





'''simple docstring'''

import argparse
from pathlib import Path

import torch

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


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







def  a__    (    lowercase :					Tuple				)		->		Tuple:





					"""simple docstring"""

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

					# pop unnecessary weights
					_UpperCamelCase       =	[
					    "decoder.version",
					    "decoder.output_projection.weight",
					]
					for key in keys_to_delete:
										if key in sd:
															sd.pop(__SCREAMING_SNAKE_CASE				)

					_UpperCamelCase       =	{
					    "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:
															_UpperCamelCase       =	sd.pop(__SCREAMING_SNAKE_CASE				)

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

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

															_UpperCamelCase       =	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
															_UpperCamelCase       =	torch.split(__SCREAMING_SNAKE_CASE, depth // 3, dim=0				)

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

					return sd







@torch.no_grad()
def  a__    (    lowercase :					Optional[Any], lowercase :					List[str], lowercase :					Tuple=None				)		->		Union[str, Any]:





					"""simple docstring"""

					_UpperCamelCase       =	load_checkpoint(__SCREAMING_SNAKE_CASE				)

					if config is not None:
										_UpperCamelCase       =	OPTConfig.from_pretrained(__SCREAMING_SNAKE_CASE				)
					else:
										_UpperCamelCase       =	OPTConfig()

					_UpperCamelCase       =	OPTModel(__SCREAMING_SNAKE_CASE				).half().eval()
					model.load_state_dict(__SCREAMING_SNAKE_CASE				)

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


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










'''simple docstring'''

import unittest

from diffusers.pipelines.pipeline_utils import is_safetensors_compatible
class     __lowerCAmelCase					(   unittest.TestCase			):






       """simple docstring"""





       def snake_case__						(							self       :		Tuple					)   ->					int:

            '''simple docstring'''




            _UpperCamelCase       =	[
                '''safety_checker/pytorch_model.bin''',
                '''safety_checker/model.safetensors''',
                '''vae/diffusion_pytorch_model.bin''',
                '''vae/diffusion_pytorch_model.safetensors''',
                '''text_encoder/pytorch_model.bin''',
                '''text_encoder/model.safetensors''',
                '''unet/diffusion_pytorch_model.bin''',
                '''unet/diffusion_pytorch_model.safetensors''',
            ]
            self.assertTrue(is_safetensors_compatible(lowerCAmelCase__					)					)





       def snake_case__						(							self       :		int					)   ->					Tuple:

            '''simple docstring'''




            _UpperCamelCase       =	[
                '''unet/diffusion_pytorch_model.bin''',
                '''unet/diffusion_pytorch_model.safetensors''',
            ]
            self.assertTrue(is_safetensors_compatible(lowerCAmelCase__					)					)





       def snake_case__						(							self       :		Optional[Any]					)   ->					List[str]:

            '''simple docstring'''




            _UpperCamelCase       =	[
                '''safety_checker/pytorch_model.bin''',
                '''safety_checker/model.safetensors''',
                '''vae/diffusion_pytorch_model.bin''',
                '''vae/diffusion_pytorch_model.safetensors''',
                '''text_encoder/pytorch_model.bin''',
                '''text_encoder/model.safetensors''',
                '''unet/diffusion_pytorch_model.bin''',
                # Removed: 'unet/diffusion_pytorch_model.safetensors',
            ]
            self.assertFalse(is_safetensors_compatible(lowerCAmelCase__					)					)





       def snake_case__						(							self       :		List[Any]					)   ->					List[Any]:

            '''simple docstring'''




            _UpperCamelCase       =	[
                '''text_encoder/pytorch_model.bin''',
                '''text_encoder/model.safetensors''',
            ]
            self.assertTrue(is_safetensors_compatible(lowerCAmelCase__					)					)





       def snake_case__						(							self       :		Dict					)   ->					Dict:

            '''simple docstring'''




            _UpperCamelCase       =	[
                '''safety_checker/pytorch_model.bin''',
                '''safety_checker/model.safetensors''',
                '''vae/diffusion_pytorch_model.bin''',
                '''vae/diffusion_pytorch_model.safetensors''',
                '''text_encoder/pytorch_model.bin''',
                # Removed: 'text_encoder/model.safetensors',
                '''unet/diffusion_pytorch_model.bin''',
                '''unet/diffusion_pytorch_model.safetensors''',
            ]
            self.assertFalse(is_safetensors_compatible(lowerCAmelCase__					)					)





