


"""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 Mapping

from packaging import version

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


SCREAMING_SNAKE_CASE :    Dict									=				logging.get_logger(__name__)

SCREAMING_SNAKE_CASE :    Optional[int]									=				{
    """hustvl/yolos-small""": """https://huggingface.co/hustvl/yolos-small/resolve/main/config.json""",
    # See all YOLOS models at https://huggingface.co/models?filter=yolos
}



class 			_UpperCAmelCase (							__snake_case				):






		'''simple docstring'''

		lowerCamelCase__				='yolos'



		def __init__(self				,       a_=7_68				,       a_=12				,       a_=12				,       a_=30_72				,       a_="gelu"				,       a_=0.0				,       a_=0.0				,       a_=0.02				,       a_=1E-12				,       a_=[5_12, 8_64]				,       a_=16				,       a_=3				,       a_=True				,       a_=1_00				,       a_=True				,       a_=False				,       a_=1				,       a_=5				,       a_=2				,       a_=5				,       a_=2				,       a_=0.1				,       **a_				,       ):





			'''simple docstring'''

			super().__init__(**a_					)

			__snake_case	:						Union[str, Any]						=				hidden_size
			__snake_case	:						Union[str, Any]						=				num_hidden_layers
			__snake_case	:						Dict						=				num_attention_heads
			__snake_case	:						str						=				intermediate_size
			__snake_case	:						List[str]						=				hidden_act
			__snake_case	:						Tuple						=				hidden_dropout_prob
			__snake_case	:						Optional[int]						=				attention_probs_dropout_prob
			__snake_case	:						Union[str, Any]						=				initializer_range
			__snake_case	:						Tuple						=				layer_norm_eps
			__snake_case	:						List[Any]						=				image_size
			__snake_case	:						Tuple						=				patch_size
			__snake_case	:						str						=				num_channels
			__snake_case	:						Tuple						=				qkv_bias
			__snake_case	:						Union[str, Any]						=				num_detection_tokens
			__snake_case	:						List[str]						=				use_mid_position_embeddings
			__snake_case	:						Tuple						=				auxiliary_loss
			# Hungarian matcher
			__snake_case	:						List[str]						=				class_cost
			__snake_case	:						int						=				bbox_cost
			__snake_case	:						int						=				giou_cost
			# Loss coefficients
			__snake_case	:						Optional[int]						=				bbox_loss_coefficient
			__snake_case	:						List[str]						=				giou_loss_coefficient
			__snake_case	:						List[Any]						=				eos_coefficient



class 			_UpperCAmelCase (							__snake_case				):






		'''simple docstring'''

		lowerCamelCase__				=version.parse('1.11'				)



		@property
		def 				SCREAMING_SNAKE_CASE  (self					):





			'''simple docstring'''

			return OrderedDict(
			    [
			        ('''pixel_values''', {0: '''batch''', 1: '''num_channels''', 2: '''height''', 3: '''width'''}),
			    ]					)



		@property
		def 				SCREAMING_SNAKE_CASE  (self					):





			'''simple docstring'''

			return 1E-4



		@property
		def 				SCREAMING_SNAKE_CASE  (self					):





			'''simple docstring'''

			return 12





