'''simple docstring'''


import sys
from pathlib import Path


__snake_case						  =		Path(__file__).resolve().parents[3] / """src"""
sys.path.insert(1, str(git_repo_path))

import dataclasses  # noqa
import io  # noqa
import itertools  # noqa
import json  # noqa
import os  # noqa
import unittest  # noqa
from copy import deepcopy  # noqa

from parameterized import parameterized  # noqa
from transformers import TrainingArguments, is_torch_available  # noqa
from transformers.deepspeed import is_deepspeed_available  # noqa
from transformers.file_utils import WEIGHTS_NAME  # noqa
from transformers.testing_utils import (  # noqa
    CaptureLogger,
    ExtendSysPath,
    TestCasePlus,
    execute_subprocess_async,
    get_gpu_count,
    mockenv_context,
    require_deepspeed,
    require_torch_gpu,
    require_torch_multi_gpu,
    slow,
)
from transformers.trainer_utils import set_seed  # noqa


set_seed(42)

__snake_case						  =		{"""base""": """patrickvonplaten/wav2vec2_tiny_random""", """robust""": """patrickvonplaten/wav2vec2_tiny_random_robust"""}

__snake_case						  =		"""zero2"""
__snake_case						  =		"""zero3"""
__snake_case						  =		[ZEROa, ZEROa]

def   A_      (       SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_						)			->int:
  # customize the test name generator function as we want both params to appear in the sub-test
  # name, as by default it shows only the first param
  lowercase_     =       parameterized.to_safe_name("""_""".join(str(UpperCAmelCase_						) for x in param.args						)						)
  return f"""{func.__name__}_{param_based_name}"""


# Cartesian-product of zero stages with models to test
__snake_case						  =		list(itertools.product(stages, models.keys()))





@slow
@require_deepspeed
@require_torch_gpu
class       _a    (		_UpperCAmelCase      ):


  """simple docstring"""

  @parameterized.expand(SCREAMING_SNAKE_CASE_   ,				name_func=SCREAMING_SNAKE_CASE_      )
  def 		lowerCamelCase__  (		self      :       Any   ,				lowercase_      :       Tuple   ,				lowercase_      :       int      ):







    '''simple docstring'''


    self.run_and_check(
        stage=SCREAMING_SNAKE_CASE_   ,				model=SCREAMING_SNAKE_CASE_   ,				distributed=SCREAMING_SNAKE_CASE_   ,				fpaa=SCREAMING_SNAKE_CASE_   ,				)




  @require_torch_multi_gpu
  @parameterized.expand(SCREAMING_SNAKE_CASE_   ,				name_func=SCREAMING_SNAKE_CASE_      )
  def 		lowerCamelCase__  (		self      :       List[str]   ,				lowercase_      :       Union[str, Any]   ,				lowercase_      :       Optional[Any]      ):







    '''simple docstring'''


    self.run_and_check(
        stage=SCREAMING_SNAKE_CASE_   ,				model=SCREAMING_SNAKE_CASE_   ,				distributed=SCREAMING_SNAKE_CASE_   ,				fpaa=SCREAMING_SNAKE_CASE_   ,				)




  @parameterized.expand(SCREAMING_SNAKE_CASE_   ,				name_func=SCREAMING_SNAKE_CASE_      )
  def 		lowerCamelCase__  (		self      :       Union[str, Any]   ,				lowercase_      :       Any   ,				lowercase_      :       List[Any]      ):







    '''simple docstring'''


    self.run_and_check(
        stage=SCREAMING_SNAKE_CASE_   ,				model=SCREAMING_SNAKE_CASE_   ,				distributed=SCREAMING_SNAKE_CASE_   ,				fpaa=SCREAMING_SNAKE_CASE_   ,				)




  @require_torch_multi_gpu
  @parameterized.expand(SCREAMING_SNAKE_CASE_   ,				name_func=SCREAMING_SNAKE_CASE_      )
  def 		lowerCamelCase__  (		self      :       Dict   ,				lowercase_      :       Optional[Any]   ,				lowercase_      :       Optional[Any]      ):







