import copy

from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto.configuration_auto import AutoConfig


__a  :					Union[str, Any]          =  logging.get_logger(__name__)

__a  :					Optional[Any]          =  {
    """facebook/musicgen-small""": """https://huggingface.co/facebook/musicgen-small/resolve/main/config.json""",
    # See all Musicgen models at https://huggingface.co/models?filter=musicgen
}




class        _UpperCamelCase				(						_UpperCAmelCase			):


			"""simple docstring"""






			__a  :			int      			=						'''musicgen_decoder'''
			__a  :			Optional[int]      			=						['''past_key_values''']





			def __init__(       self				,       lowerCAmelCase__=20_48				,       lowerCAmelCase__=20_48				,       lowerCAmelCase__=24				,       lowerCAmelCase__=40_96				,       lowerCAmelCase__=16				,       lowerCAmelCase__=0.0				,       lowerCAmelCase__=True				,       lowerCAmelCase__="gelu"				,       lowerCAmelCase__=10_24				,       lowerCAmelCase__=0.1				,       lowerCAmelCase__=0.0				,       lowerCAmelCase__=0.0				,       lowerCAmelCase__=0.02				,       lowerCAmelCase__=False				,       lowerCAmelCase__=4				,       lowerCAmelCase__=20_48				,       lowerCAmelCase__=20_48				,       lowerCAmelCase__=None				,       lowerCAmelCase__=False				,       **lowerCAmelCase__				,       )					-> List[str]:

							'''simple docstring'''


							__lowercase			      =							vocab_size
							__lowercase			      =							max_position_embeddings
							__lowercase			      =							hidden_size
							__lowercase			      =							ffn_dim
							__lowercase			      =							num_hidden_layers
							__lowercase			      =							num_attention_heads
							__lowercase			      =							dropout
							__lowercase			      =							attention_dropout
							__lowercase			      =							activation_dropout
							__lowercase			      =							activation_function
							__lowercase			      =							initializer_factor
							__lowercase			      =							layerdrop
							__lowercase			      =							use_cache
							__lowercase			      =							scale_embedding  # scale factor will be sqrt(d_model) if True
							__lowercase			      =							num_codebooks
							super().__init__(
							    pad_token_id=lowerCAmelCase__				,       bos_token_id=lowerCAmelCase__				,       eos_token_id=lowerCAmelCase__				,       tie_word_embeddings=lowerCAmelCase__				,       **lowerCAmelCase__				,       )




class        _UpperCamelCase				(						_UpperCAmelCase			):


			"""simple docstring"""






			__a  :			Optional[int]      			=						'''musicgen'''
			__a  :			Any      			=						True





			def __init__(       self				,       **lowerCAmelCase__						)					-> Union[str, Any]:

							'''simple docstring'''


							super().__init__(**lowerCAmelCase__						)
							if "text_encoder" not in kwargs or "audio_encoder" not in kwargs or "decoder" not in kwargs:
											raise ValueError('''Config has to be initialized with text_encoder, audio_encoder and decoder config'''						)

							__lowercase			      =							kwargs.pop('''text_encoder'''						)
							__lowercase			      =							text_encoder_config.pop('''model_type'''						)

							__lowercase			      =							kwargs.pop('''audio_encoder'''						)
							__lowercase			      =							audio_encoder_config.pop('''model_type'''						)

							__lowercase			      =							kwargs.pop('''decoder'''						)

							__lowercase			      =							AutoConfig.for_model(lowerCAmelCase__				,       **lowerCAmelCase__						)
							__lowercase			      =							AutoConfig.for_model(lowerCAmelCase__				,       **lowerCAmelCase__						)
							__lowercase			      =							MusicgenDecoderConfig(**lowerCAmelCase__						)
							__lowercase			      =							True





			@classmethod
			def 	_SCREAMING_SNAKE_CASE      (       cls				,       lowerCAmelCase__				,       lowerCAmelCase__				,       lowerCAmelCase__				,       **lowerCAmelCase__				,       )					-> Tuple:

							'''simple docstring'''


							return cls(
							    text_encoder=text_encoder_config.to_dict()				,       audio_encoder=audio_encoder_config.to_dict()				,       decoder=decoder_config.to_dict()				,       **lowerCAmelCase__				,       )





			def 	_SCREAMING_SNAKE_CASE      (       self						)					-> Tuple:

							'''simple docstring'''


							__lowercase			      =							copy.deepcopy(self.__dict__						)
							__lowercase			      =							self.text_encoder.to_dict()
							__lowercase			      =							self.audio_encoder.to_dict()
							__lowercase			      =							self.decoder.to_dict()
							__lowercase			      =							self.__class__.model_type
							return output
import json
import os
import tempfile

import datasets
from utils import generate_example_dataset, get_duration


__a  :					int          =  5_0_0_0_0_0

__a   ,						__a  :					Any          =  os.path.split(__file__)
__a  :					Dict          =  os.path.join(RESULTS_BASEPATH, """results""", RESULTS_FILENAME.replace(""".py""", """.json"""))





@get_duration
def     UpperCAmelCase						(   lowercase							):







				"""simple docstring"""



				__lowercase			      =							dataset.select(range(0							,      len(lowercase							)							,      2							)							)





@get_duration
def     UpperCAmelCase						(   lowercase							):







				"""simple docstring"""



				__lowercase			      =							dataset.sort('''numbers'''							)





@get_duration
def     UpperCAmelCase						(   lowercase							):







				"""simple docstring"""



				__lowercase			      =							dataset.shuffle()





@get_duration
def     UpperCAmelCase						(   lowercase							):







				"""simple docstring"""



				__lowercase			      =							dataset.train_test_split(0.1							)





@get_duration
def     UpperCAmelCase						(   lowercase							,      lowercase=10							):







				"""simple docstring"""



				for shard_id in range(lowercase							):
								__lowercase			      =							dataset.shard(lowercase							,      lowercase							)





def     UpperCAmelCase						(   ):







				"""simple docstring"""



				__lowercase			      =							{'''num examples''': SPEED_TEST_N_EXAMPLES}
				__lowercase			      =							(select, sort, shuffle, train_test_split, shard)
				with tempfile.TemporaryDirectory() as tmp_dir:
								print('''generating dataset'''							)
								__lowercase			      =							datasets.Features({'''text''': datasets.Value('''string'''							), '''numbers''': datasets.Value('''float32'''							)}							)
								__lowercase			      =							generate_example_dataset(
								    os.path.join(lowercase							,      '''dataset.arrow'''							)							,      lowercase							,      num_examples=lowercase							)
								print('''Functions'''							)
								for func in functions:
												print(func.__name__							)
												__lowercase			      =							func(lowercase							)

				with open(lowercase							,      '''wb'''							) as f:
								f.write(json.dumps(lowercase							).encode('''utf-8'''							)							)


if __name__ == "__main__":  # useful to run the profiler
		benchmark_indices_mapping()