import unittest

from transformers import JukeboxTokenizer
from transformers.testing_utils import require_torch



class 			_UpperCAmelCase (							unittest.TestCase				):






		'''simple docstring'''

		lowerCamelCase__				=JukeboxTokenizer
		lowerCamelCase__				={
		    'artist': 'Zac Brown Band',
		    'genres': 'Country',
		    'lyrics': 'I met a traveller from an antique land,\n        Who said "Two vast and trunkless legs of stone\n        Stand in the desert. . . . Near them, on the sand,\n        Half sunk a shattered visage lies, whose frown,\n        And wrinkled lip, and sneer of cold command,\n        Tell that its sculptor well those passions read\n        Which yet survive, stamped on these lifeless things,\n        The hand that mocked them, and the heart that fed;\n        And on the pedestal, these words appear:\n        My name is Ozymandias, King of Kings;\n        Look on my Works, ye Mighty, and despair!\n        Nothing beside remains. Round the decay\n        Of that colossal Wreck, boundless and bare\n        The lone and level sands stretch far away\n        ',
		}



		@require_torch
		def 				SCREAMING_SNAKE_CASE  (self					):





			'''simple docstring'''

			import torch

			__snake_case	:						str						=				JukeboxTokenizer.from_pretrained('''openai/jukebox-1b-lyrics'''					)
			__snake_case	:						List[Any]						=				tokenizer(**self.metas					)['''input_ids''']
			# fmt: off
			__snake_case	:						Optional[int]						=				[
			    torch.tensor([[
			        0, 0, 0, 71_69, 5_07, 9, 76, 39, 31, 46, 76, 27,
			        76, 46, 44, 27, 48, 31, 38, 38, 31, 44, 76, 32,
			        44, 41, 39, 76, 27, 40, 76, 27, 40, 46, 35, 43,
			        47, 31, 76, 38, 27, 40, 30, 64, 78, 76, 76, 76,
			        76, 76, 76, 76, 76, 23, 34, 41, 76, 45, 27, 35,
			        30, 76, 71, 20, 49, 41, 76, 48, 27, 45, 46, 76,
			        27, 40, 30, 76, 46, 44, 47, 40, 37, 38, 31, 45,
			        45, 76, 38, 31, 33, 45, 76, 41, 32, 76, 45, 46,
			        41, 40, 31, 78, 76, 76, 76, 76, 76, 76, 76, 76,
			        19, 46, 27, 40, 30, 76, 35, 40, 76, 46, 34, 31,
			        76, 30, 31, 45, 31, 44, 46, 63, 76, 63, 76, 63,
			        76, 63, 76, 14, 31, 27, 44, 76, 46, 34, 31, 39,
			        64, 76, 41, 40, 76, 46, 34, 31, 76, 45, 27, 40,
			        30, 64, 78, 76, 76, 76, 76, 76, 76, 76, 76, 8,
			        27, 38, 32, 76, 45, 47, 40, 37, 76, 27, 76, 45,
			        34, 27, 46, 46, 31, 44, 31, 30, 76, 48, 35, 45,
			        27, 33, 31, 76, 38, 35, 31, 45, 64, 76, 49, 34,
			        41, 45, 31, 76, 32, 44, 41, 49, 40, 64, 78, 76,
			        76, 76, 76, 76, 76, 76, 76, 1, 40, 30, 76, 49,
			        44, 35, 40, 37, 38, 31, 30, 76, 38, 35, 42, 64,
			        76, 27, 40, 30, 76, 45, 40, 31, 31, 44, 76, 41,
			        32, 76, 29, 41, 38, 30, 76, 29, 41, 39, 39, 27,
