


"""simple docstring"""



import argparse
from pathlib import Path

import torch

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


logging.set_verbosity_info()
__snake_case         =					logging.get_logger(__name__)







def 						__lowerCAmelCase		(		lowercase						:						int				)			->		Optional[Any]:


    """simple docstring"""





    snake_case					:   Dict         =					torch.load(lowercase		,							map_location="cpu"				)
    if "model" in sd.keys():
        snake_case					:   Tuple         =					torch.load(lowercase		,							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(lowercase				)

    snake_case					:   int         =					{
        "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					:   Tuple         =					sd.pop(lowercase				)

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

            snake_case					:   List[str]         =					key.replace(".qkv_proj."		,							".q_proj."				)
            snake_case					:   Dict         =					key.replace(".qkv_proj."		,							".k_proj."				)
            snake_case					:   List[str]         =					key.replace(".qkv_proj."		,							".v_proj."				)

            snake_case					:   Optional[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      ,snake_case      ,snake_case					:   Union[str, Any]         =					torch.split(lowercase		,							depth // 3		,							dim=0				)

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

    return sd







@torch.no_grad()
def 						__lowerCAmelCase		(		lowercase						:						Dict		,							lowercase						:						Optional[int]		,							lowercase						:						Dict=None				)			->		Union[str, Any]:


    """simple docstring"""





    snake_case					:   Dict         =					load_checkpoint(lowercase				)

    if config is not None:
        snake_case					:   List[str]         =					OPTConfig.from_pretrained(lowercase				)
    else:
        snake_case					:   List[str]         =					OPTConfig()

    snake_case					:   Any         =					OPTModel(lowercase				).half().eval()
    model.load_state_dict(lowercase				)

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


if __name__ == "__main__":
  __snake_case         =					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.""")
  __snake_case         =					parser.parse_args()
  convert_opt_checkpoint(args.fairseq_path, args.pytorch_dump_folder_path, config=args.hf_config)









"""simple docstring"""



# this script reports modified .py files under the desired list of top-level sub-dirs passed as a list of arguments, e.g.:
#   python ./utils/get_modified_files.py utils src tests examples
#
# it uses git to find the forking point and which files were modified - i.e. files not under git won't be considered
# since the output of this script is fed into Makefile commands it doesn't print a newline after the results

import re
import subprocess
import sys


__snake_case         =					subprocess.check_output("""git merge-base main HEAD""".split()).decode("""utf-8""")
__snake_case         =					(
    subprocess.check_output(F'''git diff --diff-filter=d --name-only {fork_point_sha}'''.split()).decode("""utf-8""").split()
)

__snake_case         =					"""|""".join(sys.argv[1:])
__snake_case         =					re.compile(RF'''^({joined_dirs}).*?\.py$''')

__snake_case         =					[x for x in modified_files if regex.match(x)]
print(""" """.join(relevant_modified_files), end="""""")





