


import unittest

from transformers import JukeboxTokenizer
from transformers.testing_utils import require_torch


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




					@require_torch
					def 			snake_case__  ( self):
								import torch

								UpperCAmelCase__					:   str       				=       JukeboxTokenizer.from_pretrained("""openai/jukebox-1b-lyrics""")
								UpperCAmelCase__					:   Optional[int]       				=       tokenizer(**self.metas)["""input_ids"""]
								# fmt: off
								UpperCAmelCase__					:   Optional[Any]       				=       [
								    torch.tensor([[
								        0, 0, 0, 7169, 507, 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, 1069, 11]]),
								    torch.tensor([[0, 0, 0, 1069, 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 			snake_case__  ( self):
								import torch

								UpperCAmelCase__					:   List[str]       				=       JukeboxTokenizer.from_pretrained("""openai/jukebox-5b-lyrics""")
								UpperCAmelCase__					:   Union[str, Any]       				=       tokenizer(**self.metas)["""input_ids"""]
								# fmt: off
								UpperCAmelCase__					:   List[Any]       				=       [
								    torch.tensor([[
								        0, 0, 0, 1069, 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, 1069, 11, -1, -1, -1, -1]]),
								    torch.tensor([[0, 0, 0, 1069, 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'''



import unittest

import numpy as np

from transformers import RoFormerConfig, is_flax_available
from transformers.testing_utils import require_flax, slow

from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask


if is_flax_available():
		import jax.numpy as jnp

		from transformers.models.roformer.modeling_flax_roformer import (
		    FlaxRoFormerForMaskedLM,
		    FlaxRoFormerForMultipleChoice,
		    FlaxRoFormerForQuestionAnswering,
		    FlaxRoFormerForSequenceClassification,
		    FlaxRoFormerForTokenClassification,
		    FlaxRoFormerModel,
		)


class 						_snake_case   (       unittest.TestCase		):




					def __init__( self							,							_lowerCamelCase							,							_lowerCamelCase=13							,							_lowerCamelCase=7							,							_lowerCamelCase=True							,							_lowerCamelCase=True							,							_lowerCamelCase=True							,							_lowerCamelCase=True							,							_lowerCamelCase=99							,							_lowerCamelCase=32							,							_lowerCamelCase=5							,							_lowerCamelCase=4							,							_lowerCamelCase=37							,							_lowerCamelCase="gelu"							,							_lowerCamelCase=0.1							,							_lowerCamelCase=0.1							,							_lowerCamelCase=512							,							_lowerCamelCase=16							,							_lowerCamelCase=2							,							_lowerCamelCase=0.02							,							_lowerCamelCase=4							,							):
								UpperCAmelCase__					:   Union[str, Any]       				=       parent
								UpperCAmelCase__					:   str       				=       batch_size
								UpperCAmelCase__					:   Tuple       				=       seq_length
								UpperCAmelCase__					:   Any       				=       is_training
								UpperCAmelCase__					:   Tuple       				=       use_attention_mask
								UpperCAmelCase__					:   Optional[Any]       				=       use_token_type_ids
								UpperCAmelCase__					:   Optional[Any]       				=       use_labels
								UpperCAmelCase__					:   str       				=       vocab_size
								UpperCAmelCase__					:   Dict       				=       hidden_size
								UpperCAmelCase__					:   int       				=       num_hidden_layers
								UpperCAmelCase__					:   Optional[int]       				=       num_attention_heads
								UpperCAmelCase__					:   Optional[int]       				=       intermediate_size
								UpperCAmelCase__					:   Tuple       				=       hidden_act
								UpperCAmelCase__					:   Optional[Any]       				=       hidden_dropout_prob
								UpperCAmelCase__					:   Union[str, Any]       				=       attention_probs_dropout_prob
								UpperCAmelCase__					:   List[Any]       				=       max_position_embeddings
								UpperCAmelCase__					:   Optional[int]       				=       type_vocab_size
								UpperCAmelCase__					:   str       				=       type_sequence_label_size
								UpperCAmelCase__					:   Optional[int]       				=       initializer_range
								UpperCAmelCase__					:   str       				=       num_choices




					def 			snake_case__  ( self):
								UpperCAmelCase__					:   List[str]       				=       ids_tensor([self.batch_size, self.seq_length]							,							self.vocab_size)