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

            '''simple docstring'''




            _UpperCamelCase       =	[
                '''safety_checker/pytorch_model.fp16.bin''',
                '''safety_checker/model.fp16.safetensors''',
                '''vae/diffusion_pytorch_model.fp16.bin''',
                '''vae/diffusion_pytorch_model.fp16.safetensors''',
                '''text_encoder/pytorch_model.fp16.bin''',
                '''text_encoder/model.fp16.safetensors''',
                '''unet/diffusion_pytorch_model.fp16.bin''',
                '''unet/diffusion_pytorch_model.fp16.safetensors''',
            ]
            _UpperCamelCase       =	'''fp16'''
            self.assertTrue(is_safetensors_compatible(lowerCAmelCase__	,			variant=lowerCAmelCase__					)					)





       def snake_case__						(							self       :		Optional[Any]					)   ->					Dict:

            '''simple docstring'''




            _UpperCamelCase       =	[
                '''unet/diffusion_pytorch_model.fp16.bin''',
                '''unet/diffusion_pytorch_model.fp16.safetensors''',
            ]
            _UpperCamelCase       =	'''fp16'''
            self.assertTrue(is_safetensors_compatible(lowerCAmelCase__	,			variant=lowerCAmelCase__					)					)





       def snake_case__						(							self       :		Tuple					)   ->					Optional[Any]:

            '''simple docstring'''




            _UpperCamelCase       =	[
                '''unet/diffusion_pytorch_model.bin''',
                '''unet/diffusion_pytorch_model.safetensors''',
            ]
            _UpperCamelCase       =	'''fp16'''
            self.assertTrue(is_safetensors_compatible(lowerCAmelCase__	,			variant=lowerCAmelCase__					)					)





       def snake_case__						(							self       :		Tuple					)   ->					Union[str, Any]:

            '''simple docstring'''




            _UpperCamelCase       =	[
                '''safety_checker/pytorch_model.fp16.bin''',
                '''safety_checker/model.fp16.safetensors''',
                '''vae/diffusion_pytorch_model.fp16.bin''',
                '''vae/diffusion_pytorch_model.fp16.safetensors''',
                '''text_encoder/pytorch_model.fp16.bin''',
                '''text_encoder/model.fp16.safetensors''',
                '''unet/diffusion_pytorch_model.fp16.bin''',
                # Removed: 'unet/diffusion_pytorch_model.fp16.safetensors',
            ]
            _UpperCamelCase       =	'''fp16'''
            self.assertFalse(is_safetensors_compatible(lowerCAmelCase__	,			variant=lowerCAmelCase__					)					)





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

            '''simple docstring'''




            _UpperCamelCase       =	[
                '''text_encoder/pytorch_model.fp16.bin''',
                '''text_encoder/model.fp16.safetensors''',
            ]
            _UpperCamelCase       =	'''fp16'''
            self.assertTrue(is_safetensors_compatible(lowerCAmelCase__	,			variant=lowerCAmelCase__					)					)





       def snake_case__						(							self       :		Optional[Any]					)   ->					str:

            '''simple docstring'''




            _UpperCamelCase       =	[
                '''text_encoder/pytorch_model.bin''',
                '''text_encoder/model.safetensors''',
            ]
            _UpperCamelCase       =	'''fp16'''
            self.assertTrue(is_safetensors_compatible(lowerCAmelCase__	,			variant=lowerCAmelCase__					)					)







       def snake_case__						(							self       :		List[str]					)   ->					Optional[int]:

            '''simple docstring'''




            _UpperCamelCase       =	[
                '''safety_checker/pytorch_model.fp16.bin''',
                '''safety_checker/model.fp16.safetensors''',
                '''vae/diffusion_pytorch_model.fp16.bin''',
                '''vae/diffusion_pytorch_model.fp16.safetensors''',
                '''text_encoder/pytorch_model.fp16.bin''',
                # 'text_encoder/model.fp16.safetensors',
                '''unet/diffusion_pytorch_model.fp16.bin''',
                '''unet/diffusion_pytorch_model.fp16.safetensors''',
            ]
            _UpperCamelCase       =	'''fp16'''
            self.assertFalse(is_safetensors_compatible(lowerCAmelCase__	,			variant=lowerCAmelCase__					)					)



