'''simple docstring'''





import argparse
from pathlib import Path

import torch

from transformers import OPTConfig, OPTModel
from transformers.utils import logging


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


def     __lowerCAmelCase						(       a_		)      ->	Optional[Any]:





     '''simple docstring'''





     SCREAMING_SNAKE_CASE					:			List[str]    	=       torch.load(a_       ,      map_location='cpu'		)
     if "model" in sd.keys():
          SCREAMING_SNAKE_CASE					:			str    	=       torch.load(a_       ,      map_location='cpu'		)['model']

     # pop unnecessary weights
     SCREAMING_SNAKE_CASE					:			Dict    	=       [
         'decoder.version',
         'decoder.output_projection.weight',
     ]
     for key in keys_to_delete:
          if key in sd:
               sd.pop(a_		)

     SCREAMING_SNAKE_CASE					:			Optional[Any]    	=       {
         'decoder.project_in_dim.weight': 'decoder.project_in.weight',
         'decoder.project_out_dim.weight': 'decoder.project_out.weight',
         'decoder.layer_norm.weight': 'decoder.final_layer_norm.weight',
         'decoder.layer_norm.bias': 'decoder.final_layer_norm.bias',
     }
     for old_key, new_key in keys_to_rename.items():
          if old_key in sd:
               SCREAMING_SNAKE_CASE					:			Tuple    	=       sd.pop(a_		)

     SCREAMING_SNAKE_CASE					:			List[Any]    	=       list(sd.keys()		)
     for key in keys:
          if ".qkv_proj." in key:
               SCREAMING_SNAKE_CASE					:			Optional[Any]    	=       sd[key]
               # We split QKV in separate Q,K,V

               SCREAMING_SNAKE_CASE					:			str    	=       key.replace('.qkv_proj.'       ,      '.q_proj.'		)
               SCREAMING_SNAKE_CASE					:			Union[str, Any]    	=       key.replace('.qkv_proj.'       ,      '.k_proj.'		)
               SCREAMING_SNAKE_CASE					:			str    	=       key.replace('.qkv_proj.'       ,      '.v_proj.'		)

               SCREAMING_SNAKE_CASE					:			List[Any]    	=       value.shape[0]
               assert depth % 3 == 0
               # `SequeuceParallelTransformerBlock` has QKV weight is separated in K,V,Q despite the naming:
               # https://cs.github.com/facebookresearch/metaseq/blob/51871bd73cd04c038f239ea2a26db1d7f6b37927/metaseq/modules/sequence_parallel_transformer_layer.py#L97
               SCREAMING_SNAKE_CASE					:			Dict    	=       torch.split(a_       ,      depth // 3       ,      dim=0		)

               SCREAMING_SNAKE_CASE					:			str    	=       q
               SCREAMING_SNAKE_CASE					:			Optional[Any]    	=       k
               SCREAMING_SNAKE_CASE					:			List[Any]    	=       v
               del sd[key]

     return sd


@torch.no_grad()
def     __lowerCAmelCase						(       a_       ,      a_       ,      a_=None		)      ->	List[Any]:





     '''simple docstring'''





     SCREAMING_SNAKE_CASE					:			Any    	=       load_checkpoint(a_		)

     if config is not None:
          SCREAMING_SNAKE_CASE					:			Any    	=       OPTConfig.from_pretrained(a_		)
     else:
          SCREAMING_SNAKE_CASE					:			Optional[int]    	=       OPTConfig()

     SCREAMING_SNAKE_CASE					:			Optional[int]    	=       OPTModel(a_		).half().eval()
     model.load_state_dict(a_		)

