
'''simple docstring'''





import math
from collections import OrderedDict

import torch
from packaging import version
from torch import Tensor, nn

from .utils import logging


a__		: Optional[Any]  							=							logging.get_logger(__name__)


class 			UpperCamelCase__	(     nn.Module):






 def __init__(      self	:Optional[Any]      )					->      Optional[Any]:







       '''simple docstring'''



       super().__init__()
       if version.parse(torch.__version__      ) < version.parse('1.12.0'      ):
             raise ImportError(
                 F'You are using torch=={torch.__version__}, but torch>=1.12.0 is required to use '
                 'PytorchGELUTanh. Please upgrade torch.'      )






 def 						lowercase_    (      self	:Optional[Any]						,					_A	:Tensor      )					->      Tensor:







       '''simple docstring'''



       return nn.functional.gelu(_A						,					approximate='tanh'      )


class 			UpperCamelCase__	(     nn.Module):






 def 						lowercase_    (      self	:Optional[Any]						,					_A	:Tensor      )					->      Tensor:







       '''simple docstring'''



       return 0.5 * input * (1.0 + torch.tanh(math.sqrt(2.0 / math.pi      ) * (input + 0.044_715 * torch.pow(_A						,					3.0      ))      ))


class 			UpperCamelCase__	(     nn.Module):






 def __init__(      self	:Optional[int]						,					_A	:bool = False      )					->      Tuple:







       '''simple docstring'''



       super().__init__()
       if use_gelu_python:
             __A													=      self._gelu_python
       else:
             __A													=      nn.functional.gelu






 def 						lowercase_    (      self	:int						,					_A	:Tensor      )					->      Tensor:







       '''simple docstring'''



       return input * 0.5 * (1.0 + torch.erf(input / math.sqrt(2.0      )      ))






 def 						lowercase_    (      self	:Optional[int]						,					_A	:Tensor      )					->      Tensor:







       '''simple docstring'''



       return self.act(_A      )


class 			UpperCamelCase__	(     nn.Module):






 def 						lowercase_    (      self	:Tuple						,					_A	:Tensor      )					->      Tensor:







       '''simple docstring'''



       return 0.5 * input * (1.0 + torch.tanh(input * 0.7_978_845_608 * (1.0 + 0.044_715 * input * input)      ))


class 			UpperCamelCase__	(     nn.Module):






 def 						lowercase_    (      self	:Optional[int]						,					_A	:Tensor      )					->      Tensor:







       '''simple docstring'''



       return input * torch.sigmoid(1.702 * input      )


class 			UpperCamelCase__	(     nn.Module):






 def __init__(      self	:List[str]						,					_A	:float						,					_A	:float      )					->      List[Any]:







       '''simple docstring'''



       if min > max:
             raise ValueError(F'min should be < max (got min: {min}, max: {max})'      )

       super().__init__()
       __A													=      min
       __A													=      max






 def 						lowercase_    (      self	:Dict						,					_A	:Tensor      )					->      Tensor:







       '''simple docstring'''



       return torch.clip(gelu(_A      )						,					self.min						,					self.max      )


class 			UpperCamelCase__	(     nn.Module):






 def __init__(      self	:Dict      )					->      Optional[int]:







       '''simple docstring'''



       super().__init__()
       __A													=      math.sqrt(2 / math.pi      )






 def 						lowercase_    (      self	:Tuple						,					_A	:Tensor      )					->      Tensor:







       '''simple docstring'''



       return 0.5 * input * (1 + torch.tanh(self.precomputed_constant * (input + 0.044_715 * torch.pow(_A						,					3      ))      ))


class 			UpperCamelCase__	(     nn.Module):






 def 						lowercase_    (      self	:int						,					_A	:Tensor      )					->      Tensor:







       '''simple docstring'''



       return nn.functional.silu(_A      )


class 			UpperCamelCase__	(     nn.Module):






 def __init__(      self	:Any      )					->      Optional[int]:







