




'''simple docstring'''







import math
from typing import Optional

import numpy as np

from ...configuration_utils import PretrainedConfig
from ...utils import logging


A     =logging.get_logger(__name__)

A     ={
    'facebook/encodec_24khz': 'https://huggingface.co/facebook/encodec_24khz/resolve/main/config.json',
    'facebook/encodec_48khz': 'https://huggingface.co/facebook/encodec_48khz/resolve/main/config.json',
}


class 			_a  (	__a ):
       __a				:     Union[str, Any]   				=					"""encodec"""
       def __init__(	self						:	Tuple   ,				lowercase						:	List[str]=[1.5, 3.0, 6.0, 12.0, 24.0]   ,				lowercase						:	Any=24_000   ,				lowercase						:	str=1   ,				lowercase						:	Optional[int]=False   ,				lowercase						:	Optional[Any]=None   ,				lowercase						:	str=None   ,				lowercase						:	Tuple=128   ,				lowercase						:	Union[str, Any]=32   ,				lowercase						:	Union[str, Any]=1   ,				lowercase						:	Optional[Any]=[8, 5, 4, 2]   ,				lowercase						:	Any="weight_norm"   ,				lowercase						:	Tuple=7   ,				lowercase						:	int=7   ,				lowercase						:	Dict=3   ,				lowercase						:	List[Any]=2   ,				lowercase						:	str=True   ,				lowercase						:	List[str]="reflect"   ,				lowercase						:	List[Any]=2   ,				lowercase						:	Optional[Any]=2   ,				lowercase						:	int=1.0   ,				lowercase						:	Dict=1_024   ,				lowercase						:	str=None   ,				lowercase						:	Union[str, Any]=True   ,				**lowercase						:	Optional[int]   ,				):



           '''simple docstring'''

           UpperCAmelCase			       =		target_bandwidths
           UpperCAmelCase			       =		sampling_rate
           UpperCAmelCase			       =		audio_channels
           UpperCAmelCase			       =		normalize
           UpperCAmelCase			       =		chunk_length_s
           UpperCAmelCase			       =		overlap
           UpperCAmelCase			       =		hidden_size
           UpperCAmelCase			       =		num_filters
           UpperCAmelCase			       =		num_residual_layers
           UpperCAmelCase			       =		upsampling_ratios
           UpperCAmelCase			       =		norm_type
           UpperCAmelCase			       =		kernel_size
           UpperCAmelCase			       =		last_kernel_size
           UpperCAmelCase			       =		residual_kernel_size
           UpperCAmelCase			       =		dilation_growth_rate
           UpperCAmelCase			       =		use_causal_conv
           UpperCAmelCase			       =		pad_mode
           UpperCAmelCase			       =		compress
           UpperCAmelCase			       =		num_lstm_layers
           UpperCAmelCase			       =		trim_right_ratio
           UpperCAmelCase			       =		codebook_size
           UpperCAmelCase			       =		codebook_dim if codebook_dim is not None else hidden_size
           UpperCAmelCase			       =		use_conv_shortcut

           if self.norm_type not in ["weight_norm", "time_group_norm"]:
               raise ValueError(
                   f"self.norm_type must be one of `\"weight_norm\"`, `\"time_group_norm\"`), got {self.norm_type}"				)

           super().__init__(**lowercase				)
       @property
       def     A      (	self						:	Dict				):



           '''simple docstring'''

           if self.chunk_length_s is None:
               return None
           else:
               return int(self.chunk_length_s * self.sampling_rate				)
       @property
       def     A      (	self						:	Union[str, Any]				):



           '''simple docstring'''

           if self.chunk_length_s is None or self.overlap is None:
               return None
           else:
               return max(1   ,				int((1.0 - self.overlap) * self.chunk_length				)				)
       @property
       def     A      (	self						:	Any				):



           '''simple docstring'''

           UpperCAmelCase			       =		np.prod(self.upsampling_ratios				)
           return math.ceil(self.sampling_rate / hop_length				)







       @property
       def     A      (	self						:	Optional[int]				):



           '''simple docstring'''

           return int(1_000 * self.target_bandwidths[-1] // (self.frame_rate * 10)				)