			        40, 30, 64, 78, 76, 76, 76, 76, 76, 76, 76, 76,
			        20, 31, 38, 38, 76, 46, 34, 27, 46, 76, 35, 46,
			        45, 76, 45, 29, 47, 38, 42, 46, 41, 44, 76, 49,
			        31, 38, 38, 76, 46, 34, 41, 45, 31, 76, 42, 27,
			        45, 45, 35, 41, 40, 45, 76, 44, 31, 27, 30, 78,
			        76, 76, 76, 76, 76, 76, 76, 76, 23, 34, 35, 29,
			        34, 76, 51, 31, 46, 76, 45, 47, 44, 48, 35, 48,
			        31, 64, 76, 45, 46, 27, 39, 42, 31, 30, 76, 41,
			        40, 76, 46, 34, 31, 45, 31, 76, 38, 35, 32, 31,
			        38, 31, 45, 45, 76, 46, 34, 35, 40, 33, 45, 64,
			        78, 76, 76, 76, 76, 76, 76, 76, 76, 20, 34, 31,
			        76, 34, 27, 40, 30, 76, 46, 34, 27, 46, 76, 39,
			        41, 29, 37, 31, 30, 76, 46, 34, 31, 39, 64, 76,
			        27, 40, 30, 76, 46, 34, 31, 76, 34, 31, 27, 44,
			        46, 76, 46, 34, 27, 46, 76, 32, 31, 30, 66, 78,
			        76, 76, 76, 76, 76, 76, 76, 76, 1, 40, 30, 76,
			        41, 40, 76, 46, 34, 31, 76, 42, 31, 30, 31, 45,
			        46, 27, 38, 64, 76, 46, 34, 31, 45, 31, 76, 49,
			        41, 44, 30, 45, 76, 27, 42, 42, 31, 27, 44, 65,
			        78, 76, 76, 76, 76, 76, 76, 76, 76, 13, 51, 76,
			        40, 27, 39, 31, 76, 35, 45, 76, 15, 52, 51, 39,
			        27, 40, 30, 35, 27, 45, 64, 76, 11, 35, 40, 33,
			        76, 41, 32, 76, 11, 35, 40, 33, 45, 66, 78, 76,
			        76, 76, 76, 76, 76, 76, 76, 12, 41, 41, 37, 76,
			        41, 40, 76, 39, 51, 76, 23, 41, 44, 37, 45, 64,
			        76, 51, 31, 76, 13, 35, 33, 34, 46, 51, 64, 76,
			        27, 40, 30, 76, 30, 31, 45, 42, 27, 35, 44, 67,
			        78, 76, 76, 76, 76, 76, 76, 76, 76, 14, 41, 46,
			        34, 35, 40, 33, 76, 28, 31, 45, 35, 30, 31, 76,
			        44, 31, 39, 27, 35, 40, 45, 63, 76, 18, 41, 47,
			        40, 30, 76, 46, 34, 31, 76, 30, 31, 29, 27, 51,
			        78, 76, 76, 76, 76, 76, 76, 76, 76, 15, 32, 76,
			        46, 34, 27, 46, 76, 29, 41, 38, 41, 45, 45, 27,
			        38, 76, 23, 44, 31, 29, 37, 64, 76, 28, 41, 47,
			        40, 30, 38, 31, 45, 45, 76, 27, 40, 30, 76, 28,
			        27, 44, 31, 78, 76, 76, 76, 76, 76, 76, 76, 76,
			        20, 34, 31, 76, 38, 41, 40, 31, 76, 27, 40, 30,
			        76, 38, 31, 48, 31, 38, 76, 45, 27, 40, 30, 45,
			        76, 45, 46, 44, 31, 46, 29, 34, 76, 32, 27, 44,
			        76, 27, 49, 27, 51, 78, 76, 76, 76, 76, 76, 76,
			        76, 76]]					),
			    torch.tensor([[0, 0, 0, 10_69, 11]]					),
			    torch.tensor([[0, 0, 0, 10_69, 11]]					),
			]
			# fmt: on
			self.assertTrue(torch.allclose(tokens[0]				,       EXPECTED_OUTPUT[0]					)					)
			self.assertTrue(torch.allclose(tokens[1]				,       EXPECTED_OUTPUT[1]					)					)
			self.assertTrue(torch.allclose(tokens[2]				,       EXPECTED_OUTPUT[2]					)					)



		@require_torch
		def 				SCREAMING_SNAKE_CASE  (self					):





			'''simple docstring'''