       '''simple docstring'''



       super().__init__()
       if version.parse(torch.__version__      ) < version.parse('1.9.0'      ):
             __A													=      self._mish_python
       else:
             __A													=      nn.functional.mish






 def 						lowercase_    (      self	:Optional[Any]						,					_A	:Tensor      )					->      Tensor:







       '''simple docstring'''



       return input * torch.tanh(nn.functional.softplus(_A      )      )






 def 						lowercase_    (      self	:Dict						,					_A	:Tensor      )					->      Tensor:







       '''simple docstring'''



       return self.act(_A      )


class 			UpperCamelCase__	(     nn.Module):






 def 						lowercase_    (      self	:str						,					_A	:Tensor      )					->      Tensor:







       '''simple docstring'''



       return input


class 			UpperCamelCase__	(     nn.Module):






 def 						lowercase_    (      self	:List[str]						,					_A	:Optional[Any]						,					_A	:Tuple=0.707_107						,					_A	:List[str]=0.282_095      )					->      Union[str, Any]:







       '''simple docstring'''



       __A													=      (input - mu).div(sigma * math.sqrt(2.0      )      )
       return 0.5 * (1.0 + torch.erf(_A      ))


class 			UpperCamelCase__	(     nn.Module):






 def 						lowercase_    (      self	:Tuple						,					_A	:Any      )					->      Optional[Any]:







       '''simple docstring'''



       __A													=      nn.functional.relu(_A      )
       __A													=      torch.square(_A      )
       return squared


class 			UpperCamelCase__	(     SCREAMING_SNAKE_CASE):






 def __getitem__(      self	:Any						,					_A	:Optional[int]      )					->      Dict:







       '''simple docstring'''



       __A													=      super().__getitem__(_A      )
       __A						,   __A													=      content if isinstance(_A						,					_A      ) else (content, {})
       return cls(**_A      )
a__		: Optional[int]  							=							{
    "gelu": GELUActivation,
    "gelu_10": (ClippedGELUActivation, {"min": -1_0, "max": 1_0}),
    "gelu_fast": FastGELUActivation,
    "gelu_new": NewGELUActivation,
    "gelu_python": (GELUActivation, {"use_gelu_python": True}),
    "gelu_pytorch_tanh": PytorchGELUTanh,
    "gelu_accurate": AccurateGELUActivation,
    "laplace": LaplaceActivation,
    "linear": LinearActivation,
    "mish": MishActivation,
    "quick_gelu": QuickGELUActivation,
    "relu": nn.ReLU,
    "relu2": ReLUSquaredActivation,
    "relu6": nn.ReLUa,
    "sigmoid": nn.Sigmoid,
    "silu": SiLUActivation,
    "swish": SiLUActivation,
    "tanh": nn.Tanh,
}
a__		: str  							=							ClassInstantier(ACTaCLS)





def 							snake_case				(		UpperCAmelCase						)->      Any:







      """simple docstring"""
      if activation_string in ACTaFN:
            return ACTaFN[activation_string]
      else:
            raise KeyError(f'function {activation_string} not found in ACT2FN mapping {list(ACTaFN.keys()						)}'						)


# For backwards compatibility with: from activations import gelu_python
a__		: Dict  							=							get_activation("gelu_python")
a__		: int  							=							get_activation("gelu_new")
a__		: Optional[int]  							=							get_activation("gelu")
a__		: Optional[Any]  							=							get_activation("gelu_fast")
a__		: Optional[Any]  							=							get_activation("quick_gelu")
a__		: Dict  							=							get_activation("silu")
a__		: Dict  							=							get_activation("mish")
a__		: int  							=							get_activation("linear")








'''simple docstring'''






import json
import os
import subprocess
import sys
import warnings
from argparse import ArgumentParser
from contextlib import AbstractContextManager
from typing import Dict, List, Optional

import requests

from ..utils import logging
from . import BaseTransformersCLICommand


__lowercase	=    logging.get_logger(__name__)  # pylint: disable=invalid-name


__lowercase	=    '''lfs-multipart-upload'''

class 							_snake_case     (  lowerCAmelCase_ ):
	"""simple docstring"""