    '''simple docstring'''


    self.run_and_check(
        stage=SCREAMING_SNAKE_CASE_   ,				model=SCREAMING_SNAKE_CASE_   ,				distributed=SCREAMING_SNAKE_CASE_   ,				fpaa=SCREAMING_SNAKE_CASE_   ,				)




  def 		lowerCamelCase__  (		self      :       List[str]   ,				lowercase_      :       Union[str, Any]      ):







    '''simple docstring'''


    pass




  def 		lowerCamelCase__  (		self      :       List[Any]   ,				lowercase_      :       str   ,				lowercase_      :       Dict   ,				lowercase_      :       int = 10   ,				lowercase_      :       List[str] = True   ,				lowercase_      :       int = True   ,				lowercase_      :       List[Any] = True   ,				):







    '''simple docstring'''


    lowercase_     =       models[model]

    lowercase_     =       self.run_trainer(
        stage=SCREAMING_SNAKE_CASE_   ,				model_name=SCREAMING_SNAKE_CASE_   ,				eval_steps=SCREAMING_SNAKE_CASE_   ,				num_train_epochs=1   ,				distributed=SCREAMING_SNAKE_CASE_   ,				fpaa=SCREAMING_SNAKE_CASE_   ,				)

    self.do_checks(SCREAMING_SNAKE_CASE_      )

    return output_dir




  def 		lowerCamelCase__  (		self      :       Any   ,				lowercase_      :       Dict   ,				lowercase_      :       Optional[int]   ,				lowercase_      :       int = 10   ,				lowercase_      :       List[Any] = 1   ,				lowercase_      :       int = True   ,				lowercase_      :       Optional[int] = True   ,				):







    '''simple docstring'''


    lowercase_     =       self.get_auto_remove_tmp_dir("""./xxx"""   ,				after=SCREAMING_SNAKE_CASE_      )
    lowercase_     =       F"""\n            --model_name_or_path {model_name}\n            --dataset_name hf-internal-testing/librispeech_asr_dummy\n            --dataset_config_name clean\n            --train_split_name validation\n            --validation_split_name validation\n            --output_dir {output_dir}\n            --num_train_epochs {str(SCREAMING_SNAKE_CASE_      )}\n            --per_device_train_batch_size 2\n            --per_device_eval_batch_size 2\n            --evaluation_strategy steps\n            --learning_rate 5e-4\n            --warmup_steps 8\n            --orthography timit\n            --preprocessing_num_workers 1\n            --group_by_length\n            --freeze_feature_extractor\n            --report_to none\n            --save_steps 0\n            --eval_steps {eval_steps}\n            --report_to none\n        """.split()

    if fpaa:
      args.extend(["""--fp16"""]      )

    # currently ds_config_wav2vec2_zero.json requires "zero_optimization.find_unused_parameters": true,
    # hence the separate config files
    lowercase_     =       F"""--deepspeed {self.test_file_dir_str}/ds_config_wav2vec2_{stage}.json""".split()
    lowercase_     =       [F"""{self.examples_dir_str}/research_projects/wav2vec2/run_asr.py"""]
    lowercase_     =       self.get_launcher(SCREAMING_SNAKE_CASE_      )

    lowercase_     =       launcher + script + args + ds_args
    # keep for quick debug
    # print(" ".join([f"\nPYTHONPATH={self.src_dir_str}"] +cmd)); die
    execute_subprocess_async(SCREAMING_SNAKE_CASE_   ,				env=self.get_env()      )

    return output_dir





  def 		lowerCamelCase__  (		self      :       Optional[Any]   ,				lowercase_      :       Dict=False      ):







    '''simple docstring'''


    lowercase_     =       min(2   ,				get_gpu_count()      ) if distributed else 1
    return F"""deepspeed --num_nodes 1 --num_gpus {num_gpus}""".split()