								UpperCAmelCase__					:   Union[str, Any]       				=       None
								if self.use_attention_mask:
											UpperCAmelCase__					:   Tuple       				=       random_attention_mask([self.batch_size, self.seq_length])

								UpperCAmelCase__					:   Dict       				=       None
								if self.use_token_type_ids:
											UpperCAmelCase__					:   Any       				=       ids_tensor([self.batch_size, self.seq_length]							,							self.type_vocab_size)

								UpperCAmelCase__					:   Optional[Any]       				=       RoFormerConfig(
								    vocab_size=self.vocab_size							,							hidden_size=self.hidden_size							,							num_hidden_layers=self.num_hidden_layers							,							num_attention_heads=self.num_attention_heads							,							intermediate_size=self.intermediate_size							,							hidden_act=self.hidden_act							,							hidden_dropout_prob=self.hidden_dropout_prob							,							attention_probs_dropout_prob=self.attention_probs_dropout_prob							,							max_position_embeddings=self.max_position_embeddings							,							type_vocab_size=self.type_vocab_size							,							is_decoder=_lowerCamelCase							,							initializer_range=self.initializer_range							,							)

								return config, input_ids, token_type_ids, attention_mask




					def 			snake_case__  ( self):
								UpperCAmelCase__					:   List[Any]       				=       self.prepare_config_and_inputs()
								UpperCAmelCase__				,    UpperCAmelCase__				,    UpperCAmelCase__				,    UpperCAmelCase__					:   Optional[Any]       				=       config_and_inputs
								UpperCAmelCase__					:   Dict       				=       {"""input_ids""": input_ids, """token_type_ids""": token_type_ids, """attention_mask""": attention_mask}
								return config, inputs_dict


@require_flax
class 						_snake_case   (       a__    ,				unittest.TestCase		):
					lowerCAmelCase :Optional[int]						=   True

					lowerCAmelCase :Any						=   (
					    (
					        FlaxRoFormerModel,
					        FlaxRoFormerForMaskedLM,
					        FlaxRoFormerForSequenceClassification,
					        FlaxRoFormerForTokenClassification,
					        FlaxRoFormerForMultipleChoice,
					        FlaxRoFormerForQuestionAnswering,
					    )
					    if is_flax_available()
					    else ()
					)




					def 			snake_case__  ( self):
								UpperCAmelCase__					:   List[str]       				=       FlaxRoFormerModelTester(self)




					@slow
					def 			snake_case__  ( self):
								for model_class_name in self.all_model_classes:
											UpperCAmelCase__					:   List[str]       				=       model_class_name.from_pretrained("""junnyu/roformer_chinese_small"""							,							from_pt=_lowerCamelCase)
											UpperCAmelCase__					:   Dict       				=       model(np.ones((1, 1)))
											self.assertIsNotNone(_lowerCamelCase)


@require_flax
class 						_snake_case   (       unittest.TestCase		):




					@slow
					def 			snake_case__  ( self):
								UpperCAmelCase__					:   Any       				=       FlaxRoFormerForMaskedLM.from_pretrained("""junnyu/roformer_chinese_base""")
								UpperCAmelCase__					:   int       				=       jnp.array([[0, 1, 2, 3, 4, 5]])
								UpperCAmelCase__					:   Optional[int]       				=       model(_lowerCamelCase)[0]

								UpperCAmelCase__					:   Union[str, Any]       				=       5_0000

								UpperCAmelCase__					:   Any       				=       (1, 6, vocab_size)
								self.assertEqual(output.shape							,							_lowerCamelCase)

								UpperCAmelCase__					:   Union[str, Any]       				=       jnp.array(
								    [[[-0.1205, -1.0265, 0.2922], [-1.5134, 0.1974, 0.1519], [-5.0135, -3.9003, -0.8404]]])

								self.assertTrue(jnp.allclose(output[:, :3, :3]							,							_lowerCamelCase							,							atol=1e-4))