	@staticmethod
	def 	__A      (						UpperCamelCase_				: ArgumentParser      ):
			lowerCAmelCase_   :       Dict    							=parser.add_parser(
			    '''lfs-enable-largefiles'''					,						help=(
			        '''Deprecated: use `huggingface-cli` instead. Configure your repository to enable upload of files > 5GB.'''
			    )					,						)
			enable_parser.add_argument('''path'''					,						type=UpperCamelCase_					,						help='''Local path to repository you want to configure.'''      )
			enable_parser.set_defaults(func=lambda UpperCamelCase_      : LfsEnableCommand(UpperCamelCase_      )      )

			lowerCAmelCase_   :       str    							=parser.add_parser(
			    UpperCamelCase_					,						help=(
			        '''Deprecated: use `huggingface-cli` instead. '''
			        '''Command will get called by git-lfs, do not call it directly.'''
			    )					,						)
			upload_parser.set_defaults(func=lambda UpperCamelCase_      : LfsUploadCommand(UpperCamelCase_      )      )







class 							_snake_case     :
	"""simple docstring"""





	def __init__(						self				: Any					,						UpperCamelCase_				: str      ):
			lowerCAmelCase_   :       Any    							=args





	def 	__A      (						self				: Optional[int]      ):
			warnings.warn(
			    '''Managing repositories through transformers-cli is deprecated. Please use `huggingface-cli` instead.'''      )
			lowerCAmelCase_   :       Optional[Any]    							=os.path.abspath(self.args.path      )
			if not os.path.isdir(UpperCamelCase_      ):
					print('''This does not look like a valid git repo.'''      )
					exit(1      )
			subprocess.run(
			    '''git config lfs.customtransfer.multipart.path transformers-cli'''.split()					,						check=UpperCamelCase_					,						cwd=UpperCamelCase_      )
			subprocess.run(
			    F'git config lfs.customtransfer.multipart.args {LFS_MULTIPART_UPLOAD_COMMAND}'.split()					,						check=UpperCamelCase_					,						cwd=UpperCamelCase_					,						)
			print('''Local repo set up for largefiles'''      )







def 		SCREAMING_SNAKE_CASE__					(							_SCREAMING_SNAKE_CASE  ):
		lowerCAmelCase_   :       Optional[int]    							=json.dumps(_SCREAMING_SNAKE_CASE  ) + '''\n'''
		sys.stdout.write(_SCREAMING_SNAKE_CASE  )
		sys.stdout.flush()







def 		SCREAMING_SNAKE_CASE__					(							):
		lowerCAmelCase_   :       List[Any]    							=json.loads(sys.stdin.readline().strip()  )

		if "terminate" in (msg.get('''type'''  ), msg.get('''event'''  )):
				# terminate message received
				return None

		if msg.get('''event'''  ) not in ("download", "upload"):
				logger.critical('''Received unexpected message'''  )
				sys.exit(1  )

		return msg

class 							_snake_case     (  lowerCAmelCase_ ):
	"""simple docstring"""





	def __init__(						self				: Tuple					,						UpperCamelCase_				: str					,						UpperCamelCase_				: int					,						UpperCamelCase_				: int      ):
			lowerCAmelCase_   :       int    							=filepath
			lowerCAmelCase_   :       Optional[Any]    							=seek_from
			lowerCAmelCase_   :       Tuple    							=read_limit
			lowerCAmelCase_   :       Tuple    							=0




	def __enter__(						self				: int      ):
			lowerCAmelCase_   :       str    							=open(self.filepath					,						'''rb'''      )
			self.f.seek(self.seek_from      )
			return self




	def __len__(						self				: Optional[Any]      ):
			lowerCAmelCase_   :       Tuple    							=os.fstat(self.f.fileno()      ).st_size
			return min(self.read_limit					,						total_length - self.seek_from      )




