
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__	=							object()

# For specifying empty leaf dict `{}`
lowerCamelCase__	=							object()


def 							__A(lowerCAmelCase						,  lowerCAmelCase )		->				List[Any]:

		"""simple docstring"""






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


def 							__A(lowerCAmelCase )		->				Union[str, Any]:

		"""simple docstring"""






		def replace(lowerCAmelCase						,  lowerCAmelCase ):
				for rule, replacement in rules:
						if _match(lowerCAmelCase						,  lowerCAmelCase ):
								return replacement
				return val

		return replace


def 							__A()		->				Tuple:

		"""simple docstring"""






		return [
		    # embeddings
		    (("transformer", "wpe", "embedding"), P("""mp"""						,  lowerCAmelCase )),
		    (("transformer", "wte", "embedding"), P("""mp"""						,  lowerCAmelCase )),
		    # atention
		    (("attention", "(q_proj|k_proj|v_proj)", "kernel"), P(lowerCAmelCase						,  """mp""" )),
		    (("attention", "out_proj", "kernel"), P("""mp"""						,  lowerCAmelCase )),
		    (("attention", "out_proj", "bias"), None),
		    # mlp
		    (("mlp", "c_fc", "kernel"), P(lowerCAmelCase						,  """mp""" )),
		    (("mlp", "c_fc", "bias"), P("""mp""" )),
		    (("mlp", "c_proj", "kernel"), P("""mp"""						,  lowerCAmelCase )),
		    (("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 							__A(lowerCAmelCase )		->				str:

		"""simple docstring"""






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





import platform
from argparse import ArgumentParser

import huggingface_hub

from .. import __version__ as version
from ..utils import is_accelerate_available, is_torch_available, is_transformers_available, is_xformers_available
from . import BaseDiffusersCLICommand


def 							__A(lowerCAmelCase )		->				Optional[int]:

		"""simple docstring"""






		return EnvironmentCommand()







class        lowerCAmelCase__      (   __lowercase	):

						@staticmethod
						def  A_				(			a				)					->      List[str]:


								'''simple docstring'''

								_UpperCamelCase						    =	parser.add_parser("""env"""				)
								download_parser.set_defaults(func=a				)

						def  A_				(			self				)					->      List[str]:


								'''simple docstring'''

								_UpperCamelCase						    =	huggingface_hub.__version__

								_UpperCamelCase						    =	"""not installed"""
								_UpperCamelCase						    =	"""NA"""
								if is_torch_available():
										import torch

										_UpperCamelCase						    =	torch.__version__
										_UpperCamelCase						    =	torch.cuda.is_available()

								_UpperCamelCase						    =	"""not installed"""
								if is_transformers_available():
										import transformers

										_UpperCamelCase						    =	transformers.__version__

								_UpperCamelCase						    =	"""not installed"""
								if is_accelerate_available():
										import accelerate

										_UpperCamelCase						    =	accelerate.__version__

								_UpperCamelCase						    =	"""not installed"""
								if is_xformers_available():
										import xformers

										_UpperCamelCase						    =	xformers.__version__

								_UpperCamelCase						    =	{
								    """`diffusers` version""": version,
								    """Platform""": platform.platform(),
								    """Python version""": platform.python_version(),
								    """PyTorch version (GPU?)""": F'{pt_version} ({pt_cuda_available})',
								    """Huggingface_hub version""": hub_version,
								    """Transformers version""": transformers_version,
								    """Accelerate version""": accelerate_version,
								    """xFormers version""": xformers_version,
								    """Using GPU in script?""": """<fill in>""",
								    """Using distributed or parallel set-up in script?""": """<fill in>""",
								}

								print("""\nCopy-and-paste the text below in your GitHub issue and FILL OUT the two last points.\n"""				)
								print(self.format_dict(a				)				)

								return info







						@staticmethod
						def  A_				(			a				)					->      Dict:


								'''simple docstring'''

								return "\n".join([F'- {prop}: {val}' for prop, val in d.items()]				) + "\n"



