import gc
import threading
import time

import psutil
import torch







class __snake_case				:




   def __init__(    self			:				Dict      ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__										=      psutil.Process()
     SCREAMING_SNAKE_CASE__										=      False




   def 	__a						(    self			:				Tuple      ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__										=      -1

     while True:
       SCREAMING_SNAKE_CASE__										=      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 	__a						(    self			:				List[Any]      ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__										=      True
     SCREAMING_SNAKE_CASE__										=      threading.Thread(target=self.peak_monitor      )
     SCREAMING_SNAKE_CASE__										=      True
     self.thread.start()




   def 	__a						(    self			:				int      ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__										=      False
     self.thread.join()
     return self.cpu_memory_peak





__lowerCamelCase			: int							   =		PeakCPUMemory()



def 	__SCREAMING_SNAKE_CASE  (					)							->					str:







  """simple docstring"""





  SCREAMING_SNAKE_CASE__										=      {"""time""": time.time()}

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

  # CPU mem
  SCREAMING_SNAKE_CASE__										=      psutil.Process().memory_info().rss
  cpu_peak_tracker.start()

  # GPU mem
  for i in range(torch.cuda.device_count()	):
    SCREAMING_SNAKE_CASE__										=      torch.cuda.memory_allocated(__UpperCamelCase	)
  torch.cuda.reset_peak_memory_stats()

  return measures



def 	__SCREAMING_SNAKE_CASE  (					__UpperCamelCase    :       str	)							->					Dict:







  """simple docstring"""





  SCREAMING_SNAKE_CASE__										=      {"""time""": time.time() - start_measures["""time"""]}

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

  # CPU mem
  SCREAMING_SNAKE_CASE__										=      (psutil.Process().memory_info().rss - start_measures["""cpu"""]) / 2**20
  SCREAMING_SNAKE_CASE__										=      (cpu_peak_tracker.stop() - start_measures["""cpu"""]) / 2**20

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

  return measures






def 	__SCREAMING_SNAKE_CASE  (					__UpperCamelCase    :       Optional[Any] ,     __UpperCamelCase    :       Optional[int]	)							->					Tuple:







  """simple docstring"""





  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(__UpperCamelCase	)]:.2f}MiB"""	)
    SCREAMING_SNAKE_CASE__										=      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"""	)

import re

from flax.core.frozen_dict import freeze
from flax.traverse_util import flatten_dict, unflatten_dict
from jax.experimental import PartitionSpec as P


# Sentinels
__lowerCamelCase			: List[str]							   =		object()

# For specifying empty leaf dict `{}`
__lowerCamelCase			: Optional[int]							   =		object()



def 	__SCREAMING_SNAKE_CASE  (					__UpperCamelCase    :       List[Any] ,     __UpperCamelCase    :       List[str]	)							->					Optional[Any]:







  """simple docstring"""





  SCREAMING_SNAKE_CASE__										=      tuple((re.compile(x + """$"""	) for x in qs)	)
  for i in range(len(__UpperCamelCase	) - len(__UpperCamelCase	) + 1	):
    SCREAMING_SNAKE_CASE__										=      [x.match(__UpperCamelCase	) for x, y in zip(__UpperCamelCase ,     ks[i:]	)]
    if matches and all(__UpperCamelCase	):
      return True
  return False



def 	__SCREAMING_SNAKE_CASE  (					__UpperCamelCase    :       Optional[int]	)							->					List[str]:







  """simple docstring"""





  def replace(__UpperCamelCase    :       Tuple ,     __UpperCamelCase    :       Any	):
    for rule, replacement in rules:
      if _match(__UpperCamelCase ,     __UpperCamelCase	):
        return replacement
    return val

  return replace



def 	__SCREAMING_SNAKE_CASE  (					)							->					List[Any]:







  """simple docstring"""





  return [
      # embeddings
      (("transformer", "wpe", "embedding"), P("""mp""" ,     __UpperCamelCase	)),
      (("transformer", "wte", "embedding"), P("""mp""" ,     __UpperCamelCase	)),
      # atention
      (("attention", "(q_proj|k_proj|v_proj)", "kernel"), P(__UpperCamelCase ,     """mp"""	)),
      (("attention", "out_proj", "kernel"), P("""mp""" ,     __UpperCamelCase	)),
      (("attention", "out_proj", "bias"), None),
      # mlp
      (("mlp", "c_fc", "kernel"), P(__UpperCamelCase ,     """mp"""	)),
      (("mlp", "c_fc", "bias"), P("""mp"""	)),
      (("mlp", "c_proj", "kernel"), P("""mp""" ,     __UpperCamelCase	)),
      (("mlp", "c_proj", "bias"), None),
      # layer norms
      ((r"ln_\d+", "bias"), None),
      ((r"\d+", r"ln_\d+", "scale"), None),
      (("ln_f", "bias"), None),
      (("ln_f", "scale"), None),
  ]






def 	__SCREAMING_SNAKE_CASE  (					__UpperCamelCase    :       Union[str, Any]	)							->					Dict:







  """simple docstring"""





  SCREAMING_SNAKE_CASE__										=      _get_partition_rules()
  SCREAMING_SNAKE_CASE__										=      _replacement_rules(__UpperCamelCase	)
  SCREAMING_SNAKE_CASE__										=      {k: _unmatched for k in flatten_dict(__UpperCamelCase	)}
  SCREAMING_SNAKE_CASE__										=      {k: replace(__UpperCamelCase ,     __UpperCamelCase	) for k, v in initd.items()}
  assert _unmatched not in result.values(), "Incomplete partition spec."
  return freeze(unflatten_dict(__UpperCamelCase	)	)