     # Check results
     Path(a_		).mkdir(exist_ok=a_		)
     model.save_pretrained(a_		)


if __name__ == "__main__":
 _lowerCAmelCase  :Dict  				=    argparse.ArgumentParser()
 # Required parameters
 parser.add_argument(
     """--fairseq_path""",
     type=str,
     help=(
         """path to fairseq checkpoint in correct format. You can find all checkpoints in the correct format here:"""
         """ https://huggingface.co/models?other=opt_metasq"""
     ),
 )
 parser.add_argument("""--pytorch_dump_folder_path""", default=None, type=str, help="""Path to the output PyTorch model.""")
 parser.add_argument("""--hf_config""", default=None, type=str, help="""Define HF config.""")
 _lowerCAmelCase  :Tuple  				=    parser.parse_args()
 convert_opt_checkpoint(args.fairseq_path, args.pytorch_dump_folder_path, config=args.hf_config)




'''simple docstring'''





import copy
import json
import os
import tempfile

from transformers import is_torch_available

from .test_configuration_utils import config_common_kwargs






class 				UpperCAmelCase (       _SCREAMING_SNAKE_CASE ):




    '''simple docstring'''







    def __init__(       self    ,							lowercase__    ,							lowercase__=None    ,							lowercase__=True    ,							lowercase__=None    ,							**lowercase__ )							-> Optional[Any]:
         SCREAMING_SNAKE_CASE					:			int    	=       parent
         SCREAMING_SNAKE_CASE					:			str    	=       config_class
         SCREAMING_SNAKE_CASE					:			Union[str, Any]    	=       has_text_modality
         SCREAMING_SNAKE_CASE					:			Any    	=       kwargs
         SCREAMING_SNAKE_CASE					:			Union[str, Any]    	=       common_properties






    def       _UpperCamelCase    (       self )							-> Union[str, Any]:
         SCREAMING_SNAKE_CASE					:			Optional[int]    	=       self.config_class(**self.inputs_dict )
         SCREAMING_SNAKE_CASE					:			int    	=       (
             ['hidden_size', 'num_attention_heads', 'num_hidden_layers']
             if self.common_properties is None
             else self.common_properties
         )

         # Add common fields for text models
         if self.has_text_modality:
              common_properties.extend(['vocab_size'] )

         # Test that config has the common properties as getters
         for prop in common_properties:
              self.parent.assertTrue(hasattr(lowercase__    ,							lowercase__ )    ,							msg=F"""`{prop}` does not exist""" )

         # Test that config has the common properties as setter
         for idx, name in enumerate(lowercase__ ):
              try:
                   setattr(lowercase__    ,							lowercase__    ,							lowercase__ )
                   self.parent.assertEqual(
                       getattr(lowercase__    ,							lowercase__ )    ,							lowercase__    ,							msg=F"""`{name} value {idx} expected, but was {getattr(lowercase__    ,							lowercase__ )}""" )
              except NotImplementedError:
                   # Some models might not be able to implement setters for common_properties
                   # In that case, a NotImplementedError is raised
                   pass

        # Test if config class can be called with Config(prop_name=..)
         for idx, name in enumerate(lowercase__ ):
              try:
                   SCREAMING_SNAKE_CASE					:			Optional[int]    	=       self.config_class(**{name: idx} )
                   self.parent.assertEqual(
                       getattr(lowercase__    ,							lowercase__ )    ,							lowercase__    ,							msg=F"""`{name} value {idx} expected, but was {getattr(lowercase__    ,							lowercase__ )}""" )
              except NotImplementedError:
                   # Some models might not be able to implement setters for common_properties
                   # In that case, a NotImplementedError is raised
                   pass






    def       _UpperCamelCase    (       self )							-> List[str]:
         SCREAMING_SNAKE_CASE					:			Optional[Any]    	=       self.config_class(**self.inputs_dict )
         SCREAMING_SNAKE_CASE					:			Any    	=       json.loads(config.to_json_string() )
         for key, value in self.inputs_dict.items():
              self.parent.assertEqual(obj[key]    ,							lowercase__ )






    def       _UpperCamelCase    (       self )							-> Optional[int]:
         SCREAMING_SNAKE_CASE					:			Tuple    	=       self.config_class(**self.inputs_dict )

