

'''simple docstring'''

import gc
import threading
import time

import psutil
import torch





class 				_snake_case			:
   def __init__(			self      :   List[Any]				):
     SCREAMING_SNAKE_CASE:List[str]       =       psutil.Process()
     SCREAMING_SNAKE_CASE:Tuple       =       False
   def      __UpperCamelCase    (			self      :   Tuple				):
     SCREAMING_SNAKE_CASE:Any       =       -1

     while True:
       SCREAMING_SNAKE_CASE:Tuple       =       max(self.process.memory_info().rss  ,self.cpu_memory_peak				)

       # can't sleep or will not catch the peak right (this comment is here on purpose)
       if not self.peak_monitoring:
         break
   def      __UpperCamelCase    (			self      :   List[Any]				):
     SCREAMING_SNAKE_CASE:List[str]       =       True
     SCREAMING_SNAKE_CASE:List[Any]       =       threading.Thread(target=self.peak_monitor				)
     SCREAMING_SNAKE_CASE:str       =       True
     self.thread.start()







   def      __UpperCamelCase    (			self      :   Union[str, Any]				):
     SCREAMING_SNAKE_CASE:Any       =       False
     self.thread.join()
     return self.cpu_memory_peak



A_							    =				PeakCPUMemory()





def  A_	(			):
  # Time
  SCREAMING_SNAKE_CASE:Optional[int]       =       {"time": time.time()}

  gc.collect()
  torch.cuda.empty_cache()

  # CPU mem
  SCREAMING_SNAKE_CASE:Optional[int]       =       psutil.Process().memory_info().rss
  cpu_peak_tracker.start()

  # GPU mem
  for i in range(torch.cuda.device_count()			):
    SCREAMING_SNAKE_CASE:Tuple       =       torch.cuda.memory_allocated(snake_case			)
  torch.cuda.reset_peak_memory_stats()

  return measures





def  A_	(			snake_case			):
  # Time
  SCREAMING_SNAKE_CASE:Tuple       =       {"time": time.time() - start_measures["time"]}

  gc.collect()
  torch.cuda.empty_cache()

  # CPU mem
  SCREAMING_SNAKE_CASE:Optional[Any]       =       (psutil.Process().memory_info().rss - start_measures["cpu"]) / 2**20
  SCREAMING_SNAKE_CASE:Optional[int]       =       (cpu_peak_tracker.stop() - start_measures["cpu"]) / 2**20

  # GPU mem
  for i in range(torch.cuda.device_count()			):
    SCREAMING_SNAKE_CASE:Any       =       (torch.cuda.memory_allocated(snake_case			) - start_measures[str(snake_case			)]) / 2**20
    SCREAMING_SNAKE_CASE:Dict       =       (torch.cuda.max_memory_allocated(snake_case			) - start_measures[str(snake_case			)]) / 2**20

  return measures





def  A_	(			snake_case   ,							snake_case			):
  print(F'''{description}:'''			)
  print(F'''- Time: {measures["time"]:.2f}s'''			)
  for i in range(torch.cuda.device_count()			):
    print(F'''- GPU {i} allocated: {measures[str(snake_case			)]:.2f}MiB'''			)
    SCREAMING_SNAKE_CASE:int       =       measures[F'''{i}-peak''']
    print(F'''- GPU {i} peak: {peak:.2f}MiB'''			)
  print(F'''- CPU RAM allocated: {measures["cpu"]:.2f}MiB'''			)
  print(F'''- CPU RAM peak: {measures["cpu-peak"]:.2f}MiB'''			)







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


_lowercase:	List[Any]       			=		logging.get_logger(__name__)

_lowercase:	int       			=		{
    '''alibaba-damo/mgp-str-base''': '''https://huggingface.co/alibaba-damo/mgp-str-base/resolve/main/config.json''',
}



class        lowerCamelCase__				(   UpperCAmelCase				):
			UpperCamelCase__    							="mgp-str"





			def __init__(       self	:	int  ,  lowercase__	:	List[Any]=[32, 1_28]  ,  lowercase__	:	str=4  ,  lowercase__	:	List[str]=3  ,  lowercase__	:	Tuple=27  ,  lowercase__	:	Optional[Any]=38  ,  lowercase__	:	Optional[Any]=5_02_57  ,  lowercase__	:	Dict=3_05_22  ,  lowercase__	:	Dict=7_68  ,  lowercase__	:	Tuple=12  ,  lowercase__	:	int=12  ,  lowercase__	:	int=4.0  ,  lowercase__	:	Tuple=True  ,  lowercase__	:	List[Any]=False  ,  lowercase__	:	int=1e-5  ,  lowercase__	:	int=0.0  ,  lowercase__	:	Optional[Any]=0.0  ,  lowercase__	:	List[Any]=0.0  ,  lowercase__	:	Union[str, Any]=False  ,  lowercase__	:	str=0.0_2  ,  **lowercase__	:	Optional[int]  ,  ):
										super().__init__(**lowercase__						)

										_lowerCAmelCase							=							image_size
										_lowerCAmelCase							=							patch_size
										_lowerCAmelCase							=							num_channels
										_lowerCAmelCase							=							max_token_length
										_lowerCAmelCase							=							num_character_labels
										_lowerCAmelCase							=							num_bpe_labels
										_lowerCAmelCase							=							num_wordpiece_labels
										_lowerCAmelCase							=							hidden_size
										_lowerCAmelCase							=							num_hidden_layers
										_lowerCAmelCase							=							num_attention_heads
										_lowerCAmelCase							=							mlp_ratio
										_lowerCAmelCase							=							distilled
										_lowerCAmelCase							=							layer_norm_eps
										_lowerCAmelCase							=							drop_rate
										_lowerCAmelCase							=							qkv_bias
										_lowerCAmelCase							=							attn_drop_rate
										_lowerCAmelCase							=							drop_path_rate
										_lowerCAmelCase							=							output_aa_attentions
										_lowerCAmelCase							=							initializer_range






