

import inspect
import os
import unittest

import torch

import accelerate
from accelerate import debug_launcher
from accelerate.test_utils import (
    execute_subprocess_async,
    require_cpu,
    require_huggingface_suite,
    require_multi_gpu,
    require_single_gpu,
)
from accelerate.utils import patch_environment





@require_huggingface_suite
class       snake_case_  (						unittest.TestCase   ):







			'''simple docstring'''

			def 							snake_case__(	self					:							List[str]				) ->str:
									snake_case_  =      inspect.getfile(accelerate.test_utils				)
									snake_case_  =      os.path.sep.join(
									    mod_file.split(os.path.sep				)[:-1] + ['''scripts''', '''external_deps''', '''test_metrics.py''']				)

									from accelerate.test_utils.scripts.external_deps import test_metrics  # noqa: F401

									snake_case_  =      test_metrics







			@require_cpu
			def 							snake_case__(	self					:							str				) ->int:
									debug_launcher(self.test_metrics.main				,  num_processes=1				)







			@require_cpu
			def 							snake_case__(	self					:							Union[str, Any]				) ->Any:
									debug_launcher(self.test_metrics.main				)







			@require_single_gpu
			def 							snake_case__(	self					:							List[Any]				) ->Tuple:
									self.test_metrics.main()







			@require_multi_gpu
			def 							snake_case__(	self					:							Any				) ->Union[str, Any]:
									print(f'''Found {torch.cuda.device_count()} devices.'''				)
									snake_case_  =      ['''torchrun''', f'''--nproc_per_node={torch.cuda.device_count()}''', self.test_file_path]
									with patch_environment(omp_num_threads=1				):
															execute_subprocess_async(_UpperCamelCase				,  env=os.environ.copy()				)


'''simple docstring'''



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


UpperCAmelCase					:			Tuple       =	logging.get_logger(__name__)

UpperCAmelCase					:			Any       =	{'ctrl': 'https://huggingface.co/ctrl/resolve/main/config.json'}







class 		lowerCAmelCase__  ( a   ):



 """simple docstring"""



 lowerCAmelCase__       = "ctrl"
 lowerCAmelCase__       = ["past_key_values"]
 lowerCAmelCase__       = {
     "max_position_embeddings": "n_positions",
     "hidden_size": "n_embd",
     "num_attention_heads": "n_head",
     "num_hidden_layers": "n_layer",
 }
 def __init__(						self   :			Tuple   ,				__SCREAMING_SNAKE_CASE   :			Tuple=246_534   ,				__SCREAMING_SNAKE_CASE   :			str=256   ,				__SCREAMING_SNAKE_CASE   :			Optional[Any]=1_280   ,				__SCREAMING_SNAKE_CASE   :			Dict=8_192   ,				__SCREAMING_SNAKE_CASE   :			Union[str, Any]=48   ,				__SCREAMING_SNAKE_CASE   :			Dict=16   ,				__SCREAMING_SNAKE_CASE   :			Union[str, Any]=0.1   ,				__SCREAMING_SNAKE_CASE   :			str=0.1   ,				__SCREAMING_SNAKE_CASE   :			Union[str, Any]=1E-6   ,				__SCREAMING_SNAKE_CASE   :			Tuple=0.02   ,				__SCREAMING_SNAKE_CASE   :			Tuple=True   ,				**__SCREAMING_SNAKE_CASE   :			Union[str, Any]   ,				)    ->					Tuple:


      """simple docstring"""




      __SCREAMING_SNAKE_CASE      = vocab_size
      __SCREAMING_SNAKE_CASE      = n_positions
      __SCREAMING_SNAKE_CASE      = n_embd
      __SCREAMING_SNAKE_CASE      = n_layer
      __SCREAMING_SNAKE_CASE      = n_head
      __SCREAMING_SNAKE_CASE      = dff
      __SCREAMING_SNAKE_CASE      = resid_pdrop
      __SCREAMING_SNAKE_CASE      = embd_pdrop
      __SCREAMING_SNAKE_CASE      = layer_norm_epsilon
      __SCREAMING_SNAKE_CASE      = initializer_range

      __SCREAMING_SNAKE_CASE      = use_cache

      super().__init__(**__SCREAMING_SNAKE_CASE     )