         with tempfile.TemporaryDirectory() as tmpdirname:
              SCREAMING_SNAKE_CASE					:			List[str]    	=       os.path.join(lowercase__    ,							'config.json' )
              config_first.to_json_file(lowercase__ )
              SCREAMING_SNAKE_CASE					:			Union[str, Any]    	=       self.config_class.from_json_file(lowercase__ )

         self.parent.assertEqual(config_second.to_dict()    ,							config_first.to_dict() )






    def       _UpperCamelCase    (       self )							-> Dict:
         SCREAMING_SNAKE_CASE					:			Optional[Any]    	=       self.config_class(**self.inputs_dict )

         with tempfile.TemporaryDirectory() as tmpdirname:
              config_first.save_pretrained(lowercase__ )
              SCREAMING_SNAKE_CASE					:			Optional[int]    	=       self.config_class.from_pretrained(lowercase__ )

         self.parent.assertEqual(config_second.to_dict()    ,							config_first.to_dict() )






    def       _UpperCamelCase    (       self )							-> int:
         SCREAMING_SNAKE_CASE					:			List[Any]    	=       self.config_class(**self.inputs_dict )

         SCREAMING_SNAKE_CASE					:			Optional[int]    	=       'test'
         with tempfile.TemporaryDirectory() as tmpdirname:
              SCREAMING_SNAKE_CASE					:			Tuple    	=       os.path.join(lowercase__    ,							lowercase__ )
              config_first.save_pretrained(lowercase__ )
              SCREAMING_SNAKE_CASE					:			Dict    	=       self.config_class.from_pretrained(lowercase__    ,							subfolder=lowercase__ )

         self.parent.assertEqual(config_second.to_dict()    ,							config_first.to_dict() )






    def       _UpperCamelCase    (       self )							-> List[Any]:
         SCREAMING_SNAKE_CASE					:			Dict    	=       self.config_class(**self.inputs_dict    ,							num_labels=5 )
         self.parent.assertEqual(len(config.idalabel )    ,							5 )
         self.parent.assertEqual(len(config.labelaid )    ,							5 )

         SCREAMING_SNAKE_CASE					:			Union[str, Any]    	=       3
         self.parent.assertEqual(len(config.idalabel )    ,							3 )
         self.parent.assertEqual(len(config.labelaid )    ,							3 )






    def       _UpperCamelCase    (       self )							-> Dict:
         if self.config_class.is_composition:
              return
         SCREAMING_SNAKE_CASE					:			int    	=       self.config_class()
         self.parent.assertIsNotNone(lowercase__ )






    def       _UpperCamelCase    (       self )							-> Tuple:
         SCREAMING_SNAKE_CASE					:			Union[str, Any]    	=       copy.deepcopy(lowercase__ )
         SCREAMING_SNAKE_CASE					:			Any    	=       self.config_class(**lowercase__ )
         SCREAMING_SNAKE_CASE					:			str    	=       []
         for key, value in config_common_kwargs.items():
              if key == "torch_dtype":
                   if not is_torch_available():
                        continue
                   else:
                        import torch

                        if config.torch_dtype != torch.floataa:
                             wrong_values.append(('torch_dtype', config.torch_dtype, torch.floataa) )
              elif getattr(lowercase__    ,							lowercase__ ) != value:
                   wrong_values.append((key, getattr(lowercase__    ,							lowercase__ ), value) )

         if len(lowercase__ ) > 0:
              SCREAMING_SNAKE_CASE					:			List[Any]    	=       '\n'.join([F"""- {v[0]}: got {v[1]} instead of {v[2]}""" for v in wrong_values] )
              raise ValueError(F"""The following keys were not properly set in the config:\n{errors}""" )






    def       _UpperCamelCase    (       self )							-> Optional[int]:
         self.create_and_test_config_common_properties()
         self.create_and_test_config_to_json_string()
         self.create_and_test_config_to_json_file()
         self.create_and_test_config_from_and_save_pretrained()
         self.create_and_test_config_from_and_save_pretrained_subfolder()
         self.create_and_test_config_with_num_labels()
         self.check_config_can_be_init_without_params()
         self.check_config_arguments_init()



