




import argparse
from pathlib import Path

import torch

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


logging.set_verbosity_info()
_lowerCamelCase	:		str							       =   logging.get_logger(__name__)







def SCREAMING_SNAKE_CASE				(       lowercase_						)   ->       Union[str, Any]:



       """simple docstring"""

       A__       =    torch.load(lowercase_ ,				map_location='''cpu'''						)
       if "model" in sd.keys():
              A__       =    torch.load(lowercase_ ,				map_location='''cpu'''						)['''model''']

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

       A__       =    {
           '''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:
                     A__       =    sd.pop(lowercase_						)

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

                     A__       =    key.replace('''.qkv_proj.''' ,				'''.q_proj.'''						)
                     A__       =    key.replace('''.qkv_proj.''' ,				'''.k_proj.'''						)
                     A__       =    key.replace('''.qkv_proj.''' ,				'''.v_proj.'''						)

                     A__       =    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
                     A__ ,							A__ ,							A__       =    torch.split(lowercase_ ,				depth // 3 ,				dim=0						)

                     A__       =    q
                     A__       =    k
                     A__       =    v
                     del sd[key]

       return sd







@torch.no_grad()
def SCREAMING_SNAKE_CASE				(       lowercase_ ,				lowercase_ ,				lowercase_=None						)   ->       Optional[int]:



       """simple docstring"""

       A__       =    load_checkpoint(lowercase_						)

       if config is not None:
              A__       =    OPTConfig.from_pretrained(lowercase_						)
       else:
              A__       =    OPTConfig()

       A__       =    OPTModel(lowercase_						).half().eval()
       model.load_state_dict(lowercase_						)

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


if __name__ == "__main__":
  _lowerCamelCase	:		List[Any]							       =   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	:		str							       =   parser.parse_args()
  convert_opt_checkpoint(args.fairseq_path, args.pytorch_dump_folder_path, config=args.hf_config)




"""simple docstring"""





import json
import os
from pathlib import Path

import pytest

from datasets.download.download_config import DownloadConfig
from datasets.download.download_manager import DownloadManager
from datasets.utils.file_utils import hash_url_to_filename


_a														=		"""http://www.mocksite.com/file1.txt"""
_a														=		"""\"text\": [\"foo\", \"foo\"]"""
_a														=		"""6d8ce9aa78a471c7477201efbeabd3bb01ac2e7d100a6dc024ba1608361f90a8"""






class     _UpperCAmelCase:
		lowercase__						=      2_00
		lowercase__						=      {'Content-Length': '100'}
		lowercase__						=      {}



		def 						UpperCAmelCase							(					self				,		**__a)       ->       Optional[int]:






							'''simple docstring'''
							return [bytes(__a				,		'''utf-8''')]





def       lowerCamelCase__		(			*__snake_case,     **__snake_case	)							->		int:


					"""simple docstring"""





					return MockResponse()



@pytest.mark.parametrize('''urls_type''',     [str, list, dict]	)
def       lowerCamelCase__		(			__snake_case,     __snake_case,     __snake_case	)							->		Dict:


					"""simple docstring"""





					import requests

					monkeypatch.setattr(__snake_case,     '''request''',     __snake_case	)

					_UpperCamelCase							 =  URL
					if issubclass(__snake_case,     __snake_case	):
										_UpperCamelCase							 =  url
					elif issubclass(__snake_case,     __snake_case	):
										_UpperCamelCase							 =  [url]
					elif issubclass(__snake_case,     __snake_case	):
										_UpperCamelCase							 =  {'''train''': url}
					_UpperCamelCase							 =  '''dummy'''
					_UpperCamelCase							 =  '''downloads'''
					_UpperCamelCase							 =  tmp_path
					_UpperCamelCase							 =  DownloadConfig(
					    cache_dir=os.path.join(__snake_case,     __snake_case	),     use_etag=__snake_case,     )
					_UpperCamelCase							 =  DownloadManager(dataset_name=__snake_case,     download_config=__snake_case	)
					_UpperCamelCase							 =  dl_manager.download(__snake_case	)
					_UpperCamelCase							 =  urls
					for downloaded_paths in [downloaded_paths]:
										if isinstance(__snake_case,     __snake_case	):
															_UpperCamelCase							 =  [downloaded_paths]
															_UpperCamelCase							 =  [urls]
										elif isinstance(__snake_case,     __snake_case	):
															assert "train" in downloaded_paths.keys()
															_UpperCamelCase							 =  downloaded_paths.values()
															_UpperCamelCase							 =  urls.values()
										assert downloaded_paths
										for downloaded_path, input_url in zip(__snake_case,     __snake_case	):
															assert downloaded_path == dl_manager.downloaded_paths[input_url]
															_UpperCamelCase							 =  Path(__snake_case	)
															_UpperCamelCase							 =  downloaded_path.parts
															assert parts[-1] == HASH
															assert parts[-2] == cache_subdir
															assert downloaded_path.exists()
															_UpperCamelCase							 =  downloaded_path.read_text()
															assert content == CONTENT
															_UpperCamelCase							 =  downloaded_path.with_suffix('''.json'''	)
															assert metadata_downloaded_path.exists()
															_UpperCamelCase							 =  json.loads(metadata_downloaded_path.read_text()	)
															assert metadata_content == {"url": URL, "etag": None}