	def 	__A      (						self				: Any					,						UpperCamelCase_				: str=-1      ):
			if self.n_seen >= self.read_limit:
					return b""
			lowerCAmelCase_   :       str    							=self.read_limit - self.n_seen
			lowerCAmelCase_   :       Optional[int]    							=self.f.read(remaining_amount if n < 0 else min(UpperCamelCase_					,						UpperCamelCase_      )      )
			self.n_seen += len(UpperCamelCase_      )
			return data




	def __iter__(						self				: int      ):
			yield self.read(n=4 * 1024 * 1024      )





	def __exit__(						self				: Tuple					,						*UpperCamelCase_				: Tuple      ):
			self.f.close()







class 							_snake_case     :
	"""simple docstring"""





	def __init__(						self				: List[str]					,						UpperCamelCase_				: List[str]      ):
			lowerCAmelCase_   :       int    							=args





	def 	__A      (						self				: List[Any]      ):
			# Immediately after invoking a custom transfer process, git-lfs
			# sends initiation data to the process over stdin.
			# This tells the process useful information about the configuration.
			lowerCAmelCase_   :       Union[str, Any]    							=json.loads(sys.stdin.readline().strip()      )
			if not (init_msg.get('''event'''      ) == "init" and init_msg.get('''operation'''      ) == "upload"):
					write_msg({'''error''': {'''code''': 32, '''message''': '''Wrong lfs init operation'''}}      )
					sys.exit(1      )

			# The transfer process should use the information it needs from the
			# initiation structure, and also perform any one-off setup tasks it
			# needs to do. It should then respond on stdout with a simple empty
			# confirmation structure, as follows:
			write_msg({}      )

			# After the initiation exchange, git-lfs will send any number of
			# transfer requests to the stdin of the transfer process, in a serial sequence.
			while True:
					lowerCAmelCase_   :       List[Any]    							=read_msg()
					if msg is None:
							# When all transfers have been processed, git-lfs will send
							# a terminate event to the stdin of the transfer process.
							# On receiving this message the transfer process should
							# clean up and terminate. No response is expected.
							sys.exit(0      )

					lowerCAmelCase_   :       List[Any]    							=msg['''oid''']
					lowerCAmelCase_   :       List[str]    							=msg['''path''']
					lowerCAmelCase_   :       int    							=msg['''action''']['''href''']
					lowerCAmelCase_   :       List[Any]    							=msg['''action''']['''header''']
					lowerCAmelCase_   :       Union[str, Any]    							=int(header.pop('''chunk_size'''      )      )
					lowerCAmelCase_   :       List[str]    							=list(header.values()      )

					lowerCAmelCase_   :       Dict    							=[]
					for i, presigned_url in enumerate(UpperCamelCase_      ):
							with FileSlice(UpperCamelCase_					,						seek_from=i * chunk_size					,						read_limit=UpperCamelCase_      ) as data:
									lowerCAmelCase_   :       Optional[Any]    							=requests.put(UpperCamelCase_					,						data=UpperCamelCase_      )
									r.raise_for_status()
									parts.append(
									    {
									        '''etag''': r.headers.get('''etag'''      ),
									        '''partNumber''': i + 1,
									    }      )
									# In order to support progress reporting while data is uploading / downloading,
									# the transfer process should post messages to stdout
									write_msg(
									    {
									        '''event''': '''progress''',
									        '''oid''': oid,
									        '''bytesSoFar''': (i + 1) * chunk_size,
									        '''bytesSinceLast''': chunk_size,
									    }      )
									# Not precise but that's ok.

					lowerCAmelCase_   :       Optional[Any]    							=requests.post(
					    UpperCamelCase_					,						json={
					        '''oid''': oid,
					        '''parts''': parts,
					    }					,						)
					r.raise_for_status()

					write_msg({'''event''': '''complete''', '''oid''': oid}      )