			import torch

			__snake_case	:						List[Any]						=				JukeboxTokenizer.from_pretrained('''openai/jukebox-5b-lyrics'''					)
			__snake_case	:						Optional[int]						=				tokenizer(**self.metas					)['''input_ids''']
			# fmt: off
			__snake_case	:						Any						=				[
			    torch.tensor([[
			        0, 0, 0, 10_69, 11, -1, -1, -1, -1, 9, 77, 39,
			        31, 46, 77, 27, 77, 46, 44, 27, 48, 31, 38, 38,
			        31, 44, 77, 32, 44, 41, 39, 77, 27, 40, 77, 27,
			        40, 46, 35, 43, 47, 31, 77, 38, 27, 40, 30, 64,
			        79, 77, 77, 77, 77, 77, 77, 77, 77, 23, 34, 41,
			        77, 45, 27, 35, 30, 77, 72, 20, 49, 41, 77, 48,
			        27, 45, 46, 77, 27, 40, 30, 77, 46, 44, 47, 40,
			        37, 38, 31, 45, 45, 77, 38, 31, 33, 45, 77, 41,
			        32, 77, 45, 46, 41, 40, 31, 79, 77, 77, 77, 77,
			        77, 77, 77, 77, 19, 46, 27, 40, 30, 77, 35, 40,
			        77, 46, 34, 31, 77, 30, 31, 45, 31, 44, 46, 63,
			        77, 63, 77, 63, 77, 63, 77, 14, 31, 27, 44, 77,
			        46, 34, 31, 39, 64, 77, 41, 40, 77, 46, 34, 31,
			        77, 45, 27, 40, 30, 64, 79, 77, 77, 77, 77, 77,
			        77, 77, 77, 8, 27, 38, 32, 77, 45, 47, 40, 37,
			        77, 27, 77, 45, 34, 27, 46, 46, 31, 44, 31, 30,
			        77, 48, 35, 45, 27, 33, 31, 77, 38, 35, 31, 45,
			        64, 77, 49, 34, 41, 45, 31, 77, 32, 44, 41, 49,
			        40, 64, 79, 77, 77, 77, 77, 77, 77, 77, 77, 1,
			        40, 30, 77, 49, 44, 35, 40, 37, 38, 31, 30, 77,
			        38, 35, 42, 64, 77, 27, 40, 30, 77, 45, 40, 31,
			        31, 44, 77, 41, 32, 77, 29, 41, 38, 30, 77, 29,
			        41, 39, 39, 27, 40, 30, 64, 79, 77, 77, 77, 77,
			        77, 77, 77, 77, 20, 31, 38, 38, 77, 46, 34, 27,
			        46, 77, 35, 46, 45, 77, 45, 29, 47, 38, 42, 46,
			        41, 44, 77, 49, 31, 38, 38, 77, 46, 34, 41, 45,
			        31, 77, 42, 27, 45, 45, 35, 41, 40, 45, 77, 44,
			        31, 27, 30, 79, 77, 77, 77, 77, 77, 77, 77, 77,
			        23, 34, 35, 29, 34, 77, 51, 31, 46, 77, 45, 47,
			        44, 48, 35, 48, 31, 64, 77, 45, 46, 27, 39, 42,
			        31, 30, 77, 41, 40, 77, 46, 34, 31, 45, 31, 77,
			        38, 35, 32, 31, 38, 31, 45, 45, 77, 46, 34, 35,
			        40, 33, 45, 64, 79, 77, 77, 77, 77, 77, 77, 77,
			        77, 20, 34, 31, 77, 34, 27, 40, 30, 77, 46, 34,
			        27, 46, 77, 39, 41, 29, 37, 31, 30, 77, 46, 34,
			        31, 39, 64, 77, 27, 40, 30, 77, 46, 34, 31, 77,
			        34, 31, 27, 44, 46, 77, 46, 34, 27, 46, 77, 32,
			        31, 30, 66, 79, 77, 77, 77, 77, 77, 77, 77, 77,
			        1, 40, 30, 77, 41, 40, 77, 46, 34, 31, 77, 42,
			        31, 30, 31, 45, 46, 27, 38, 64, 77, 46, 34, 31,
			        45, 31, 77, 49, 41, 44, 30, 45, 77, 27, 42, 42,
			        31, 27, 44, 65, 79, 77, 77, 77, 77, 77, 77, 77,
			        77, 13, 51, 77, 40, 27, 39, 31, 77, 35, 45, 77,
			        15, 52, 51, 39, 27, 40, 30, 35, 27, 45, 64, 77,
			        11, 35, 40, 33, 77, 41, 32, 77, 11, 35, 40, 33,
			        45, 66, 79, 77, 77, 77, 77, 77, 77, 77, 77, 12,
			        41, 41, 37, 77, 41, 40, 77, 39, 51, 77, 23, 41,
			        44, 37, 45, 64, 77, 51, 31, 77, 13, 35, 33, 34,
			        46, 51, 64, 77, 27, 40, 30, 77, 30, 31, 45, 42,
			        27, 35, 44, 67, 79, 77, 77, 77, 77, 77, 77, 77,
			        77, 14, 41, 46, 34, 35, 40, 33, 77, 28, 31, 45,
			        35, 30, 31, 77, 44, 31, 39, 27, 35, 40, 45, 63,
			        77, 18, 41, 47, 40, 30, 77, 46, 34, 31, 77, 30,
			        31, 29, 27, 51, 79, 77, 77, 77, 77, 77, 77, 77,
			        77, 15, 32, 77, 46, 34, 27, 46, 77, 29, 41, 38,
			        41, 45, 45, 27, 38, 77, 23, 44, 31, 29, 37, 64,
			        77, 28, 41, 47, 40, 30, 38, 31, 45, 45, 77, 27,
			        40, 30, 77, 28, 27, 44, 31, 79, 77, 77, 77, 77,
			        77, 77, 77, 77, 20, 34, 31, 77, 38, 41, 40, 31,
			        77, 27, 40, 30, 77, 38, 31, 48, 31, 38, 77, 45,
			        27, 40, 30, 45, 77, 45, 46, 44, 31, 46, 29, 34,
			        77, 32, 27, 44, 77, 27, 49, 27, 51, 79, 77, 77,
			        77, 77, 77, 77, 77, 77]]					),
			    torch.tensor([[0, 0, 0, 10_69, 11, -1, -1, -1, -1]]					),
			    torch.tensor([[0, 0, 0, 10_69, 11, -1, -1, -1, -1]]					),
			]
			# fmt: on
			self.assertTrue(torch.allclose(tokens[0]				,       EXPECTED_OUTPUT[0]					)					)
			self.assertTrue(torch.allclose(tokens[1]				,       EXPECTED_OUTPUT[1]					)					)
			self.assertTrue(torch.allclose(tokens[2]				,       EXPECTED_OUTPUT[2]					)					)