'''simple docstring'''







import argparse
import json
import logging
import os
import sys
from unittest.mock import patch

from transformers.testing_utils import TestCasePlus, get_gpu_count, slow


A     =[
    os.path.join(os.path.dirname(__file__), dirname)
    for dirname in [
        'text-classification',
        'language-modeling',
        'summarization',
        'token-classification',
        'question-answering',
    ]
]
sys.path.extend(SRC_DIRS)


if SRC_DIRS is not None:
   import run_clm_flax
   import run_flax_glue
   import run_flax_ner
   import run_mlm_flax
   import run_qa
   import run_summarization_flax
   import run_ta_mlm_flax


logging.basicConfig(level=logging.DEBUG)

A     =logging.getLogger()





def 						snake_case_							():
    UpperCAmelCase			       =		argparse.ArgumentParser()
    parser.add_argument('''-f'''     )
    UpperCAmelCase			       =		parser.parse_args()
    return args.f





def 						snake_case_							(_a	:							List[str]    ,   _a	:							Union[str, Any]="eval"     ):
    UpperCAmelCase			       =		os.path.join(_a    ,   F"{split}_results.json"     )
    if os.path.exists(_a     ):
        with open(_a    ,   '''r'''     ) as f:
            return json.load(_a     )
    raise ValueError(F"can't find {path}"     )


A     =logging.StreamHandler(sys.stdout)
logger.addHandler(stream_handler)







class 			_a  (	__a ):
       def     A      (	self						:	Any				):



           '''simple docstring'''

           UpperCAmelCase			       =		self.get_auto_remove_tmp_dir()
           UpperCAmelCase			       =		f"\n            run_glue.py\n            --model_name_or_path distilbert-base-uncased\n            --output_dir {tmp_dir}\n            --train_file ./tests/fixtures/tests_samples/MRPC/train.csv\n            --validation_file ./tests/fixtures/tests_samples/MRPC/dev.csv\n            --per_device_train_batch_size=2\n            --per_device_eval_batch_size=1\n            --learning_rate=1e-4\n            --eval_steps=2\n            --warmup_steps=2\n            --seed=42\n            --max_seq_length=128\n            ".split()

           with patch.object(lowercase   ,				'''argv'''   ,				lowercase				):
               run_flax_glue.main()
               UpperCAmelCase			       =		get_results(lowercase				)
               self.assertGreaterEqual(result['''eval_accuracy''']   ,				0.75				)
       @slow
       def     A      (	self						:	Any				):



           '''simple docstring'''

           UpperCAmelCase			       =		self.get_auto_remove_tmp_dir()
           UpperCAmelCase			       =		f"\n            run_clm_flax.py\n            --model_name_or_path distilgpt2\n            --train_file ./tests/fixtures/sample_text.txt\n            --validation_file ./tests/fixtures/sample_text.txt\n            --do_train\n            --do_eval\n            --block_size 128\n            --per_device_train_batch_size 4\n            --per_device_eval_batch_size 4\n            --num_train_epochs 2\n            --logging_steps 2 --eval_steps 2\n            --output_dir {tmp_dir}\n            --overwrite_output_dir\n            ".split()

           with patch.object(lowercase   ,				'''argv'''   ,				lowercase				):
               run_clm_flax.main()
               UpperCAmelCase			       =		get_results(lowercase				)
               self.assertLess(result['''eval_perplexity''']   ,				100				)
       @slow
       def     A      (	self						:	str				):



           '''simple docstring'''

           UpperCAmelCase			       =		self.get_auto_remove_tmp_dir()
           UpperCAmelCase			       =		f"\n            run_summarization.py\n            --model_name_or_path t5-small\n            --train_file tests/fixtures/tests_samples/xsum/sample.json\n            --validation_file tests/fixtures/tests_samples/xsum/sample.json\n            --test_file tests/fixtures/tests_samples/xsum/sample.json\n            --output_dir {tmp_dir}\n            --overwrite_output_dir\n            --num_train_epochs=3\n            --warmup_steps=8\n            --do_train\n            --do_eval\n            --do_predict\n            --learning_rate=2e-4\n            --per_device_train_batch_size=2\n            --per_device_eval_batch_size=1\n            --predict_with_generate\n        ".split()

           with patch.object(lowercase   ,				'''argv'''   ,				lowercase				):
               run_summarization_flax.main()
               UpperCAmelCase			       =		get_results(lowercase   ,				split='''test'''				)
               self.assertGreaterEqual(result['''test_rouge1''']   ,				10				)
               self.assertGreaterEqual(result['''test_rouge2''']   ,				2				)
               self.assertGreaterEqual(result['''test_rougeL''']   ,				7				)
               self.assertGreaterEqual(result['''test_rougeLsum''']   ,				7				)
       @slow
       def     A      (	self						:	int				):



