






import argparse
from pathlib import Path

import torch

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


logging.set_verbosity_info()
__lowerCamelCase      :    List[Any]   		=   logging.get_logger(__name__)







def   SCREAMING_SNAKE_CASE       (				snake_case_      :							int     ):
 snake_case__				:   List[Any]     =						torch.load(snake_case_  ,						map_location="cpu"     )
 if "model" in sd.keys():
  snake_case__				:   List[Any]     =						torch.load(snake_case_  ,						map_location="cpu"     )["model"]

 # pop unnecessary weights
 snake_case__				:   List[str]     =						[
     "decoder.version",
     "decoder.output_projection.weight",
 ]
 for key in keys_to_delete:
  if key in sd:
   sd.pop(snake_case_     )

 snake_case__				:   Union[str, 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:
   snake_case__				:   Optional[int]     =						sd.pop(snake_case_     )

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

   snake_case__				:   List[Any]     =						key.replace(".qkv_proj."  ,						".q_proj."     )
   snake_case__				:   Any     =						key.replace(".qkv_proj."  ,						".k_proj."     )
   snake_case__				:   Optional[int]     =						key.replace(".qkv_proj."  ,						".v_proj."     )

   snake_case__				:   int     =						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
   snake_case__				:   Dict     =						torch.split(snake_case_  ,						depth // 3  ,						dim=0     )

   snake_case__				:   Union[str, Any]     =						q
   snake_case__				:   Optional[Any]     =						k
   snake_case__				:   Union[str, Any]     =						v
   del sd[key]

 return sd







@torch.no_grad()
def   SCREAMING_SNAKE_CASE       (				snake_case_      :							Union[str, Any]  ,						snake_case_      :							List[Any]  ,						snake_case_      :							Any=None     ):
 snake_case__				:   int     =						load_checkpoint(snake_case_     )

 if config is not None:
  snake_case__				:   Tuple     =						OPTConfig.from_pretrained(snake_case_     )
 else:
  snake_case__				:   Tuple     =						OPTConfig()

 snake_case__				:   Union[str, Any]     =						OPTModel(snake_case_     ).half().eval()
 model.load_state_dict(snake_case_     )

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


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      :    Optional[int]   		=   parser.parse_args()
 convert_opt_checkpoint(args.fairseq_path, args.pytorch_dump_folder_path, config=args.hf_config)











# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run

import sys
import warnings
from os.path import abspath, dirname, join


# allow having multiple repository checkouts and not needing to remember to rerun
# 'pip install -e .[dev]' when switching between checkouts and running tests.
__lowerCamelCase      :    Dict   		=   abspath(join(dirname(dirname(__file__)), """src"""))
sys.path.insert(1, git_repo_path)

# silence FutureWarning warnings in tests since often we can't act on them until
# they become normal warnings - i.e. the tests still need to test the current functionality
warnings.simplefilter(action="""ignore""", category=FutureWarning)







def   SCREAMING_SNAKE_CASE       (				snake_case_      :							str     ):
	from diffusers.utils.testing_utils import pytest_addoption_shared

	pytest_addoption_shared(snake_case_     )







def   SCREAMING_SNAKE_CASE       (				snake_case_      :							Any     ):
	from diffusers.utils.testing_utils import pytest_terminal_summary_main

	snake_case__				:   Optional[int]     =						terminalreporter.config.getoption("--make-reports"     )
	if make_reports:
		pytest_terminal_summary_main(snake_case_  ,						id=snake_case_     )