'''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


A_							: Any						 =	logging.get_logger(__name__)

A_							: Optional[int]						 =	{
    """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       (  _lowerCamelCase				):


 """simple docstring"""


 UpperCAmelCase							=  """longformer"""







 def __init__(							self  ,a_ = 512  ,a_ = 2  ,a_ = 1  ,a_ = 0  ,a_ = 2  ,a_ = 30_522  ,a_ = 768  ,a_ = 12  ,a_ = 12  ,a_ = 3_072  ,a_ = "gelu"  ,a_ = 0.1  ,a_ = 0.1  ,a_ = 512  ,a_ = 2  ,a_ = 0.02  ,a_ = 1E-1_2  ,a_ = False  ,**a_  ,)		->   List[Any]:
        super().__init__(pad_token_id=a_  ,**a_							)

        _UpperCAmelCase  :						List[Any]			     = attention_window
        _UpperCAmelCase  :						Any			     = sep_token_id
        _UpperCAmelCase  :						Dict			     = bos_token_id
        _UpperCAmelCase  :						Tuple			     = eos_token_id
        _UpperCAmelCase  :						Tuple			     = vocab_size
        _UpperCAmelCase  :						Optional[Any]			     = hidden_size
        _UpperCAmelCase  :						Optional[int]			     = num_hidden_layers
        _UpperCAmelCase  :						Union[str, Any]			     = num_attention_heads
        _UpperCAmelCase  :						Optional[int]			     = hidden_act
        _UpperCAmelCase  :						str			     = intermediate_size
        _UpperCAmelCase  :						List[Any]			     = hidden_dropout_prob
        _UpperCAmelCase  :						Union[str, Any]			     = attention_probs_dropout_prob
        _UpperCAmelCase  :						List[str]			     = max_position_embeddings
        _UpperCAmelCase  :						Optional[int]			     = type_vocab_size
        _UpperCAmelCase  :						Any			     = initializer_range
        _UpperCAmelCase  :						Optional[int]			     = layer_norm_eps
        _UpperCAmelCase  :						Union[str, Any]			     = onnx_export







class 							lowercase       (  _lowerCamelCase				):


 """simple docstring"""


 def __init__(							self  ,a_  ,a_ = "default"  ,a_ = None							)		->   int:
        super().__init__(a_  ,a_  ,a_							)
        _UpperCAmelCase  :						Tuple			     = True







 @property
 def _snake_case (							self							)		->   Mapping[str, Mapping[int, str]]:
        if self.task == "multiple-choice":
               _UpperCAmelCase  :						Optional[int]			     = {0: """batch""", 1: """choice""", 2: """sequence"""}
        else:
               _UpperCAmelCase  :						Tuple			     = {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]]:
        _UpperCAmelCase  :						str			     = super().outputs
        if self.task == "default":
               _UpperCAmelCase  :						int			     = {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  ,a_  ,a_ = -1  ,a_ = -1  ,a_ = False  ,a_ = None  ,)		->   Mapping[str, Any]:
        _UpperCAmelCase  :						List[str]			     = 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  :						int			     = torch.zeros_like(inputs["""input_ids"""]							)
        # make every second token global
        _UpperCAmelCase  :						List[str]			     = 1

        return inputs