'''simple docstring'''



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


A__						:   Tuple				=    logging.get_logger(__name__)

A__						:   Dict				=    {
    """RWKV/rwkv-4-169m-pile""": """https://huggingface.co/RWKV/rwkv-4-169m-pile/resolve/main/config.json""",
    """RWKV/rwkv-4-430m-pile""": """https://huggingface.co/RWKV/rwkv-4-430m-pile/resolve/main/config.json""",
    """RWKV/rwkv-4-1b5-pile""": """https://huggingface.co/RWKV/rwkv-4-1b5-pile/resolve/main/config.json""",
    """RWKV/rwkv-4-3b-pile""": """https://huggingface.co/RWKV/rwkv-4-3b-pile/resolve/main/config.json""",
    """RWKV/rwkv-4-7b-pile""": """https://huggingface.co/RWKV/rwkv-4-7b-pile/resolve/main/config.json""",
    """RWKV/rwkv-4-14b-pile""": """https://huggingface.co/RWKV/rwkv-4-14b-pile/resolve/main/config.json""",
    """RWKV/rwkv-raven-1b5""": """https://huggingface.co/RWKV/rwkv-raven-1b5/resolve/main/config.json""",
    """RWKV/rwkv-raven-3b""": """https://huggingface.co/RWKV/rwkv-raven-3b/resolve/main/config.json""",
    """RWKV/rwkv-raven-7b""": """https://huggingface.co/RWKV/rwkv-raven-7b/resolve/main/config.json""",
    """RWKV/rwkv-raven-14b""": """https://huggingface.co/RWKV/rwkv-raven-14b/resolve/main/config.json""",
}





class   UpperCAmelCase_    (_UpperCAmelCase    ):





    """simple docstring"""






    lowerCamelCase    :   List[Any]					=     'rwkv'
    lowerCamelCase    :   Any					=     {'max_position_embeddings': 'context_length'}







    def __init__(				self     ,	SCREAMING_SNAKE_CASE_=5_02_77     ,	SCREAMING_SNAKE_CASE_=10_24     ,	SCREAMING_SNAKE_CASE_=40_96     ,	SCREAMING_SNAKE_CASE_=32     ,	SCREAMING_SNAKE_CASE_=None     ,	SCREAMING_SNAKE_CASE_=None     ,	SCREAMING_SNAKE_CASE_=1E-5     ,	SCREAMING_SNAKE_CASE_=0     ,	SCREAMING_SNAKE_CASE_=0     ,	SCREAMING_SNAKE_CASE_=6     ,	SCREAMING_SNAKE_CASE_=False     ,	SCREAMING_SNAKE_CASE_=True     ,	**SCREAMING_SNAKE_CASE_     ,	)							->	Optional[Any]:
         __lowerCamelCase  :      Optional[int]														=						vocab_size
         __lowerCamelCase  :      Tuple														=						context_length
         __lowerCamelCase  :      str														=						hidden_size
         __lowerCamelCase  :      List[str]														=						num_hidden_layers
         __lowerCamelCase  :      Any														=						attention_hidden_size if attention_hidden_size is not None else hidden_size
         __lowerCamelCase  :      Optional[int]														=						intermediate_size if intermediate_size is not None else 4 * hidden_size
         __lowerCamelCase  :      Optional[Any]														=						layer_norm_epsilon
         __lowerCamelCase  :      int														=						rescale_every
         __lowerCamelCase  :      Tuple														=						use_cache

         __lowerCamelCase  :      int														=						bos_token_id
         __lowerCamelCase  :      Optional[Any]														=						eos_token_id

         super().__init__(
             tie_word_embeddings=SCREAMING_SNAKE_CASE_     ,	bos_token_id=SCREAMING_SNAKE_CASE_     ,	eos_token_id=SCREAMING_SNAKE_CASE_     ,	**SCREAMING_SNAKE_CASE_      )