           '''simple docstring'''

           UpperCAmelCase			       =		self.get_auto_remove_tmp_dir()
           UpperCAmelCase			       =		f"\n            run_mlm.py\n            --model_name_or_path distilroberta-base\n            --train_file ./tests/fixtures/sample_text.txt\n            --validation_file ./tests/fixtures/sample_text.txt\n            --output_dir {tmp_dir}\n            --overwrite_output_dir\n            --max_seq_length 128\n            --per_device_train_batch_size 4\n            --per_device_eval_batch_size 4\n            --logging_steps 2 --eval_steps 2\n            --do_train\n            --do_eval\n            --num_train_epochs=1\n        ".split()

           with patch.object(lowercase   ,				'''argv'''   ,				lowercase				):
               run_mlm_flax.main()
               UpperCAmelCase			       =		get_results(lowercase				)
               self.assertLess(result['''eval_perplexity''']   ,				42				)
       @slow
       def     A      (	self						:	Tuple				):



           '''simple docstring'''

           UpperCAmelCase			       =		self.get_auto_remove_tmp_dir()
           UpperCAmelCase			       =		f"\n            run_t5_mlm_flax.py\n            --model_name_or_path t5-small\n            --train_file ./tests/fixtures/sample_text.txt\n            --validation_file ./tests/fixtures/sample_text.txt\n            --do_train\n            --do_eval\n            --max_seq_length 128\n            --per_device_train_batch_size 4\n            --per_device_eval_batch_size 4\n            --num_train_epochs 2\n            --logging_steps 2 --eval_steps 2\n            --output_dir {tmp_dir}\n            --overwrite_output_dir\n            ".split()

           with patch.object(lowercase   ,				'''argv'''   ,				lowercase				):
               run_ta_mlm_flax.main()
               UpperCAmelCase			       =		get_results(lowercase				)
               self.assertGreaterEqual(result['''eval_accuracy''']   ,				0.42				)
       @slow
       def     A      (	self						:	Tuple				):



           '''simple docstring'''

           UpperCAmelCase			       =		7 if get_gpu_count() > 1 else 2

           UpperCAmelCase			       =		self.get_auto_remove_tmp_dir()
           UpperCAmelCase			       =		f"\n            run_flax_ner.py\n            --model_name_or_path bert-base-uncased\n            --train_file tests/fixtures/tests_samples/conll/sample.json\n            --validation_file tests/fixtures/tests_samples/conll/sample.json\n            --output_dir {tmp_dir}\n            --overwrite_output_dir\n            --do_train\n            --do_eval\n            --warmup_steps=2\n            --learning_rate=2e-4\n            --logging_steps 2 --eval_steps 2\n            --per_device_train_batch_size=2\n            --per_device_eval_batch_size=2\n            --num_train_epochs={epochs}\n            --seed 7\n        ".split()

           with patch.object(lowercase   ,				'''argv'''   ,				lowercase				):
               run_flax_ner.main()
               UpperCAmelCase			       =		get_results(lowercase				)
               self.assertGreaterEqual(result['''eval_accuracy''']   ,				0.75				)
               self.assertGreaterEqual(result['''eval_f1''']   ,				0.3				)







       @slow
       def     A      (	self						:	Union[str, Any]				):



           '''simple docstring'''

           UpperCAmelCase			       =		self.get_auto_remove_tmp_dir()
           UpperCAmelCase			       =		f"\n            run_qa.py\n            --model_name_or_path bert-base-uncased\n            --version_2_with_negative\n            --train_file tests/fixtures/tests_samples/SQUAD/sample.json\n            --validation_file tests/fixtures/tests_samples/SQUAD/sample.json\n            --output_dir {tmp_dir}\n            --overwrite_output_dir\n            --num_train_epochs=3\n            --warmup_steps=2\n            --do_train\n            --do_eval\n            --logging_steps 2 --eval_steps 2\n            --learning_rate=2e-4\n            --per_device_train_batch_size=2\n            --per_device_eval_batch_size=1\n        ".split()

           with patch.object(lowercase   ,				'''argv'''   ,				lowercase				):
               run_qa.main()
               UpperCAmelCase			       =		get_results(lowercase				)
               self.assertGreaterEqual(result['''eval_f1''']   ,				30				)
               self.assertGreaterEqual(result['''eval_exact''']   ,				30				)




