
"""simple docstring"""





import unittest

from transformers import JukeboxTokenizer
from transformers.testing_utils import require_torch


class A_	(unittest.TestCase      ):




  '''simple docstring'''
  SCREAMING_SNAKE_CASE__			:						Tuple       =		JukeboxTokenizer
  SCREAMING_SNAKE_CASE__			:						List[Any]       =		{
      """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        UpperCamelCase__					(		self  ):

     """simple docstring"""
     import torch

     UpperCAmelCase_					:					Optional[Any]			     =    JukeboxTokenizer.from_pretrained("openai/jukebox-1b-lyrics"  )
     UpperCAmelCase_					:					List[Any]			     =    tokenizer(**self.metas  )["input_ids"]
     # fmt: off
     UpperCAmelCase_					:					Dict			     =    [
         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        UpperCamelCase__					(		self  ):

     """simple docstring"""
     import torch

     UpperCAmelCase_					:					str			     =    JukeboxTokenizer.from_pretrained("openai/jukebox-5b-lyrics"  )
     UpperCAmelCase_					:					List[Any]			     =    tokenizer(**self.metas  )["input_ids"]
     # fmt: off
     UpperCAmelCase_					:					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]  )  )




from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_sentencepiece_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


_A   =     {"configuration_xglm": ["XGLM_PRETRAINED_CONFIG_ARCHIVE_MAP", "XGLMConfig"]}

try:
			if not is_sentencepiece_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			_A   =     ["XGLMTokenizer"]

try:
			if not is_tokenizers_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			_A   =     ["XGLMTokenizerFast"]

try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			_A   =     [
			    "XGLM_PRETRAINED_MODEL_ARCHIVE_LIST",
			    "XGLMForCausalLM",
			    "XGLMModel",
			    "XGLMPreTrainedModel",
			]


try:
			if not is_flax_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			_A   =     [
			    "FlaxXGLMForCausalLM",
			    "FlaxXGLMModel",
			    "FlaxXGLMPreTrainedModel",
			]


try:
			if not is_tf_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			_A   =     [
			    "TF_XGLM_PRETRAINED_MODEL_ARCHIVE_LIST",
			    "TFXGLMForCausalLM",
			    "TFXGLMModel",
			    "TFXGLMPreTrainedModel",
			]


if TYPE_CHECKING:
			from .configuration_xglm import XGLM_PRETRAINED_CONFIG_ARCHIVE_MAP, XGLMConfig

			try:
						if not is_sentencepiece_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .tokenization_xglm import XGLMTokenizer

			try:
						if not is_tokenizers_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .tokenization_xglm_fast import XGLMTokenizerFast

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_xglm import XGLM_PRETRAINED_MODEL_ARCHIVE_LIST, XGLMForCausalLM, XGLMModel, XGLMPreTrainedModel

			try:
						if not is_flax_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_flax_xglm import FlaxXGLMForCausalLM, FlaxXGLMModel, FlaxXGLMPreTrainedModel

			try:
						if not is_tf_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_tf_xglm import (
						    TF_XGLM_PRETRAINED_MODEL_ARCHIVE_LIST,
						    TFXGLMForCausalLM,
						    TFXGLMModel,
						    TFXGLMPreTrainedModel,
						)


else:
			import sys

			_A   =     _LazyModule(__name__, globals()["__file__"], _import_structure)