@pytest.mark.parametrize('''paths_type''',     [str, list, dict]	)
def       lowerCamelCase__		(			__snake_case,     __snake_case,     __snake_case	)							->		List[str]:


					"""simple docstring"""





					_UpperCamelCase							 =  str(__snake_case	)
					if issubclass(__snake_case,     __snake_case	):
										_UpperCamelCase							 =  filename
					elif issubclass(__snake_case,     __snake_case	):
										_UpperCamelCase							 =  [filename]
					elif issubclass(__snake_case,     __snake_case	):
										_UpperCamelCase							 =  {'''train''': filename}
					_UpperCamelCase							 =  '''dummy'''
					_UpperCamelCase							 =  xz_file.parent
					_UpperCamelCase							 =  '''extracted'''
					_UpperCamelCase							 =  DownloadConfig(
					    cache_dir=__snake_case,     use_etag=__snake_case,     )
					_UpperCamelCase							 =  DownloadManager(dataset_name=__snake_case,     download_config=__snake_case	)
					_UpperCamelCase							 =  dl_manager.extract(__snake_case	)
					_UpperCamelCase							 =  paths
					for extracted_paths in [extracted_paths]:
										if isinstance(__snake_case,     __snake_case	):
															_UpperCamelCase							 =  [extracted_paths]
															_UpperCamelCase							 =  [paths]
										elif isinstance(__snake_case,     __snake_case	):
															assert "train" in extracted_paths.keys()
															_UpperCamelCase							 =  extracted_paths.values()
															_UpperCamelCase							 =  paths.values()
										assert extracted_paths
										for extracted_path, input_path in zip(__snake_case,     __snake_case	):
															assert extracted_path == dl_manager.extracted_paths[input_path]
															_UpperCamelCase							 =  Path(__snake_case	)
															_UpperCamelCase							 =  extracted_path.parts
															assert parts[-1] == hash_url_to_filename(__snake_case,     etag=__snake_case	)
															assert parts[-2] == extracted_subdir
															assert extracted_path.exists()
															_UpperCamelCase							 =  extracted_path.read_text()
															_UpperCamelCase							 =  text_file.read_text()
															assert extracted_file_content == expected_file_content



def       lowerCamelCase__		(			__snake_case,     __snake_case	)							->		Optional[Any]:


					"""simple docstring"""





					assert path.endswith('''.jsonl'''	)
					for num_items, line in enumerate(__snake_case,     start=1	):
										_UpperCamelCase							 =  json.loads(line.decode('''utf-8'''	)	)
										assert item.keys() == {"col_1", "col_2", "col_3"}
					assert num_items == 4



@pytest.mark.parametrize('''archive_jsonl''',     ['''tar_jsonl_path''', '''zip_jsonl_path''']	)
def       lowerCamelCase__		(			__snake_case,     __snake_case	)							->		int:


					"""simple docstring"""





					_UpperCamelCase							 =  request.getfixturevalue(__snake_case	)
					_UpperCamelCase							 =  DownloadManager()
					for num_jsonl, (path, file) in enumerate(dl_manager.iter_archive(__snake_case	),     start=1	):
										_test_jsonl(__snake_case,     __snake_case	)
					assert num_jsonl == 2



@pytest.mark.parametrize('''archive_nested_jsonl''',     ['''tar_nested_jsonl_path''', '''zip_nested_jsonl_path''']	)
def       lowerCamelCase__		(			__snake_case,     __snake_case	)							->		int:


					"""simple docstring"""





					_UpperCamelCase							 =  request.getfixturevalue(__snake_case	)
					_UpperCamelCase							 =  DownloadManager()
					for num_tar, (path, file) in enumerate(dl_manager.iter_archive(__snake_case	),     start=1	):
										for num_jsonl, (subpath, subfile) in enumerate(dl_manager.iter_archive(__snake_case	),     start=1	):
															_test_jsonl(__snake_case,     __snake_case	)
					assert num_tar == 1
					assert num_jsonl == 2



def       lowerCamelCase__		(			__snake_case	)							->		Dict:


					"""simple docstring"""





					_UpperCamelCase							 =  DownloadManager()
					for num_file, file in enumerate(dl_manager.iter_files(__snake_case	),     start=1	):
										assert os.path.basename(__snake_case	) == ("test.txt" if num_file == 1 else "train.txt")
					assert num_file == 2






