



"""simple docstring"""





import unittest

from transformers import JukeboxTokenizer
from transformers.testing_utils import require_torch
class    lowercase__     (					unittest.TestCase   ):
       UpperCamelCase		=  JukeboxTokenizer
       UpperCamelCase		=  {
           '''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   lowercase__       (							self    :						int					)				->		int:


             '''simple docstring'''




             import torch

             UpperCAmelCase_    				=							JukeboxTokenizer.from_pretrained("openai/jukebox-1b-lyrics"					)
             UpperCAmelCase_    				=							tokenizer(**self.metas					)["input_ids"]
             # fmt: off
             UpperCAmelCase_    				=							[
                 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   lowercase__       (							self    :						Tuple					)				->		Optional[int]:


             '''simple docstring'''




             import torch

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





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


lowerCamelCase      =		logging.get_logger(__name__)

lowerCamelCase      =		{
    """google/mobilenet_v1_1.0_224""": """https://huggingface.co/google/mobilenet_v1_1.0_224/resolve/main/config.json""",
    """google/mobilenet_v1_0.75_192""": """https://huggingface.co/google/mobilenet_v1_0.75_192/resolve/main/config.json""",
    # See all MobileNetV1 models at https://huggingface.co/models?filter=mobilenet_v1
}
class    lowercase__     (					SCREAMING_SNAKE_CASE   ):







       '''simple docstring'''


       UpperCamelCase		=  '''mobilenet_v1'''



       def __init__(							self    :						Tuple	,       _UpperCAmelCase    :						int=3	,       _UpperCAmelCase    :						Union[str, Any]=224	,       _UpperCAmelCase    :						Any=1.0	,       _UpperCAmelCase    :						Any=8	,       _UpperCAmelCase    :						List[Any]="relu6"	,       _UpperCAmelCase    :						List[str]=True	,       _UpperCAmelCase    :						Dict=0.999	,       _UpperCAmelCase    :						List[Any]=0.02	,       _UpperCAmelCase    :						List[Any]=0.001	,       **_UpperCAmelCase    :						str	,       )				->		Optional[int]:


             '''simple docstring'''




             super().__init__(**_UpperCAmelCase					)

             if depth_multiplier <= 0:
                   raise ValueError("depth_multiplier must be greater than zero."					)

             UpperCAmelCase_    				=							num_channels
             UpperCAmelCase_    				=							image_size
             UpperCAmelCase_    				=							depth_multiplier
             UpperCAmelCase_    				=							min_depth
             UpperCAmelCase_    				=							hidden_act
             UpperCAmelCase_    				=							tf_padding
             UpperCAmelCase_    				=							classifier_dropout_prob
             UpperCAmelCase_    				=							initializer_range
             UpperCAmelCase_    				=							layer_norm_eps



class    lowercase__     (					SCREAMING_SNAKE_CASE   ):







       '''simple docstring'''


       UpperCamelCase		=  version.parse('''1.11'''   )



       @property
       def   lowercase__       (							self    :						List[Any]					)				->		Mapping[str, Mapping[int, str]]:


             '''simple docstring'''




             return OrderedDict([("pixel_values", {0: "batch"})]					)



       @property
       def   lowercase__       (							self    :						List[Any]					)				->		Mapping[str, Mapping[int, str]]:


             '''simple docstring'''




             if self.task == "image-classification":
                   return OrderedDict([("logits", {0: "batch"})]					)
             else:
                   return OrderedDict([("last_hidden_state", {0: "batch"}), ("pooler_output", {0: "batch"})]					)







       @property
       def   lowercase__       (							self    :						Tuple					)				->		float:


             '''simple docstring'''




             return 1e-4




